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Cover image for Day 12 - AWS Cloudwatch
Rahul Joshi
Rahul Joshi

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Day 12 - AWS Cloudwatch

#masterclassdevsecops #webdev #tutorial #devops

Modern cloud infrastructure is impossible to manage without monitoring.

You can deploy the best applications, Kubernetes clusters, serverless systems, or microservices — but if you cannot observe what’s happening inside them, production failures become nightmares.

That’s where Amazon Web Services CloudWatch comes in.

AWS CloudWatch is the central monitoring and observability platform inside AWS.

It helps engineers:

  • Monitor infrastructure
  • Collect logs
  • Track metrics
  • Create alerts
  • Visualize system health
  • Detect failures
  • Improve performance
  • Automate operational responses

Whether you are:

  • DevOps Engineer
  • Cloud Engineer
  • SRE
  • Security Engineer
  • Backend Developer
  • Platform Engineer

CloudWatch is one of the most important AWS services you must learn deeply.

🔗 Resources

  • Support the Journey on GitHub: If you're following along, consider starring and forking the repo:

https://github.com/17J/30-Days-Cloud-DevSecOps-Journey

  • AWS Command Sheet:

https://aws-command.vercel.app/

🚀 What is AWS CloudWatch?

AWS CloudWatch is a monitoring and observability service provided by AWS.

It collects and tracks:

  • Metrics
  • Logs
  • Events
  • Application telemetry
  • Infrastructure health data

from AWS resources and applications.

Think of CloudWatch as the eyes and ears of your AWS infrastructure.

🧠 Why CloudWatch Matters

Without monitoring:

  • You won’t know when servers fail
  • CPU spikes go unnoticed
  • Applications crash silently
  • Security incidents become invisible
  • Downtime increases
  • Customer experience suffers

CloudWatch helps teams move from:

Reactive Operations → Proactive Monitoring
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🏗️ Core Components of CloudWatch

CloudWatch mainly consists of four major pillars:

Component Purpose
Logs Store and analyze logs
Metrics Numerical performance data
Alarms Automated alerting
Dashboards Visualization and monitoring

📜 CloudWatch Logs

CloudWatch Logs allow you to collect, store, and analyze logs from:

  • EC2 Instances
  • Lambda Functions
  • ECS Containers
  • EKS Clusters
  • API Gateway
  • VPC Flow Logs
  • CloudTrail
  • Applications
  • Custom applications

🧩 Types of Logs in AWS

1️⃣ Application Logs

Generated by applications.

Example:

User login successful
Payment failed
Database timeout
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2️⃣ System Logs

Generated by operating systems.

Example:

Disk full
Kernel panic
SSH login
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3️⃣ Service Logs

Generated by AWS services.

Examples:

  • Lambda execution logs
  • API Gateway access logs
  • VPC Flow Logs

📦 CloudWatch Log Structure

CloudWatch logs are organized as:

Log Group
   ↓
Log Stream
   ↓
Log Events
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⚙️ How Logs Reach CloudWatch

Applications and servers send logs using:

  • CloudWatch Agent
  • Fluent Bit
  • Fluentd
  • AWS SDK
  • Lambda integration

🛠️ Installing CloudWatch Agent on EC2 

sudo yum install amazon-cloudwatch-agent
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Start agent:

sudo systemctl start amazon-cloudwatch-agent
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🔎 CloudWatch Logs Insights

CloudWatch Logs Insights helps search logs using queries.

Example query:

fields @timestamp, @message
| filter @message like /ERROR/
| sort @timestamp desc
| limit 20
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This is extremely useful during:

  • Production incidents
  • Security investigations
  • Debugging
  • Root cause analysis

Image log flow

✅ Logs Flow Architecture Diagram

EC2 / Lambda / Containers
          ↓
     CloudWatch Logs
          ↓
      Logs Insights
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📊 CloudWatch Metrics

Metrics are numerical data points collected over time.

Examples:

Resource Metric
EC2 CPU Utilization
RDS Free Storage Space
Lambda Invocation Count
ALB Request Count
ECS Memory Usage

🧠 Understanding Metrics

Metrics help answer questions like:

  • Is CPU usage high?
  • Is traffic increasing?
  • Are requests failing?
  • Is memory exhausted?
  • Is latency growing?

📈 Metric Anatomy

A metric contains:

Component Description
Namespace AWS service category
Metric Name Name of measurement
Dimensions Resource identifiers
Timestamp Time of metric
Value Actual measured value

Example 

Namespace: AWS/EC2
Metric: CPUUtilization

Value: 82%
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📌 Default AWS Metrics

AWS automatically publishes many metrics.

Examples:

Service Metric
EC2 CPUUtilization
Lambda Errors
RDS DatabaseConnections
API Gateway 4XXError
S3 BucketSizeBytes

📤 Custom Metrics

You can also publish custom metrics.

Example:

aws cloudwatch put-metric-data \
--namespace "Payments" \
--metric-name Transactions \
--value 150
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This is useful for:

  • Business KPIs
  • User signups
  • Orders processed
  • Failed payments

🚨 CloudWatch Alarms

CloudWatch Alarms monitor metrics and trigger actions when thresholds are crossed.

Example:

If CPU > 80% for 5 minutes → Trigger Alarm
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🧠 Why Alarms Matter

Without alarms:

  • Engineers discover issues too late
  • Downtime increases
  • Customer complaints arrive first

With alarms:

  • Teams respond quickly
  • Automation becomes possible
  • Reliability improves

⚡ Alarm States

CloudWatch alarms have three states:

State Meaning
OK Everything normal
ALARM Threshold breached
INSUFFICIENT_DATA Not enough data

🔔 Alarm Actions

Alarms can trigger:

  • SNS Notifications
  • Auto Scaling
  • Lambda Functions
  • Incident Management
  • EC2 Recovery

Image alarm

✅ Alarm Workflow Diagram

Metric Threshold Breached
            ↓
      CloudWatch Alarm
            ↓
        SNS Alert
            ↓
      Email / Slack
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📩 SNS Integration Example 

CloudWatch Alarm
        ↓
SNS Topic
        ↓
Email / Slack / SMS
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📈 Example CPU Alarm

Scenario:

If EC2 CPU exceeds 80% for 10 minutes:
→ Send Email Alert
→ Trigger Auto Scaling
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⚙️ Common Alarm Use Cases

Use Case Alarm
High CPU CPU > 80%
Disk Full Free Space < 10%
Failed Lambda Errors > 5
DDoS Attack Request spike
Database Stress High connections

📉 CloudWatch Dashboards

Dashboards provide centralized visual monitoring.

You can combine:

  • Metrics
  • Graphs
  • Logs
  • Alarms
  • Widgets

into one monitoring interface.

🖥️ Why Dashboards Matter

Dashboards help teams:

  • Monitor infrastructure visually
  • Detect anomalies quickly
  • Track production health
  • Share operational visibility

📊 Dashboard Widgets

Common widgets include:

Widget Purpose
Line Graph Trends over time
Number Widget Single metric value
Stacked Area Resource comparison
Text Widget Notes/documentation
Alarm Status Alert visibility

🧠 Example Production Dashboard

A real production dashboard may contain:

CPU Usage
Memory Usage
Request Count
Error Rate
Latency
Database Connections
Network Traffic
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Image dashboard

Image cpu

🏗️ Real World CloudWatch Architecture 

Applications / AWS Services
            ↓
      CloudWatch
   ↙      ↓       ↘
Logs   Metrics   Events
  ↓        ↓        ↓
Insights  Alarms  Automation
               ↓
          Dashboards
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✅ CloudWatch Architecture Diagram

Image clouwatch

🔍 CloudWatch for DevOps

CloudWatch is heavily used in DevOps workflows.

Area Usage
CI/CD Deployment monitoring
Kubernetes Container monitoring
Auto Scaling Scaling decisions
Incident Response Alerting
Security Threat detection

🔐 CloudWatch Security Monitoring

CloudWatch also supports security operations.

Examples:

  • Unauthorized API calls
  • Suspicious login attempts
  • Traffic spikes
  • IAM policy violations

Combined with:

  • Amazon Web Services CloudTrail
  • GuardDuty
  • Security Hub

it becomes part of a complete cloud security stack.

⚡ CloudWatch vs CloudTrail

Many beginners confuse them.

CloudWatch CloudTrail
Monitoring Auditing
Metrics & Logs API Activity
Performance Compliance
Real-time visibility Historical tracking

💰 CloudWatch Pricing Basics

CloudWatch pricing depends on:

  • Number of metrics
  • Log ingestion
  • Log storage
  • Dashboards
  • Alarms

Important:

Large log ingestion can become expensive.

🧠 Cost Optimization Tips

🔹 Set Log Retention Policies

Do not keep logs forever unnecessarily.

Example:

Dev Logs → 7 Days
Production Logs → 30-90 Days
Compliance Logs → Longer Retention
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🔹 Filter Unnecessary Logs

Avoid sending noisy logs.

🔹 Use Metric Filters

Extract metrics instead of storing massive logs.

🔹 Archive Old Logs

Move old logs to S3 if needed.

🏆 Best Practices

✅ Use Structured Logging

Prefer JSON logs.

Bad:

Error happened
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Good:

{
  "service":"payment-api",
  "status":"failed",
  "error":"database timeout"
}
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✅ Create Meaningful Alarms

Avoid alert fatigue.

✅ Build Service Dashboards

Every production service should have dashboards.

✅ Monitor Business Metrics

Not only infrastructure.

Examples:

  • Orders per minute
  • Failed transactions
  • Revenue events

✅ Use Centralized Logging

Aggregate logs from all systems.

☁️ CloudWatch in Modern Architectures

CloudWatch is heavily used in:

  • Microservices
  • Kubernetes
  • Serverless
  • Fintech systems
  • SaaS platforms
  • AI infrastructure

because observability is now critical for reliability engineering.

🧪 Example End-to-End Monitoring Flow

Image Flow

🎯 Final Thoughts

AWS CloudWatch is not just a monitoring tool.

It is the operational nervous system of AWS infrastructure.

If you truly want to become:

  • DevOps Engineer
  • Cloud Engineer
  • SRE
  • Platform Engineer
  • Security Engineer

you must deeply understand:

  • Logs
  • Metrics
  • Alarms
  • Dashboards
  • Observability
  • Monitoring automation

Because in modern cloud systems:

"If you cannot observe it,
you cannot reliably operate it."
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