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Guidance for Monitoring High-Cardinality Telecom Metrics on AWS

Overview

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.

How it works

These technical details feature an architecture diagram to illustrate how to effectively use this solution. The architecture diagram shows the key components and their interactions, providing an overview of the architecture's structure and functionality step-by-step.

Well-Architected Pillars

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.

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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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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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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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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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.

Read the Cost Optimization 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.

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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.
Open sample code on GitHub

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.