DevOps & MLOps Automation
Automate the delivery pipeline so engineers stay on product.
CI/CD, infrastructure as code, observability, and model lifecycle — we automate the plumbing end-to-end so your team ships more and on-calls less.
— The problem
Sound familiar?
- 01Your deploys are manual, slow, and a risk — releases take hours and roll-backs are scary.
- 02You have infrastructure but no reproducibility — no Terraform, no drift detection, no environments.
- 03Your ML models are deployed like static code — no versioning, no A/B, no drift monitoring.
— What we deliver
Concrete outputs. Nothing hand-wavy.
CI/CD pipelines — GitHub Actions, ArgoCD, or CodePipeline — with environments and approvals.
Infrastructure as code — Terraform modules, OIDC authentication, drift detection.
Secrets and config management — AWS Secrets Manager, Parameter Store, or HashiCorp Vault.
Observability — CloudWatch, Grafana, OpenTelemetry traces, log pipelines.
MLOps — model registry, A/B routing, eval gating, drift monitoring, retrain cadence.
On-call rotations, runbooks, and SLO-backed incident response.
— Methodology
How we run the engagement.
Phase 1
Discover
Delivery baseline — cycle time, MTTR, deployment frequency.
Phase 2
Design
Pipeline topology, env strategy, observability stack.
Phase 3
Build
Pipelines, IaC, observability, MLOps wiring.
Phase 4
Operate
On-call, SLOs, quarterly reviews, continuous improvement.
— Stack we work in
Opinionated but pragmatic.
We're deepest on AWS and Claude/Bedrock. We also ship on Azure, GCP, and open-source where they're the right fit.
CI/CD
- GitHub Actions + OIDC
- ArgoCD
- CodePipeline
IaC
- Terraform
- CDK
- Ansible for config
Observability
- CloudWatch
- Grafana
- OpenTelemetry
- Loki
MLOps
- MLflow
- SageMaker Model Registry
- BentoML
- custom
— Where we apply it
Industries we've built patterns for.
— FAQ
Frequently asked.
Get started
Ready to scope your DevOps & MLOps Automation engagement?
Book 30 minutes with our team — we'll tell you honestly whether we're the right fit.