DevOps and platform engineering
CI/CD, infrastructure as code, and container platforms, so shipping a change stops being an event.
The deploy everyone dreads
Most mid-market engineering teams have a deployment process that grew organically: a script someone wrote three years ago, a manual checklist taped to a monitor, a Friday-afternoon freeze because releases have gone wrong before. It works, technically, but nobody trusts it, and every release costs more anxiety than it should.
The fix usually isn't more process. It's less manual process: pipelines that test and deploy the same way every time, infrastructure defined in code instead of remembered by one person, and container platforms that make "it worked on my machine" a non-issue.
We build this incrementally. A CI/CD pipeline for the highest-risk application first, then infrastructure as code for the environments that change most often, then a container platform if the workload actually benefits from one. We don't rebuild what already works.
What's included
- CI/CD pipeline designBuild, test, and deploy pipelines in GitHub Actions, GitLab CI, or Azure DevOps, with automated tests gating every release.
- Infrastructure as codeTerraform or equivalent for repeatable, version-controlled environments, so "what changed" has an answer.
- Container platform setupDocker and Kubernetes, or a managed equivalent like ECS or Azure Container Apps, sized to the workload rather than defaulted into.
- Secrets and configuration managementCentralized secrets handling that gets credentials out of scripts and environment files.
- Release strategyBlue-green or canary deployment patterns where the risk of a bad release justifies the setup.
- Observability hooksDeployment events wired into the monitoring stack, so a bad release is caught in minutes, not from a support ticket.
How the engagement runs
- 01Pipeline assessmentA look at how releases happen today: what's manual, what's fragile, and what would break first under more traffic or more releases.
- 02Pilot pipelineOne application gets a real CI/CD pipeline end to end, proving the pattern before it spreads.
- 03Infrastructure as code rolloutEnvironments brought under version control, starting with the one that changes most often.
- 04Handoff and documentationYour team ends up owning and operating the pipeline, not calling us for every change.
Technologies and platforms
- GitHub Actions
- GitLab CI
- Azure DevOps
- Terraform
- Docker
- Kubernetes
- AWS ECS
- Azure Container Apps
Proof
This is the same discipline behind our own SaaS platforms: automated pipelines, infrastructure as code, and deployments that don't require anyone to hold their breath. We build client platforms the way we build our own.
Common questions
Do we need Kubernetes, or is that overkill for us?
Often overkill. Kubernetes earns its complexity at a certain scale and workload shape; plenty of estates are better served by a simpler container platform or none at all. The assessment tells you honestly which camp you're in before anything gets built.
Can you work with our existing pipeline instead of replacing it?
Yes. Most engagements improve what exists rather than ripping it out: adding tests, fixing a fragile deploy step, or bringing one environment under infrastructure as code before touching the rest.
Who owns the pipeline after you build it?
Your team does. We document and hand off deliberately so you are not calling us for every routine change; ongoing support is available if you want it, not required.
How is this different from hiring a DevOps engineer?
A staff augmentation placement is one option if you want a dedicated person; this service is project-based, aimed at getting a specific pipeline or platform built and handed off.
Related services
Bring the release that went wrong last time.
Thirty minutes on what broke and why. We'll tell you which piece to fix first.