# Utilizing workload observability Utilizing workload observability 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. 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. AWS offers specific tools like [Amazon CloudWatch](https://aws.amazon.com/cloudwatch/) for monitoring and logging, and [AWS X-Ray](https://aws.amazon.com/xray/) for distributed tracing. These services integrate effortlessly with various AWS resources, allowing for efficient data collection, setting up alerts based on predefined thresholds, and presenting data on dashboards for easy interpretation. By leveraging these insights, you can make well-informed, data-driven decisions that align with your operational goals. **Topics** + [ # OPS08-BP01 Analyze workload metrics ](ops_workload_observability_analyze_workload_metrics.md) + [ # OPS08-BP02 Analyze workload logs ](ops_workload_observability_analyze_workload_logs.md) + [ # OPS08-BP03 Analyze workload traces ](ops_workload_observability_analyze_workload_traces.md) + [ # OPS08-BP04 Create actionable alerts ](ops_workload_observability_create_alerts.md) + [ # OPS08-BP05 Create dashboards ](ops_workload_observability_create_dashboards.md) # OPS08-BP01 Analyze workload metrics OPS08-BP01 Analyze workload metrics After implementing application telemetry, regularly analyze the collected metrics. While latency, requests, errors, and capacity (or quotas) provide insights into system performance, it's vital to prioritize the review of business outcome metrics. This ensures you're making data-driven decisions aligned with your business objectives. **Desired outcome:** Accurate insights into workload performance that drive data-informed decisions, ensuring alignment with business objectives. **Common anti-patterns:** + Analyzing metrics in isolation without considering their impact on business outcomes. + Over-reliance on technical metrics while sidelining business metrics. + Infrequent review of metrics, missing out on real-time decision-making opportunities. **Benefits of establishing this best practice:** + Enhanced understanding of the correlation between technical performance and business outcomes. + Improved decision-making process informed by real-time data. + Proactive identification and mitigation of issues before they affect business outcomes. **Level of risk exposed if this best practice is not established:** Medium ## Implementation guidance Implementation guidance Leverage tools like Amazon CloudWatch to perform metric analysis. AWS services such as CloudWatch anomaly detection and Amazon DevOps Guru can be used to detect anomalies, especially when static thresholds are unknown or when patterns of behavior are more suited for anomaly detection. ### Implementation steps Implementation steps 1. **Analyze and review:** Regularly review and interpret your workload metrics. 1. Prioritize business outcome metrics over purely technical metrics. 1. Understand the significance of spikes, drops, or patterns in your data. 1. **Utilize Amazon CloudWatch:** Use Amazon CloudWatch for a centralized view and deep-dive analysis. 1. Configure CloudWatch dashboards to visualize your metrics and compare them over time. 1. Use [percentiles in CloudWatch](https://aws-observability.github.io/observability-best-practices/guides/operational/business/sla-percentile/) to get a clear view of metric distribution, which can help in defining SLAs and understanding outliers. 1. Set up [CloudWatch anomaly detection](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch_Anomaly_Detection.html) to identify unusual patterns without relying on static thresholds. 1. Implement [CloudWatch cross-account observability](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-Unified-Cross-Account.html) to monitor and troubleshoot applications that span multiple accounts within a Region. 1. Use [CloudWatch Metric Insights](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/query_with_cloudwatch-metrics-insights.html) to query and analyze metric data across accounts and Regions, identifying trends and anomalies. 1. Apply [CloudWatch Metric Math](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/using-metric-math.html) to transform, aggregate, or perform calculations on your metrics for deeper insights. 1. **Employ Amazon DevOps Guru:** Incorporate [Amazon DevOps Guru](https://aws.amazon.com/devops-guru/) for its machine learning-enhanced anomaly detection to identify early signs of operational issues for your serverless applications and remediate them before they impact your customers. 1. **Optimize based on insights:** Make informed decisions based on your metric analysis to adjust and improve your workloads. **Level of effort for the Implementation Plan:** Medium ## Resources Resources **Related best practices:** + [OPS04-BP01 Identify key performance indicators](ops_observability_identify_kpis.md) + [OPS04-BP02 Implement application telemetry](ops_observability_application_telemetry.md) **Related documents:** + [ The Wheel Blog - Emphasizing the importance of continually reviewing metrics ](https://aws.amazon.com/blogs/opensource/the-wheel/) + [ Percentile are important ](https://aws-observability.github.io/observability-best-practices/guides/operational/business/sla-percentile/) + [ Using AWS Cost Anomaly Detection](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch_Anomaly_Detection.html) + [ CloudWatch cross-account observability ](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-Unified-Cross-Account.html) + [ Query your metrics with CloudWatch Metrics Insights ](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/query_with_cloudwatch-metrics-insights.html) **Related videos:** + [ Enable Cross-Account Observability in Amazon CloudWatch ](https://www.youtube.com/watch?v=lUaDO9dqISc) + [ Introduction to Amazon DevOps Guru ](https://www.youtube.com/watch?v=2uA8q-8mTZY) + [ Continuously Analyze Metrics using AWS Cost Anomaly Detection](https://www.youtube.com/watch?v=IpQYBuay5OE) **Related examples:** + [ One Observability Workshop ](https://catalog.workshops.aws/observability/en-US/intro) + [ Gaining operation insights with AIOps using Amazon DevOps Guru ](https://catalog.us-east-1.prod.workshops.aws/workshops/f92df379-6add-4101-8b4b-38b788e1222b/en-US) # OPS08-BP02 Analyze workload logs OPS08-BP02 Analyze workload logs Regularly analyzing workload logs is essential for gaining a deeper understanding of the operational aspects of your application. By efficiently sifting through, visualizing, and interpreting log data, you can continually optimize application performance and security. **Desired outcome:** Rich insights into application behavior and operations derived from thorough log analysis, ensuring proactive issue detection and mitigation. **Common anti-patterns:** + Neglecting the analysis of logs until a critical issue arises. + Not using the full suite of tools available for log analysis, missing out on critical insights. + Solely relying on manual review of logs without leveraging automation and querying capabilities. **Benefits of establishing this best practice:** + Proactive identification of operational bottlenecks, security threats, and other potential issues. + Efficient utilization of log data for continuous application optimization. + Enhanced understanding of application behavior, aiding in debugging and troubleshooting. **Level of risk exposed if this best practice is not established:** Medium ## Implementation guidance Implementation guidance [Amazon CloudWatch Logs](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/WhatIsCloudWatchLogs.html) is a powerful tool for log analysis. Integrated features like CloudWatch Logs Insights and Contributor Insights make the process of deriving meaningful information from logs intuitive and efficient. ### Implementation steps Implementation steps 1. **Set up CloudWatch Logs**: Configure applications and services to send logs to CloudWatch Logs. 1. **Use log anomaly detection:** Utilize [Amazon CloudWatch Logs anomaly detection](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/LogsAnomalyDetection.html) to automatically identify and alert on unusual log patterns. This tool helps you proactively manage anomalies in your logs and detect potential issues early. 1. **Set up CloudWatch Logs Insights**: Use [CloudWatch Logs Insights](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/AnalyzingLogData.html) to interactively search and analyze your log data. 1. Craft queries to extract patterns, visualize log data, and derive actionable insights. 1. Use [CloudWatch Logs Insights pattern analysis](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/CWL_AnalyzeLogData_Patterns.html) to analyze and visualize frequent log patterns. This feature helps you understand common operational trends and potential outliers in your log data. 1. Use [CloudWatch Logs compare (diff)](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/CWL_AnalyzeLogData_Compare.html) to perform differential analysis between different time periods or across different log groups. Use this capability to pinpoint changes and assess their impacts on your system's performance or behavior. 1. **Monitor logs in real-time with Live Tail:** Use [Amazon CloudWatch Logs Live Tail](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/CloudWatchLogs_LiveTail.html) to view log data in real-time. You can actively monitor your application's operational activities as they occur, which provides immediate visibility into system performance and potential issues. 1. **Leverage Contributor Insights**: Use [CloudWatch Contributor Insights](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/ContributorInsights.html) to identify top talkers in high cardinality dimensions like IP addresses or user-agents. 1. **Implement CloudWatch Logs metric filters**: Configure [CloudWatch Logs metric filters](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/MonitoringLogData.html) to convert log data into actionable metrics. This allows you to set alarms or further analyze patterns. 1. **Implement [CloudWatch cross-account observability](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-Unified-Cross-Account.html):** Monitor and troubleshoot applications that span multiple accounts within a Region. 1. **Regular review and refinement**: Periodically review your log analysis strategies to capture all relevant information and continually optimize application performance. **Level of effort for the implementation plan:** Medium ## Resources Resources **Related best practices:** + [OPS04-BP01 Identify key performance indicators](ops_observability_identify_kpis.md) + [OPS04-BP02 Implement application telemetry](ops_observability_application_telemetry.md) + [OPS08-BP01 Analyze workload metrics](ops_workload_observability_analyze_workload_metrics.md) **Related documents:** + [Analyzing Log Data with CloudWatch Logs Insights](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/AnalyzingLogData.html) + [Using CloudWatch Contributor Insights](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/ContributorInsights.html) + [Creating and Managing CloudWatch Log Metric Filters](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/MonitoringLogData.html) **Related videos:** + [Analyze Log Data with CloudWatch Logs Insights](https://www.youtube.com/watch?v=2s2xcwm8QrM) + [Use CloudWatch Contributor Insights to Analyze High-Cardinality Data](https://www.youtube.com/watch?v=ErWRBLFkjGI) **Related examples:** + [CloudWatch Logs Sample Queries](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/CWL_QuerySyntax-examples.html) + [One Observability Workshop](https://catalog.workshops.aws/observability/en-US/intro) # OPS08-BP03 Analyze workload traces OPS08-BP03 Analyze workload traces Analyzing trace data is crucial for achieving a comprehensive view of an application's operational journey. By visualizing and understanding the interactions between various components, performance can be fine-tuned, bottlenecks identified, and user experiences enhanced. **Desired outcome:** Achieve clear visibility into your application's distributed operations, enabling quicker issue resolution and an enhanced user experience. **Common anti-patterns:** + Overlooking trace data, relying solely on logs and metrics. + Not correlating trace data with associated logs. + Ignoring the metrics derived from traces, such as latency and fault rates. **Benefits of establishing this best practice:** + Improve troubleshooting and reduce mean time to resolution (MTTR). + Gain insights into dependencies and their impact. + Swift identification and rectification of performance issues. + Leveraging trace-derived metrics for informed decision-making. + Improved user experiences through optimized component interactions. **Level of risk exposed if this best practice is not established:** Medium ## Implementation guidance Implementation guidance [AWS X-Ray](https://www.docs.aws.com/xray/latest/devguide/aws-xray.html) offers a comprehensive suite for trace data analysis, providing a holistic view of service interactions, monitoring user activities, and detecting performance issues. Features like ServiceLens, X-Ray Insights, X-Ray Analytics, and Amazon DevOps Guru enhance the depth of actionable insights derived from trace data. ### Implementation steps Implementation steps The following steps offer a structured approach to effectively implementing trace data analysis using AWS services: 1. **Integrate AWS X-Ray**: Ensure X-Ray is integrated with your applications to capture trace data. 1. **Analyze X-Ray metrics**: Delve into metrics derived from X-Ray traces, such as latency, request rates, fault rates, and response time distributions, using the [service map](https://docs.aws.amazon.com/xray/latest/devguide/xray-console-servicemap.html#xray-console-servicemap-view) to monitor application health. 1. **Use ServiceLens**: Leverage the [ServiceLens map](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/servicelens_service_map.html) for enhanced observability of your services and applications. This allows for integrated viewing of traces, metrics, logs, alarms, and other health information. 1. **Enable X-Ray Insights**: 1. Turn on [X-Ray Insights](https://docs.aws.amazon.com/xray/latest/devguide/xray-console-insights.html) for automated anomaly detection in traces. 1. Examine insights to pinpoint patterns and ascertain root causes, such as increased fault rates or latencies. 1. Consult the insights timeline for a chronological analysis of detected issues. 1. **Use X-Ray Analytics**: [X-Ray Analytics](https://docs.aws.amazon.com/xray/latest/devguide/xray-console-analytics.html) allows you to thoroughly explore trace data, pinpoint patterns, and extract insights. 1. **Use groups in X-Ray**: Create groups in X-Ray to filter traces based on criteria such as high latency, allowing for more targeted analysis. 1. **Incorporate Amazon DevOps Guru**: Engage [Amazon DevOps Guru](https://aws.amazon.com/devops-guru/) to benefit from machine learning models pinpointing operational anomalies in traces. 1. **Use CloudWatch Synthetics**: Use [CloudWatch Synthetics](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch_Synthetics_Canaries_tracing.html) to create canaries for continually monitoring your endpoints and workflows. These canaries can integrate with X-Ray to provide trace data for in-depth analysis of the applications being tested. 1. **Use Real User Monitoring (RUM)**: With [AWS X-Ray and CloudWatch RUM](https://docs.aws.amazon.com/xray/latest/devguide/xray-services-RUM.html), you can analyze and debug the request path starting from end users of your application through downstream AWS managed services. This helps you identify latency trends and errors that impact your end users. 1. **Correlate with logs**: Correlate [trace data with related logs](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/servicelens_troubleshooting.html#servicelens_troubleshooting_Nologs) within the X-Ray trace view for a granular perspective on application behavior. This allows you to view log events directly associated with traced transactions. 1. **Implement [CloudWatch cross-account observability](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-Unified-Cross-Account.html):** Monitor and troubleshoot applications that span multiple accounts within a Region. **Level of effort for the implementation plan:** Medium ## Resources Resources **Related best practices:** + [OPS08-BP01 Analyze workload metrics](ops_workload_observability_analyze_workload_metrics.md) + [OPS08-BP02 Analyze workload logs](ops_workload_observability_analyze_workload_logs.md) **Related documents:** + [Using ServiceLens to Monitor Application Health](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/ServiceLens.html) + [Exploring Trace Data with X-Ray Analytics](https://docs.aws.amazon.com/xray/latest/devguide/xray-console-analytics.html) + [Detecting Anomalies in Traces with X-Ray Insights](https://docs.aws.amazon.com/xray/latest/devguide/xray-insights.html) + [Continuous Monitoring with CloudWatch Synthetics](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch_Synthetics_Canaries.html) **Related videos:** + [Analyze and Debug Applications Using Amazon CloudWatch Synthetics & AWS X-Ray](https://www.youtube.com/watch?v=s2WvaV2eDO4) + [Use AWS X-Ray Insights](https://www.youtube.com/watch?v=tl8OWHl6jxw) **Related examples:** + [One Observability Workshop](https://catalog.workshops.aws/observability/en-US/intro) + [Implementing X-Ray with AWS Lambda](https://docs.aws.amazon.com/lambda/latest/dg/services-xray.html) + [CloudWatch Synthetics Canary Templates](https://github.com/aws-samples/cloudwatch-synthetics-canary-terraform) # OPS08-BP04 Create actionable alerts OPS08-BP04 Create actionable alerts Promptly detecting and responding to deviations in your application's behavior is crucial. Especially vital is recognizing when outcomes based on key performance indicators (KPIs) are at risk or when unexpected anomalies arise. Basing alerts on KPIs ensures that the signals you receive are directly tied to business or operational impact. This approach to actionable alerts promotes proactive responses and helps maintain system performance and reliability. **Desired outcome:** Receive timely, relevant, and actionable alerts for rapid identification and mitigation of potential issues, especially when KPI outcomes are at risk. **Common anti-patterns:** + Setting up too many non-critical alerts, leading to alert fatigue. + Not prioritizing alerts based on KPIs, making it hard to understand the business impact of issues. + Neglecting to address root causes, leading to repetitive alerts for the same issue. **Benefits of establishing this best practice:** + Reduced alert fatigue by focusing on actionable and relevant alerts. + Improved system uptime and reliability through proactive issue detection and mitigation. + Enhanced team collaboration and quicker issue resolution by integrating with popular alerting and communication tools. **Level of risk exposed if this best practice is not established:** High ## Implementation guidance Implementation guidance To create an effective alerting mechanism, it's vital to use metrics, logs, and trace data that flag when outcomes based on KPIs are at risk or anomalies are detected. ### Implementation steps Implementation steps 1. **Determine key performance indicators (KPIs)**: Identify your application's KPIs. Alerts should be tied to these KPIs to reflect the business impact accurately. 1. **Implement anomaly detection**: + **Use Amazon CloudWatch anomaly detection**: Set up [Amazon CloudWatch anomaly detection](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch_Anomaly_Detection.html) to automatically detect unusual patterns, which helps you only generate alerts for genuine anomalies. + **Use AWS X-Ray Insights**: 1. Set up [X-Ray Insights](https://docs.aws.amazon.com/xray/latest/devguide/xray-console-insights.html) to detect anomalies in trace data. 1. Configure [notifications for X-Ray Insights](https://docs.aws.amazon.com/xray/latest/devguide/xray-console-insights.html#xray-console-insight-notifications) to be alerted on detected issues. + **Integrate with Amazon DevOps Guru**: 1. Leverage [Amazon DevOps Guru](https://aws.amazon.com/devops-guru/) for its machine learning capabilities in detecting operational anomalies with existing data. 1. Navigate to the [notification settings](https://docs.aws.amazon.com/devops-guru/latest/userguide/update-notifications.html#navigate-to-notification-settings) in DevOps Guru to set up anomaly alerts. 1. **Implement actionable alerts**: Design alerts that provide adequate information for immediate action. 1. Monitor [AWS Health events with Amazon EventBridge rules](https://docs.aws.amazon.com/health/latest/ug/cloudwatch-events-health.html), or integrate programatically with the AWS Health API to automate actions when you receive AWS Health events. These can be general actions, such as sending all planned lifecycle event messages to a chat interface, or specific actions, such as the initiation of a workflow in an IT service management tool. 1. **Reduce alert fatigue**: Minimize non-critical alerts. When teams are overwhelmed with numerous insignificant alerts, they can lose oversight of critical issues, which diminishes the overall effectiveness of the alert mechanism. 1. **Set up composite alarms**: Use [Amazon CloudWatch composite alarms](https://aws.amazon.com/bloprove-monitoring-efficiency-using-amazon-cloudwatch-composite-alarms-2/) to consolidate multiple alarms. 1. **Integrate with alert tools**: Incorporate tools like [Ops Genie](https://www.atlassian.com/software/opsgenie) and [PagerDuty](https://www.pagerduty.com/). 1. **Engage Amazon Q Developer in chat applications**: Integrate [Amazon Q Developer in chat applications](https://aws.amazon.com/chatbot/) to relay alerts to Amazon Chime, Microsoft Teams, and Slack. 1. **Alert based on logs**: Use [log metric filters](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/MonitoringLogData.html) in CloudWatch to create alarms based on specific log events. 1. **Review and iterate**: Regularly revisit and refine alert configurations. **Level of effort for the implementation plan:** Medium ## Resources Resources **Related best practices:** + [OPS04-BP01 Identify key performance indicators](ops_observability_identify_kpis.md) + [OPS04-BP02 Implement application telemetry](ops_observability_application_telemetry.md) + [OPS04-BP03 Implement user experience telemetry](ops_observability_customer_telemetry.md) + [OPS04-BP04 Implement dependency telemetry](ops_observability_dependency_telemetry.md) + [OPS04-BP05 Implement distributed tracing](ops_observability_dist_trace.md) + [OPS08-BP01 Analyze workload metrics](ops_workload_observability_analyze_workload_metrics.md) + [OPS08-BP02 Analyze workload logs](ops_workload_observability_analyze_workload_logs.md) + [OPS08-BP03 Analyze workload traces](ops_workload_observability_analyze_workload_traces.md) **Related documents:** + [Using Amazon CloudWatch alarms](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/AlarmThatSendsEmail.html) + [Create a composite alarm](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/Create_Composite_Alarm.html) + [Create a CloudWatch alarm based on anomaly detection](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/Create_Anomaly_Detection_Alarm.html) + [DevOps Guru Notifications](https://docs.aws.amazon.com/devops-guru/latest/userguide/update-notifications.html) + [X-ray insights notifications](https://docs.aws.amazon.com/xray/latest/devguide/xray-console-insights.html#xray-console-insight-notifications) + [Monitor, operate, and troubleshoot your AWS resources with interactive ChatOps](https://aws.amazon.com/chatbot/) + [Amazon CloudWatch Integration Guide \$1 PagerDuty](https://support.pagerduty.com/docs/amazon-cloudwatch-integration-guide) + [Integrate Opsgenie with Amazon CloudWatch](https://support.atlassian.com/opsgenie/docs/integrate-opsgenie-with-amazon-cloudwatch/) **Related videos:** + [Create Composite Alarms in Amazon CloudWatch](https://www.youtube.com/watch?v=0LMQ-Mu-ZCY) + [Amazon Q Developer in chat applications Overview](https://www.youtube.com/watch?v=0jUSEfHbTYk) + [AWS On Air ft. Mutative Commands in Amazon Q Developer in chat applications](https://www.youtube.com/watch?v=u2pkw2vxrtk) **Related examples:** + [Alarms, incident management, and remediation in the cloud with Amazon CloudWatch](https://aws.amazon.com/bloarms-incident-management-and-remediation-in-the-cloud-with-amazon-cloudwatch/) + [Tutorial: Creating an Amazon EventBridge rule that sends notifications to Amazon Q Developer in chat applications](https://docs.aws.amazon.com/chatbot/latest/adminguide/create-eventbridge-rule.html) + [One Observability Workshop](https://catalog.workshops.aws/observability/en-US/intro) # OPS08-BP05 Create dashboards OPS08-BP05 Create dashboards Dashboards are the human-centric view into the telemetry data of your workloads. While they provide a vital visual interface, they should not replace alerting mechanisms, but complement them. When crafted with care, not only can they offer rapid insights into system health and performance, but they can also present stakeholders with real-time information on business outcomes and the impact of issues. **Desired outcome:** Clear, actionable insights into system and business health using visual representations. **Common anti-patterns:** + Overcomplicating dashboards with too many metrics. + Relying on dashboards without alerts for anomaly detection. + Not updating dashboards as workloads evolve. **Benefits of this best practice:** + Immediate visibility into critical system metrics and KPIs. + Enhanced stakeholder communication and understanding. + Rapid insight into the impact of operational issues. **Level of risk if this best practice isn't established:** Medium ## Implementation guidance Implementation guidance **Business-centric dashboards** Dashboards tailored to business KPIs engage a wider array of stakeholders. While these individuals might not be interested in system metrics, they are keen on understanding the business implications of these numbers. A business-centric dashboard ensures that all technical and operational metrics being monitored and analyzed are in sync with overarching business goals. This alignment provides clarity, ensuring everyone is on the same page regarding what's essential and what's not. Additionally, dashboards that highlight business KPIs tend to be more actionable. Stakeholders can quickly understand the health of operations, areas that need attention, and the potential impact on business outcomes. With this in mind, when creating your dashboards, ensure that there's a balance between technical metrics and business KPIs. Both are vital, but they cater to different audiences. Ideally, you should have dashboards that provide a holistic view of the system's health and performance while also emphasizing key business outcomes and their implications. Amazon CloudWatch Dashboards are customizable home pages in the CloudWatch console that you can use to monitor your resources in a single view, even those resources that are spread across different AWS Regions and accounts. ### Implementation steps Implementation steps 1. **Create a basic dashboard:** [Create a new dashboard in CloudWatch](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/create_dashboard.html), giving it a descriptive name. 1. **Use Markdown widgets:** Before diving into the metrics, [use Markdown widgets](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/add_remove_text_dashboard.html) to add textual context at the top of your dashboard. This should explain what the dashboard covers, the significance of the represented metrics, and can also contain links to other dashboards and troubleshooting tools. 1. **Create dashboard variables:** [Incorporate dashboard variables](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/cloudwatch_dashboard_variables.html) where appropriate to allow for dynamic and flexible dashboard views. 1. **Create metrics widgets:** [Add metric widgets](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/create-and-work-with-widgets.html) to visualize various metrics your application emits, tailoring these widgets to effectively represent system health and business outcomes. 1. **Log Insights queries:** Utilize [CloudWatch Log Insights](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/CWL_ExportQueryResults.html) to derive actionable metrics from your logs and display these insights on your dashboard. 1. **Set up alarms:** Integrate [CloudWatch Alarms](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/add_remove_alarm_dashboard.html) into your dashboard for a quick view of any metrics breaching their thresholds. 1. **Use Contributor Insights:** Incorporate [CloudWatch Contributor Insights](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/ContributorInsights-ViewReports.html) to analyze high-cardinality fields and get a clearer understanding of your resource's top contributors. 1. **Design custom widgets:** For specific needs not met by standard widgets, consider creating [custom widgets](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/add_custom_widget_dashboard.html). These can pull from various data sources or represent data in unique ways. 1. **Use AWS Health:** AWS Health is the authoritative source of information about the health of your AWS Cloud resources. Use [AWS Health Dashboard](https://health.aws.amazon.com/health/status) out of the box, or use AWS Health data in your own dashboards and tools so you have the right information available to make informed decisions. 1. **Iterate and refine:** As your application evolves, regularly revisit your dashboard to ensure its relevance. ## Resources Resources **Related best practices:** + [OPS04-BP01 Identify key performance indicators](ops_observability_identify_kpis.md) + [OPS08-BP01 Analyze workload metrics](ops_workload_observability_analyze_workload_metrics.md) + [OPS08-BP02 Analyze workload logs](ops_workload_observability_analyze_workload_logs.md) + [OPS08-BP03 Analyze workload traces](ops_workload_observability_analyze_workload_traces.md) + [OPS08-BP04 Create actionable alerts](ops_workload_observability_create_alerts.md) **Related documents:** + [Building Dashboards for Operational Visibility](https://aws.amazon.com/builders-library/building-dashboards-for-operational-visibility/) + [Using Amazon CloudWatch Dashboards](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch_Dashboards.html) **Related videos:** + [Create Cross Account & Cross Region CloudWatch Dashboards](https://www.youtube.com/watch?v=eIUZdaqColg) + [AWS re:Invent 2021 - Gain enterprise visibility with AWS Cloud operation dashboards)](https://www.youtube.com/watch?v=NfMpYiGwPGo) **Related examples:** + [One Observability Workshop](https://catalog.workshops.aws/observability/en-US/intro) + [Application Monitoring with Amazon CloudWatch](https://aws.amazon.com/solutions/implementations/application-monitoring-with-cloudwatch/) + [AWS Health Events Intelligence Dashboards and Insights](https://aws.amazon.com/blogs/mt/aws-health-events-intelligence-dashboards-insights/) + [Visualize AWS Health events using Amazon Managed Grafana](https://aws.amazon.com/blogs/mt/visualize-aws-health-events-using-amazon-managed-grafana/)