Delivery speed is a feature.
When releases take six weeks and every deploy is an event, the problem is rarely one tool. It is the accumulated weight of decisions nobody owns. We take one delivery bottleneck, own it end to end, and hand back a pipeline your team actually uses.
DevOps engagements with us are narrow on purpose: one pipeline, one bottleneck, one number to move — cycle time, deploy frequency, mean time to recover. We work with Kubernetes and Docker for runtimes, Terraform for infrastructure as code, GitHub Actions for CI/CD, Prometheus and Grafana for observability, on AWS and Google Cloud. Redis and friends where the architecture calls for them.
The deliverable is never a diagram. It is a working pipeline with the old path retired, the team onboarded, and a before/after measurement of the number we agreed to move. If your platform team inherits it without needing us again, the engagement worked.
Technologies
- Temporal: The candidate pipeline that could not get stuck
- Redis: The candidate pipeline that could not get stuck
- Celery: The candidate pipeline that could not get stuck
- Kubernetes
- Docker: The candidate pipeline that could not get stuck, Identity-anchored AI link discovery with Exa
- Terraform
- GitHub Actions: The candidate pipeline that could not get stuck
- Grafana
- Prometheus
- AWS
- Google Cloud: The candidate pipeline that could not get stuck, Identity-anchored AI link discovery with Exa
- Cloud Run: The candidate pipeline that could not get stuck, Identity-anchored AI link discovery with Exa
- Sentry: The candidate pipeline that could not get stuck
For corporates
The release process everyone complains about and nobody can schedule time to fix. We fix it from outside.
For startups
Infrastructure that will not embarrass you at scale, built while you focus on the product.
The evidence
Cycle-time and deploy-frequency numbers, before and after, from your own repos.