Ship Software Faster. Break Things Less Often.
The Engineering Problem DevOps Solves
Before DevOps practices, the path from code commit to production deployment was manual, inconsistent, and slow. Developers checked code into a repository. A human ran a build. Another human tested it. Another human deployed it to a staging environment. Eventually, after a coordination process that could take days, a deployment happened — accompanied by a tense period of watching logs to see if it broke something.
This process does not scale. It does not deliver the deployment frequency modern applications require. It does not provide the reliability that production systems need. And it does not give engineering teams the confidence to deploy changes without fear.
DevOps engineering practices — containerization, automated CI/CD, and infrastructure as code — change the economics of software delivery. They make deployments boring because they are consistent, automated, and reversible.
Our Three DevOps Services
Containerization & Orchestration — Packaging applications into containers and deploying them on Kubernetes or Cloud Run: Dockerfile standards, image build and registry management, GKE cluster configuration, workload deployment manifests, and operational runbooks for the containerized platform.
CI/CD Pipelines — Automating the path from code commit to production deployment: build, test, security scan, artifact publishing, environment deployment, and rollback — with the gates and approval steps appropriate for each environment.
Infrastructure as Code — Managing cloud infrastructure through version-controlled Terraform: modular Terraform design, state management, environment parity, and the CI/CD pipeline that validates and applies infrastructure changes with the same rigor applied to application code.
- Docker containerization: Dockerfile optimization and multi-stage builds
- GKE cluster setup: node pools, workload identity, RBAC, network policies
- Kubernetes workload deployment: Deployments, StatefulSets, HPA, PDB
- Helm chart development for Kubernetes application packaging
- CI/CD pipeline design: build, test, scan, deploy stages
- GitHub Actions and Cloud Build pipeline implementation
- ArgoCD GitOps deployment setup
- Container image security scanning and supply chain policy
- Terraform modular Infrastructure as Code design and implementation
- Infrastructure CI/CD: plan validation, apply pipeline, state management
How we deliver this service.
Delivery Pipeline Assessment
Current deployment process documented: how code moves from commit to production, where the manual steps are, what the deployment frequency is, and what causes the most deployment failures or rollbacks. This baseline determines the DevOps improvement roadmap.
Containerization and Platform Design
Container strategy for each application type. GKE or Cloud Run selection per workload. CI/CD pipeline architecture: stages, gates, environments, and the toolchain (GitHub Actions, Cloud Build, ArgoCD).
Platform Implementation
GKE cluster provisioned, base platform components deployed (ingress, monitoring, certificate management), and initial application workloads containerized and deployed via the CI/CD pipeline.
Pipeline and IaC Implementation
CI/CD pipelines built for each application. Infrastructure as Code written for all infrastructure in scope, with the pipeline that validates and applies changes.
Operational Handover
Monitoring dashboards, alert policies, deployment runbooks, and rollback procedures. Engineering team trained on the pipelines and platform operations. DORA metrics baseline established for ongoing improvement tracking.