DevOps Engineering & Automation

DevOps is the practice of breaking down the wall between development and operations - making the same team responsible for building and running software. The practical result is faster deploys, fewer incidents, and faster recovery when things go wrong. Companies that invest in DevOps engineering typically deploy 200x more frequently and recover from failures 24x faster than those that do not.

Our primary tool is GitHub Actions because it integrates tightly with code review workflows. We also work with GitLab CI, Bitbucket Pipelines, CircleCI, and Jenkins. For complex multi-repo pipelines we use tools like Nx or Turborepo for monorepo-aware builds. We adapt to what your team already uses rather than forcing a migration.

We implement blue-green or rolling deployments depending on your infrastructure. Blue-green creates an identical production environment, switches traffic at the load balancer level, and keeps the old environment live for instant rollback. Rolling deployments replace instances gradually, maintaining capacity throughout. Both approaches eliminate the maintenance windows that erode user trust.

Secrets never live in source code, environment files committed to git, or unencrypted CI variables. We store sensitive values in AWS Secrets Manager, HashiCorp Vault, or GitHub Encrypted Secrets depending on your stack, and inject them at runtime with short-lived credentials where possible. We also set up automatic rotation for database passwords and API keys.

It has three pillars: metrics (what is happening), logs (why it happened), and traces (where in the system it happened). We connect these in a single tool - Datadog, Grafana + Loki + Tempo, or the AWS native stack - so you can jump from an alert to the offending request in seconds. We also set up SLOs so you know whether your system is meeting user expectations.

Yes - this is one of the most common engagements we do. We start by documenting your current deploy process, identify the manual steps, and automate them incrementally. We never do a big-bang switch; each sprint leaves the pipeline more automated than the week before. Most teams reach fully automated deployments within 4-6 weeks.

Migrations run as a pre-deploy step before the new application version starts serving traffic. We use tools like Flyway, Liquibase, or framework-native migrate commands. Migrations must be backwards-compatible with the previous application version so a rollback does not require a matching schema rollback - which is rarely safe to perform automatically.

Yes. For Kubernetes workloads we use ArgoCD or Flux to synchronise cluster state with git. Any change to the cluster goes through a pull request, not a kubectl apply from a laptop. This gives you a complete audit trail, peer review of infrastructure changes, and automatic drift correction when the cluster state diverges from the declared state.

We apply changes to a staging environment first, run integration tests against it, and promote to production only after passing. For Terraform changes we run terraform plan in CI and require a human approval before apply. We also use tools like Infracost to surface unexpected cost changes in pull request reviews.

We configure PagerDuty or Opsgenie with escalation policies, set alert thresholds based on error budgets rather than arbitrary numbers, and write runbooks for every alert so the on-call engineer knows exactly what to do. We also conduct post-mortems after incidents and use the findings to close gaps in monitoring or automation.

It depends on where you start. The foundational setup - CI/CD pipeline, containerised deployments, basic monitoring, secrets management - is scoped before we begin, so you get a date rather than a guess from a web page. A mature setup adding GitOps, SLOs, chaos engineering and multi-environment promotion takes 8-12 weeks. The biggest variable is how many legacy deployment patterns we have to refactor on the way.

Yes - knowledge transfer is built into every engagement. We pair with your engineers throughout the project, document every decision in ADRs (Architecture Decision Records), and hold handover sessions covering daily operations, incident response, and future extension patterns. Our goal is a team that is more capable after working with us, not dependent on us.