Cloud Optimization

WoodSkine — Cloud Cost Reduction & Elastic Infrastructure

Cloud spend reduced ~40%; 99.9%+ uptime maintained throughout migration.

What We Were Asked to Solve

WoodSkine’s platform had grown organically and was bleeding cloud spend on over-provisioned, poorly structured AWS infrastructure. Unoptimized Lambda functions, expensive always-on EC2 instances, and no autoscaling meant costs scaled linearly with traffic — unsustainably for a growth-stage company.

5-Step Engagement Framework

01

Technical Forensic Call

Mapped all AWS resources, identified the top 10 cost drivers, and quantified monthly waste.

02

Architecture Audit & Blueprint

Designed an elastically-scaled architecture and wrote a cost-reduction roadmap with projected savings per workload.

03

System Hardening

Migrated to containerized workloads, implemented autoscaling groups, and set up cost allocation tags across all environments.

04

High-Velocity Migration Sprints

Iteratively migrated services with zero-downtime deployments using blue-green strategy.

05

Hardened Handoff

Delivered full IaC (Terraform), runbooks, cost dashboards, on-call documentation, and team onboarding.

Technologies Used

AWS (EC2, Lambda, RDS, ECS, CloudFront)  ·  Terraform  ·  Docker  ·  GitHub Actions  ·  Datadog

8 Weeks

End-to-end delivery

$30,000 – $50,000

Total engagement range

Measurable Outcomes

  • ✓ Cloud spend reduced by ~40% within 60 days of deployment
  • ✓ 99.9%+ uptime maintained throughout the entire migration
  • ✓ Zero production incidents during the migration window
  • ✓ Full IaC coverage — infrastructure reproducible in under 15 minutes
  • ✓ Engineering team onboarded to cost-conscious cloud practices

“We were burning cash on cloud without knowing it. Zenveus came in, found the leaks, and fixed them — all while keeping the platform running without a single outage.”

CTO, WoodSkine

Chief Technology Officer

Related Work

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Carrier-broker platform live; passed DD.

B2B SaaS

Gryso

Passed technical DD; Series A path cleared.

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