Cloud foundations on AWS, GCP or Azure
Networking, identity, environments and account structure laid out properly once, so the next ten services inherit it instead of improvising.
Releases get slower for reasons nobody wrote down: manual steps, undocumented environments, a deploy only one person understands. We do platform engineering and DevOps work that puts the whole thing in code — infrastructure, pipelines, monitoring — so shipping stops depending on who is awake.
Kubernetes · AWS/GCP · Terraform
Every release takes longer than the last one and nobody is sure why.
Deploys happen at 11pm because that is when it is safe to break things.
The cloud bill grew faster than traffic and nobody can point at the cause.
Networking, identity, environments and account structure laid out properly once, so the next ten services inherit it instead of improvising.
Cluster setup, autoscaling, resource limits and health checks — configured for the load you actually have, not a reference architecture for a company ten times your size.
Terraform, OpenTofu or Pulumi with state managed properly and modules your team can read. Environments become reproducible instead of archaeological.
Build, test, deploy and rollback as one automated path with staged environments and progressive delivery, so a bad release is reversible in minutes.
Metrics, logs, traces and alerts that page a human only when a human is needed — plus cost attribution per service, which is usually where the surprise lives.
Tell us what your deploy process looks like today. We reply within a day with the two or three changes that would move the needle first.
Send us a short description of what you're building or what's broken. We'll reply within a day with honest thoughts on scope, approach, and whether we're the right fit.