Who Should Take This
Junior and mid‑level developers, system administrators, or site‑reliability engineers who have basic scripting or version‑control experience and want to adopt DevOps practices will benefit. They seek practical knowledge to design CI/CD pipelines, manage infrastructure as code, and containerize applications for faster, repeatable releases.
What's Included in AccelaStudy® AI
Adaptive Knowledge Graph
Practice Questions
Lesson Modules
Console Simulator Labs
Exam Tips & Strategy
20 Activity Formats
Course Outline
60 learning goals
1
DevOps Culture and Principles
2 topics
DevOps Philosophy
- Describe the core DevOps principles including breaking down silos between development and operations, shared responsibility, continuous improvement, and the CALMS framework (Culture, Automation, Lean, Measurement, Sharing)
- Describe the Three Ways of DevOps including systems thinking (flow), amplifying feedback loops, and continuous experimentation and learning as described in The Phoenix Project
- Analyze how DevOps practices reduce lead time, increase deployment frequency, lower change failure rate, and shorten mean time to recovery as measured by the DORA metrics
Organizational Patterns
- Describe team topologies for DevOps including platform teams, stream-aligned teams, enabling teams, and complicated subsystem teams and explain Conway's Law implications
- Evaluate the trade-offs between centralized platform teams and embedded DevOps engineers and analyze how organization size affects the optimal DevOps team structure
2
Version Control Workflows
3 topics
Branching Strategies
- Describe common branching strategies including GitFlow, GitHub Flow, trunk-based development, and release branching and explain the trade-offs of each model
- Analyze trunk-based development practices including short-lived feature branches, feature flags for incomplete work, and how they enable continuous integration
- Evaluate branching strategy selection criteria based on team size, release cadence, regulatory requirements, and the relationship between branching model and deployment frequency
Code Review and Collaboration
- Describe pull request workflows including code review practices, approval gates, automated checks, and merge strategies (merge commit, squash, rebase) for collaborative development
- Implement semantic versioning conventions (MAJOR.MINOR.PATCH) and changelog generation for release management and dependency compatibility communication
Repository Management
- Describe monorepo versus polyrepo strategies and explain how each affects dependency management, code sharing, CI pipeline complexity, and team autonomy
- Implement git hooks including pre-commit, pre-push, and commit-msg hooks for automated code quality enforcement before changes enter the repository
- Evaluate repository access control strategies including branch protection rules, required reviewers, and signed commits for supply chain security
3
Continuous Integration
3 topics
CI Principles and Practices
- Describe continuous integration principles including frequent commits to mainline, automated builds on every commit, fast feedback loops, and the practice of fixing broken builds immediately
- Implement a CI pipeline structure including source checkout, dependency installation, compilation, unit testing, integration testing, static analysis, and artifact generation stages
- Analyze CI pipeline optimization techniques including parallel test execution, build caching, incremental builds, and test selection strategies to minimize feedback time
Build and Test Automation
- Describe the testing pyramid including unit tests, integration tests, and end-to-end tests and explain how each level contributes to CI confidence with different speed and coverage trade-offs
- Implement artifact versioning and management strategies including semantic version tagging, immutable artifacts, and artifact repositories for build output storage
- Implement pipeline-as-code patterns using declarative configuration files that define build steps, triggers, and environment requirements for reproducible CI pipelines
Code Quality and Static Analysis
- Describe code quality tools including linters, formatters, SAST scanners, and code coverage reporters and explain how each integrates into CI pipelines for automated quality gates
- Implement code coverage thresholds and quality gate policies that block merges when coverage drops below defined percentages or new code introduces unresolved issues
- Analyze the trade-offs between strict quality gates that may slow velocity and lenient gates that allow technical debt accumulation and evaluate adaptive threshold strategies
4
Continuous Delivery and Deployment
3 topics
Deployment Strategies
- Describe the difference between continuous delivery and continuous deployment and explain how deployment pipelines automate the path from commit to production
- Describe deployment strategies including blue-green deployment, canary releases, rolling updates, and recreate and explain the risk and downtime characteristics of each
- Implement a blue-green deployment workflow including traffic switching, health checks, and rollback procedures for zero-downtime production releases
- Implement canary deployment with progressive traffic shifting, automated metrics evaluation, and automatic rollback triggers based on error rate thresholds
- Analyze deployment strategy selection criteria based on application architecture, risk tolerance, infrastructure capabilities, and rollback requirements
Release Management
- Implement feature flag patterns to decouple deployment from release and enable dark launches, A/B testing, and gradual feature rollouts without code changes
- Describe database migration strategies for zero-downtime deployments including expand-contract pattern, backward-compatible schema changes, and data migration ordering
- Evaluate rollback strategies including code rollback, database rollback, and configuration rollback and analyze the challenges of rolling back stateful versus stateless applications
Environment Management
- Describe deployment environment tiers including development, staging, and production and explain how environment parity reduces deployment risk and debugging difficulty
- Implement environment-specific configuration management using environment variables, config files, and secrets injection for secure deployment across multiple environments
- Implement infrastructure provisioning patterns for ephemeral environments that are created per pull request and destroyed after merge for isolated integration testing
- Analyze configuration drift between environments and evaluate strategies including GitOps and declarative configuration to ensure environment consistency
5
Infrastructure as Code and Containerization
3 topics
Infrastructure as Code Concepts
- Describe infrastructure as code principles including declarative versus imperative approaches, idempotency, version-controlled infrastructure, and the benefits over manual provisioning
- Describe configuration management concepts including desired state configuration, drift detection, convergence, and the difference between provisioning tools and configuration tools
- Analyze the immutable infrastructure pattern versus mutable infrastructure and evaluate how treating servers as cattle rather than pets affects reliability and deployment speed
Containerization Concepts
- Describe containerization principles including process isolation, image layering, container registries, and how containers differ from virtual machines in resource utilization
- Describe container image best practices including minimal base images, multi-stage builds, layer caching, security scanning, and image tagging strategies for production use
- Analyze the benefits and challenges of containerized deployments including environment consistency, resource isolation, networking complexity, and persistent storage considerations
Orchestration Concepts
- Describe container orchestration concepts including service discovery, load balancing, auto-scaling, rolling updates, and self-healing for managing containerized applications at scale
- Analyze the operational complexity of container orchestration and evaluate when the overhead of orchestration platforms is justified versus simpler deployment models
6
Monitoring, Observability, and SRE
4 topics
Monitoring and Observability
- Describe the three pillars of observability including metrics (counters, gauges, histograms), structured logs, and distributed traces and explain how each contributes to system understanding
- Implement monitoring strategies including the USE method (utilization, saturation, errors) for infrastructure and the RED method (rate, errors, duration) for services
- Implement alerting strategies including meaningful thresholds, alert routing, escalation policies, and on-call rotations to reduce alert fatigue and improve response times
- Analyze the difference between monitoring and observability and evaluate how observability enables debugging of unknown-unknowns in complex distributed systems
SRE Principles
- Describe SRE fundamentals including service level indicators (SLIs), service level objectives (SLOs), service level agreements (SLAs), and error budgets as reliability management tools
- Implement SLO definition and error budget calculation for a service and explain how error budget consumption drives decisions about feature velocity versus reliability investment
- Analyze the relationship between SRE practices and DevOps culture and evaluate how toil reduction, blameless postmortems, and automation priorities align with DevOps principles
Incident Management
- Describe incident management lifecycle including detection, triage, response, communication, resolution, and post-incident review with blameless postmortem practices
- Implement incident response procedures including severity classification, incident commander role assignment, stakeholder communication templates, and status page updates
- Implement blameless postmortem documentation including timeline reconstruction, root cause analysis, contributing factors, action items, and process improvement recommendations
- Evaluate chaos engineering principles including controlled fault injection, blast radius limitation, and steady-state hypothesis testing as proactive reliability practices
Logging and Tracing
- Implement structured logging practices using JSON log formats with correlation IDs, severity levels, timestamps, and contextual fields for searchable log aggregation
- Describe distributed tracing concepts including trace context propagation, span hierarchies, and how traces connect request flows across multiple services for latency debugging
- Implement dashboard design principles including the four golden signals, meaningful aggregations, and drill-down capabilities for effective operational visibility
7
Security and Compliance in DevOps
1 topic
DevSecOps Practices
- Describe the shift-left security approach and explain how integrating security scanning, dependency auditing, and compliance checks into CI/CD pipelines reduces vulnerability exposure
- Implement secrets management practices including environment variable injection, vault integration patterns, and secret rotation strategies to prevent credential exposure in code and logs
- Implement supply chain security practices including dependency scanning, software bill of materials (SBOM), signed artifacts, and container image vulnerability scanning
- Analyze the trade-offs between security gate strictness and deployment velocity and evaluate strategies for balancing security requirements with developer productivity
Scope
Included Topics
- DevOps culture, principles, and practices including continuous integration, continuous delivery, continuous deployment, infrastructure as code concepts, configuration management concepts, and the DevOps lifecycle from development through operations
- CI/CD pipeline design including build automation, automated testing integration, artifact management, deployment strategies (blue-green, canary, rolling, feature flags), and pipeline-as-code patterns
- Monitoring and observability fundamentals including the three pillars (metrics, logs, traces), incident management, SRE principles (SLOs, SLIs, error budgets), version control workflows (GitFlow, trunk-based), and containerization concepts
Not Covered
- Specific cloud provider services and consoles (AWS, Azure, GCP)
- Specific infrastructure as code tools (Terraform, CloudFormation, Pulumi)
- Specific container orchestration platforms (Kubernetes, Docker Swarm)
- Specific CI/CD tools (Jenkins, GitHub Actions, GitLab CI)
- Programming language-specific build systems and testing frameworks
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