Case Studies
Real Problems. Real Outcomes.
Engineering challenges, solutions, and the metrics that prove it worked.
Multi-Cloud / Infrastructure
Daily Releases Across 3,300+ Servers Across Multi-Cloud
A fast-growing SaaS company scaling from hundreds to 3,300+ Linux VMs across DigitalOcean, AWS, GCP, and Azure needed daily production releases without downtime. Manual deployments were taking hours and causing drift across environments.
The Challenge
3,300+ servers across four cloud platforms, different configuration states, daily release cadence, zero tolerance for downtime, and a lean ops team stretched too thin to manage it manually.
3,300+
Linux VMs managed across clouds
~1 hr
Daily releases across all servers
99.98%
Uptime maintained year-round
AWS / Cloud Migration
Single Server E-Commerce Platform Moved to AWS 99.9% Uptime Achieved
A growing e-commerce company had outgrown their single dedicated server. Every flash sale brought the site to its knees, and the team had no way to scale or recover quickly when things went wrong.
The Challenge
Migrate from a single dedicated server to a scalable AWS architecture, with codebase optimisation, database tuning, and a caching layer, so the platform could handle traffic spikes without going down.
99.9%
Uptime post-migration
6x
Faster page load times
10x
Peak traffic handled automatically
AWS / Kubernetes Migration
12 Microservices Migrated from EC2 to Kubernetes Zero-Downtime Deployments and 3x Faster Scaling
A SaaS platform running 12 microservices across individual EC2 Auto Scaling Groups had reached a breaking point. Each service had its own over-provisioned instance fleet, deployments meant taking services offline for 3-5 minutes at a time, and scaling out during traffic spikes took 8-12 minutes - long enough for customers to notice. The ops team was spending more time managing instance fleets than improving the platform.
The Challenge
Migrate 12 production microservices from EC2 Auto Scaling Groups to AWS EKS, introducing rolling deployments with readiness probes, Horizontal Pod Autoscaling for second-level scale-out, and resource limits that eliminated over-provisioning. All without a maintenance window on a live platform.
90 sec
Deploy time (was 5 minutes)
60 sec
Scale-out time (was 10 minutes)
40%
Reduction in EC2 costs through bin-packing
GCP / AI Integration
AI-Powered Support Platform Cuts Ticket Volume by 40%
An e-commerce company processing 10,000+ daily support requests needed intelligent triage and auto-resolution - without losing the human touch for complex cases.
The Challenge
Build an AI layer that handles routine requests automatically while routing complex cases to the right human agent, all within existing support tooling.
40%
Support tickets automated
2x
Agent productivity
DigitalOcean / Cost Optimisation
45% Cloud Cost Reduction for a B2B SaaS Company on DigitalOcean
A B2B SaaS company running their entire platform on DigitalOcean had watched their monthly infrastructure bill double in 18 months - without a meaningful increase in customers. Over-provisioned Droplets, inefficient database queries hammering read replicas unnecessarily, bloated container images, and zero caching meant every new customer added disproportionate infrastructure cost.
The Challenge
Step in as their extended DevOps team: audit the full stack, right-size Droplets, optimise slow queries and database connection pooling, introduce a Redis caching layer, and clean up CI/CD pipelines that were spinning up redundant resources on every build. All without disrupting a live platform with paying customers.
45%
Reduction in monthly cloud spend
4x
Reduction in database load
60%
Faster average API response times
DevOps / Platform Engineering
From 4-Hour Deploys to 12-Minute Pipelines for a Healthcare SaaS
A healthcare SaaS provider with strict compliance requirements was doing manual, error-prone deployments that blocked every team and caused release anxiety every two weeks.
The Challenge
Build a fully automated, HIPAA-compliant CI/CD pipeline that gives the team confidence to deploy daily, with audit trails and approval gates at every stage.
12 min
Deploy time (was 4 hours)
0
Failed deploys in 6 months
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