Skip to content
Diatom Labs
Free 30-min consultation Let's work together
- · DevOps

DevOps Automation.

We implement DevOps practices and tools to automate your software delivery pipeline and improve collaboration. Delivered AI-augmented, with AI-aware capabilities (eval gates, MCP servers, agent skills, plugins) when you need them.

DevOps Automation

We build and run software delivery machinery: CI/CD, GitOps, infrastructure as code, and the observability to know it is all working. This is the core of what Diatom Labs does, and the discipline behind every case study we publish.

For a preview of how we think, read the write-up of the pipeline framework our founder presented at DevOpsCon Munich 2025: Streamlining CI/CD with metadata - metadata-driven pipelines that scale across tenants, AWS accounts, and teams without copy-paste.

What we do

CI/CD

  • Pipeline architecture on GitHub Actions, GitLab CI, or Jenkins - designed once, reused across every service
  • Keyless cloud deployments (OIDC), progressive rollouts, consistent versioning and changelogs
  • Eval gates for AI workloads, when your pipeline ships models and prompts alongside code

GitOps

  • ArgoCD and Flux on Kubernetes
  • Terraform PR automation for infrastructure changes, with plan output in the review
  • An audit story a regulator can follow: every change reviewed, merged, and on the record

Infrastructure as code

  • Terraform, CloudFormation, and Pulumi
  • Module design, drift detection, plan-and-apply in CI
  • Ansible and configuration management where servers still matter

Observability

  • Prometheus, Grafana, the ELK stack, Datadog
  • Alerting tied to what actually pages someone, dashboards tied to what someone actually asks
  • On-call you can evidence: runbooks and escalation paths, not tribal knowledge

How we work

  1. Assess - where delivery hurts today: speed, safety, or traceability
  2. Design - a delivery model that fits your team, not a reference architecture pasted on top of it
  3. Implement - incrementally, alongside your engineers, without a deployment freeze
  4. Operate and transfer - we run it with you until your team runs it without us

When this is the wrong service

If deployments are rare and the team is two people, a simpler setup wins - one well-configured GitHub Actions workflow beats a platform. DevOps tooling should remove friction, not add ceremony, and we will tell you which side of that line you are on.

Contact us if shipping software feels harder than building it.

- Our approach

A four-stage delivery loop.

  1. 01
    Culture
    Foster a DevOps mindset and practices.
  2. 02
    Automation
    Implement CI/CD and infrastructure automation.
  3. 03
    Monitoring
    Set up comprehensive monitoring and alerting.
  4. 04
    Improvement
    Continuous process improvement and optimization.
- Outcomes

What this engagement delivers.

01
Pipelines that scale by design
Our metadata-driven pipeline framework - presented at DevOpsCon Munich 2025 - scales across tenants, accounts, and teams without copy-paste.
02
GitOps as the operating model
Who changed what, and who approved it, answered by git. The delivery model our regulated clients pass audits with.
03
Observability included
Alerting people can act on and dashboards people actually read - delivery machinery you can see inside of.
04
AI-aware when needed
Eval gates, LLM observability, and GPU workloads folded into the same pipelines when your product ships models and prompts, not just code.

Ready to put this in motion?
A 30-minute call sets the direction.

Book free consultation See where we've shipped