# The pillars of the framework
The pillars of the framework

Creating a software system is a lot like constructing a building. If the foundation is not solid, structural problems can undermine the integrity and function of the building. When architecting technology solutions, if you neglect the six pillars of operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability, it can become challenging to build a system that delivers on your expectations and requirements. Incorporating these pillars into your architecture will help you produce stable and efficient systems. This will allow you to focus on the other aspects of design, such as functional requirements. 

**Topics**
+ [

# Operational excellence
](operational-excellence.md)
+ [

# Security
](security.md)
+ [

# Reliability
](reliability.md)
+ [

# Performance efficiency
](performance-efficiency.md)
+ [

# Cost optimization
](cost-optimization.md)
+ [

# Sustainability
](sustainability.md)

# Operational excellence
Operational excellence

Operational excellence (OE) is a commitment to build software correctly while consistently delivering a great customer experience. The operational excellence pillar contains best practices for organizing your team, designing your workload, operating it at scale, and evolving it over time.

 The operational excellence pillar provides an overview of design principles, best practices, and questions. You can find prescriptive guidance on implementation in the [Operational Excellence Pillar whitepaper](https://docs.aws.amazon.com/wellarchitected/latest/operational-excellence-pillar/welcome.html). 

**Topics**
+ [

# Design principles
](oe-design-principles.md)
+ [

# Definition
](oe-definition.md)
+ [

# Best practices
](oe-bp.md)
+ [

# Resources
](oe-resources.md)

# Design principles


 The following are design principles for operational excellence in the cloud: 
+  **Organize teams around business outcomes:** The ability of a team to achieve business outcomes comes from leadership vision, effective operations, and a business-aligned operating model. Leadership should be fully invested and committed to a CloudOps transformation with a suitable cloud operating model that incentivizes teams to operate in the most efficient way and meet business outcomes. The right operating model uses people, process, and technology capabilities to scale, optimize for productivity, and differentiate through agility, responsiveness, and adaptation. The organization's long-term vision is translated into goals that are communicated across the enterprise to stakeholders and consumers of your cloud services. Goals and operational KPIs are aligned at all levels. This practice sustains the long-term value derived from implementing the following design principles.
+  **Implement observability for actionable insights:** Gain a comprehensive understanding of workload behavior, performance, reliability, cost, and health. Establish key performance indicators (KPIs) and leverage observability telemetry to make informed decisions and take prompt action when business outcomes are at risk. Proactively improve performance, reliability, and cost based on actionable observability data. 
+  **Safely automate where possible:** In the cloud, you can apply the same engineering discipline that you use for application code to your entire environment. You can define your entire workload and its operations (applications, infrastructure, configuration, and procedures) as code, and update it. You can then automate your workload’s operations by initiating them in response to events. In the cloud, you can employ automation safety by configuring guardrails, including rate control, error thresholds, and approvals. Through effective automation, you can achieve consistent responses to events, limit human error, and reduce operator toil. 
+  **Make frequent, small, reversible changes:** Design workloads that are scalable and loosely coupled to permit components to be updated regularly. Automated deployment techniques together with smaller, incremental changes reduces the blast radius and allows for faster reversal when failures occur. This increases confidence to deliver beneficial changes to your workload while maintaining quality and adapting quickly to changes in market conditions.
+  **Refine operations procedures frequently:** As you evolve your workloads, evolve your operations appropriately. As you use operations procedures, look for opportunities to improve them. Hold regular reviews and validate that all procedures are effective and that teams are familiar with them. Where gaps are identified, update procedures accordingly. Communicate procedural updates to all stakeholders and teams. Gamify your operations to share best practices and educate teams.
+  **Anticipate failure:** Maximize operational success by driving failure scenarios to understand the workload’s risk profile and its impact on your business outcomes. Test the effectiveness of your procedures and your team’s response against these simulated failures. Make informed decisions to manage open risks that are identified by your testing.
+  **Learn from all operational events and metrics:** Drive improvement through lessons learned from all operational events and failures. Share what is learned across teams and through the entire organization. Learnings should highlight data and anecdotes on how operations contribute to business outcomes.
+  **Use managed services:** Reduce operational burden by using AWS managed services where possible. Build operational procedures around interactions with those services. 

# Definition


 There are four best practice areas for operational excellence in the cloud: 
+  **Organization** 
+  **Prepare** 
+  **Operate** 
+  **Evolve** 

 Your organization’s leadership defines business objectives. Your organization must understand requirements and priorities and use these to organize and conduct work to support the achievement of business outcomes. Your workload must emit the information necessary to support it. Implementing services to achieve integration, deployment, and delivery of your workload will create an increased flow of beneficial changes into production by automating repetitive processes. 

 There may be risks inherent in the operation of your workload. Understand those risks and make an informed decision to enter production. Your teams must be able to support your workload. Business and operational metrics derived from desired business outcomes will permit you to understand the health of your workload, your operations activities, and respond to incidents. Your priorities will change as your business needs and business environment changes. Use these as a feedback loop to continually drive improvement for your organization and the operation of your workload. 

# Best practices


**Note**  
 All operational excellence questions have the OPS prefix as a shorthand for the pillar. 

**Topics**
+ [

# Organization
](oe-organization.md)
+ [

# Prepare
](oe-prepare.md)
+ [

# Operate
](oe-operate.md)
+ [

# Evolve
](oe-evolve.md)

# Organization


 Your teams must have a shared understanding of your entire workload, their role in it, and shared business goals to set the priorities that will achieve business success. Well-defined priorities will maximize the benefits of your efforts. Evaluate internal and external customer needs involving key stakeholders, including business, development, and operations teams, to determine where to focus efforts. Evaluating customer needs will verify that you have a thorough understanding of the support that is required to achieve business outcomes. Verify that you are aware of guidelines or obligations defined by your organizational governance and external factors, such as regulatory compliance requirements and industry standards that may mandate or emphasize specific focus. Validate that you have mechanisms to identify changes to internal governance and external compliance requirements. If no requirements are identified, validate that you have applied due diligence to this determination. Review your priorities regularly so that they can be updated as needs change. 

 Evaluate threats to the business (for example, business risk and liabilities, and information security threats) and maintain this information in a risk registry. Evaluate the impact of risks, and tradeoffs between competing interests or alternative approaches. For example, accelerating speed to market for new features may be emphasized over cost optimization, or you may choose a relational database for non-relational data to simplify the effort to migrate a system without refactoring. Manage benefits and risks to make informed decisions when determining where to focus efforts. Some risks or choices may be acceptable for a time, it may be possible to mitigate associated risks, or it may become unacceptable to permit a risk to remain, in which case you will take action to address the risk. 

 Your teams must understand their part in achieving business outcomes. Teams must understand their roles in the success of other teams, the role of other teams in their success, and have shared goals. Understanding responsibility, ownership, how decisions are made, and who has authority to make decisions will help focus efforts and maximize the benefits from your teams. The needs of a team will be shaped by the customer they support, their organization, the makeup of the team, and the characteristics of their workload. It's unreasonable to expect a single operating model to be able to support all teams and their workloads in your organization. 

 Verify that there are identified owners for each application, workload, platform, and infrastructure component, and that each process and procedure has an identified owner responsible for its definition, and owners responsible for their performance. 

 Having understanding of the business value of each component, process, and procedure, of why those resources are in place or activities are performed, and why that ownership exists will inform the actions of your team members. Clearly define the responsibilities of team members so that they may act appropriately and have mechanisms to identify responsibility and ownership. Have mechanisms to request additions, changes, and exceptions so that you do not constrain innovation. Define agreements between teams describing how they work together to support each other and your business outcomes. 

 Provide support for your team members so that they can be more effective in taking action and supporting your business outcomes. Engaged senior leadership should set expectations and measure success. Senior leadership should be the sponsor, advocate, and driver for the adoption of best practices and evolution of the organization. Let team members take action when outcomes are at risk to minimize impact and encourage them to escalate to decision makers and stakeholders when they believe there is a risk so that it can be addressed and incidents avoided. Provide timely, clear, and actionable communications of known risks and planned events so that team members can take timely and appropriate action. 

 Encourage experimentation to accelerate learning and keep team members interested and engaged. Teams must grow their skill sets to adopt new technologies, and to support changes in demand and responsibilities. Support and encourage this by providing dedicated structured time for learning. Verify that your team members have the resources, both tools and team members, to be successful and scale to support your business outcomes. Leverage cross-organizational diversity to seek multiple unique perspectives. Use this perspective to increase innovation, challenge your assumptions, and reduce the risk of confirmation bias. Grow inclusion, diversity, and accessibility within your teams to gain beneficial perspectives. 

 If there are external regulatory or compliance requirements that apply to your organization, you should use the resources provided by [AWS Cloud Compliance](https://aws.amazon.com/compliance/?ref=wellarchitected-wp) to help educate your teams so that they can determine the impact on your priorities. The Well-Architected Framework emphasizes learning, measuring, and improving. It provides a consistent approach for you to evaluate architectures, and implement designs that will scale over time. AWS provides the AWS Well-Architected Tool to help you review your approach before development, the state of your workloads before production, and the state of your workloads in production. You can compare workloads to the latest AWS architectural best practices, monitor their overall status, and gain insight into potential risks. AWS Trusted Advisor is a tool that provides access to a core set of checks that recommend optimizations that may help shape your priorities. Business and Enterprise Support customers receive access to additional checks focusing on security, reliability, performance, cost-optimization, and sustainability that can further help shape their priorities. 

 AWS can help you educate your teams about AWS and its services to increase their understanding of how their choices can have an impact on your workload. Use the resources provided by AWS Support (AWS Knowledge Center, AWS Discussion Forums, and AWS Support Center) and AWS Documentation to educate your teams. Reach out to AWS Support through AWS Support Center for help with your AWS questions. AWS also shares best practices and patterns that we have learned through the operation of AWS in The Amazon Builders' Library. A wide variety of other useful information is available through the AWS Blog and The Official AWS Podcast. AWS Training and Certification provides some training through self-paced digital courses on AWS fundamentals. You can also register for instructor-led training to further support the development of your teams’ AWS skills. 

 Use tools or services that permit you to centrally govern your environments across accounts, such as AWS Organizations, to help manage your operating models. Services like AWS Control Tower expand this management capability by allowing you to define blueprints (supporting your operating models) for the setup of accounts, apply ongoing governance using AWS Organizations, and automate provisioning of new accounts. Managed Services providers such as AWS Managed Services, AWS Managed Services Partners, or Managed Services Providers in the AWS Partner Network, provide expertise implementing cloud environments, and support your security and compliance requirements and business goals. Adding Managed Services to your operating model can save you time and resources, and lets you keep your internal teams lean and focused on strategic outcomes that will differentiate your business, rather than developing new skills and capabilities. 

 The following questions focus on these considerations for operational excellence. (For a list of operational excellence questions and best practices, see the [Appendix](a-organization.md).)


| OPS 1:  How do you determine what your priorities are? | 
| --- | 
|  Everyone must understand their part in achieving business success. Have shared goals in order to set priorities for resources. This will maximize the benefits of your efforts.  | 


| OPS 2:  How do you structure your organization to support your business outcomes? | 
| --- | 
| Your teams must understand their part in achieving business outcomes. Teams must understand their roles in the success of other teams, the role of other teams in their success, and have shared goals. Understanding responsibility, ownership, how decisions are made, and who has authority to make decisions will help focus efforts and maximize the benefits from your teams.  | 


| OPS 3:  How does your organizational culture support your business outcomes? | 
| --- | 
|  Provide support for your team members so that they can be more effective in taking action and supporting your business outcome.  | 

 You might find that you want to emphasize a small subset of your priorities at some point in time. Use a balanced approach over the long term to verify the development of needed capabilities and management of risk. Review your priorities regularly and update them as needs change. When responsibility and ownership are undefined or unknown, you are at risk of both not performing necessary action in a timely fashion and of redundant and potentially conflicting efforts emerging to address those needs. Organizational culture has a direct impact on team member job satisfaction and retention. Activate the engagement and capabilities of your team members to achieve the success of your business. Experimentation is required for innovation to happen and turn ideas into outcomes. Recognize that an undesired result is a successful experiment that has identified a path that will not lead to success. 

# Prepare


 To prepare for operational excellence, you have to understand your workloads and their expected behaviors. You will then be able to design them to provide insight to their status and build the procedures to support them. 

 Design your workload so that it provides the information necessary for you to understand its internal state (for example, metrics, logs, events, and traces) across all components in support of observability and investigating issues. Observability goes beyond simple monitoring, providing a comprehensive understanding of a system's internal workings based on its external outputs. Rooted in metrics, logs, and traces, observability offers profound insights into system behavior and dynamics. With effective observability, teams can discern patterns, anomalies, and trends, allowing them to proactively address potential issues and maintain optimal system health. Identifying key performance indicators (KPIs) is pivotal to ensure alignment between monitoring activities and business objectives. This alignment ensures that teams are making data-driven decisions using metrics that genuinely matter, optimizing both system performance and business outcomes. Furthermore, observability empowers businesses to be proactive rather than reactive. Teams can understand the cause-and-effect relationships within their systems, predicting and preventing issues rather than just reacting to them. As workloads evolve, it's essential to revisit and refine the observability strategy, ensuring it remains relevant and effective. 

 Adopt approaches that improve the flow of changes into production and that achieves refactoring, fast feedback on quality, and bug fixing. These accelerate beneficial changes entering production, limit issues deployed, and activate rapid identification and remediation of issues introduced through deployment activities or discovered in your environments. 

 Adopt approaches that provide fast feedback on quality and achieves rapid recovery from changes that do not have desired outcomes. Using these practices mitigates the impact of issues introduced through the deployment of changes. Plan for unsuccessful changes so that you are able to respond faster if necessary and test and validate the changes you make. Be aware of planned activities in your environments so that you can manage the risk of changes impacting planned activities. Emphasize frequent, small, reversible changes to limit the scope of change. This results in faster troubleshooting and remediation with the option to roll back a change. It also means you are able to get the benefit of valuable changes more frequently. 

 Evaluate the operational readiness of your workload, processes, procedures, and personnel to understand the operational risks related to your workload. Use a consistent process (including manual or automated checklists) to know when you are ready to go live with your workload or a change. This will also help you to find any areas that you must make plans to address. Have runbooks that document your routine activities and playbooks that guide your processes for issue resolution. Understand the benefits and risks to make informed decisions to permit changes to enter production. 

 AWS allows you to view your entire workload (applications, infrastructure, policy, governance, and operations) as code. This means you can apply the same engineering discipline that you use for application code to every element of your stack and share these across teams or organizations to magnify the benefits of development efforts. Use operations as code in the cloud and the ability to safely experiment to develop your workload, your operations procedures, and practice failure. Using CloudFormation allows you to have consistent, templated, sandbox development, test, and production environments with increasing levels of operations control. 

 The following questions focus on these considerations for operational excellence. 


| OPS 4:  How do you implement observability in your workload? | 
| --- | 
| Implement observability in your workload so that you can understand its state and make data-driven decisions based on business requirements. | 


| OPS 5:  How do you reduce defects, ease remediation, and improve flow into production? | 
| --- | 
|  Adopt approaches that improve flow of changes into production that achieve refactoring fast feedback on quality, and bug fixing. These accelerate beneficial changes entering production, limit issues deployed, and achieve rapid identification and remediation of issues introduced through deployment activities.  | 


| OPS 6:  How do you mitigate deployment risks? | 
| --- | 
|  Adopt approaches that provide fast feedback on quality and achieve rapid recovery from changes that do not have desired outcomes. Using these practices mitigates the impact of issues introduced through the deployment of changes.  | 


| OPS 7:  How do you know that you are ready to support a workload? | 
| --- | 
|  Evaluate the operational readiness of your workload, processes and procedures, and personnel to understand the operational risks related to your workload.  | 

 Invest in implementing operations activities as code to maximize the productivity of operations personnel, minimize error rates, and achieve automated responses. Use “pre-mortems” to anticipate failure and create procedures where appropriate. Apply metadata using Resource Tags and AWS Resource Groups following a consistent tagging strategy to achieve identification of your resources. Tag your resources for organization, cost accounting, access controls, and targeting the running of automated operations activities. Adopt deployment practices that take advantage of the elasticity of the cloud to facilitate development activities, and pre-deployment of systems for faster implementations. When you make changes to the checklists you use to evaluate your workloads, plan what you will do with live systems that no longer comply. 

# Operate


 Observability allows you to focus on meaningful data and understand your workload's interactions and output. By concentrating on essential insights and eliminating unnecessary data, you maintain a straightforward approach to understanding workload performance. It's essential not only to collect data but also to interpret it correctly. Define clear baselines, set appropriate alert thresholds, and actively monitor for any deviations. A shift in a key metric, especially when correlated with other data, can pinpoint specific problem areas. With observability, you're better equipped to foresee and address potential challenges, ensuring that your workload operates smoothly and meets business needs. 

 Successful operation of a workload is measured by the achievement of business and customer outcomes. Define expected outcomes, determine how success will be measured, and identify metrics that will be used in those calculations to determine if your workload and operations are successful. Operational health includes both the health of the workload and the health and success of the operations activities performed in support of the workload (for example, deployment and incident response). Establish metrics baselines for improvement, investigation, and intervention, collect and analyze your metrics, and then validate your understanding of operations success and how it changes over time. Use collected metrics to determine if you are satisfying customer and business needs, and identify areas for improvement. 

 Efficient and effective management of operational events is required to achieve operational excellence. This applies to both planned and unplanned operational events. Use established runbooks for well-understood events, and use playbooks to aid in investigation and resolution of issues. Prioritize responses to events based on their business and customer impact. Verify that if an alert is raised in response to an event, there is an associated process to run with a specifically identified owner. Define in advance the personnel required to resolve an event and include escalation processes to engage additional personnel, as it becomes necessary, based on urgency and impact. Identify and engage individuals with the authority to make a decision on courses of action where there will be a business impact from an event response not previously addressed. 

 Communicate the operational status of workloads through dashboards and notifications that are tailored to the target audience (for example, customer, business, developers, operations) so that they may take appropriate action, so that their expectations are managed, and so that they are informed when normal operations resume. 

 In AWS, you can generate dashboard views of your metrics collected from workloads and natively from AWS. You can leverage CloudWatch or third-party applications to aggregate and present business, workload, and operations level views of operations activities. AWS provides workload insights through logging capabilities including AWS X-Ray, CloudWatch, CloudTrail, and VPC Flow Logs to identify workload issues in support of root cause analysis and remediation. 

 The following questions focus on these considerations for operational excellence. 


| OPS 8:  How do you utilize workload observability in your organization? | 
| --- | 
| Ensure optimal workload health by leveraging observability. Utilize relevant metrics, logs, and traces to gain a comprehensive view of your workload's performance and address issues efficiently. | 


| OPS 9:  How do you understand the health of your operations? | 
| --- | 
|  Define, capture, and analyze operations metrics to gain visibility to operations events so that you can take appropriate action.  | 


| OPS 10:  How do you manage workload and operations events? | 
| --- | 
|  Prepare and validate procedures for responding to events to minimize their disruption to your workload.  | 

 All of the metrics you collect should be aligned to a business need and the outcomes they support. Develop scripted responses to well-understood events and automate their performance in response to recognizing the event. 

# Evolve


 Learn, share, and continuously improve to sustain operational excellence. Dedicate work cycles to making nearly continuous incremental improvements. Perform post-incident analysis of all customer impacting events. Identify the contributing factors and preventative action to limit or prevent recurrence. Communicate contributing factors with affected communities as appropriate. Regularly evaluate and prioritize opportunities for improvement (for example, feature requests, issue remediation, and compliance requirements), including both the workload and operations procedures. 

 Include feedback loops within your procedures to rapidly identify areas for improvement and capture learnings from running operations. 

 Share lessons learned across teams to share the benefits of those lessons. Analyze trends within lessons learned and perform cross-team retrospective analysis of operations metrics to identify opportunities and methods for improvement. Implement changes intended to bring about improvement and evaluate the results to determine success. 

 On AWS, you can export your log data to Amazon S3 or send logs directly to Amazon S3 for long-term storage. Using AWS Glue, you can discover and prepare your log data in Amazon S3 for analytics, and store associated metadata in the AWS Glue Data Catalog. Amazon Athena, through its native integration with AWS Glue, can then be used to analyze your log data, querying it using standard SQL. Using a business intelligence tool like Amazon Quick, you can visualize, explore, and analyze your data. Discovering trends and events of interest that may drive improvement. 

 The following question focuses on these considerations for operational excellence. 


| OPS 11:  How do you evolve operations? | 
| --- | 
|  Dedicate time and resources for nearly continuous incremental improvement to evolve the effectiveness and efficiency of your operations.  | 

 Successful evolution of operations is founded in: frequent small improvements; providing safe environments and time to experiment, develop, and test improvements; and environments in which learning from failures is encouraged. Operations support for sandbox, development, test, and production environments, with increasing level of operational controls, facilitates development and increases the predictability of successful results from changes deployed into production. 

# Resources


 Refer to the following resources to learn more about our best practices for Operational Excellence. 

## Documentation

+  [DevOps and AWS](https://aws.amazon.com/devops/?ref=wellarchitected-wp) 

## Whitepaper

+  [Operational Excellence Pillar](https://docs.aws.amazon.com/wellarchitected/latest/operational-excellence-pillar/welcome.html?ref=wellarchitected-wp) 

## Video

+  [DevOps at Amazon](https://www.youtube.com/watch?v=esEFaY0FDKc&ref=wellarchitected-wp) 

# Security
Security

The Security pillar encompasses the ability to protect data, systems, and assets to take advantage of cloud technologies to improve your security. 

The security pillar provides an overview of design principles, best practices, and questions. You can find prescriptive guidance on implementation in the [Security Pillar whitepaper](https://docs.aws.amazon.com/wellarchitected/latest/security-pillar/welcome.html?ref=wellarchitected-wp). 

**Topics**
+ [

# Design principles
](sec-design.md)
+ [

# Definition
](sec-def.md)
+ [

# Best practices
](sec-bp.md)
+ [

# Resources
](sec-resources.md)

# Design principles


In the cloud, there are a number of principles that can help you strengthen your workload security:
+ **Implement a strong identity foundation:** Implement the principle of least privilege and enforce separation of duties with appropriate authorization for each interaction with your AWS resources. Centralize identity management, and aim to eliminate reliance on long-term static credentials.
+ **Maintain traceability:** Monitor, alert, and audit actions and changes to your environment in real time. Integrate log and metric collection with systems to automatically investigate and take action.
+ **Apply security at all layers:** Apply a defense in depth approach with multiple security controls. Apply to all layers (for example, edge of network, VPC, load balancing, every instance and compute service, operating system, application, and code).
+ **Automate security best practices:** Automated software-based security mechanisms improve your ability to securely scale more rapidly and cost-effectively. Create secure architectures, including the implementation of controls that are defined and managed as code in version-controlled templates.
+ **Protect data in transit and at rest**: Classify your data into sensitivity levels and use mechanisms, such as encryption, tokenization, and access control where appropriate.
+ **Keep people away from data:** Use mechanisms and tools to reduce or eliminate the need for direct access or manual processing of data. This reduces the risk of mishandling or modification and human error when handling sensitive data.
+ **Prepare for security events:** Prepare for an incident by having incident management and investigation policy and processes that align to your organizational requirements. Run incident response simulations and use tools with automation to increase your speed for detection, investigation, and recovery.

# Definition


 There are seven best practice areas for security in the cloud: 
+ Security foundations
+ Identity and access management
+ Detection
+ Infrastructure protection
+ Data protection
+ Incident response
+ Application security

 Before you architect any workload, you need to put in place practices that influence security. You will want to control who can do what. In addition, you want to be able to identify security incidents, protect your systems and services, and maintain the confidentiality and integrity of data through data protection. You should have a well-defined and practiced process for responding to security incidents. These tools and techniques are important because they support objectives such as preventing financial loss or complying with regulatory obligations. 

 The AWS Shared Responsibility Model helps organizations that adopt the cloud to achieve their security and compliance goals. Because AWS physically secures the infrastructure that supports our cloud services, as an AWS customer you can focus on using services to accomplish your goals. The AWS Cloud also provides greater access to security data and an automated approach to responding to security events. 

# Best practices


**Topics**
+ [

# Security foundations
](sec-security.md)
+ [

# Identity and access management
](sec-iam.md)
+ [

# Detection
](sec-detection.md)
+ [

# Infrastructure protection
](sec-infrastructure.md)
+ [

# Data protection
](sec-dataprot.md)
+ [

# Incident response
](sec-incresp.md)
+ [

# Application security
](sec-appsec.md)

# Security foundations


The following question focuses on these considerations for security. (For a list of security questions and best practices, see the [Appendix](a-security.md).). 


| SEC 1:  How do you securely operate your workload? | 
| --- | 
| To operate your workload securely, you must apply overarching best practices to every area of security. Take requirements and processes that you have defined in operational excellence at an organizational and workload level, and apply them to all areas.  Staying up to date with recommendations from AWS, industry sources, and threat intelligence helps you evolve your threat model and control objectives. Automating security processes, testing, and validation allow you to scale your security operations. | 

 In AWS, segregating different workloads by account, based on their function and compliance or data sensitivity requirements, is a recommended approach. 

# Identity and access management


 Identity and access management are key parts of an information security program, ensuring that only authorized and authenticated users and components are able to access your resources, and only in a manner that you intend. For example, you should define principals (that is, accounts, users, roles, and services that can perform actions in your account), build out policies aligned with these principals, and implement strong credential management. These privilege-management elements form the core of authentication and authorization. 

 In AWS, privilege management is primarily supported by the AWS Identity and Access Management (IAM) service, which allows you to control user and programmatic access to AWS services and resources. You should apply granular policies, which assign permissions to a user, group, role, or resource. You also have the ability to require strong password practices, such as complexity level, avoiding re-use, and enforcing multi-factor authentication (MFA). You can use federation with your existing directory service. For workloads that require systems to have access to AWS, IAM allows for secure access through roles, instance profiles, identity federation, and temporary credentials. 

 The following questions focus on these considerations for security. 


| SEC 2:  How do you manage identities for people and machines? | 
| --- | 
|  There are two types of identities you need to manage when approaching operating secure AWS workloads. Understanding the type of identity you need to manage and grant access helps you verify the right identities have access to the right resources under the right conditions.  Human Identities: Your administrators, developers, operators, and end users require an identity to access your AWS environments and applications. These are members of your organization, or external users with whom you collaborate, and who interact with your AWS resources via a web browser, client application, or interactive command line tools.  Machine Identities: Your service applications, operational tools, and workloads require an identity to make requests to AWS services, for example, to read data. These identities include machines running in your AWS environment such as Amazon EC2 instances or AWS Lambda functions. You may also manage machine identities for external parties who need access. Additionally, you may also have machines outside of AWS that need access to your AWS environment.   | 


| SEC 3:  How do you manage permissions for people and machines? | 
| --- | 
| Manage permissions to control access to people and machine identities that require access to AWS and your workload. Permissions control who can access what, and under what conditions.  | 

 Credentials must not be shared between any user or system. User access should be granted using a least-privilege approach with best practices including password requirements and MFA enforced. Programmatic access, including API calls to AWS services, should be performed using temporary and limited-privilege credentials, such as those issued by the AWS Security Token Service.

Users need programmatic access if they want to interact with AWS outside of the AWS Management Console. The way to grant programmatic access depends on the type of user that's accessing AWS.

To grant users programmatic access, choose one of the following options.


****  

| Which user needs programmatic access? | To | By | 
| --- | --- | --- | 
| IAM | (Recommended) Use console credentials as temporary credentials to sign programmatic requests to the AWS CLI, AWS SDKs, or AWS APIs. |  Following the instructions for the interface that you want to use. [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/wellarchitected/latest/framework/sec-iam.html)  | 
|  Workforce identity (Users managed in IAM Identity Center)  | Use temporary credentials to sign programmatic requests to the AWS CLI, AWS SDKs, or AWS APIs. |  Following the instructions for the interface that you want to use. [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/wellarchitected/latest/framework/sec-iam.html)  | 
| IAM | Use temporary credentials to sign programmatic requests to the AWS CLI, AWS SDKs, or AWS APIs. | Following the instructions in [Using temporary credentials with AWS resources](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_use-resources.html) in the IAM User Guide. | 
| IAM | (Not recommended)Use long-term credentials to sign programmatic requests to the AWS CLI, AWS SDKs, or AWS APIs. |  Following the instructions for the interface that you want to use. [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/wellarchitected/latest/framework/sec-iam.html)  | 

 AWS provides resources that can help you with identity and access management. To help learn best practices, explore our hands-on labs on [managing credentials & authentication](https://wellarchitectedlabs.com/Security/Quest_Managing_Credentials_and_Authentication/README.html?ref=wellarchitected-wp), [controlling human access](https://wellarchitectedlabs.com/Security/Quest_Control_Human_Access/README.html?ref=wellarchitected-wp), and [controlling programmatic access](https://wellarchitectedlabs.com/Security/Quest_Control_Programmatic_Access/README.html?ref=wellarchitected-wp). 

# Detection


 You can use detective controls to identify a potential security threat or incident. They are an essential part of governance frameworks and can be used to support a quality process, a legal or compliance obligation, and for threat identification and response efforts. There are different types of detective controls. For example, conducting an inventory of assets and their detailed attributes promotes more effective decision making (and lifecycle controls) to help establish operational baselines. You can also use internal auditing, an examination of controls related to information systems, to verify that practices meet policies and requirements and that you have set the correct automated alerting notifications based on defined conditions. These controls are important reactive factors that can help your organization identify and understand the scope of anomalous activity. 

 In AWS, you can implement detective controls by processing logs, events, and monitoring that allows for auditing, automated analysis, and alarming. CloudTrail logs, AWS API calls, and CloudWatch provide monitoring of metrics with alarming, and AWS Config provides configuration history. Amazon GuardDuty is a managed threat detection service that continuously monitors for malicious or unauthorized behavior to help you protect your AWS accounts and workloads. Service-level logs are also available, for example, you can use Amazon Simple Storage Service (Amazon S3) to log access requests. 

 The following question focuses on these considerations for security. 


| SEC 4:  How do you detect and investigate security events? | 
| --- | 
| Capture and analyze events from logs and metrics to gain visibility. Take action on security events and potential threats to help secure your workload. | 

 Log management is important to a Well-Architected workload for reasons ranging from security or forensics to regulatory or legal requirements. It is critical that you analyze logs and respond to them so that you can identify potential security incidents. AWS provides functionality that makes log management easier to implement by giving you the ability to define a data-retention lifecycle or define where data will be preserved, archived, or eventually deleted. This makes predictable and reliable data handling simpler and more cost effective. 

# Infrastructure protection


 Infrastructure protection encompasses control methodologies, such as defense in depth, necessary to meet best practices and organizational or regulatory obligations. Use of these methodologies is critical for successful, ongoing operations in either the cloud or on-premises. 

 In AWS, you can implement stateful and stateless packet inspection, either by using AWS-native technologies or by using partner products and services available through the AWS Marketplace. You should use Amazon Virtual Private Cloud (Amazon VPC) to create a private, secured, and scalable environment in which you can define your topology—including gateways, routing tables, and public and private subnets. 

 The following questions focus on these considerations for security. 


| SEC 5:  How do you protect your network resources? | 
| --- | 
| Any workload that has some form of network connectivity, whether it’s the internet or a private network, requires multiple layers of defense to help protect from external and internal network-based threats. | 


| SEC 6:  How do you protect your compute resources? | 
| --- | 
| Compute resources in your workload require multiple layers of defense to help protect from external and internal threats. Compute resources include EC2 instances, containers, AWS Lambda functions, database services, IoT devices, and more. | 

 Multiple layers of defense are advisable in any type of environment. In the case of infrastructure protection, many of the concepts and methods are valid across cloud and on-premises models. Enforcing boundary protection, monitoring points of ingress and egress, and comprehensive logging, monitoring, and alerting are all essential to an effective information security plan. 

 AWS customers are able to tailor, or harden, the configuration of an Amazon Elastic Compute Cloud (Amazon EC2), Amazon Elastic Container Service (Amazon ECS) container, or AWS Elastic Beanstalk instance, and persist this configuration to an immutable Amazon Machine Image (AMI). Then, whether launched by Auto Scaling or launched manually, all new virtual servers (instances) launched with this AMI receive the hardened configuration. 

# Data protection


 Before architecting any system, foundational practices that influence security should be in place. For example, data classification provides a way to categorize organizational data based on levels of sensitivity, and encryption protects data by way of rendering it unintelligible to unauthorized access. These tools and techniques are important because they support objectives such as preventing financial loss or complying with regulatory obligations. 

 In AWS, the following practices facilitate protection of data: 
+  As an AWS customer you maintain full control over your data. 
+  AWS makes it easier for you to encrypt your data and manage keys, including regular key rotation, which can be easily automated by AWS or maintained by you. 
+  Detailed logging that contains important content, such as file access and changes, is available. 
+  AWS has designed storage systems for exceptional resiliency. For example, Amazon S3 Standard, S3 Standard–IA, S3 One Zone-IA, and Amazon Glacier are all designed to provide 99.999999999% durability of objects over a given year. This durability level corresponds to an average annual expected loss of 0.000000001% of objects. 
+  Versioning, which can be part of a larger data lifecycle management process, can protect against accidental overwrites, deletes, and similar harm. 
+  AWS never initiates the movement of data between Regions. Content placed in a Region will remain in that Region unless you explicitly use a feature or leverage a service that provides that functionality. 

 The following questions focus on these considerations for security. 


| SEC 7:  How do you classify your data? | 
| --- | 
| Classification provides a way to categorize data, based on criticality and sensitivity in order to help you determine appropriate protection and retention controls. | 


| SEC 8:  How do you protect your data at rest? | 
| --- | 
| Protect your data at rest by implementing multiple controls, to reduce the risk of unauthorized access or mishandling. | 


| SEC 9:  How do you protect your data in transit? | 
| --- | 
| Protect your data in transit by implementing multiple controls to reduce the risk of unauthorized access or loss. | 

 AWS provides multiple means for encrypting data at rest and in transit. We build features into our services that make it easier to encrypt your data. For example, we have implemented server-side encryption (SSE) for Amazon S3 to make it easier for you to store your data in an encrypted form. You can also arrange for the entire HTTPS encryption and decryption process (generally known as SSL termination) to be handled by Elastic Load Balancing (ELB). 

# Incident response


 Even with extremely mature preventive and detective controls, your organization should still put processes in place to respond to and mitigate the potential impact of security incidents. The architecture of your workload strongly affects the ability of your teams to operate effectively during an incident, to isolate or contain systems, and to restore operations to a known good state. Putting in place the tools and access ahead of a security incident, then routinely practicing incident response through game days, will help you verify that your architecture can accommodate timely investigation and recovery. 

 In AWS, the following practices facilitate effective incident response: 
+  Detailed logging is available that contains important content, such as file access and changes. 
+  Events can be automatically processed and launch tools that automate responses through the use of AWS APIs. 
+  You can pre-provision tooling and a “clean room” using AWS CloudFormation. This allows you to carry out forensics in a safe, isolated environment. 

 The following question focuses on these considerations for security. 


| SEC 10:  How do you anticipate, respond to, and recover from incidents? | 
| --- | 
| Preparation is critical to timely and effective investigation, response to, and recovery from security incidents to help minimize disruption to your organization. | 

 Verify that you have a way to quickly grant access for your security team, and automate the isolation of instances as well as the capturing of data and state for forensics. 

# Application security


 Application security (AppSec) describes the overall process of how you design, build, and test the security properties of the workloads you develop. You should have appropriately trained people in your organization, understand the security properties of your build and release infrastructure, and use automation to identify security issues. 

 Adopting application security testing as a regular part of your software development lifecycle (SDLC) and post release processes help validate that you have a structured mechanism to identify, fix, and prevent application security issues entering your production environment. 

 Your application development methodology should include security controls as you design, build, deploy, and operate your workloads. While doing so, align the process for continuous defect reduction and minimizing technical debt. For example, using threat modeling in the design phase helps you uncover design flaws early, which makes them easier and less costly to fix as opposed to waiting and mitigating them later. 

 The cost and complexity to resolve defects is typically lower the earlier you are in the SDLC. The easiest way to resolve issues is to not have them in the first place, which is why starting with a threat model helps you focus on the right outcomes from the design phase. As your AppSec program matures, you can increase the amount of testing that is performed using automation, improve the fidelity of feedback to builders, and reduce the time needed for security reviews. All of these actions improve the quality of the software you build, and increase the speed of delivering features into production. 

 These implementation guidelines focus on four areas: organization and culture, security *of* the pipeline, security *in* the pipeline, and dependency management. Each area provides a set of principles that you can implement and provides an end-to-end view of how you design, develop, build, deploy, and operate workloads. 

 In AWS, there are a number of approaches you can use when addressing your application security program. Some of these approaches rely on technology while others focus on the people and organizational aspects of your application security program. 

The following question focuses on these considerations for application security.


| SEC 11:  How do you incorporate and validate the security properties of applications throughout the design, development, and deployment lifecycle? | 
| --- | 
| Training people, testing using automation, understanding dependencies, and validating the security properties of tools and applications help to reduce the likelihood of security issues in production workloads. | 

# Resources


 Refer to the following resources to learn more about our best practices for Security. 

## Documentation

+  [AWS Cloud Security](https://aws.amazon.com/security/?ref=wellarchitected-wp) 
+  [AWS Compliance](https://aws.amazon.com/compliance/?ref=wellarchitected-wp) 
+  [AWS Security Blog](http://blogs.aws.amazon.com/security/?ref=wellarchitected-wp) 
+  [AWS Security Maturity Model](https://maturitymodel.security.aws.dev/en/0.-introduction/) 

## Whitepaper

+  [Security Pillar](https://docs.aws.amazon.com/wellarchitected/latest/security-pillar/welcome.html?ref=wellarchitected-wp) 
+  [AWS Security Overview](https://d1.awsstatic.com/whitepapers/Security/AWS%20Security%20Whitepaper.pdf?ref=wellarchitected-wp) 
+  [AWS Risk and Compliance](https://d1.awsstatic.com/whitepapers/compliance/AWS_Risk_and_Compliance_Whitepaper.pdf?ref=wellarchitected-wp) 

## Video

+  [AWS Security State of the Union](https://youtu.be/Wvyc-VEUOns?ref=wellarchitected-wp) 
+  [Shared Responsibility Overview](https://www.youtube.com/watch?v=U632-ND7dKQ&ref=wellarchitected-wp) 

# Reliability
Reliability

The Reliability pillar encompasses the ability of a workload to perform its intended function correctly and consistently when it’s expected to. This includes the ability to operate and test the workload through its total lifecycle. This paper provides in-depth, best practice guidance for implementing reliable workloads on AWS. 

The reliability pillar provides an overview of design principles, best practices, and questions. You can find prescriptive guidance on implementation in the [Reliability Pillar whitepaper](https://docs.aws.amazon.com/wellarchitected/latest/reliability-pillar/welcome.html?ref=wellarchitected-wp). 

**Topics**
+ [

# Design principles
](rel-dp.md)
+ [

# Definition
](rel-def.md)
+ [

# Best practices
](rel-bp.md)
+ [

# Resources
](rel-resources.md)

# Design principles


 There are five design principles for reliability in the cloud: 
+  **Automatically recover from failure**: By monitoring a workload for key performance indicators (KPIs), you can start automation when a threshold is breached. These KPIs should be a measure of business value, not of the technical aspects of the operation of the service. This provides for automatic notification and tracking of failures, and for automated recovery processes that work around or repair the failure. With more sophisticated automation, it’s possible to anticipate and remediate failures before they occur. 
+  **Test recovery procedures**: In an on-premises environment, testing is often conducted to prove that the workload works in a particular scenario. Testing is not typically used to validate recovery strategies. In the cloud, you can test how your workload fails, and you can validate your recovery procedures. You can use automation to simulate different failures or to recreate scenarios that led to failures before. This approach exposes failure pathways that you can test and fix before a real failure scenario occurs, thus reducing risk. 
+  **Scale horizontally to increase aggregate workload availability**: Replace one large resource with multiple small resources to reduce the impact of a single failure on the overall workload. Distribute requests across multiple, smaller resources to verify that they don’t share a common point of failure. 
+  **Stop guessing capacity**: A common cause of failure in on-premises workloads is resource saturation, when the demands placed on a workload exceed the capacity of that workload (this is often the objective of denial of service attacks). In the cloud, you can monitor demand and workload utilization, and automate the addition or removal of resources to maintain the more efficient level to satisfy demand without over- or under-provisioning. There are still limits, but some quotas can be controlled and others can be managed (see Manage Service Quotas and Constraints). 
+  **Manage change through automation**: Changes to your infrastructure should be made using automation. The changes that must be managed include changes to the automation, which then can be tracked and reviewed. 

# Definition


 There are four best practice areas for reliability in the cloud: 
+ Foundations 
+ Workload architecture 
+ Change management 
+ Failure management 

 To achieve reliability, you must start with the foundations — an environment where Service Quotas and network topology accommodate the workload. The workload architecture of the distributed system must be designed to prevent and mitigate failures. The workload must handle changes in demand or requirements, and it must be designed to detect failure and automatically heal itself. 

# Best practices


**Topics**
+ [

# Foundations
](rel-found.md)
+ [

# Workload architecture
](rel-workload-arch.md)
+ [

# Change management
](rel-chg-mgmt.md)
+ [

# Failure management
](rel-failmgmt.md)

# Foundations


 Foundational requirements are those whose scope extends beyond a single workload or project. Before architecting any system, foundational requirements that influence reliability should be in place. For example, you must have sufficient network bandwidth to your data center. 

 With AWS, most of these foundational requirements are already incorporated or can be addressed as needed. The cloud is designed to be nearly limitless, so it’s the responsibility of AWS to satisfy the requirement for sufficient networking and compute capacity, permitting you to change resource size and allocations on demand. 

 The following questions focus on these considerations for reliability. (For a list of reliability questions and best practices, see the [Appendix](a-reliability.md).). 


| REL 1:  How do you manage Service Quotas and constraints? | 
| --- | 
| For cloud-based workload architectures, there are Service Quotas (which are also referred to as service limits). These quotas exist to prevent accidentally provisioning more resources than you need and to limit request rates on API operations so as to protect services from abuse. There are also resource constraints, for example, the rate that you can push bits down a fiber-optic cable, or the amount of storage on a physical disk.  | 


| REL 2:  How do you plan your network topology? | 
| --- | 
| Workloads often exist in multiple environments. These include multiple cloud environments (both publicly accessible and private) and possibly your existing data center infrastructure. Plans must include network considerations such as intra- and inter-system connectivity, public IP address management, private IP address management, and domain name resolution. | 

# Workload architecture


 A reliable workload starts with upfront design decisions for both software and infrastructure. Your architecture choices will impact your workload behavior across all of the Well-Architected pillars. For reliability, there are specific patterns you must follow. 

 With AWS, workload developers have their choice of languages and technologies to use. AWS SDKs take the complexity out of coding by providing language-specific APIs for AWS services. These SDKs, plus the choice of languages, permits developers to implement the reliability best practices listed here. Developers can also read about and learn from how Amazon builds and operates software in [The Amazon Builders' Library](https://aws.amazon.com/builders-library/?ref=wellarchitected-wp). 

 The following questions focus on these considerations for reliability. 


| REL 3:  How do you design your workload service architecture? | 
| --- | 
| Build highly scalable and reliable workloads using a service-oriented architecture (SOA) or a microservices architecture. Service-oriented architecture (SOA) is the practice of making software components reusable via service interfaces. Microservices architecture goes further to make components smaller and simpler. | 


| REL 4:  How do you design interactions in a distributed system to prevent failures? | 
| --- | 
| Distributed systems rely on communications networks to interconnect components, such as servers or services. Your workload must operate reliably despite data loss or latency in these networks. Components of the distributed system must operate in a way that does not negatively impact other components or the workload. These best practices prevent failures and improve mean time between failures (MTBF). | 


| REL 5:  How do you design interactions in a distributed system to mitigate or withstand failures? | 
| --- | 
| Distributed systems rely on communications networks to interconnect components (such as servers or services). Your workload must operate reliably despite data loss or latency over these networks. Components of the distributed system must operate in a way that does not negatively impact other components or the workload. These best practices permit workloads to withstand stresses or failures, more quickly recover from them, and mitigate the impact of such impairments. The result is improved mean time to recovery (MTTR). | 

# Change management


 Changes to your workload or its environment must be anticipated and accommodated to achieve reliable operation of the workload. Changes include those imposed on your workload, such as spikes in demand, and also those from within, such as feature deployments and security patches. 

 Using AWS, you can monitor the behavior of a workload and automate the response to KPIs. For example, your workload can add additional servers as a workload gains more users. You can control who has permission to make workload changes and audit the history of these changes. 

 The following questions focus on these considerations for reliability. 


| REL 6:  How do you monitor workload resources? | 
| --- | 
| Logs and metrics are powerful tools to gain insight into the health of your workload. You can configure your workload to monitor logs and metrics and send notifications when thresholds are crossed or significant events occur. Monitoring allows your workload to recognize when low-performance thresholds are crossed or failures occur, so it can recover automatically in response. | 


| REL 7:  How do you design your workload to adapt to changes in demand? | 
| --- | 
| A scalable workload provides elasticity to add or remove resources automatically so that they closely match the current demand at any given point in time. | 


| REL 8:  How do you implement change? | 
| --- | 
| Controlled changes are necessary to deploy new functionality, and to verify that the workloads and the operating environment are running known software and can be patched or replaced in a predictable manner. If these changes are uncontrolled, then it makes it difficult to predict the effect of these changes, or to address issues that arise because of them.  | 

 When you architect a workload to automatically add and remove resources in response to changes in demand, this not only increases reliability but also validates that business success doesn't become a burden. With monitoring in place, your team will be automatically alerted when KPIs deviate from expected norms. Automatic logging of changes to your environment permits you to audit and quickly identify actions that might have impacted reliability. Controls on change management certify that you can enforce the rules that deliver the reliability you need. 

# Failure management


 In any system of reasonable complexity, it is expected that failures will occur. Reliability requires that your workload be aware of failures as they occur and take action to avoid impact on availability. Workloads must be able to both withstand failures and automatically repair issues. 

 With AWS, you can take advantage of automation to react to monitoring data. For example, when a particular metric crosses a threshold, you can initiate an automated action to remedy the problem. Also, rather than trying to diagnose and fix a failed resource that is part of your production environment, you can replace it with a new one and carry out the analysis on the failed resource out of band. Since the cloud allows you to stand up temporary versions of a whole system at low cost, you can use automated testing to verify full recovery processes. 

 The following questions focus on these considerations for reliability. 


| REL 9:  How do you back up data? | 
| --- | 
| Back up data, applications, and configuration to meet your requirements for recovery time objectives (RTO) and recovery point objectives (RPO). | 


| REL 10:  How do you use fault isolation to protect your workload? | 
| --- | 
| Fault isolation limits the impact of a component or system failure to a defined boundary. With proper isolation, components outside of the boundary are unaffected by the failure. Running your workload across multiple fault isolation boundaries can make it more resilient to failure. | 


| REL 11:  How do you design your workload to withstand component failures? | 
| --- | 
| Workloads with a requirement for high availability and low mean time to recovery (MTTR) must be architected for resiliency. | 


| REL 12:  How do you test reliability? | 
| --- | 
| After you have designed your workload to be resilient to the stresses of production, testing is the only way to verify that it will operate as designed, and deliver the resiliency you expect. | 


| REL 13:  How do you plan for disaster recovery (DR)? | 
| --- | 
| Having backups and redundant workload components in place is the start of your DR strategy. [RTO and RPO are your objectives](https://docs.aws.amazon.com/wellarchitected/latest/reliability-pillar/disaster-recovery-dr-objectives.html) for restoration of your workload. Set these based on business needs. Implement a strategy to meet these objectives, considering locations and function of workload resources and data. The probability of disruption and cost of recovery are also key factors that help to inform the business value of providing disaster recovery for a workload. | 

 Regularly back up your data and test your backup files to verify that you can recover from both logical and physical errors. A key to managing failure is the frequent and automated testing of workloads to cause failure, and then observe how they recover. Do this on a regular schedule and verify that such testing is also initiated after significant workload changes. Actively track KPIs, and also the recovery time objective (RTO) and recovery point objective (RPO), to assess a workload's resiliency (especially under failure-testing scenarios). Tracking KPIs will help you identify and mitigate single points of failure. The objective is to thoroughly test your workload-recovery processes so that you are confident that you can recover all your data and continue to serve your customers, even in the face of sustained problems. Your recovery processes should be as well exercised as your normal production processes. 

# Resources


 Refer to the following resources to learn more about our best practices for Reliability. 

## Documentation

+  [AWS Documentation](https://docs.aws.amazon.com/index.html?ref=wellarchitected-wp) 
+  [AWS Global Infrastructure](https://aws.amazon.com/about-aws/global-infrastructure?ref=wellarchitected-wp) 
+  [AWS Auto Scaling: How Scaling Plans Work](https://docs.aws.amazon.com/autoscaling/plans/userguide/how-it-works.html?ref=wellarchitected-wp) 
+  [What Is AWS Backup?](https://docs.aws.amazon.com/aws-backup/latest/devguide/whatisbackup.html?ref=wellarchitected-wp) 

## Whitepaper

+  [Reliability Pillar: AWS Well-Architected](https://docs.aws.amazon.com/wellarchitected/latest/reliability-pillar/welcome.html?ref=wellarchitected-wp) 
+  [Implementing Microservices on AWS](https://docs.aws.amazon.com/whitepapers/latest/microservices-on-aws/introduction.html?ref=wellarchitected-wp) 

# Performance efficiency
Performance efficiency

The performance efficiency pillar includes the ability to use cloud resources efficiently to meet performance requirements, and to maintain that efficiency as demand changes and technologies evolve.

 The performance efficiency pillar provides an overview of design principles, best practices, and questions. You can find prescriptive guidance on implementation in the [Performance Efficiency Pillar whitepaper](https://docs.aws.amazon.com/wellarchitected/latest/performance-efficiency-pillar/welcome.html?ref=wellarchitected-wp). 

**Topics**
+ [

# Design principles
](perf-dp.md)
+ [

# Definition
](perf-def.md)
+ [

# Best practices
](perf-bp.md)
+ [

# Resources
](perf-resources.md)

# Design principles


 There are five design principles for performance efficiency in the cloud: 
+  **Democratize advanced technologies**: Make advanced technology implementation smoother for your team by delegating complex tasks to your cloud vendor. Rather than asking your IT team to learn about hosting and running a new technology, consider consuming the technology as a service. For example, NoSQL databases, media transcoding, and machine learning are all technologies that require specialized expertise. In the cloud, these technologies become services that your team can consume, permitting your team to focus on product development rather than resource provisioning and management. 
+  **Go global in minutes**: Deploying your workload in multiple AWS Regions around the world permits you to provide lower latency and a better experience for your customers at minimal cost. 
+  **Use serverless architectures**: Serverless architectures remove the need for you to run and maintain physical servers for traditional compute activities. For example, serverless storage services can act as static websites (removing the need for web servers) and event services can host code. This removes the operational burden of managing physical servers, and can lower transactional costs because managed services operate at cloud scale. 
+  **Experiment more often**: With virtual and automatable resources, you can quickly carry out comparative testing using different types of instances, storage, or configurations. 
+  **Consider mechanical sympathy**: Understand how cloud services are consumed and always use the technology approach that aligns with your workload goals. For example, consider data access patterns when you select database or storage approaches. 

# Definition


 There are five best practice areas for performance efficiency in the cloud: 
+  **Architecture selection** 
+  **Compute and hardware** 
+  **Data management** 
+  **Networking and content delivery** 
+  **Process and culture** 

 Take a data-driven approach to building a high-performance architecture. Gather data on all aspects of the architecture, from the high-level design to the selection and configuration of resource types. 

 Reviewing your choices on a regular basis validates that you are taking advantage of the continually evolving AWS Cloud. Monitoring verifies that you are aware of any deviance from expected performance. Make trade-offs in your architecture to improve performance, such as using compression or caching, or relaxing consistency requirements. 

# Best practices


**Topics**
+ [

# Architecture selection
](perf-arch.md)
+ [

# Compute and hardware
](perf-compute.md)
+ [

# Data management
](perf-data.md)
+ [

# Networking and content delivery
](perf-networking.md)
+ [

# Process and culture
](perf-process.md)

# Architecture selection


 The optimal solution for a particular workload varies, and solutions often combine multiple approaches. Well-Architected workloads use multiple solutions and allow different features to improve performance. 

 AWS resources are available in many types and configurations, which makes it easier to find an approach that closely matches your needs. You can also find options that are not easily achievable with on-premises infrastructure. For example, a managed service such as Amazon DynamoDB provides a fully managed NoSQL database with single-digit millisecond latency at any scale. 

 The following question focuses on these considerations for performance efficiency. (For a list of performance efficiency questions and best practices, see the [Appendix](a-performance-efficiency.md).). 


| PERF 1:  How do you select appropriate cloud resources and architecture patterns for your workload? | 
| --- | 
|  Often, multiple approaches are required for more effective performance across a workload. Well-Architected systems use multiple solutions and features to improve performance.  | 

# Compute and hardware


 The optimal compute choice for a particular workload can vary based on application design, usage patterns, and configuration settings. Architectures may use different compute choices for various components and allow different features to improve performance. Selecting the wrong compute choice for an architecture can lead to lower performance efficiency. 

 In AWS, compute is available in three forms: instances, containers, and functions: 
+  **Instances** are virtualized servers, permitting you to change their capabilities with a button or an API call. Because resource decisions in the cloud aren’t fixed, you can experiment with different server types. At AWS, these virtual server instances come in different families and sizes, and they offer a wide variety of capabilities, including solid-state drives (SSDs) and graphics processing units (GPUs). 
+  **Containers** are a method of operating system virtualization that permit you to run an application and its dependencies in resource-isolated processes. AWS Fargate is serverless compute for containers or Amazon EC2 can be used if you need control over the installation, configuration, and management of your compute environment. You can also choose from multiple container orchestration platforms: Amazon Elastic Container Service (ECS) or Amazon Elastic Kubernetes Service (EKS). 
+  **Functions** abstract the run environment from the code you want to apply. For example, AWS Lambda permits you to run code without running an instance. 

 The following question focuses on these considerations for performance efficiency. 


| PERF 2:  How do you select and use compute resources in your workload? | 
| --- | 
| The more efficient compute solution for a workload varies based on application design, usage patterns, and configuration settings. Architectures can use different compute solutions for various components and turn on different features to improve performance. Selecting the wrong compute solution for an architecture can lead to lower performance efficiency. | 

# Data management


 The optimal data management solution for a particular system varies based on the kind of data type (block, file, or object), access patterns (random or sequential), required throughput, frequency of access (online, offline, archival), frequency of update (WORM, dynamic), and availability and durability constraints. Well-Architected workloads use purpose-built data stores which allow different features to improve performance. 

 In AWS, storage is available in three forms: object, block, and file: 
+  **Object storage** provides a scalable, durable platform to make data accessible from any internet location for user-generated content, active archive, serverless computing, Big Data storage or backup and recovery. Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. Amazon S3 is designed for 99.999999999% (11 9's) of durability, and stores data for millions of applications for companies all around the world. 
+  **Block storage** provides highly available, consistent, low-latency block storage for each virtual host and is analogous to direct-attached storage (DAS) or a Storage Area Network (SAN). Amazon Elastic Block Store (Amazon EBS) is designed for workloads that require persistent storage accessible by EC2 instances that helps you tune applications with the right storage capacity, performance and cost. 
+  **File storage** provides access to a shared file system across multiple systems. File storage solutions like Amazon Elastic File System (Amazon EFS) are ideal for use cases such as large content repositories, development environments, media stores, or user home directories. Amazon FSx makes it efficient and cost effective to launch and run popular file systems so you can leverage the rich feature sets and fast performance of widely used open source and commercially-licensed file systems. 

 The following question focuses on these considerations for performance efficiency. 


| PERF 3:  How do you store, manage, and access data in your workload? | 
| --- | 
|  The more efficient storage solution for a system varies based on the kind of access operation (block, file, or object), patterns of access (random or sequential), required throughput, frequency of access (online, offline, archival), frequency of update (WORM, dynamic), and availability and durability constraints. Well-architected systems use multiple storage solutions and turn on different features to improve performance and use resources efficiently.  | 

# Networking and content delivery


 The optimal networking solution for a workload varies based on latency, throughput requirements, jitter, and bandwidth. Physical constraints, such as user or on-premises resources, determine location options. These constraints can be offset with edge locations or resource placement. 

 On AWS, networking is virtualized and is available in a number of different types and configurations. This makes it easier to match your networking needs. AWS offers product features (for example, Enhanced Networking, Amazon EC2 networking optimized instances, Amazon S3 transfer acceleration, and dynamic Amazon CloudFront) to optimize network traffic. AWS also offers networking features (for example, Amazon Route 53 latency routing, Amazon VPC endpoints, AWS Direct Connect, and AWS Global Accelerator) to reduce network distance or jitter. 

 The following question focuses on these considerations for performance efficiency. 


| PERF 4:  How do you select and configure networking resources in your workload? | 
| --- | 
|  This question includes guidance and best practices to design, configure, and operate efficient networking and content delivery solutions in the cloud.  | 

# Process and culture


 When architecting workloads, there are principles and practices that you can adopt to help you better run efficient high-performing cloud workloads. To adopt a culture that fosters performance efficiency of cloud workloads, consider these key principles and practices. 

 Consider these key principles to build this culture: 
+  **Infrastructure as code:** Define your infrastructure as code using approaches such as AWS CloudFormation templates. The use of templates allows you to place your infrastructure into source control alongside your application code and configurations. This allows you to apply the same practices you use to develop software in your infrastructure so you can iterate rapidly. 
+  **Deployment pipeline:** Use a continuous integration/continuous deployment (CI/CD) pipeline (for example, source code repository, build systems, deployment, and testing automation) to deploy your infrastructure. This allows you to deploy in a repeatable, consistent, and low-cost fashion as you iterate. 
+  **Well-defined metrics:** Set up and monitor metrics to capture key performance indicators (KPIs). We recommend that you use both technical and business metrics. For websites or mobile apps, key metrics are capturing time-to-first-byte or rendering. Other generally applicable metrics include thread count, garbage collection rate, and wait states. Business metrics, such as the aggregate cumulative cost per request, can alert you to ways to drive down costs. Carefully consider how you plan to interpret metrics. For example, you could choose the maximum or 99th percentile instead of the average. 
+  **Performance test automatically:** As part of your deployment process, automatically start performance tests after the quicker running tests have passed successfully. The automation should create a new environment, set up initial conditions such as test data, and then run a series of benchmarks and load tests. Results from these tests should be tied back to the build so you can track performance changes over time. For long-running tests, you can make this part of the pipeline asynchronous from the rest of the build. Alternatively, you could run performance tests overnight using Amazon EC2 Spot Instances. 
+  **Load generation:** You should create a series of test scripts that replicate synthetic or prerecorded user journeys. These scripts should be idempotent and not coupled, and you might need to include *pre-warming* scripts to yield valid results. As much as possible, your test scripts should replicate the behavior of usage in production. You can use software or software-as-a-service (SaaS) solutions to generate the load. Consider using [AWS Marketplace](https://aws.amazon.com/marketplace/) solutions and [Spot Instances](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-spot-instances.html) — they can be cost-effective ways to generate the load. 
+  **Performance visibility:** Key metrics should be visible to your team, especially metrics against each build version. This allows you to see any significant positive or negative trend over time. You should also display metrics on the number of errors or exceptions to make sure you are testing a working system. 
+ **Visualization:** Use visualization techniques that make it clear where performance issues, hot spots, wait states, or low utilization is occurring. Overlay performance metrics over architecture diagrams — call graphs or code can help identify issues quickly. 
+  **Regular review process:** Architectures performing poorly is usually the result of a non-existent or broken performance review process. If your architecture is performing poorly, implementing a performance review process allows you to drive iterative improvement. 
+  **Continual optimization:** Adopt a culture to continually optimize the performance efficiency of your cloud workload. 

 The following question focuses on these considerations for performance efficiency. 


| PERF 5:  What process do you use to support more performance efficiency for your workload?  | 
| --- | 
|  When architecting workloads, there are principles and practices that you can adopt to help you better run efficient high-performing cloud workloads. To adopt a culture that fosters performance efficiency of cloud workloads, consider these key principles and practices.  | 

# Resources


 Refer to the following resources to learn more about our best practices for Performance Efficiency. 

## Documentation

+  [Amazon S3 Performance Optimization](https://docs.aws.amazon.com/AmazonS3/latest/dev/PerformanceOptimization.html?ref=wellarchitected-wp) 
+  [Amazon EBS Volume Performance](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSPerformance.html?ref=wellarchitected-wp) 

## Whitepaper

+  [Performance Efficiency Pillar](https://docs.aws.amazon.com/wellarchitected/latest/performance-efficiency-pillar/welcome.html?ref=wellarchitected-wp) 

## Video

+  [AWS re:Invent 2019: Amazon EC2 foundations (CMP211-R2)](https://www.youtube.com/watch?v=kMMybKqC2Y0&ref=wellarchitected-wp) 
+  [AWS re:Invent 2019: Leadership session: Storage state of the union (STG201-L)](https://www.youtube.com/watch?v=39vAsGi6eEI&ref=wellarchitected-wp) 
+  [AWS re:Invent 2019: Leadership session: AWS purpose-built databases (DAT209-L)](https://www.youtube.com/watch?v=q81TVuV5u28&ref=wellarchitected-wp) 
+  [AWS re:Invent 2019: Connectivity to AWS and hybrid AWS network architectures (NET317-R1)](https://www.youtube.com/watch?v=eqW6CPb58gs&ref=wellarchitected-wp) 
+  [AWS re:Invent 2019: Powering next-gen Amazon EC2: Deep dive into the Nitro system (CMP303-R2)](https://www.youtube.com/watch?v=rUY-00yFlE4&ref=wellarchitected-wp) 
+  [AWS re:Invent 2019: Scaling up to your first 10 million users (ARC211-R)](https://www.youtube.com/watch?v=kKjm4ehYiMs&ref=wellarchitected-wp) 

# Cost optimization
Cost optimization

 The Cost Optimization pillar includes the ability to run systems to deliver business value at the lowest price point. 

 The cost optimization pillar provides an overview of design principles, best practices, and questions. You can find prescriptive guidance on implementation in the [Cost Optimization Pillar whitepaper](https://docs.aws.amazon.com/wellarchitected/latest/cost-optimization-pillar/welcome.html?ref=wellarchitected-wp). 

**Topics**
+ [

# Design principles
](cost-dp.md)
+ [

# Definition
](cost-def.md)
+ [

# Best practices
](cost-bp.md)
+ [

# Resources
](cost-resources.md)

# Design principles


 There are five design principles for cost optimization in the cloud: 
+  **Implement Cloud Financial Management**: To achieve financial success and accelerate business value realization in the cloud, invest in Cloud Financial Management and Cost Optimization. Your organization should dedicate time and resources to build capability in this new domain of technology and usage management. Similar to your Security or Operational Excellence capability, you need to build capability through knowledge building, programs, resources, and processes to become a cost-efficient organization. 
+  **Adopt a consumption model**: Pay only for the computing resources that you require and increase or decrease usage depending on business requirements, not by using elaborate forecasting. For example, development and test environments are typically only used for eight hours a day during the work week. You can stop these resources when they are not in use for a potential cost savings of 75% (40 hours versus 168 hours). 
+  **Measure overall efficiency**: Measure the business output of the workload and the costs associated with delivering it. Use this measure to know the gains you make from increasing output and reducing costs. 
+  **Stop spending money on undifferentiated heavy lifting**: AWS does the heavy lifting of data center operations like racking, stacking, and powering servers. It also removes the operational burden of managing operating systems and applications with managed services. This permits you to focus on your customers and business projects rather than on IT infrastructure. 
+  **Analyze and attribute expenditure**: The cloud makes it simple to accurately identify the usage and cost of systems, which then permits transparent attribution of IT costs to individual workload owners. This helps measure return on investment (ROI) and gives workload owners an opportunity to optimize their resources and reduce costs. 

# Definition


 There are five best practice areas for cost optimization in the cloud: 
+  **Practice Cloud Financial Management** 
+  **Expenditure and usage awareness** 
+  **Cost-effective resources** 
+  **Manage demand and supply resources** 
+  **Optimize over time** 

 As with the other pillars within the Well-Architected Framework, there are tradeoffs to consider, for example, whether to optimize for speed-to-market or for cost. In some cases, it’s more efficient to optimize for speed, going to market quickly, shipping new features, or meeting a deadline, rather than investing in upfront cost optimization. Design decisions are sometimes directed by haste rather than data, and the temptation always exists to overcompensate “just in case” rather than spend time benchmarking for the most cost-optimal deployment. This might lead to over-provisioned and under-optimized deployments. However, this is a reasonable choice when you must “lift and shift” resources from your on-premises environment to the cloud and then optimize afterwards. Investing the right amount of effort in a cost optimization strategy up front permits you to realize the economic benefits of the cloud more readily by achieving a consistent adherence to best practices and avoiding unnecessary over provisioning. The following sections provide techniques and best practices for both the initial and ongoing implementation of Cloud Financial Management and cost optimization of your workloads. 

# Best practices


**Topics**
+ [

# Practice Cloud Financial Management
](cost-cfm.md)
+ [

# Expenditure and usage awareness
](cost-aware.md)
+ [

# Cost-effective resources
](cost-cereso.md)
+ [

# Manage demand and supply resources
](cost-mandem.md)
+ [

# Optimize over time
](cost-opti.md)

# Practice Cloud Financial Management


 With the adoption of cloud, technology teams innovate faster due to shortened approval, procurement, and infrastructure deployment cycles. A new approach to financial management in the cloud is required to realize business value and financial success. This approach is Cloud Financial Management, and builds capability across your organization by implementing organizational wide knowledge building, programs, resources, and processes. 

 Many organizations are composed of many different units with different priorities. The ability to align your organization to an agreed set of financial objectives, and provide your organization the mechanisms to meet them, will create a more efficient organization. A capable organization will innovate and build faster, be more agile and adjust to any internal or external factors. 

 In AWS you can use Cost Explorer, and optionally Amazon Athena and Amazon QuickSight with the Cost and Usage Report (CUR), to provide cost and usage awareness throughout your organization. AWS Budgets provides proactive notifications for cost and usage. The AWS blogs provide information on new services and features to verify you keep up to date with new service releases. 

 The following question focuses on these considerations for cost optimization. (For a list of cost optimization questions and best practices, see the [Appendix](a-cost-optimization.md).). 


| COST 1:  How do you implement cloud financial management? | 
| --- | 
| Implementing Cloud Financial Management helps organizations realize business value and financial success as they optimize their cost and usage and scale on AWS. | 

 When building a cost optimization function, use members and supplement the team with experts in CFM and cost optimization. Existing team members will understand how the organization currently functions and how to rapidly implement improvements. Also consider including people with supplementary or specialist skill sets, such as analytics and project management. 

 When implementing cost awareness in your organization, improve or build on existing programs and processes. It is much faster to add to what exists than to build new processes and programs. This will result in achieving outcomes much faster. 

# Expenditure and usage awareness


 The increased flexibility and agility that the cloud provides encourages innovation and fast-paced development and deployment. It decreases the manual processes and time associated with provisioning on-premises infrastructure, including identifying hardware specifications, negotiating price quotations, managing purchase orders, scheduling shipments, and then deploying the resources. However, the ease of use and virtually unlimited on-demand capacity requires a new way of thinking about expenditures. 

 Many businesses are composed of multiple systems run by various teams. The capability to attribute resource costs to the individual organization or product owners drives efficient usage behavior and helps reduce waste. Accurate cost attribution permits you to know which products are truly profitable, and permits you to make more informed decisions about where to allocate budget. 

 In AWS, you create an account structure with AWS Organizations or AWS Control Tower, which provides separation and assists in allocation of your costs and usage. You can also use resource tagging to apply business and organization information to your usage and cost. Use AWS Cost Explorer for visibility into your cost and usage, or create customized dashboards and analytics with Amazon Athena and Amazon QuickSight. Controlling your cost and usage is done by notifications through AWS Budgets, and controls using AWS Identity and Access Management (IAM), and Service Quotas. 

 The following questions focus on these considerations for cost optimization. 


| COST 2:  How do you govern usage? | 
| --- | 
| Establish policies and mechanisms to validate that appropriate costs are incurred while objectives are achieved. By employing a checks-and-balances approach, you can innovate without overspending.  | 


| COST 3:  How do you monitor usage and cost? | 
| --- | 
| Establish policies and procedures to monitor and appropriately allocate your costs. This permits you to measure and improve the cost efficiency of this workload. | 


| COST 4:  How do you decommission resources? | 
| --- | 
| Implement change control and resource management from project inception to end-of-life. This facilitates shutting down unused resources to reduce waste. | 

 You can use cost allocation tags to categorize and track your AWS usage and costs. When you apply tags to your AWS resources (such as EC2 instances or S3 buckets), AWS generates a cost and usage report with your usage and your tags. You can apply tags that represent organization categories (such as cost centers, workload names, or owners) to organize your costs across multiple services. 

 Verify that you use the right level of detail and granularity in cost and usage reporting and monitoring. For high level insights and trends, use daily granularity with AWS Cost Explorer. For deeper analysis and inspection use hourly granularity in AWS Cost Explorer, or Amazon Athena and Amazon Quick with the Cost and Usage Report (CUR) at an hourly granularity. 

 Combining tagged resources with entity lifecycle tracking (employees, projects) makes it possible to identify orphaned resources or projects that are no longer generating value to the organization and should be decommissioned. You can set up billing alerts to notify you of predicted overspending. 

# Cost-effective resources


 Using the appropriate instances and resources for your workload is key to cost savings. For example, a reporting process might take five hours to run on a smaller server but one hour to run on a larger server that is twice as expensive. Both servers give you the same outcome, but the smaller server incurs more cost over time. 

 A well-architected workload uses the most cost-effective resources, which can have a significant and positive economic impact. You also have the opportunity to use managed services to reduce costs. For example, rather than maintaining servers to deliver email, you can use a service that charges on a per-message basis. 

 AWS offers a variety of flexible and cost-effective pricing options to acquire instances from Amazon EC2 and other services in a way that more effectively fits your needs. *On-Demand* *Instances* permit you to pay for compute capacity by the hour, with no minimum commitments required. *Savings Plans and Reserved Instances* offer savings of up to 75% off On-Demand pricing. With Spot Instances, you can leverage unused Amazon EC2 capacity and offer savings of up to 90% off On-Demand pricing. *Spot Instances* are appropriate where the system can tolerate using a fleet of servers where individual servers can come and go dynamically, such as stateless web servers, batch processing, or when using HPC and big data. 

 Appropriate service selection can also reduce usage and costs; such as CloudFront to minimize data transfer, or decrease costs, such as utilizing Amazon Aurora on Amazon RDS to remove expensive database licensing costs. 

 The following questions focus on these considerations for cost optimization. 


| COST 5:  How do you evaluate cost when you select services? | 
| --- | 
| Amazon EC2, Amazon EBS, and Amazon S3 are building-block AWS services. Managed services, such as Amazon RDS and Amazon DynamoDB, are higher level, or application level, AWS services. By selecting the appropriate building blocks and managed services, you can optimize this workload for cost. For example, using managed services, you can reduce or remove much of your administrative and operational overhead, freeing you to work on applications and business-related activities. | 


| COST 6:  How do you meet cost targets when you select resource type, size and number? | 
| --- | 
| Verify that you choose the appropriate resource size and number of resources for the task at hand. You minimize waste by selecting the most cost effective type, size, and number. | 


| COST 7:  How do you use pricing models to reduce cost? | 
| --- | 
| Use the pricing model that is most appropriate for your resources to minimize expense. | 


| COST 8:  How do you plan for data transfer charges? | 
| --- | 
| Verify that you plan and monitor data transfer charges so that you can make architectural decisions to minimize costs. A small yet effective architectural change can drastically reduce your operational costs over time.  | 

 By factoring in cost during service selection, and using tools such as Cost Explorer and AWS Trusted Advisor to regularly review your AWS usage, you can actively monitor your utilization and adjust your deployments accordingly. 

# Manage demand and supply resources


 When you move to the cloud, you pay only for what you need. You can supply resources to match the workload demand at the time they’re needed, this decreases the need for costly and wasteful over provisioning. You can also modify the demand, using a throttle, buffer, or queue to smooth the demand and serve it with less resources resulting in a lower cost, or process it at a later time with a batch service. 

 In AWS, you can automatically provision resources to match the workload demand. Auto Scaling using demand or time-based approaches permit you to add and remove resources as needed. If you can anticipate changes in demand, you can save more money and validate that your resources match your workload needs. You can use Amazon API Gateway to implement throttling, or Amazon SQS to implementing a queue in your workload. These will both permit you to modify the demand on your workload components. 

 The following question focuses on these considerations for cost optimization. 


| COST 9:  How do you manage demand, and supply resources? | 
| --- | 
| For a workload that has balanced spend and performance, verify that everything you pay for is used and avoid significantly underutilizing instances. A skewed utilization metric in either direction has an adverse impact on your organization, in either operational costs (degraded performance due to over-utilization), or wasted AWS expenditures (due to over-provisioning). | 

 When designing to modify demand and supply resources, actively think about the patterns of usage, the time it takes to provision new resources, and the predictability of the demand pattern. When managing demand, verify you have a correctly sized queue or buffer, and that you are responding to workload demand in the required amount of time. 

# Optimize over time


 As AWS releases new services and features, it's a best practice to review your existing architectural decisions to verify they continue to be the most cost effective. As your requirements change, be aggressive in decommissioning resources, entire services, and systems that you no longer require. 

 Implementing new features or resource types can optimize your workload incrementally, while minimizing the effort required to implement the change. This provides continual improvements in efficiency over time and provides you remain on the most updated technology to reduce operating costs. You can also replace or add new components to the workload with new services. This can provide significant increases in efficiency, so it's essential to regularly review your workload, and implement new services and features. 

 The following questions focus on these considerations for cost optimization. 


| COST 10:  How do you evaluate new services? | 
| --- | 
| As AWS releases new services and features, it's a best practice to review your existing architectural decisions to verify they continue to be the most cost effective. | 

 When regularly reviewing your deployments, assess how newer services can help save you money. For example, Amazon Aurora on Amazon RDS can reduce costs for relational databases. Using serverless such as Lambda can remove the need to operate and manage instances to run code. 


| COST 11:  How do you evaluate the cost of effort? | 
| --- | 
|  Evaluate the cost of effort for operations in the cloud, review your time-consuming cloud operations, and automate them to reduce human efforts and cost by adopting related AWS services, third-party products, or custom tools.  | 

# Resources


 Refer to the following resources to learn more about our best practices for Cost Optimization. 

## Documentation

+  [AWS Documentation](https://docs.aws.amazon.com/index.html?ref=wellarchitected-wp) 

## Whitepaper

+  [Cost Optimization Pillar](https://docs.aws.amazon.com/wellarchitected/latest/cost-optimization-pillar/welcome.html?ref=wellarchitected-wp) 

# Sustainability
Major update

Sustainability Pillar added to the framework.

The Sustainability pillar focuses on environmental impacts, especially energy consumption and efficiency, since they are important levers for architects to inform direct action to reduce resource usage. You can find prescriptive guidance on implementation in the [Sustainability Pillar whitepaper](https://docs.aws.amazon.com/wellarchitected/latest/sustainability-pillar/sustainability-pillar.html?ref=wellarchitected-wp). 

**Topics**
+ [

# Design principles
](sus-design-principles.md)
+ [

# Definition
](sus-def.md)
+ [

# Best practices
](sus-bp.md)
+ [

# Resources
](sus-resources.md)

# Design principles


 There are six design principles for sustainability in the cloud: 
+  **Understand your impact:** Measure the impact of your cloud workload and model the future impact of your workload. Include all sources of impact, including impacts resulting from customer use of your products, and impacts resulting from their eventual decommissioning and retirement. Compare the productive output with the total impact of your cloud workloads by reviewing the resources and emissions required per unit of work. Use this data to establish key performance indicators (KPIs), evaluate ways to improve productivity while reducing impact, and estimate the impact of proposed changes over time. 
+  **Establish sustainability goals:** For each cloud workload, establish long-term sustainability goals such as reducing the compute and storage resources required per transaction. Model the return on investment of sustainability improvements for existing workloads, and give owners the resources they must invest in sustainability goals. Plan for growth, and architect your workloads so that growth results in reduced impact intensity measured against an appropriate unit, such as per user or per transaction. Goals help you support the wider sustainability goals of your business or organization, identify regressions, and prioritize areas of potential improvement. 
+  **Maximize utilization:** Right-size workloads and implement efficient design to verify high utilization and maximize the energy efficiency of the underlying hardware. Two hosts running at 30% utilization are less efficient than one host running at 60% due to baseline power consumption per host. At the same time, reduce or minimize idle resources, processing, and storage to reduce the total energy required to power your workload. 
+  **Anticipate and adopt new, more efficient hardware and software offerings:** Support the upstream improvements your partners and suppliers make to help you reduce the impact of your cloud workloads. Continually monitor and evaluate new, more efficient hardware and software offerings. Design for flexibility to permit the rapid adoption of new efficient technologies. 
+  **Use managed services:** Sharing services across a broad customer base helps maximize resource utilization, which reduces the amount of infrastructure needed to support cloud workloads. For example, customers can share the impact of common data center components like power and networking by migrating workloads to the AWS Cloud and adopting managed services, such as AWS Fargate for serverless containers, where AWS operates at scale and is responsible for their efficient operation. Use managed services that can help minimize your impact, such as automatically moving infrequently accessed data to cold storage with Amazon S3 Lifecycle configurations or Amazon EC2 Auto Scaling to adjust capacity to meet demand.
+  **Reduce the downstream impact of your cloud workloads:** Reduce the amount of energy or resources required to use your services. Reduce the need for customers to upgrade their devices to use your services. Test using device farms to understand expected impact and test with customers to understand the actual impact from using your services. 

# Definition


 There are six best practice areas for sustainability in the cloud: 
+ Region selection
+ Alignment to demand
+ Software and architecture
+ Data
+ Hardware and services
+ Process and culture

 Sustainability in the cloud is a nearly continuous effort focused primarily on energy reduction and efficiency across all components of a workload by achieving the maximum benefit from the resources provisioned and minimizing the total resources required. This effort can range from the initial selection of an efficient programming language, adoption of modern algorithms, use of efficient data storage techniques, deploying to correctly sized and efficient compute infrastructure, and minimizing requirements for high-powered end user hardware. 

# Best practices


**Topics**
+ [

# Region selection
](sus-region-selection.md)
+ [

# Alignment to demand
](sus-user-behavior-patterns.md)
+ [

# Software and architecture
](sus-software-architecture-patterns.md)
+ [

# Data management
](sus-data-patterns.md)
+ [

# Hardware and services
](sus-hardware-patterns.md)
+ [

# Process and culture
](sus-development-deployment-patterns.md)

# Region selection


The choice of Region for your workload significantly affects its KPIs, including performance, cost, and carbon footprint. To improve these KPIs, you should choose Regions for your workloads based on both business requirements and sustainability goals.

 The following question focuses on these considerations for sustainability. (For a list of sustainability questions and best practices, see the [Appendix](a-sustainability.md).)


| SUS 1:  How do you select Regions for your workload? | 
| --- | 
| The choice of Region for your workload significantly affects its KPIs, including performance, cost, and carbon footprint. To improve these KPIs, you should choose Regions for your workloads based on both business requirements and sustainability goals. | 

# Alignment to demand


The way users and applications consume your workloads and other resources can help you identify improvements to meet sustainability goals. Scale infrastructure to continually match demand and verify that you use only the minimum resources required to support your users. Align service levels to customer needs. Position resources to limit the network required for users and applications to consume them. Remove unused assets. Provide your team members with devices that support their needs and minimize their sustainability impact.

 The following question focuses on this consideration for sustainability:


| SUS 2:  How do you align cloud resources to your demand? | 
| --- | 
|  The way users and applications consume your workloads and other resources can help you identify improvements to meet sustainability goals. Scale infrastructure to continually match demand and verify that you use only the minimum resources required to support your users. Align service levels to customer needs. Position resources to limit the network required for users and applications to consume them. Remove unused assets. Provide your team members with devices that support their needs and minimize their sustainability impact.  | 

Scale infrastructure with user load: Identify periods of low or no utilization and scale resources to reduce excess capacity and improve efficiency.

Align SLAs with sustainability goals: Define and update service level agreements (SLAs) such as availability or data retention periods to minimize the number of resources required to support your workload while continuing to meet business requirements.

Decrease creation and maintenance of unused assets: Analyze application assets (such as pre-compiled reports, datasets, and static images) and asset access patterns to identify redundancy, underutilization, and potential decommission targets. Consolidate generated assets with redundant content (for example, monthly reports with overlapping or common datasets and outputs) to reduce the resources consumed when duplicating outputs. Decommission unused assets (for example, images of products that are no longer sold) to release consumed resources and reduce the number of resources used to support the workload. 

Optimize geographic placement of workloads for user locations: Analyze network access patterns to identify where your customers are connecting from geographically. Select Regions and services that reduce the distance that network traffic must travel to decrease the total network resources required to support your workload. 

Optimize team member resources for activities performed: Optimize resources provided to team members to minimize the sustainability impact while supporting their needs. For example, perform complex operations, such as rendering and compilation, on highly used shared cloud desktops instead of on under-utilized high-powered single user systems.

# Software and architecture


Implement patterns for performing load smoothing and maintaining consistent high utilization of deployed resources to minimize the resources consumed. Components might become idle from lack of use because of changes in user behavior over time. Revise patterns and architecture to consolidate under-utilized components to increase overall utilization. Retire components that are no longer required. Understand the performance of your workload components, and optimize the components that consume the most resources. Be aware of the devices that your customers use to access your services, and implement patterns to minimize the need for device upgrades. 

 The following question focuses on these considerations for sustainability:


| SUS 3:  How do you take advantage of software and architecture patterns to support your sustainability goals? | 
| --- | 
|  Implement patterns for performing load smoothing and maintaining consistent high utilization of deployed resources to minimize the resources consumed. Components might become idle from lack of use because of changes in user behavior over time. Revise patterns and architecture to consolidate under-utilized components to increase overall utilization. Retire components that are no longer required. Understand the performance of your workload components, and optimize the components that consume the most resources. Be aware of the devices that your customers use to access your services, and implement patterns to minimize the need for device upgrades.   | 

Optimize software and architecture for asynchronous and scheduled jobs: Use efficient software designs and architectures to minimize the average resources required per unit of work. Implement mechanisms that result in even utilization of components to reduce resources that are idle between tasks and minimize the impact of load spikes. 

Remove or refactor workload components with low or no use: Monitor workload activity to identify changes in utilization of individual components over time. Remove components that are unused and no longer required, and refactor components with little utilization, to limit wasted resources.

Optimize areas of code that consume the most time or resources: Monitor workload activity to identify application components that consume the most resources. Optimize the code that runs within these components to minimize resource usage while maximizing performance. 

Optimize impact on customer devices and equipment: Understand the devices and equipment that your customers use to consume your services, their expected lifecycle, and the financial and sustainability impact of replacing those components. Implement software patterns and architectures to minimize the need for customers to replace devices and upgrade equipment. For example, implement new features using code that is backward compatible with earlier hardware and operating system versions, or manage the size of payloads so they don’t exceed the storage capacity of the target device. 

Use software patterns and architectures that most effectively supports data access and storage patterns: Understand how data is used within your workload, consumed by your users, transferred, and stored. Select technologies to minimize data processing and storage requirements.

# Data management


 The following question focuses on these considerations for sustainability:


| SUS 4:  How do you take advantage of data management policies and patterns to support your sustainability goals? | 
| --- | 
|  Implement data management practices to reduce the provisioned storage required to support your workload, and the resources required to use it. Understand your data, and use storage technologies and configurations that most effectively supports the business value of the data and how it’s used. Lifecycle data to more efficient, less performant storage when requirements decrease, and delete data that’s no longer required.  | 

Implement a data classification policy: Classify data to understand its significance to business outcomes. Use this information to determine when you can move data to more energy-efficient storage or safely delete it. 

Use technologies that support data access and storage patterns: Use storage that most effectively supports how your data is accessed and stored to minimize the resources provisioned while supporting your workload. For example, solid state devices (SSDs) are more energy intensive than magnetic drives and should be used only for active data use cases. Use energy-efficient, archival-class storage for infrequently accessed data. 

Use lifecycle policies to delete unnecessary data: Manage the lifecycle of all your data and automatically enforce deletion timelines to minimize the total storage requirements of your workload.

Minimize over-provisioning in block storage: To minimize total provisioned storage, create block storage with size allocations that are appropriate for the workload. Use elastic volumes to expand storage as data grows without having to resize storage attached to compute resources. Regularly review elastic volumes and shrink over-provisioned volumes to fit the current data size. 

Remove unneeded or redundant data: Duplicate data only when necessary to minimize total storage consumed. Use backup technologies that deduplicate data at the file and block level. Limit the use of Redundant Array of Independent Drives (RAID) configurations except where required to meet SLAs.

Use shared file systems or object storage to access common data: Adopt shared storage and single sources of truth to avoid data duplication and reduce the total storage requirements of your workload. Fetch data from shared storage only as needed. Detach unused volumes to release resources. Minimize data movement across networks: Use shared storage and access data from Regional data stores to minimize the total networking resources required to support data movement for your workload. 

Back up data only when difficult to recreate: To minimize storage consumption, only back up data that has business value or is required to satisfy compliance requirements. Examine backup policies and exclude ephemeral storage that doesn’t provide value in a recovery scenario. 

# Hardware and services


Look for opportunities to reduce workload sustainability impacts by making changes to your hardware management practices. Minimize the amount of hardware needed to provision and deploy, and select the most efficient hardware and services for your individual workload.

 The following question focuses on these considerations for sustainability:


| SUS 5:  How do you select and use cloud hardware and services in your architecture to support your sustainability goals? | 
| --- | 
|  Look for opportunities to reduce workload sustainability impacts by making changes to your hardware management practices. Minimize the amount of hardware needed to provision and deploy, and select the most efficient hardware and services for your individual workload.  | 

Use the minimum amount of hardware to meet your needs: Using the capabilities of the cloud, you can make frequent changes to your workload implementations. Update deployed components as your needs change. 

Use instance types with the least impact: Continually monitor the release of new instance types and take advantage of energy efficiency improvements, including those instance types designed to support specific workloads such as machine learning training and inference, and video transcoding.

Use managed services: Managed services shift responsibility for maintaining high average utilization, and sustainability optimization of the deployed hardware, to AWS. Use managed services to distribute the sustainability impact of the service across all tenants of the service, reducing your individual contribution. 

Optimize your use of GPUs: Graphics processing units (GPUs) can be a source of high-power consumption, and many GPU workloads are highly variable, such as rendering, transcoding, and machine learning training and modeling. Only run GPUs instances for the time needed, and decommission them with automation when not required to minimize resources consumed. 

# Process and culture


Look for opportunities to reduce your sustainability impact by making changes to your development, test, and deployment practices.

 The following question focuses on these considerations for sustainability:


| SUS 6:  How do your organizational processes support your sustainability goals? | 
| --- | 
|  Look for opportunities to reduce your sustainability impact by making changes to your development, test, and deployment practices.  | 

Adopt operations that can rapidly introduce sustainability improvements: Test and validate potential improvements before deploying them to production. Account for the cost of testing when calculating potential future benefit of an improvement. Develop low-cost testing operations to drive delivery of small improvements. 

Keep your workload up to date: Up-to-date operating systems, libraries, and applications can improve workload efficiency and create adoption of more efficient technologies. Up-to-date software might also include features to measure the sustainability impact of your workload more accurately, as vendors deliver features to meet their own sustainability goals.

Increase utilization of build environments: Use automation and infrastructure as code to bring up pre-production environments when needed and take them down when not used. A common pattern is to schedule periods of availability that coincide with the working hours of your development team members. Hibernation is a useful tool to preserve state and rapidly bring instances online only when needed. Use instance types with burst capacity, Spot Instances, elastic database services, containers, and other technologies to align development and test capacity with use. 

Use managed device farms for testing: Managed device farms spread the sustainability impact of hardware manufacturing and resource usage across multiple tenants. Managed device farms offer diverse device types so you can support earlier, less popular hardware, and avoid customer sustainability impact from unnecessary device upgrades.

# Resources


 Refer to the following resources to learn more about our best practices for sustainability. 

## Whitepaper

+  [Sustainability Pillar](https://docs.aws.amazon.com/wellarchitected/latest/sustainability-pillar/sustainability-pillar.html?ref=wellarchitected-wp) 

## Video

+  [The Climate Pledge](https://www.youtube.com/watch?v=oz9iO0EOpI0&ref=wellarchitected-wp)