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This Guidance demonstrates how telecom operators can use Amazon CloudWatch to better monitor key performance indicators (KPIs) for their hardware devices, endpoints, services, and software that often have many unique values, or high-cardinality. CloudWatch anomaly detection applies statistical and machine learning algorithms to CloudWatch metrics, calculates normal baselines, and surfaces anomalies with minimal user intervention.
Please note: [Disclaimer]
Architecture Diagram
[Architecture diagram description]
Step 1a
An Amazon EventBridge rule invokes an AWS Lambda function every minute that generates simulated telecommunications telemetry using the Amazon CloudWatch embedded metric format.
Step 1b
Real telecommunications telemetry is sent to CloudWatch using the CloudWatch embedded metric format through the CloudWatch agent or PutLogEvents API. For an example of how our customers use this, refer to How BT uses Amazon CloudWatch to monitor millions of devices.
Step 2
CloudWatch recognizes the embedded metric format in incoming log events, then extracts and generates aggregated metrics asynchronously.
Step 3
The CloudWatch alarms are configured for each KPI with anomaly detection. Composite alarms are also created for each geographic boundary and combined individual KPI alarms.
Step 4
One CloudWatch dashboard is created for each geographic level. That is, USA, Washington State, and Seattle would each have their own dashboard which shows the corresponding alarms, metrics, and logs for each level.
Step 5
A geographic map is generated and displayed on the CloudWatch dashboards using custom widgets which color codes the map according to the alarm status. A custom widget is a CloudWatch dashboard widget that can call any Lambda function with custom parameters. It then displays the returned HTML or JSON file.
Step 1a
An Amazon EventBridge rule invokes an AWS Lambda function every minute that generates simulated telecommunications telemetry using the Amazon CloudWatch embedded metric format.
Step 1b
Real telecommunications telemetry is sent to CloudWatch using the CloudWatch embedded metric format through the CloudWatch agent or PutLogEvents API. For an example of how our customers use this, refer to How BT uses Amazon CloudWatch to monitor millions of devices.
Step 2
CloudWatch recognizes the embedded metric format in incoming log events, then extracts and generates aggregated metrics asynchronously.
Step 3
The CloudWatch alarms are configured for each KPI with anomaly detection. Composite alarms are also created for each geographic boundary and combined individual KPI alarms.
Step 4
One CloudWatch dashboard is created for each geographic level. That is, USA, Washington State, and Seattle would each have their own dashboard which shows the corresponding alarms, metrics, and logs for each level.
Step 5
A geographic map is generated and displayed on the CloudWatch dashboards using custom widgets which color codes the map according to the alarm status. A custom widget is a CloudWatch dashboard widget that can call any Lambda function with custom parameters. It then displays the returned HTML or JSON file.
Well-Architected Pillars
The AWS Well-Architected Framework helps you understand the pros and cons of the decisions you make when building systems in the cloud. The six pillars of the Framework allow you to learn architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable systems. Using the AWS Well-Architected Tool, available at no charge in the AWS Management Console, you can review your workloads against these best practices by answering a set of questions for each pillar.
The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.
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Operational ExcellenceRead the Operational Excellence whitepaper
CloudWatch collects and displays real-time logs, metrics, and event data in automated dashboards to streamline your infrastructure and application maintenance. Lambda is used to enhance the capabilities in CloudWatch dashboards with custom widgets.
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SecurityRead the Security whitepaper
CloudWatch logs are compliant with Payment Card Industry (PCI) and Federal Risk and Authorization Management Program (FedRAMP). CloudWatch is also integrated with AWS Identity and Access Management (IAM) so you can control which users and resources can access your data, and set permissions for how your data is accessed. You can also define data protection policies to discover and protect sensitive data logged by systems and applications. Lastly, data in this Guidance is encrypted at rest and in transit.
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ReliabilityRead the Reliability whitepaper
To keep your applications running smoothly, use CloudWatch to gain system-wide visibility into resource utilization, application performance, and operational health. CloudWatch is a fundamental service that equips you to collect logs, gather metrics, and send notifications when thresholds are crossed or significant events occur.
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Performance EfficiencyRead the Performance Efficiency whitepaper
CloudWatch is a monitoring and observability service that provides you with both data and actionable insights. It helps you monitor your workloads so you can better respond to changes in performance of your systems and processes.
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Cost OptimizationRead the Cost Optimization whitepaper
The CloudWatch embedded metric format allows you to asynchronously generate custom metrics in the form of logs that are written to CloudWatch logs. CloudWatch then automatically creates an aggregated metric, which in turn provides a cost-effective way to monitor resources. Additionally, by using the embedded metric format, the cost of the PutMetricData API is removed.
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SustainabilityRead the Sustainability whitepaper
CloudWatch streamlines data storage and eliminates the need to call the PutMetricData API to generate metrics, eliminating the need for additional compute. CloudWatch logs are also stored and estimated to be 15% of log volume ingested (due to compression). To further minimize your required resources, you can set a retention policy on individual log groups.
Implementation Resources
The sample code is a starting point. It is industry validated, prescriptive but not definitive, and a peek under the hood to help you begin.
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Disclaimer
The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.
References to third-party services or organizations in this Guidance do not imply an endorsement, sponsorship, or affiliation between Amazon or AWS and the third party. Guidance from AWS is a technical starting point, and you can customize your integration with third-party services when you deploy the architecture.