📖 3 min read

What Is Cloud & Infrastructure?#

Cloud & infrastructure engineering covers the tools and practices that move software from a developer’s machine into production and keep it running reliably at scale. This learning track spans containerization, CI/CD automation, cloud platforms, and distributed microservices design.

Containerization with Docker#

Docker packages an application and all its dependencies into a portable container image — a lightweight, isolated unit that runs identically across environments. Key skills include writing optimized Dockerfiles with layer caching and multi-stage builds, managing images and running containers with the Docker CLI, and applying security best practices such as non-root users, image scanning with Trivy, and secrets management.

CI/CD and Deployment#

Continuous Integration (CI) automatically builds and tests code on every commit. Continuous Delivery (CD) takes passing builds and deploys them to staging or production without manual intervention. This track covers GitHub Actions workflows and GitLab CI pipelines — triggers, jobs, matrix builds, caching, and artifact management — as well as advanced deployment strategies including Blue-Green (zero-downtime switching), Canary (gradual traffic rollout), and GitOps (Git as the single source of truth for infrastructure state).

Continuous Code Quality#

SonarQube is an AI-native code verification platform that continuously analyzes source code for bugs, vulnerabilities, code smells, and test coverage gaps. Integrating SonarQube quality gates into a CI pipeline enforces a “Clean as You Code” discipline: new code must meet quality standards before it can be merged, without blocking existing legacy issues.

Cloud Platforms and AWS Services#

Modern applications deploy onto cloud infrastructure managed by providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform. The cloud service model — IaaS, PaaS, SaaS — determines how much infrastructure a team manages versus delegates to the provider. Core AWS services for developers include EC2 (virtual machines), S3 (object storage), RDS (managed relational databases), Lambda (serverless functions), ECS/EKS (container orchestration), IAM (identity and access management), and VPC (networking).

Microservices Architecture#

Microservices decompose a monolithic application into small, independently deployable services — each owning its own data store and communicating over well-defined APIs. This track covers:

  • API Gateway: the single entry point that routes client requests to the correct downstream service, handling authentication, rate limiting, and protocol translation

  • Async communication: message brokers (e.g., RabbitMQ, Kafka) decouple services so that a producer can publish an event without waiting for consumers to process it

  • SAGA pattern: a sequence of local transactions coordinated through events or orchestration to manage distributed transactions without two-phase commit

  • Redis caching: in-memory key-value store used to cache expensive database queries, session data, and computed results to reduce latency

  • Observability: structured logging, distributed tracing, and metrics collection give operators insight into system behavior in production