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Learner Guide: C1391 AWS Certified DevOps Engineer Associate Training

Guide Overview

This learner guide provides a step-by-step path through the AWS Certified DevOps Engineer course labs. The labs are grouped by the AWS DevOps Engineer exam domains: SDLC Automation, Configuration Management and Infrastructure as Code, Resilient Cloud Solutions, Monitoring and Logging, Incident and Event Response, and Security and Compliance.

The course is designed as a five-day practical course. Learners can complete activities in a live AWS account, an instructor sandbox, or as guided architecture walkthroughs when live access is not available.

Learning Outcomes

By the end of this guide, learners will be able to:

  • Design CI/CD pipelines for single-account and multi-account environments.
  • Integrate automated tests, build stages, artifact repositories, and deployment strategies.
  • Use infrastructure as code concepts with CloudFormation, SAM, CDK, StackSets, and reusable components.
  • Automate account provisioning, configuration, patching, inventory, and compliance checks.
  • Design highly available, scalable, and self-healing AWS workloads.
  • Configure centralized logs, metrics, alarms, dashboards, and traces.
  • Build event-driven incident response and remediation workflows.
  • Apply security controls, audit automation, encryption, identity governance, and compliance monitoring.
  • Prepare for AWS DevOps Engineer exam scenarios.

Recommended 5-Day Sequence

Day Labs Domain Focus
Day 1 Labs 01-02 SDLC automation, CI/CD, tests, artifacts, deployments
Day 2 Labs 03-04 IaC, reusable components, multi-account operations, Systems Manager
Day 3 Labs 05-06 Resilience, scaling, disaster recovery, RTO, RPO
Day 4 Labs 07-08 Monitoring, logging, incident response, event-driven remediation
Day 5 Labs 09-10 Security, compliance, audit automation, capstone readiness

Before You Start

Step 1: Confirm AWS Access

  1. Confirm whether you will use a personal AWS account or an instructor sandbox.
  2. Confirm the AWS Region assigned for the course.
  3. Confirm the naming prefix required by the instructor.
  4. Confirm whether multi-account features are simulated or available live.

Example:

Region: ap-southeast-1
Name prefix: learner01
Multi-account access: simulated

Step 2: Install Tools

  1. Install AWS CLI v2.
  2. Install Git.
  3. Install AWS SAM CLI.
  4. Install Docker Desktop or a compatible container runtime if SAM local testing is required.
  5. Install Python 3.11 or Node.js 20 LTS.
  6. Install a code editor.
  7. Review Lab Tools and Setup.

Step 3: Configure AWS CLI

aws configure --profile c1391

Validate the profile:

aws sts get-caller-identity --profile c1391

For the lab session, set environment variables.

export AWS_PROFILE=c1391
export AWS_REGION=ap-southeast-1

For Windows PowerShell:

$env:AWS_PROFILE = "c1391"
$env:AWS_REGION = "ap-southeast-1"

Step 4: Use a Naming Standard

Use the same prefix across labs.

c1391-<learner-prefix>-<service>-<purpose>

Examples:

c1391-learner01-pipeline-app
c1391-learner01-cfn-network
c1391-learner01-alarm-errors

Domain 1: SDLC Automation

Labs Covered

  • Lab 01: CI/CD Pipeline Foundations
  • Lab 02: Automated Testing, Artifacts, and Deployment Strategies

Step-by-Step Learning Path

  1. Map the software delivery lifecycle.
  2. Build a pipeline model with source, build, test, artifact, deploy, and validation stages.
  3. Select repositories for source code, packages, container images, and deployment artifacts.
  4. Add automated tests at appropriate pipeline stages.
  5. Compare deployment strategies for EC2, ECS, EKS, Lambda, and serverless applications.

Key Questions

  • Which stages should exist in a production CI/CD pipeline?
  • What artifact should move between build and deploy stages?
  • When should canary or blue-green deployment be used?
  • How do secrets move through the pipeline without being stored in source code?

Domain 2: Configuration Management and IaC

Labs Covered

  • Lab 03: Infrastructure as Code with CloudFormation, SAM, and CDK
  • Lab 04: Multi-Account Automation and Systems Manager Operations

Step-by-Step Learning Path

  1. Define infrastructure as reusable code.
  2. Compare CloudFormation, SAM, CDK, StackSets, and Service Catalog.
  3. Plan account baselines using Organizations, Control Tower, SCPs, and IAM roles.
  4. Use Systems Manager and AWS Config concepts for inventory, patching, configuration, and compliance.
  5. Create automation plans for repeatable operational tasks.

Key Questions

  • What is the difference between template drift and configuration drift?
  • When should StackSets be used?
  • How do SCPs differ from IAM policies?
  • Which service should collect inventory and run patch automation?

Domain 3: Resilient Cloud Solutions

Labs Covered

  • Lab 05: Highly Available and Scalable Workloads
  • Lab 06: Automated Recovery, Backup, RTO, and RPO

Step-by-Step Learning Path

  1. Translate business availability requirements into technical architecture.
  2. Identify single points of failure.
  3. Apply Multi-AZ, multi-Region, load balancing, auto scaling, and caching patterns.
  4. Select backup and disaster recovery strategies.
  5. Plan failover tests against RTO and RPO targets.

Key Questions

  • What is the difference between RTO and RPO?
  • When is warm standby better than pilot light?
  • Which metrics should drive scaling?
  • How can Route 53 support failover?

Domain 4: Monitoring and Logging

Lab Covered

  • Lab 07: Centralized Monitoring, Logs, Metrics, and Dashboards

Step-by-Step Learning Path

  1. Define application and infrastructure signals.
  2. Collect logs and metrics centrally.
  3. Create metric filters, alarms, and dashboards.
  4. Use Logs Insights and X-Ray concepts for troubleshooting.
  5. Apply log retention and encryption controls.

Key Questions

  • Which logs should be retained centrally?
  • Which metrics indicate system health?
  • When should a metric filter become an alarm?
  • How does tracing help in distributed applications?

Domain 5: Incident and Event Response

Lab Covered

  • Lab 08: Event-Driven Incident Response and Remediation

Step-by-Step Learning Path

  1. Identify event sources such as CloudTrail, AWS Health, Config, and EventBridge.
  2. Route events to processing workflows.
  3. Notify operators through SNS or chat integrations.
  4. Trigger remediation with Lambda, Systems Manager Automation, or Step Functions.
  5. Document root cause analysis and post-incident actions.

Key Questions

  • Which events should notify humans?
  • Which events can be remediated automatically?
  • What evidence is required before closing an incident?
  • How do you prevent automation from making an incident worse?

Domain 6: Security and Compliance

Lab Covered

  • Lab 09: DevSecOps Security, Compliance, and Audit Automation

Step-by-Step Learning Path

  1. Design identity and access at scale.
  2. Apply least privilege, permission boundaries, SCPs, and role assumptions.
  3. Automate encryption and data protection.
  4. Use GuardDuty, Inspector, Security Hub, IAM Access Analyzer, Config, and CloudTrail.
  5. Build alerting and audit evidence workflows.

Key Questions

  • What is the difference between permission boundaries and SCPs?
  • Which service detects public S3 buckets or unencrypted resources?
  • How should security findings become operational tickets or events?
  • Which logs prove who changed a resource?

Capstone Readiness

Lab Covered

  • Lab 10: Capstone: AWS DevOps Engineer Readiness

Step-by-Step Learning Path

  1. Read the scenario carefully.
  2. Identify SDLC, IaC, resilience, observability, incident response, and security requirements.
  3. Choose AWS services and justify each choice.
  4. Create a deployment, operations, and incident response plan.
  5. Complete the readiness checklist.

Lab Reporting Template

Lab number:
Domain:
Scenario:
AWS services:
Design choices:
Commands or configuration:
Validation evidence:
Failure symptoms:
Troubleshooting notes:
Security notes:
Cleanup completed:
Exam notes:

Cleanup Checklist

At the end of each lab day:

  1. Delete unused CloudFormation and SAM stacks.
  2. Delete test pipelines, build projects, deployment applications, and artifact repositories.
  3. Delete test Lambda functions, queues, topics, event rules, and Step Functions workflows.
  4. Delete log groups, dashboards, alarms, and test metrics if instructed.
  5. Delete test IAM roles, policies, KMS keys or aliases, secrets, and parameters.
  6. Empty and delete lab S3 buckets.
  7. Confirm no costly resources remain running.

Final Review Checklist

  1. Review all six exam domains.
  2. Practice explaining service selection under constraints.
  3. Review deployment patterns and rollback triggers.
  4. Review IaC drift, StackSets, Organizations, and SCP scenarios.
  5. Review monitoring evidence for failed deployments and incidents.
  6. Review security and compliance automation workflows.

References