Introduction to AWS CloudWatch Key Features

Welcome! In this guide, you’ll learn how to build a centralized observability system in AWS using CloudWatch. You’ll see how to configure alarms, notifications, logging, and more—so you can maintain application health and swiftly diagnose issues.

The image illustrates AWS CloudWatch use cases, focusing on building centralized alarms, notifications, logging, and observability systems, with a detailed architecture diagram of AWS services.

What Is AWS CloudWatch?

AWS CloudWatch is a unified monitoring service that collects metrics, logs, and events from your AWS resources, applications, and on-premises systems. It provides:

Full-stack visibility: From infrastructure (EC2, Lambda) to application layers.
Centralized dashboarding: Aggregate data in one place.
Automated actions: Trigger alerts, runbooks, or remediation workflows.

Note

CloudWatch integrates seamlessly with AWS services like EC2, RDS, Lambda, and EventBridge to give you holistic insight.

Why Full-Stack Observability Matters

Early issue detection: Catch anomalies before they impact users.
Faster troubleshooting: Correlate logs, metrics, and traces in one console.
Cost optimization: Identify underutilized resources.

The image is an introduction to AWS CloudWatch, highlighting its key features such as alarms, rules, RUM, metrics insights, events, logs, and synthetics.

AWS CloudWatch Feature Overview

Feature	Description	Example Use Case
Alarms	Notify when metrics breach thresholds	Trigger an SNS notification if CPU > 80% for 5 minutes
Rules	Automate workflows based on event patterns	Run a Lambda function on EC2 state change
Real User Monitoring	Collect user session data to analyze performance and behavior	Track page load times for web customers
Metrics Insights	Perform SQL-like queries on metric data	Analyze trends across multiple dimensions
Events	Schedule or respond to infrastructure and application events	Schedule daily backups; react to Auto Scaling events
Logs	Ingest, store, and analyze log data	Create dashboards to track error rates in application logs
CloudWatch Synthetics	Run canaries to simulate user journeys and API checks	Verify endpoint availability every 5 minutes

Deep Dive: Key Features

1. Alarms

CloudWatch Alarms monitor metrics and send notifications when values cross thresholds. Use SNS, Lambda, or Auto Scaling actions for immediate response.

Example: Create an alarm for high CPU utilization

aws cloudwatch put-metric-alarm \
  --alarm-name HighCPU \
  --metric-name CPUUtilization \
  --namespace AWS/EC2 \
  --statistic Average \
  --period 300 \
  --threshold 80 \
  --comparison-operator GreaterThanThreshold \
  --dimensions Name=InstanceId,Value=i-0123456789abcdef0 \
  --evaluation-periods 2 \
  --alarm-actions arn:aws:sns:us-east-1:123456789012:HighCPUAlert

2. Rules

CloudWatch Rules (EventBridge) let you define event patterns or schedules to trigger actions.

Example: Schedule a Lambda function at midnight

aws events put-rule \
  --name DailyJob \
  --schedule-expression "cron(0 0 * * ? *)"

3. Real User Monitoring (RUM)

RUM captures actual user sessions in web applications to reveal performance bottlenecks and user behavior patterns.

Warning

Monitor RUM data ingestion and retention settings to control costs—especially for high-traffic applications.

4. Metrics Insights

Run advanced, ad-hoc queries on your metrics with a SQL-like language. This helps you spot trends and correlations across large datasets.

5. Events

CloudWatch supports:

Time-based events (scheduled tasks)
Event-driven triggers (e.g., EC2 state changes, CodePipeline transitions)

6. Logs

Centralize application and system logs. Use filters to extract meaningful patterns, set metric filters, and attach alarms.

Example: Create a metric filter for ERROR logs

aws logs put-metric-filter \
  --log-group-name /aws/my-app \
  --filter-name ErrorFilter \
  --filter-pattern "ERROR" \
  --metric-transformations \
      metricName=ErrorCount,metricNamespace=MyApp,metricValue=1

7. CloudWatch Synthetics

Create canaries—scripts that run on a schedule to simulate user workflows, ping APIs, and validate endpoints.

Example: Define a canary in YAML

Name: MyCanary
Schedule:
  Expression: rate(5 minutes)
Source:
  Handler: index.handler
  Script: |
    const synthetics = require('Synthetics');
    // your canary script here
RuntimeVersion: syn-nodejs-puppeteer-3.4

Next Steps

In the following lessons, we'll walk through hands-on examples:

Deploying alarms and dashboards via Terraform
Querying Metrics Insights for capacity planning
Automating log analysis with Lambda

References and Further Reading

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