Managed DevOps For Teams That Ship Weekly
CI/CD pipelines, Kubernetes, infrastructure as code and observability delivered as a managed service.
What is broken today
- Manual deploys that only one engineer is willing to run
- No staging parity, so bugs appear only in production
- Infrastructure configured by hand and undocumented
What you get
- Automated pipelines with quality gates
- Infrastructure as code and reproducible environments
- Kubernetes with autoscaling and rollout safety
- Metrics, logs and traces in one place
What actually breaks
One engineer owns deployment, and that engineer is the constraint. Releases cluster on Thursday evening because that is when they can be watched. Staging exists but has drifted, so it proves nothing, and bugs are found by production traffic. Infrastructure was configured by hand, which means the only record of how it works is in someone's memory and a console. Rolling back means restoring a database and hoping.
How we build it
Environments are defined in Terraform and rebuilt from that definition, which is the only way staging stays comparable to production. Pipelines build the artefact once and promote it: the container that passed tests is the container that reaches production. Quality gates run tests, type checks, dependency and container scanning and a migration check, and a failing gate blocks promotion rather than warning about it. Database migrations are separated from application deploys and written to stay backwards compatible for one version, because that is what makes rollback possible at all.
What goes wrong on these projects
Kubernetes is not always the answer, and choosing it by default adds an operational surface a small team cannot carry; for many workloads, containers on a managed runtime are cheaper and simpler, and we will say so. Second, the migration path is where rollback promises break, because application code rolls back and schema changes do not. Third, slow pipelines get bypassed, so pipeline speed is a reliability feature.
What changes after
Any engineer can deploy, on any day, because the pipeline handles the risky parts. Staging tells you something because it is built from the same definition. When a release goes wrong it stops at a health check instead of at a customer.
Before you ask
Do you work with our in-house engineers?
Yes. Most Foxquart DevOps engagements run jointly with your in-house engineers, and we document and train as the work happens. The intended result is a team that can run its own pipelines and infrastructure afterwards, not a dependency, which is why every environment is reproducible infrastructure as code.
Is Kubernetes always the answer?
No, and Foxquart will say so when it is not. For many workloads, containers on a managed runtime are cheaper and simpler to operate, and simpler infrastructure fails less often. Kubernetes earns its place when you need autoscaling and rollout safety across many services, not by default.
Can you document infrastructure nobody wrote down?
Yes. Foxquart rebuilds hand-configured infrastructure as code, so environments become reproducible and documented instead of a server nobody dares touch. That also restores staging parity, which is what stops bugs from appearing only in production, and it removes the single point of failure of one engineer who remembers the setup.
What happens when a deploy goes wrong?
It gets caught or rolled back. Foxquart builds automated pipelines with quality gates before the deploy and rollout safety after it, so a bad release does not become an evening of debate. Metrics, logs and traces sit in one place, so what broke is answered from data rather than guessed at.
Do you replace our existing pipelines or improve them?
Whichever is cheaper to live with. Foxquart audits the existing pipelines first, hardens what works and replaces only what cannot be made reliable. The usual finding is manual deploys that a single engineer is willing to run, so automating that path with quality gates comes before any rebuild.
Is managed DevOps a retainer or a project?
Both, in sequence. Foxquart scopes and prices the setup work per phase after a fixed-price discovery, then ongoing cover runs as a retainer, because pipelines, clusters and observability need maintaining rather than installing once. Your team can take the estate over later, since everything is code and documented.
