Most teams don't have a DevOps problem, they have a specific bottleneck — deploys that take an hour, an AWS bill nobody can explain, or a cluster nobody fully understands anymore. We start with an infrastructure audit, fix what's actually costing you time or money, and hand off pipelines and infrastructure-as-code your team can run without us.
Infrastructure work is easy to postpone until it becomes an incident. A dedicated team fixes it before that happens — and leaves you able to maintain it.
We map your current pipelines, cloud spend, and deployment process first — so recommendations are based on what's actually there, not a generic checklist.
Pipelines built around how your team already works — tests, staging, approvals — so adoption doesn't require retraining everyone.
Right-sizing, reserved capacity, and architecture fixes that come with a before/after bill, not a vague promise of savings.
We tell you when a managed container service or serverless setup is simpler and cheaper — Kubernetes isn't the default answer.
Terraform-managed environments that are reproducible and reviewable, instead of manually configured resources only one person understands.
Documentation, runbooks, and access your in-house engineers actually use after we're done — not a black box that needs us on retainer forever.
Scoped to the bottleneck you have — not a fixed bundle of services you'll pay for and never touch.
A concrete review of pipelines, cloud architecture, and spend, with prioritized fixes and estimated impact.
Automated build, test, and deploy pipelines on GitHub Actions, GitLab CI, or your existing tooling.
Moving to or restructuring AWS, GCP, or Azure environments for reliability and cost, not just because it's trendy.
Cluster setup, scaling policies, and observability for teams that genuinely need container orchestration.
Terraform modules for reproducible, version-controlled environments across dev, staging, and production.
Right-sizing resources, monitoring, and incident-response setup so 3am pages become the exception, not the norm.
We start with an infrastructure audit — pipelines, cloud architecture, and spend — then scope specific work from there: CI/CD setup, cloud migration, Kubernetes, cost optimization, or a mix. You get a prioritized plan, not a fixed package.
It depends on scope — a CI/CD setup for a single product costs far less than a full cloud migration with Kubernetes. We give a fixed estimate after the audit rather than a generic range, so you're not paying for work you don't need yet.
It usually comes down to what your team already knows, what your existing stack integrates with, and specific service needs — AWS has the broadest ecosystem, GCP often wins on data/ML tooling, Azure fits if you're already in the Microsoft stack. We recommend based on your actual constraints, not a default.
For a single product with a reasonably standard test suite, yes. Pipelines are built around how your team already ships — branching model, approvals, staging — so adoption doesn't require a process overhaul on top of the tooling change.
Often serverless or a managed container service is simpler and cheaper, especially below a certain scale or team size. We recommend Kubernetes when you have the workload complexity and team capacity to justify it — not as a default architecture choice.
Tell us where deploys, cloud costs, or reliability are slowing you down — we'll audit your setup and scope a fixed plan to fix it.