DevOps & CI/CD Consulting

CI/CD That Actually Works

A CI/CD pipeline is only valuable if the team trusts it. That means it needs to be fast (under 10 minutes for most builds), reliable (no flaky tests that undermine confidence), and comprehensive (catching real bugs, not just checking syntax).

We structure pipelines in stages: lint and type-check first (fast feedback), then unit tests, then integration tests, then build artifacts, then deploy to staging, then production. Each stage provides a meaningful gate, and failures include clear error messages so developers can fix issues without debugging the pipeline itself.

For monorepos, we configure affected-based testing — only running tests and builds for packages that actually changed. This keeps pipeline times fast even as the codebase grows. Tools like Turborepo or Nx provide intelligent caching that can cut build times by 80%.

Containerization and Infrastructure as Code

Docker containers solve the "works on my machine" problem, but poorly written Dockerfiles create new problems: 2GB images, 10-minute builds, and security vulnerabilities from running as root. We write optimized multi-stage Dockerfiles that produce small, secure, fast-building images with non-root user execution and layer caching optimized for your specific dependency patterns.

We use Terraform as our default IaC tool because of its cloud-agnostic nature, mature ecosystem, and excellent state management. Every piece of infrastructure — from VPCs and databases to DNS records and SSL certificates — is defined in code, reviewed in pull requests, and applied through automated pipelines. Our Terraform configurations follow a modular structure with shared modules for common patterns, environment-specific variables, and remote state stored in S3 or GCS with state locking.

For local development, we provide docker-compose configurations that spin up the full application stack — database, cache, message queue, and application servers — with a single command. New developers go from git clone to running application in under five minutes.

Monitoring That Prevents Outages

Monitoring is not about collecting metrics — it is about knowing when something is wrong and having enough context to fix it quickly. We set up monitoring at three levels: infrastructure (CPU, memory, disk, network), application (request latency, error rates, queue depths), and business (signups, orders, revenue).

Alerts are configured with care. We use error budgets and SLO-based alerting — paging the on-call engineer when the error rate threatens the service level objective, not on every individual error. This prevents alert fatigue while ensuring real problems get attention fast.