Monitoring and Logging with Amazon CloudWatch

Amazon CloudWatch is a powerful monitoring and observability service provided by Amazon Web Services (AWS). It allows you to collect and track metrics, monitor log files, set alarms and automatically react to changes in your AWS resources. CloudWatch provides insights into the operational health of your AWS services and applications enabling you to maintain high availability, performance and security.

Introduction to Amazon CloudWatch

What is Amazon CloudWatch?

Amazon CloudWatch is a monitoring service for AWS cloud resources and applications. It collects and tracks metrics, monitors log files and allows you to set alarms. CloudWatch provides a unified view of your AWS resources, applications and services that run on AWS and on-premises environments.

Key Features of Amazon CloudWatch

Metrics Monitoring : CloudWatch collects metrics from AWS services, EC2 instances and custom applications allowing you to visualize operational data in graphs, dashboards and automated alarms.
Logs Monitoring : CloudWatch Logs enables you to monitor, store and access log files from Amazon EC2 instances, AWS CloudTrail, Lambda functions and other sources.
Alarms and Notifications : Set alarms based on thresholds for metrics and get notifications via Amazon SNS (Simple Notification Service) when thresholds are breached.
Dashboards : Create customizable dashboards to monitor metrics and logs from multiple AWS resources in a single view.
Integration with AWS Services : CloudWatch integrates with various AWS services like EC2, S3, RDS, Lambda and more providing detailed insights and metrics specific to each service.

Getting Started with Amazon CloudWatch

1. Monitoring AWS Resources with CloudWatch Metrics

Basic Monitoring

AWS services automatically send metrics to CloudWatch. These include CPU utilization, disk I/O and network traffic for EC2 instances as well as request rates and error rates for Amazon S3 buckets.

Custom Metrics

You can publish your own custom metrics to CloudWatch using the AWS SDK or CLI. This allows you to monitor application-specific metrics and key performance indicators (KPIs).

Example of publishing a custom metric using AWS CLI :-

aws cloudwatch put-metric-data --namespace MyNamespace --metric-name MyMetric --value 10 --dimensions InstanceId=i-1234567890abcdef0

2. Monitoring Log Files with CloudWatch Logs

Log Groups and Log Streams

CloudWatch Logs organizes log data into log groups and log streams. Log groups represent a collection of log streams that share the same retention, monitoring and access control settings.

Subscriptions and Filters

You can create subscriptions to stream log data to other AWS services like Amazon S3, Amazon Kinesis Data Streams or AWS Lambda. Additionally CloudWatch Logs allows you to create metric filters to extract information from logs and create CloudWatch metrics.

3. Creating Alarms and Notifications

Setting Alarms

Alarms in CloudWatch monitor metrics and trigger actions based on defined thresholds. You can set alarms to notify you via Amazon SNS, execute an AWS Lambda function or Auto Scaling policy.

Example of creating an alarm using AWS CLI :-

aws cloudwatch put-metric-alarm --alarm-name CPUHigh --metric-name CPUUtilization --namespace AWS/EC2 --statistic Average --period 300 --threshold 70 --comparison-operator GreaterThanThreshold --evaluation-periods 2 --alarm-actions arn:aws:sns:us-east-1:123456789012:MyTopic

4. Creating Dashboards

Building Dashboards

CloudWatch Dashboards allow you to create customizable views of your metrics and logs. You can add graphs, text widgets and alarms from multiple AWS services to a single dashboard.

Example of creating a dashboard via AWS Management Console :-

Navigate to CloudWatch Console.
Click on "Dashboards" in the left navigation pane.
Click "Create Dashboard" and add widgets based on your metrics and logs.

Advanced CloudWatch Features

1. CloudWatch Logs Insights

CloudWatch Logs Insights enables you to interactively search and analyze log data in real-time. You can query log events and build visualizations to gain deeper insights into application behavior and performance issues.

Example query in CloudWatch Logs Insights :-

fields @timestamp, @message
| filter @message like /ERROR/
| sort @timestamp desc
| limit 20

2. CloudWatch Synthetics

CloudWatch Synthetics allows you to create canaries that monitor your endpoints and APIs. These canaries can be configured to perform scripted actions, simulate user behavior and test application workflows.

Example of creating a canary using AWS CLI :-

aws synthetics create-canary --name MyCanary --artifact-s3-location s3://my-bucket/my-script.zip --execution-role-arn arn:aws:iam::123456789012:role/MyCanaryRole --schedule-expression rate(5 minutes)

3. CloudWatch Contributor Insights

CloudWatch Contributor Insights helps you analyze high-cardinality data to identify the top contributors to changes in your system. It automatically detects anomalies and provides insights into resource usage patterns.

Example of setting up Contributor Insights :-

aws cloudwatch put-insight-rule --rule-name MyContributorInsight --rule-definition "MetricName=HTTPCode_Target_2xx, Dimensions=[{Name=LoadBalancer, Value=MyLoadBalancer}]" --state ENABLED

Best Practices for Using Amazon CloudWatch

1. Define Clear Monitoring Goals

Before configuring CloudWatch define your monitoring objectives and metrics. Identify key performance indicators (KPIs) and set appropriate thresholds for alarms.

2. Use Custom Metrics Wisely

Publish custom metrics for application-specific insights but avoid excessive data collection to minimize costs.

3. Implement Secure Access Controls

Apply least privilege principles by configuring IAM roles and policies to control access to CloudWatch resources and data.

4. Monitor and Optimize Costs

Regularly review CloudWatch usage and optimize costs by adjusting metric retention periods and evaluating the necessity of detailed monitoring for all resources.

Conclusion

Amazon CloudWatch is essential for monitoring and managing the performance and operational health of your AWS resources and applications. By leveraging its capabilities to monitor metrics, analyze logs and set alarms you can ensure high availability, efficient resource utilization and proactive issue resolution.