DevOps Engineer roadmap

Linux powers the vast majority of cloud servers and containers running modern web applications. The command line interface lets you interact directly with the operating system using text commands instead of graphical menus. This is vital because cloud servers rarely have screens or desktop environments attached.

Imagine you need to find why a web server crashed; you use terminal commands to read log files in real time and check available disk space. This skill matters because every deployment, troubleshooting session, and automation script relies on navigating Linux environments smoothly.

• Navigate directories using cd, ls, and pwd
• Inspect file contents with cat, tail, and grep
• Manage running processes using top and kill
• Modify file permissions with chmod and chown

Shell scripting involves writing short files containing sequences of terminal commands that run automatically in order. Instead of typing out ten repetitive commands every morning to back up a database, you write them once in a Bash script and run it with a single command.

Think of it as recording a macro for your daily administrative chores. You can add logic like loops and conditions to handle errors gracefully. This matters for DevOps because automation eliminates human typing mistakes and saves hours of manual work across server fleets.

• Use the standard shebang line at the top of scripts
• Store and reference values using variables
• Control execution flow with if statements and loops
• Capture exit codes to handle command failures

Networking is the invisible glue connecting users, servers, databases, and microservices across the internet. It relies on agreed rules and addresses to ensure data packets reach their intended destination securely and accurately.

For example, when your browser loads a website, it translates a human-readable domain name into an IP address using DNS, then opens a secure connection over specific network ports. Understanding networking matters because most deployment bugs stem from misconfigured firewalls, blocked ports, or routing errors.

• Explain how IP addresses and subnets divide networks
• Trace domain resolution using DNS records
• Distinguish between TCP reliability and UDP speed
• Secure remote access using SSH keys and ports

Git is a distributed version control system that records every change made to your source code and infrastructure configurations over time. It allows multiple people to work on the same project simultaneously without overwriting each other's work.

Imagine writing a report where you can instantly revert to yesterday's draft or test a new chapter in a separate copy before merging it into the final version. Git matters for DevOps because all automation scripts, pipeline definitions, and server configurations must be tracked and reviewed safely.

• Initialise local repositories and track file changes
• Create branches to experiment with new features safely
• Combine work from others using pull requests and merges
• Resolve merge conflicts when overlapping edits occur

Docker packages your application code, runtime, libraries, and operating system files into a single self-contained unit called a container. This guarantees that the application runs identically whether it is on your local laptop, a staging server, or a cloud cluster.

Think of it as shipping a fragile product inside a sturdy, standardized wooden crate that fits onto any delivery truck. This matters because it eliminates the classic frustrating excuse that code worked fine on a developer's local machine but failed in production.

• Write reproducible instructions inside a Dockerfile
• Build immutable container images from those files
• Run isolated containers locally with mapped ports
• Persist data safely using Docker volumes

Kubernetes is an orchestration platform that automates the deployment, scaling, and operational management of containerized applications across multiple servers. If a server hosting your containers crashes, Kubernetes automatically spins up replacements on healthy machines.

Picture an automated warehouse manager that notices a delivery line is slowing down and instantly assigns extra robotic workers to handle the load. This matters because modern systems require high availability that manual server management cannot provide reliably.

• Define application state using Pod and Deployment manifests
• Expose services internally and externally using Services
• Scale replica counts up and down dynamically
• Inspect cluster health using command line tools

Helm is a package manager for Kubernetes that helps you define, install, and upgrade even the most complex Kubernetes applications. It introduces templating to configuration files so you can reuse the same setup across development, staging, and production environments.

Think of it like an installer wizard on your computer that asks you a few simple questions before setting up a complex software suite. Helm matters because managing raw YAML files across multiple clusters quickly becomes messy and error-prone without structured packaging.

• Structure applications into reusable Helm charts
• Customise deployments using values files per environment
• Upgrade and rollback releases smoothly
• Search and install pre-made charts from repositories

Continuous Integration is the practice where members of a team integrate their code changes frequently, usually multiple times a day. Each integration is verified automatically by an automated build and test machine to detect integration errors as early as possible.

Imagine a bricklayer checking each newly laid brick with a spirit level immediately rather than waiting until the entire wall is finished. CI matters because catching bugs immediately prevents costly debugging sessions later when many changes are bundled together.

• Trigger automated checks on every code push
• Run unit tests and linting automatically
• Fail builds immediately when tests encounter errors
• Provide fast feedback loops to developers

GitHub Actions is an automation platform built directly into GitHub that lets you create custom CI and CD pipelines using YAML configuration files. It spins up virtual runner environments to execute your workflows whenever repository events occur.

Think of it as an invisible assistant sitting inside your code repository who automatically runs your test checklist every time someone suggests a change. This matters because keeping your pipelines close to your source code makes maintenance simple and transparent.

• Define workflows using YAML inside the github workflows folder
• Trigger workflows on pull requests and pushes
• Use pre-built community actions for common tasks
• Secure sensitive tokens using repository secrets

Deployment strategies are structured methods for releasing new software updates into production without causing downtime or disrupting active users. Different approaches balance speed, risk, and infrastructure complexity in various ways.

For example, a rolling update replaces old server instances with new ones a few at a time so the service never goes offline. This matters because modern users expect continuous availability, meaning maintenance windows are no longer acceptable for routine releases.

• Perform rolling updates to replace instances gradually
• Use blue-green environments for instant cutovers
• Route a small subset of traffic using canary releases
• Plan quick rollbacks for faulty deployments

Cloud computing lets you rent servers, storage, and networking hardware from providers over the internet instead of buying physical computers. You only pay for what you use, and you can scale resources up or down in seconds.

Think of it like renting a fully equipped commercial kitchen for an evening rather than building a restaurant from scratch. Cloud basics matter because modern DevOps engineers operate entirely within these virtual datacentres.

• Provision virtual compute instances on demand
• Store files securely in managed object storage
• Isolate resources using virtual private clouds
• Connect managed databases with automated backups

Terraform is an Infrastructure as Code tool that lets you define cloud resources in human-readable configuration files. It calculates what needs to change and creates, updates, or destroys cloud infrastructure safely and repeatably.

Imagine writing a blueprint for a house that automatically builds itself when submitted to a contractor. This matters because clicking around in a web console leads to undocumented mistakes, whereas code is version-controlled and reviewable.

• Write infrastructure definitions using HashiCorp Configuration Language
• Preview planned changes using the plan command
• Apply configurations to create cloud resources
• Manage state files securely across teams

Cloud security involves protecting your data, servers, and networks from unauthorized access using strict access controls and encryption. The principle of least privilege ensures users and services only get the exact permissions they need to do their jobs.

Think of giving staff members keys only to the specific rooms they need to work in, rather than a master key to the entire building. This matters because a single misconfigured storage bucket can expose sensitive customer data to the public internet.

• Enforce least privilege access using identity policies
• Store passwords and keys in managed secret managers
• Isolate sensitive workloads in private subnets
• Enable encryption for data at rest and in transit

Configuration management tools like Ansible ensure that your servers are set up correctly and remain in a known, consistent state over time. They install required software, update settings, and fix configuration drift without manual intervention.

Picture a cleaning crew that visits an office every night to ensure every desk, computer, and chair is arranged according to company standards. This matters because servers left untouched often accumulate undocumented changes that cause mysterious bugs.

• Write idempotent automation playbooks
• Manage server setups over secure SSH connections
• Organise variables and templates cleanly
• Detect and correct configuration drift automatically

Centralised logging collects log output from all your distributed servers, containers, and applications into one searchable platform. Instead of logging into twenty different servers to find an error, you query a single dashboard.

Think of it like having a central security desk that receives status reports from every security camera in a large building simultaneously. This matters because complex microservice architectures make tracing errors impossible without unified log streams.

• Forward structured JSON logs from applications
• Aggregate streams into a central searchable store
• Query logs efficiently using filters and time ranges
• Mask sensitive information like passwords in logs

Metrics monitoring involves tracking numeric performance indicators like CPU usage, memory consumption, request latency, and error rates over time. These numbers are displayed on real-time dashboards to give you a quick overview of system health.

Imagine the dashboard of a car showing your speed, fuel level, and engine temperature while you drive. This matters because spotting a rising memory trend early lets you fix a memory leak before the server crashes.

• Scrape numeric time-series data from services
• Design clear dashboards for operational health
• Track key performance indicators and resource usage
• Store historical metrics for trend analysis

Alerting and incident response define how your team finds out about production failures and how you work together to fix them calmly. Good alerts wake engineers only for real user-facing problems, and post-incident reviews prevent repeat failures.

Think of a smoke detector that sounds an alarm only when there is an actual fire, accompanied by a clear fire escape plan. This matters because reliable systems require fast human intervention when automated self-healing fails.

• Configure actionable alerts based on symptom thresholds
• Route notifications to the right on-call engineers
• Follow structured troubleshooting runbooks
• Conduct blameless post-mortem reviews after outages

Site Reliability Engineering applies software engineering principles to infrastructure and operations problems. It uses service level objectives and error budgets to balance the speed of releasing new features with the need for system stability.

Think of a budget where you can spend money on risks as long as you stay above a minimum savings threshold. This matters because it gives teams a data-driven way to decide when to slow down and fix bugs versus when to build new features.

• Define user-focused service level indicators
• Set realistic service level objectives with stakeholders
• Manage risk using measurable error budgets
• Automate away repetitive operational toil