Case Studies

Outcomes, not slides

A selection of recent engagements. Names changed where we're under NDA.

• From 3-hour deployment windows to 8 minutes — with zero downtime

  Restaurant Tech · Series C

  We rebuilt the entire release pipeline on GitHub Actions with parallelised test suites cutting CI from 42 to 9 minutes. Blue-green deployments on ECS Fargate replaced the rolling restarts that caused downtime. LaunchDarkly feature flags decoupled deploys from releases so the team could ship daily and toggle features independently. Automated smoke tests and Datadog SLO dashboards gave the on-call rotation a live view of every release health check.

  • 8 min Deploy time (was 3 hr)

  • 23 → 1 Hotfixes per quarter

  • 99.99% Uptime since go-live

  • 0 Rollback incidents

• Survived a 40× traffic spike on Black Friday — on a smaller cluster than before

  E-commerce · Scale-up

  We replaced HPA with KEDA event-driven autoscaling tied to real-time queue depth, bringing scale-out time from 12 minutes to 18 seconds. A scheduled pre-warm strategy automatically upsizes the cluster 30 minutes before known high-traffic windows. Cloudflare cache rules were tuned to serve product pages and inventory snapshots from the edge, cutting origin load by 73%. k6 load tests now run in CI on every deploy, and a Litmus chaos suite validates failover behaviour weekly.

  • 40× Peak traffic handled

  • 18 sec Scale-out time (was 12 min)

  • −31% Infra cost vs prior peak

  • 0 Downtime on Black Friday

• SOC 2 Type II and HIPAA audit-ready in 11 weeks — cleared on first attempt

  HealthTech · Series B

  We deployed HashiCorp Vault with dynamic secrets for every service, eliminating all hardcoded credentials in 72 hours. OPA/Gatekeeper enforced policy-as-code at the Kubernetes admission layer — no workload could deploy without a compliant security context. Centralised SIEM via Wazuh gave auditors a tamper-proof log trail. Automated access reviews via Terraform reduced the 3-week process to a 2-hour weekly job. A scheduled external pen testing programme closed the remaining attack surface gaps before the audit window.

  • 17 → 0 Critical compliance gaps

  • 11 wk To audit-ready

  • 100% Automated policy enforcement

  • 2 hr Access review cycle (was 3 wk)

• Cut GPU inference costs 47% while improving latency — at growing model scale

  AI SaaS · Seed

  We designed a multi-region EKS platform using Karpenter to manage spot GPU node pools with automatic on-demand fallback, achieving 80%+ spot utilisation without reliability risk. NVIDIA Triton Inference Server enabled model batching and INT8 quantisation, cutting per-request compute by 35%. Per-model Kubernetes namespaces with Prometheus cost labels gave the team real-time spend visibility. Dev environments were migrated to GPU time-sharing, eliminating idle full-GPU reservations overnight.

  • −47% Monthly infra cost

  • 4.2s → 2.6s p95 inference latency

  • 99.95% SLO met

  • 80%+ Spot GPU utilisation

• Slashed CDN spend by 58% and fixed APAC buffering in six weeks

  Media Streaming · Growth

  We built a multi-CDN orchestration layer with Cloudflare Workers routing each viewer to the lowest-latency provider in real time, with Fastly as a cost-optimised fallback for bulk traffic. Origin shielding reduced direct origin hits by 91%, and HLS manifest edge caching with 10-second TTLs eliminated the regeneration load entirely. Terraform-managed CDN rules allow the team to roll configuration changes in minutes. Real-time CDN cost allocation by region and content type gave finance the granularity they had been asking for.

  • −58% Monthly CDN spend

  • 0.6% Buffering ratio (was 4.2%)

  • 1.4s APAC p95 latency (was 8.1s)

  • 99.98% Global availability

• Scaled from 150 to 1,200 tenants with zero noisy-neighbour incidents

  B2B SaaS · Series A

  We designed a cell-based architecture with three cluster tiers — Standard, Business, and Enterprise — matched to tenant SLA requirements. Cilium enforced L7 network policies between namespace boundaries, eliminating the blast radius of any single tenant failure. GitOps-driven onboarding via ArgoCD ApplicationSets reduced provisioning to a 4-minute automated pipeline triggered by a single API call. Prometheus metrics labelled per tenant feed a Grafana dashboard that shows real-time CPU, memory, and egress costs per customer — directly usable by the sales team in renewal conversations.

  • 1,200 Tenants (was 150)

  • 4 min Onboarding (was 2 days)

  • 45 → 3 min MTTR

  • 0 Noisy-neighbour incidents

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