# Data
**Topics**
+ [SUS 4 How do you take advantage of data management policies and patterns to support your sustainability goals?](sus-04.md)
# 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 more effectively support 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.
**Topics**
+ [SUS04-BP01 Implement a data classification policy](sus_sus_data_a2.md)
+ [SUS04-BP02 Use technologies that support data access and storage patterns](sus_sus_data_a3.md)
+ [SUS04-BP03 Use policies to manage the lifecycle of your datasets](sus_sus_data_a4.md)
+ [SUS04-BP04 Use elasticity and automation to expand block storage or file system](sus_sus_data_a5.md)
+ [SUS04-BP05 Remove unneeded or redundant data](sus_sus_data_a6.md)
+ [SUS04-BP06 Use shared file systems or storage to access common data](sus_sus_data_a7.md)
+ [SUS04-BP07 Minimize data movement across networks](sus_sus_data_a8.md)
+ [SUS04-BP08 Back up data only when difficult to recreate](sus_sus_data_a9.md)
# SUS04-BP01 Implement a data classification policy
Classify data to understand its criticality to business outcomes and choose the right energy-efficient storage tier to store the data.
**Common anti-patterns:**
+ You do not identify data assets with similar characteristics (such as sensitivity, business criticality, or regulatory requirements) that are being processed or stored.
+ You have not implemented a data catalog to inventory your data assets.
**Benefits of establishing this best practice:** Implementing a data classification policy allows you to determine the most energy-efficient storage tier for data.
**Level of risk exposed if this best practice is not established:** Medium
## Implementation guidance
Data classification involves identifying the types of data that are being processed and stored in an information system owned or operated by an organization. It also involves making a determination on the criticality of the data and the likely impact of a data compromise, loss, or misuse.
Implement data classification policy by working backwards from the contextual use of the data and creating a categorization scheme that takes into account the level of criticality of a given dataset to an organization’s operations.
### Implementation steps
+ **Perform data inventory:** Conduct an inventory of the various data types that exist for your workload.
+ **Group data:** Determine criticality, confidentiality, integrity, and availability of data based on risk to the organization. Use these requirements to group data into one of the data classification tiers that you adopt. As an example, see [Four simple steps to classify your data and secure your startup](https://aws.amazon.com/blogs/startups/four-simple-steps-to-classify-your-data-and-secure-your-startup/).
+ **Define data classification levels and policies:** For each data group, define data classification level (for example, public or confidential) and handling policies. Tag data accordingly. For more detail on data classification categories, see Data Classification whitepaper.
+ **Periodically review:** Periodically review and audit your environment for untagged and unclassified data. Use automation to identify this data, and classify and tag the data appropriately. As an example, see [Data Catalog and crawlers in AWS Glue](https://docs.aws.amazon.com/glue/latest/dg/catalog-and-crawler.html).
+ **Establish a data catalog:** Establish a data catalog that provides audit and governance capabilities.
+ **Documentation:** Document data classification policies and handling procedures for each data class.
## Resources
**Related documents:**
+ [Leveraging AWS Cloud to Support Data Classification](https://docs.aws.amazon.com/whitepapers/latest/data-classification/leveraging-aws-cloud-to-support-data-classification.html)
+ [Tag policies from AWS Organizations](https://docs.aws.amazon.com/organizations/latest/userguide/orgs_manage_policies_tag-policies.html)
**Related videos:**
+ [AWS re:Invent 2022 - Enabling agility with data governance on AWS](https://www.youtube.com/watch?v=vznDgJkoH7k)
+ [AWS re:Invent 2023 - Data protection and resilience with AWS storage ](https://www.youtube.com/watch?v=rdG8JV3Fhk4)
# SUS04-BP02 Use technologies that support data access and storage patterns
Use storage technologies that best support how your data is accessed and stored to minimize the resources provisioned while supporting your workload.
**Common anti-patterns:**
+ You assume that all workloads have similar data storage and access patterns.
+ You only use one tier of storage, assuming all workloads fit within that tier.
+ You assume that data access patterns will stay consistent over time.
**Benefits of establishing this best practice:** Selecting and optimizing your storage technologies based on data access and storage patterns will help you reduce the required cloud resources to meet your business needs and improve the overall efficiency of cloud workload.
**Level of risk exposed if this best practice is not established:** Low
## Implementation guidance
Select the storage solution that aligns best to your access patterns, or consider changing your access patterns to align with the storage solution to maximize performance efficiency.
### Implementation steps
+ **Evaluate data and access characteristics:** Evaluate your data characteristics and access pattern to collect the key characteristics of your storage needs. Key characteristics to consider include:
+ **Data type:** structured, semi-structured, unstructured
+ **Data growth:** bounded, unbounded
+ **Data durability:** persistent, ephemeral, transient
+ **Access patterns:** reads or writes, frequency, spiky, or consistent
+ **Choose the right storage technology:** Migrate data to the appropriate storage technology that supports your data characteristics and access pattern. Here are some examples of AWS storage technologies and their key characteristics:
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/wellarchitected/2024-06-27/framework/sus_sus_data_a3.html)
+ **Automate storage allocation:** For storage systems that are a fixed size, such as Amazon EBS or Amazon FSx, monitor the available storage space and automate storage allocation on reaching a threshold. You can leverage Amazon CloudWatch to collect and analyze different metrics for [Amazon EBS](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using_cloudwatch_ebs.html) and [Amazon FSx](https://docs.aws.amazon.com/fsx/latest/WindowsGuide/monitoring-cloudwatch.html).
+ **Choose the right storage class:** Choose the appropriate storage class for your data.
+ Amazon S3 storage classes can be configured at the object level. A single bucket can contain objects stored across all of the storage classes.
+ You can use [Amazon S3 Lifecycle policies](https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lifecycle-mgmt.html) to automatically transition objects between storage classes or remove data without any application changes. In general, you have to make a trade-off between resource efficiency, access latency, and reliability when considering these storage mechanisms.
## Resources
**Related documents:**
+ [Amazon EBS volume types](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ebs-volume-types.html)
+ [Amazon EC2 instance store](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html)
+ [Amazon S3 Intelligent-Tiering](https://docs.aws.amazon.com/AmazonS3/latest/userguide/intelligent-tiering.html)
+ [ Amazon EBS I/O Characteristics ](https://docs.aws.amazon.com/AWSEC2/latest/WindowsGuide/ebs-io-characteristics.html)
+ [ Using Amazon S3 storage classes ](https://docs.aws.amazon.com/AmazonS3/latest/userguide/storage-class-intro.html)
+ [What is Amazon Glacier?](https://docs.aws.amazon.com/amazonglacier/latest/dev/introduction.html)
**Related videos:**
+ [AWS re:Invent 2023 - Improve Amazon EBS efficiency and be more cost-efficient ](https://www.youtube.com/watch?v=7-CB02rqiuw)
+ [AWS re:Invent 2023 - Optimizing storage price and performance with Amazon S3 ](https://www.youtube.com/watch?v=RxgYNrXPOLw)
+ [AWS re:Invent 2023 - Building and optimizing a data lake on Amazon S3 ](https://www.youtube.com/watch?v=mpQa_Zm1xW8)
+ [AWS re:Invent 2022 - Building modern data architectures on AWS](https://www.youtube.com/watch?v=Uk2CqEt5f0o)
+ [AWS re:Invent 2022 - Modernize apps with purpose-built databases ](https://www.youtube.com/watch?v=V-DiplATdi0)
+ [AWS re:Invent 2022 - Building data mesh architectures on AWS](https://www.youtube.com/watch?v=nGRvlobeM_U)
+ [AWS re:Invent 2023 - Deep dive into Amazon Aurora and its innovations ](https://www.youtube.com/watch?v=je6GCOZ22lI)
+ [AWS re:Invent 2023 - Advanced data modeling with Amazon DynamoDB ](https://www.youtube.com/watch?v=PVUofrFiS_A)
**Related examples:**
+ [ Amazon S3 Examples ](https://docs.aws.amazon.com/sdk-for-javascript/v2/developer-guide/s3-examples.html)
+ [AWS Purpose Built Databases Workshop ](https://catalog.us-east-1.prod.workshops.aws/workshops/93f64257-52be-4c12-a95b-c0a1ff3b7e2b/en-US)
+ [ Databases for Developers ](https://catalog.workshops.aws/db4devs/en-US)
+ [AWS Modern Data Architecture Immersion Day ](https://catalog.us-east-1.prod.workshops.aws/workshops/32f3e732-d67d-4c63-b967-c8c5eabd9ebf/en-US)
+ [ Build a Data Mesh on AWS](https://catalog.us-east-1.prod.workshops.aws/workshops/23e6326b-58ee-4ab0-9bc7-3c8d730eb851/en-US)
# SUS04-BP03 Use policies to manage the lifecycle of your datasets
Manage the lifecycle of all of your data and automatically enforce deletion to minimize the total storage required for your workload.
**Common anti-patterns:**
+ You manually delete data.
+ You do not delete any of your workload data.
+ You do not move data to more energy-efficient storage tiers based on its retention and access requirements.
**Benefits of establishing this best practice:** Using data lifecycle policies ensures efficient data access and retention in a workload.
**Level of risk exposed if this best practice is not established:** Medium
## Implementation guidance
Datasets usually have different retention and access requirements during their lifecycle. For example, your application may need frequent access to some datasets for a limited period of time. After that, those datasets are infrequently accessed.
To efficiently manage your datasets throughout their lifecycle, configure lifecycle policies, which are rules that define how to handle datasets.
With Lifecycle configuration rules, you can tell the specific storage service to transition a dataset to more energy-efficient storage tiers, archive it, or delete it.
**Implementation steps**
+ [Classify datasets in your workload.](https://docs.aws.amazon.com/wellarchitected/latest/sustainability-pillar/sus_sus_data_a2.html)
+ Define handling procedures for each data class.
+ Set automated lifecycle policies to enforce lifecycle rules. Here are some examples of how to set up automated lifecycle policies for different AWS storage services:
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/wellarchitected/2024-06-27/framework/sus_sus_data_a4.html)
+ Delete unused volumes, snapshots, and data that is out of its retention period. Leverage native service features like [Amazon DynamoDB Time To Live](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/TTL.html) or [Amazon CloudWatch log retention](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/Working-with-log-groups-and-streams.html#SettingLogRetention) for deletion.
+ Aggregate and compress data where applicable based on lifecycle rules.
## Resources
**Related documents:**
+ [Optimize your Amazon S3 Lifecycle rules with Amazon S3 Storage Class Analysis](https://docs.aws.amazon.com/AmazonS3/latest/userguide/analytics-storage-class.html)
+ [Evaluating Resources with AWS Config Rules](https://docs.aws.amazon.com/config/latest/developerguide/evaluate-config.html)
**Related videos:**
+ [AWS re:Invent 2021 - Amazon S3 Lifecycle best practices to optimize your storage spend ](https://www.youtube.com/watch?v=yGNXn7jOytA)
+ [AWS re:Invent 2023 - Optimizing storage price and performance with Amazon S3 ](https://www.youtube.com/watch?v=RxgYNrXPOLw)
+ [Simplify Your Data Lifecycle and Optimize Storage Costs With Amazon S3 Lifecycle](https://www.youtube.com/watch?v=53eHNSpaMJI)
+ [ Reduce Your Storage Costs Using Amazon S3 Storage Lens ](https://www.youtube.com/watch?v=A8qOBLM6ITY)
# SUS04-BP04 Use elasticity and automation to expand block storage or file system
Use elasticity and automation to expand block storage or file system as data grows to minimize the total provisioned storage.
**Common anti-patterns:**
+ You procure large block storage or file system for future need.
+ You overprovision the input and output operations per second (IOPS) of your file system.
+ You do not monitor the utilization of your data volumes.
**Benefits of establishing this best practice:** Minimizing over-provisioning for storage system reduces the idle resources and improves the overall efficiency of your workload.
**Level of risk exposed if this best practice is not established:** Medium
## Implementation guidance
Create block storage and file systems with size allocation, throughput, and latency that are appropriate for your workload. Use elasticity and automation to expand block storage or file system as data grows without having to over-provision these storage services.
### Implementation steps
+ For fixed size storage like [Amazon EBS](https://aws.amazon.com/ebs/), verify that you are monitoring the amount of storage used versus the overall storage size and create automation, if possible, to increase the storage size when reaching a threshold.
+ Use elastic volumes and managed block data services to automate allocation of additional storage as your persistent data grows. As an example, you can use [Amazon EBS Elastic Volumes](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ebs-modify-volume.html) to change volume size, volume type, or adjust the performance of your Amazon EBS volumes.
+ Choose the right storage class, performance mode, and throughput mode for your file system to address your business need, not exceeding that.
+ [ Amazon EFS performance ](https://docs.aws.amazon.com/efs/latest/ug/performance.html)
+ [ Amazon EBS volume performance on Linux instances ](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSPerformance.html)
+ Set target levels of utilization for your data volumes, and resize volumes outside of expected ranges.
+ Right size read-only volumes to fit the data.
+ Migrate data to object stores to avoid provisioning the excess capacity from fixed volume sizes on block storage.
+ Regularly review elastic volumes and file systems to terminate idle volumes and shrink over-provisioned resources to fit the current data size.
## Resources
**Related documents:**
+ [ Extend the file system after resizing an EBS volume ](https://docs.aws.amazon.com/ebs/latest/userguide/recognize-expanded-volume-linux.html)
+ [ Modify a volume using Amazon EBS Elastic Volumes ](https://docs.aws.amazon.com/ebs/latest/userguide/ebs-modify-volume.html)
+ [Amazon FSx Documentation](https://docs.aws.amazon.com/fsx/index.html)
+ [What is Amazon Elastic File System?](https://docs.aws.amazon.com/efs/latest/ug/whatisefs.html)
**Related videos:**
+ [ Deep Dive on Amazon EBS Elastic Volumes ](https://www.youtube.com/watch?v=Vi_1Or7QuOg)
+ [ Amazon EBS and Snapshot Optimization Strategies for Better Performance and Cost Savings ](https://www.youtube.com/watch?v=h1hzRCsJefs)
+ [ Optimizing Amazon EFS for cost and performance, using best practices ](https://www.youtube.com/watch?v=9kfeh6_uZY8)
# SUS04-BP05 Remove unneeded or redundant data
Remove unneeded or redundant data to minimize the storage resources required to store your datasets.
**Common anti-patterns:**
+ You duplicate data that can be easily obtained or recreated.
+ You back up all data without considering its criticality.
+ You only delete data irregularly, on operational events, or not at all.
+ You store data redundantly irrespective of the storage service's durability.
+ You turn on Amazon S3 versioning without any business justification.
**Benefits of establishing this best practice:** Removing unneeded data reduces the storage size required for your workload and the workload environmental impact.
**Level of risk exposed if this best practice is not established:** Medium
## Implementation guidance
Do not store data that you do not need. Automate the deletion of unneeded data. Use technologies that deduplicate data at the file and block level. Leverage native data replication and redundancy features of services.
**Implementation steps**
+ Evaluate if you can avoid storing data by using existing publicly available datasets in [AWS Data Exchange](https://aws.amazon.com/data-exchange/) and [Open Data on AWS](https://registry.opendata.aws/).
+ Use mechanisms that can deduplicate data at the block and object level. Here are some examples of how to deduplicate data on AWS:
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/wellarchitected/2024-06-27/framework/sus_sus_data_a6.html)
+ Analyze the data access to identify unneeded data. Automate lifecycle policies. Leverage native service features like [Amazon DynamoDB Time To Live](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/TTL.html), [Amazon S3 Lifecycle](https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lifecycle-mgmt.html), or [Amazon CloudWatch log retention](https://docs.aws.amazon.com/managedservices/latest/userguide/log-customize-retention.html) for deletion.
+ Use data virtualization capabilities on AWS to maintain data at its source and avoid data duplication.
+ [Cloud Native Data Virtualization on AWS](https://www.youtube.com/watch?v=BM6sMreBzoA)
+ [Optimize Data Pattern Using Amazon Redshift Data Sharing](https://catalog.workshops.aws/well-architected-sustainability/en-US/3-data/optimize-data-pattern-using-redshift-data-sharing)
+ Use backup technology that can make incremental backups.
+ Leverage the durability of [Amazon S3](https://docs.aws.amazon.com/AmazonS3/latest/userguide/DataDurability.html) and [replication of Amazon EBS](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ebs-volumes.html) to meet your durability goals instead of self-managed technologies (such as a redundant array of independent disks (RAID)).
+ Centralize log and trace data, deduplicate identical log entries, and establish mechanisms to tune verbosity when needed.
+ Pre-populate caches only where justified.
+ Establish cache monitoring and automation to resize the cache accordingly.
+ Remove out-of-date deployments and assets from object stores and edge caches when pushing new versions of your workload.
## Resources
**Related documents:**
+ [Change log data retention in CloudWatch Logs](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/Working-with-log-groups-and-streams.html#SettingLogRetention)
+ [Data deduplication on Amazon FSx for Windows File Server](https://docs.aws.amazon.com/fsx/latest/WindowsGuide/using-data-dedup.html)
+ [Features of Amazon FSx for ONTAP including data deduplication](https://docs.aws.amazon.com/fsx/latest/ONTAPGuide/what-is-fsx-ontap.html#features-overview)
+ [Invalidating Files on Amazon CloudFront](https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/Invalidation.html)
+ [Using AWS Backup to back up and restore Amazon EFS file systems](https://docs.aws.amazon.com/efs/latest/ug/awsbackup.html)
+ [What is Amazon CloudWatch Logs?](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/WhatIsCloudWatchLogs.html)
+ [Working with backups on Amazon RDS](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_WorkingWithAutomatedBackups.html)
+ [Integrate and deduplicate datasets using AWS Lake Formation](https://aws.amazon.com/blogs/big-data/integrate-and-deduplicate-datasets-using-aws-lake-formation-findmatches/)
**Related videos:**
+ [Amazon Redshift Data Sharing Use Cases](https://www.youtube.com/watch?v=sIoTB8B5nn4)
**Related examples:**
+ [How do I analyze my Amazon S3 server access logs using Amazon Athena?](https://aws.amazon.com/premiumsupport/knowledge-center/analyze-logs-athena/)
# SUS04-BP06 Use shared file systems or storage to access common data
Adopt shared file systems or storage to avoid data duplication and allow for more efficient infrastructure for your workload.
**Common anti-patterns:**
+ You provision storage for each individual client.
+ You do not detach data volume from inactive clients.
+ You do not provide access to storage across platforms and systems.
**Benefits of establishing this best practice:** Using shared file systems or storage allows for sharing data to one or more consumers without having to copy the data. This helps to reduce the storage resources required for the workload.
**Level of risk exposed if this best practice is not established:** Medium
## Implementation guidance
If you have multiple users or applications accessing the same datasets, using shared storage technology is crucial to use efficient infrastructure for your workload. Shared storage technology provides a central location to store and manage datasets and avoid data duplication. It also enforces consistency of the data across different systems. Moreover, shared storage technology allows for more efficient use of compute power, as multiple compute resources can access and process data at the same time in parallel.
Fetch data from these shared storage services only as needed and detach unused volumes to free up resources.
**Implementation steps**
+ Migrate data to shared storage when the data has multiple consumers. Here are some examples of shared storage technology on AWS:
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/wellarchitected/2024-06-27/framework/sus_sus_data_a7.html)
+ Copy data to or fetch data from shared file systems only as needed. As an example, you can create an [Amazon FSx for Lustre file system backed by Amazon S3](https://aws.amazon.com/blogs/storage/new-enhancements-for-moving-data-between-amazon-fsx-for-lustre-and-amazon-s3/) and only load the subset of data required for processing jobs to Amazon FSx.
+ Delete data as appropriate for your usage patterns as outlined in [SUS04-BP03 Use policies to manage the lifecycle of your datasets](sus_sus_data_a4.md).
+ Detach volumes from clients that are not actively using them.
## Resources
**Related documents:**
+ [ Linking your file system to an Amazon S3 bucket ](https://docs.aws.amazon.com/fsx/latest/LustreGuide/create-dra-linked-data-repo.html)
+ [ Using Amazon EFS for AWS Lambda in your serverless applications ](https://aws.amazon.com/blogs/compute/using-amazon-efs-for-aws-lambda-in-your-serverless-applications/)
+ [ Amazon EFS Intelligent-Tiering Optimizes Costs for Workloads with Changing Access Patterns ](https://aws.amazon.com/blogs/aws/new-amazon-efs-intelligent-tiering-optimizes-costs-for-workloads-with-changing-access-patterns/)
+ [ Using Amazon FSx with your on-premises data repository ](https://docs.aws.amazon.com/fsx/latest/LustreGuide/fsx-on-premises.html)
**related videos:**
+ [ Storage cost optimization with Amazon EFS ](https://www.youtube.com/watch?v=0nYAwPsYvBo)
+ [AWS re:Invent 2023 - What's new with AWS file storage](https://www.youtube.com/watch?v=yXIeIKlTFV0)
+ [AWS re:Invent 2023 - File storage for builders and data scientists on Amazon Elastic File System](https://www.youtube.com/watch?v=g0f6lrmEyRM)
# SUS04-BP07 Minimize data movement across networks
Use shared file systems or object storage to access common data and minimize the total networking resources required to support data movement for your workload.
**Common anti-patterns:**
+ You store all data in the same AWS Region independent of where the data users are.
+ You do not optimize data size and format before moving it over the network.
**Benefits of establishing this best practice:** Optimizing data movement across the network reduces the total networking resources required for the workload and lowers its environmental impact.
**Level of risk exposed if this best practice is not established:** Medium
## Implementation guidance
Moving data around your organization requires compute, networking, and storage resources. Use techniques to minimize data movement and improve the overall efficiency of your workload.
## Implementation steps
+ Consider proximity to the data or users as a decision factor when [selecting a Region for your workload](https://aws.amazon.com/blogs/architecture/how-to-select-a-region-for-your-workload-based-on-sustainability-goals/).
+ Partition Regionally consumed services so that their Region-specific data is stored within the Region where it is consumed.
+ Use efficient file formats (such as Parquet or ORC) and compress data before moving it over the network.
+ Don't move unused data. Some examples that can help you avoid moving unused data:
+ Reduce API responses to only relevant data.
+ Aggregate data where detailed (record-level information is not required).
+ See [Well-Architected Lab - Optimize Data Pattern Using Amazon Redshift Data Sharing](https://catalog.workshops.aws/well-architected-sustainability/en-US/3-data/optimize-data-pattern-using-redshift-data-sharing).
+ Consider [Cross-account data sharing in AWS Lake Formation](https://docs.aws.amazon.com/lake-formation/latest/dg/cross-account-permissions.html).
+ Use services that can help you run code closer to users of your workload.
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/wellarchitected/2024-06-27/framework/sus_sus_data_a8.html)
## Resources
**Related documents:**
+ [Optimizing your AWS Infrastructure for Sustainability, Part III: Networking](https://aws.amazon.com/blogs/architecture/optimizing-your-aws-infrastructure-for-sustainability-part-iii-networking/)
+ [AWS Global Infrastructure](https://aws.amazon.com/about-aws/global-infrastructure/)
+ [Amazon CloudFront Key Features including the CloudFront Global Edge Network](https://aws.amazon.com/cloudfront/features/)
+ [Compressing HTTP requests in Amazon OpenSearch Service](https://docs.aws.amazon.com/opensearch-service/latest/developerguide/gzip.html)
+ [Intermediate data compression with Amazon EMR](https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-plan-output-compression.html#HadoopIntermediateDataCompression)
+ [Loading compressed data files from Amazon S3 into Amazon Redshift](https://docs.aws.amazon.com/redshift/latest/dg/t_loading-gzip-compressed-data-files-from-S3.html)
+ [Serving compressed files with Amazon CloudFront](https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/ServingCompressedFiles.html)
**Related videos:**
+ [ Demystifying data transfer on AWS](https://www.youtube.com/watch?v=-MqXgzw1IGA)
**Related examples:**
+ [ Architecting for sustainability - Minimize data movement across networks ](https://catalog.us-east-1.prod.workshops.aws/workshops/7c4f8394-8081-4737-aa1b-6ae811d46e0a/en-US)
# SUS04-BP08 Back up data only when difficult to recreate
Avoid backing up data that has no business value to minimize storage resources requirements for your workload.
**Common anti-patterns:**
+ You do not have a backup strategy for your data.
+ You back up data that can be easily recreated.
**Benefits of establishing this best practice:** Avoiding back-up of non-critical data reduces the required storage resources for the workload and lowers its environmental impact.
**Level of risk exposed if this best practice is not established:** Medium
## Implementation guidance
Avoiding the back up of unnecessary data can help lower cost and reduce the storage resources used by the workload. Only back up data that has business value or is needed to satisfy compliance requirements. Examine backup policies and exclude ephemeral storage that doesn’t provide value in a recovery scenario.
**Implementation steps**
+ Implement data classification policy as outlined in [SUS04-BP01 Implement a data classification policy](sus_sus_data_a2.md).
+ Use the criticality of your data classification and design backup strategy based on your [recovery time objective (RTO) and recovery point objective (RPO](https://docs.aws.amazon.com/wellarchitected/latest/reliability-pillar/rel_planning_for_recovery_objective_defined_recovery.html)). Avoid backing up non-critical data.
+ Exclude data that can be easily recreated.
+ Exclude ephemeral data from your backups.
+ Exclude local copies of data, unless the time required to restore that data from a common location exceeds your service-level agreements (SLAs).
+ Use an automated solution or managed service to back up business-critical data.
+ [AWS Backup](https://docs.aws.amazon.com/aws-backup/latest/devguide/whatisbackup.html) is a fully-managed service that makes it easy to centralize and automate data protection across AWS services, in the cloud, and on premises. For hands-on guidance on how to create automated backups using AWS Backup, see [Well-Architected Labs - Testing Backup and Restore of Data](https://wellarchitectedlabs.com/reliability/200_labs/200_testing_backup_and_restore_of_data/).
+ [Automate backups and optimize backup costs for Amazon EFS using AWS Backup](https://aws.amazon.com/blogs/storage/automating-backups-and-optimizing-backup-costs-for-amazon-efs-using-aws-backup/).
## Resources
**Related best practices:**
+ [REL09-BP01 Identify and back up all data that needs to be backed up, or reproduce the data from sources](https://docs.aws.amazon.com/wellarchitected/latest/reliability-pillar/rel_backing_up_data_identified_backups_data.html)
+ [REL09-BP03 Perform data backup automatically](https://docs.aws.amazon.com/wellarchitected/latest/reliability-pillar/rel_backing_up_data_automated_backups_data.html)
+ [REL13-BP02 Use defined recovery strategies to meet the recovery objectives](https://docs.aws.amazon.com/wellarchitected/latest/reliability-pillar/rel_planning_for_recovery_disaster_recovery.html)
**Related documents:**
+ [Using AWS Backup to back up and restore Amazon EFS file systems](https://docs.aws.amazon.com/efs/latest/ug/awsbackup.html)
+ [Amazon EBS snapshots](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSSnapshots.html)
+ [Working with backups on Amazon Relational Database Service](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_WorkingWithAutomatedBackups.html)
+ [ APN Partner: partners that can help with backup ](https://partners.amazonaws.com/search/partners?keyword=Backup)
+ [AWS Marketplace: products that can be used for backup ](https://aws.amazon.com/marketplace/search/results?searchTerms=Backup)
+ [ Backing Up Amazon EFS ](https://docs.aws.amazon.com/efs/latest/ug/efs-backup-solutions.html)
+ [ Backing Up Amazon FSx for Windows File Server ](https://docs.aws.amazon.com/fsx/latest/WindowsGuide/using-backups.html)
+ [ Backup and Restore for Amazon ElastiCache (Redis OSS) ](https://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/backups.html)
**Related videos:**
+ [AWS re:Invent 2023 - Backup and disaster recovery strategies for increased resilience](https://www.youtube.com/watch?v=E073XISxrSU)
+ [AWS re:Invent 2023 - What's new with AWS Backup](https://www.youtube.com/watch?v=QIffkOyTf7I)
+ [AWS re:Invent 2021 - Backup, disaster recovery, and ransomware protection with AWS](https://www.youtube.com/watch?v=Ru4jxh9qazc)
**Related examples:**
+ [ Well-Architected Lab - Backup data](https://catalog.workshops.aws/well-architected-reliability/en-US/4-failure-management/1-backup)