Cloud & Infrastructure
Scales to peak. Costs collapse at idle.
Cloud infrastructure for systems that absorb the biggest week of the year and contract back to baseline by Monday. Migrations without freezing revenue. Pipelines that ship without drama.
The traffic shape we engineer for
Absorbs the peak. Costs collapse at idle.
Black Friday. Diwali drop. Holiday gift surge. The infra has to flex up by an order of magnitude and back down by Monday — without a war room, without burning capacity, without a 3am page.
Live traffic · last 14 days
Targets we engineer to, verified in load test
Cold start
< 800ms
Auto-scale up
4 min to peak
Auto-scale down
Idle in 30 min
Cost per request
Flat under load
Multi-cloud deployment surface
AWS
Primitives
Primary for retail clients
Google Cloud
Primitives
Primary for data + AI workloads
Azure
Primitives
When clients run M365 stack
Operating practices
Every engagement runs on the same discipline.
6 layers · multi-cloud · minimal-downtime · FinOps-aware.
Cloud migration & re-architecture
Lift-and-shift, replatform, refactor — we pick the path that protects revenue first. On-prem to AWS, GCP, or Azure. Legacy hosting to managed services. Phased cutover, no big-bang risk.
Auto-scaling for peak events
Black Friday, Mother's Day, product drops — infrastructure that absorbs an order-of-magnitude surge and contracts back down by morning. Load-tested against your real traffic patterns, not guessed.
Kubernetes & container orchestration
EKS, GKE, AKS — production-grade clusters with sane defaults, security baselines, and the observability hooks your SRE team actually wants. Helm charts, GitOps via Argo, blue-green rollouts.
CI/CD pipelines & GitOps
GitHub Actions, GitLab CI, Jenkins — pipelines that run fast, fail loud, and never let a regression past the gate. Trunk-based, with preview environments per PR.
Infrastructure as code
Terraform and OpenTofu modules built for reuse across environments. State management, drift detection, and policy-as-code via Sentinel or OPA. No more snowflake servers.
Cost optimization & FinOps
Right-sizing, reserved capacity strategy, spot fleet management. Tag enforcement, per-team chargeback, and dashboards that put your cloud bill in plain English.
What you get
Day 1 to Day 30 — concrete deliverables, not roadmaps.
Every cloud engagement starts shipping infrastructure on day 1. Here is what lands at each milestone.
Working environment
Day 1Terraformed staging account live · IaC repo seeded · CI baseline + pre-commit hooks · auth + secrets via vault.
First service in prod
Day 7Auto-scaled service deployed behind CDN · health checks · structured logs · OTel traces wired to Datadog.
Resilience proven
Day 14Load test at 10× baseline · auto-scale verified · failover drill (region cutover) · runbook for each scenario.
FinOps + SLO baseline
Day 30Cost-per-request dashboards · SLO targets agreed · on-call rotation handed over · runbook validated by your team.
Day-1 staging URL
Not credentials and a kickoff deck
Hand-over by Day 30
Your team owns the runbook
On-call shadowed
We back up your team for 60 days
Peak commerce readiness
Calm on a normal day. Ready on the day revenue spikes.
Infrastructure for commerce teams that cannot afford fragile releases or peak-season surprises. The checklist we run before every high-traffic window.
- Traffic capacityLoad-tested against your real patterns, with headroom.
- Checkout healthThe buy path watched and budgeted separately.
- API latencyp95 monitored; slow calls off the critical path.
- Inventory syncReal-time, with retries and a dead-letter queue.
- Error rateAlerted against a baseline, not a guess.
- Deployment statusProgressive rollout with health gates.
- Rollback readinessScripted, rehearsed, one command away.
- Alert coverageEvery critical path pages a human.
Alert coverage is only as good as what reads the signal — we feed the same instrumentation into MetriQ, our AI anomaly layer, so latency, error-rate, and saturation spikes surface as a page to a human, not a dashboard nobody is watching at 2am. Storefront speed is its own discipline — see commerce performance.
Where we built
Real-time trading platform, built for sustained load.
99.99%Uptime across 6 months of live trading — 10K+ concurrent connections, data latency 2s to sub-100ms
Read the case studyAI-assisted QA included.
Tests aren't a separate line item — they're how engineers ship covered code. Lower QA budget, faster feedback, better coverage than traditional QA cycles.
Auto-generated E2E
Playwright + LLM scaffold tests from product flows.
Self-healing selectors
Tests don't break when copy or DOM shifts.
Production replay
Real traffic patterns become regression suites.
PR-level impact
Only the relevant tests run on each diff.
Across the work
Built and operated
Multi-cloud
AWS, GCP, Azure
Minimal-downtime
migrations by design
FinOps
cost discipline at every release