Cloud & DevOps
Scalable cloud infrastructure with CI/CD pipelines, monitoring, and 99.9% uptime
Kubernetes performs rolling updates by default, which leads many teams to believe they have zero-downtime deployments. Then they watch error rates during a deploy and find a burst of failed requests every time. The default is a rolling update, not a graceful one, and the gap between them is a handful of specific configurations.
We build deployment pipelines and infrastructure that are boring in the way infrastructure should be: deploys are routine, rollback has been tested, and someone gets alerted before your customers notice.
What's Included
Key Benefits
Deployments That Genuinely Drop No Requests
Most remaining deploy errors come from one subtle race. When a pod terminates, the container receives a termination signal and the pod is removed from service endpoints — concurrently, with no ordering guarantee. During the moment endpoint removal takes to propagate, traffic is still routed to a pod that has begun shutting down.
We add a pre-stop delay that outlasts propagation, ensure the application drains in-flight requests before exiting, and verify the signal actually reaches your process rather than being swallowed by a shell wrapper. Combined with readiness and liveness checks that answer different questions, this is what turns a rolling update into a graceful one.
Pipelines Fast Enough to Trust
A pipeline that takes half an hour changes behavior. Developers batch changes to avoid waiting, which makes each deployment larger and riskier, and they start merging on partial results. Under ten minutes to a deployable artifact is the target, reached through parallel jobs, dependency caching keyed on lock files, and sharded test suites.
Equally important is that the artifact is built once and promoted unchanged through every environment. Rebuilding per environment means the thing you tested is not the thing you shipped, which quietly invalidates all the testing that came before it.
Migrations That Do Not Break Mid-Rollout
Application deployment is a solved problem. Schema changes are not, because during a rolling update the old and new versions run simultaneously against one database. Any migration that breaks the old version causes errors for as long as the rollout takes.
We apply expand-and-contract discipline so every breaking change becomes a sequence of non-breaking ones — add nullable, backfill, then enforce. The rule is that any deployment must work against both the previous schema and the next one. Without it, you do not have zero-downtime deployments regardless of how the rollout is configured.
Observability and Cost Control
We instrument with distributed tracing to answer where latency is going, metrics for alerting because alerting on log patterns is fragile, and structured logs carrying trace IDs so a log search becomes a single request's story rather than an archaeology exercise.
On cost, the largest wins are usually unglamorous: right-sizing instances that were provisioned for a guess, committed-use discounts on steady baseline load, lifecycle policies on stored data, and finding the environments nobody turned off. We measure before recommending, because cloud bills rarely break down the way people assume.
How We Work
- 1
Infrastructure audit
Current architecture, deployment process, monitoring coverage, security posture, and cost breakdown, with findings prioritized by risk.
- 2
Infrastructure as code
Existing infrastructure captured in Terraform so environments are reproducible and changes are reviewable rather than manual.
- 3
Pipeline build
Test, build once, deploy to staging, gate, deploy to production — with OIDC federation instead of long-lived stored credentials.
- 4
Zero-downtime deployment
Health checks, graceful shutdown, rollout configuration, and a rollback path that is actually exercised rather than assumed.
- 5
Monitoring & handover
Dashboards, alerting on symptoms rather than causes, runbooks, and training so your team can operate it without us.
Frequently Asked Questions
Do we actually need Kubernetes?
Frequently not. Kubernetes earns its operational cost when you are running many services, need sophisticated scheduling, or have a team to operate it. For a handful of services, managed container platforms deliver most of the benefit for a fraction of the complexity. We recommend based on your team size and service count, and we will talk you out of it when it is not warranted.
Can you reduce our cloud bill?
Usually, and often significantly. The reductions typically come from right-sizing over-provisioned instances, commitment discounts on predictable baseline load, storage lifecycle policies, eliminating cross-zone data transfer, and shutting down forgotten environments. We start with an audit that quantifies the opportunity before proposing any work.
How do you handle secrets in CI pipelines?
With OIDC federation rather than stored long-lived credentials — the workflow exchanges a short-lived token for temporary cloud credentials scoped to that specific workflow and branch, so nothing durable is stored. We also pin third-party actions to commit hashes, since a version tag is mutable and represents an implicit trust relationship with whoever controls it.
Can you work with our existing infrastructure?
Yes, and that is most of our infrastructure work. We rarely recommend rebuilding working systems. The usual path is capturing what exists in code, closing the highest-risk gaps first, and improving incrementally without a disruptive migration.
What does the handover look like?
Infrastructure as code in your repository, documented runbooks for common operational tasks, dashboards and alerts configured, and training sessions with your team. The objective is that you can operate it without us — retainers exist for teams who prefer ongoing support, not because the system requires our involvement.