Platform layer

DevOps Support

A steady operating layer for your GCP environment so apps, data, and pipelines run predictably without a full-time DevOps engineer.

Outcome

A maintained GCP environment: workflows, IaC, and day-to-day operations handled so your team can focus on product.

Typical timeline

2–4 weeks to set up the core workflows, then ongoing support.

Best for

Teams running meaningful workloads on GCP without a dedicated DevOps or platform engineer.

What you actually get

You get DevOps support that behaves like part of your infrastructure, not a string of one-off fixes.

Deployments, jobs, and environments are defined in code instead of living in ClickOps trails nobody can reproduce.

Spend, quotas, and failures are monitored systematically, not discovered by accident.

  • IaC-managed projects, services, and policies in a shared repository.
  • CI/CD pipelines for apps, data jobs, and scheduled workloads.
  • Runbooks for recurring operational tasks that shouldn’t depend on heroics.
  • Hands-on help via Slack or ticketing when something needs to change.

You're here when

  • The operational backlog grows faster than anyone can clear it.
  • Deploys rely on best-effort heroics from whoever 'knows GCP'.
  • No one consistently watches spend, quotas, or job failures.
  • Every new service ends up as a one-off instead of following a pattern.

How it works under the hood

Anriku works directly inside your GCP environment with a clear intake queue, shared IaC, and a steady cadence so DevOps work stops being reactive.

  1. 01

    Set up an intake queue for fixes, changes, and improvements.

  2. 02

    Keep projects, services, and policies in a shared IaC repository with review.

  3. 03

    Run automation jobs, checks, and monitors inside your GCP environment.

  4. 04

    Weekly or bi-weekly reviews to align priorities and surface issues early.

  5. 05

    Ship short reports summarizing what changed, what broke, and what’s next.

What the project looks like

First version in 2–4 weeks to stand up the toolkit, then a steady operating rhythm.

Phase 1 – Set up guardrails

Get enough access, context, and structure in place to move fast without breaking anything important.

  • Review infra layout, IAM, networking, and observability gaps.
  • Configure repositories, workflows, and communication channels.

Phase 2 – Tackle priority fixes

Clear the high-impact backlog so operations stop being the bottleneck.

  • Ship the first wave of pipeline, cost, reliability, and security fixes.
  • Document what changed and how it's operated day to day.

Phase 3 – Ongoing support

Move into a stable cadence where DevOps work is planned, visible, and predictable.

  • Manage requests, monitor jobs, and keep IaC in sync with reality.
  • Surface roadmap candidates for the next upgrades and simplifications.

What becomes possible after this

Once DevOps is calm, shipping warehouses, alerts, and dashboards becomes a configuration task instead of a new firefight.

  • A stable operational backbone makes data, alerting, and product work faster to ship.
  • Deployments stop blocking features because environments behave the same every time.
  • Budget and architecture decisions are backed by real usage data rather than assumptions.
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This is overkill if

Your workloads still run comfortably on a single VM or simple SaaS tooling.

You only need a one-off fix, not an ongoing operating model.

Your team doesn’t need a shared operational layer to coordinate changes.

Need DevOps support?

Share your current GCP footprint, backlog, and priorities — Anriku will tell you if ongoing DevOps support actually makes sense.