Cloud & DevOps Engineering
Ship faster, stay up longer, spend less without a re-architecture.
End-to-end cloud migration, architecture, and CI/CD automation across AWS, Azure, GCP, and OCI. From Platform Engineering and GitOps to FinOps, AI inference cost governance, and full-stack observability, we've delivered 99.99% uptime for enterprises processing millions of daily transactions.
What We Deliver
Core Capabilities
- Cloud Migration & Architecture
- Platform Engineering & Internal Developer Platforms
- CI/CD & GitOps Implementation (Argo CD, Flux)
- Infrastructure as Code (Terraform, Pulumi)
- Observability — OpenTelemetry, Metrics & Distributed Tracing
- FinOps & Multi-Cloud Cost Optimisation
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By the Numbers
What clients achieve with GYSP
identified and recovered within 90 days of a FinOps engagement without a re-architecture project
for enterprise clients processing millions of daily transactions across multi-region deployments
after Platform Engineering implementation, same team, same headcount, faster delivery
How much cloud are you paying for and not using?
12 questions. ~5 minutes. Get a dollar estimate of your recoverable cloud waste — broken down by 6 categories (commitment gaps, zombie resources, over-provisioning, and more) with specific Week 1 actions.
Proven Results
Cloud & DevOps Case Studies
Enterprise TechnologyGlobal Enterprise AI Platform
A global enterprise AI platform operating ML workloads across recommendation engines, demand forecasting systems, and fraud detection pipelines needed to scale from 4 to 18 data scientists without GPU spend spiralling out of control. GYSP engineered a Kubernetes-native, multi-tenant MLOps platform with Run:ai fractional GPU virtualisation, Karpenter dynamic compute provisioning, and a full FinOps enforcement layer that cut monthly GPU infrastructure spend from $68,000 to $18,000 while driving average GPU utilisation from 27% to 91%.
FinTechGlobal Fintech Platform
Fraud was being caught too late, reconciliation was a manual bottleneck, and cloud costs across staging and production had no governance. GYSP rebuilt the platform from the data layer up: predictive ensemble models in production on EKS, 92% accuracy, 30% less cloud spend.
FinTechGlobal Banking Institution
A global banking institution migrating to AEM as a Cloud Service needed a content architecture supporting global content reuse across independent regional viewpoints, with UK, US, and APAC divisions sharing a unified content model while maintaining independent editorial control. GYSP spearheaded content taxonomy modeling, configured optimised JCR node hierarchies with Apache Sling path resolution for multi-device delivery, and automated staging pipelines via AEM Cloud Manager and Bitbucket.
Industry Expertise
Industries We Serve with Cloud & DevOps
Client Voices
What our clients say
“GYSP's expertise in secure, compliant infrastructure allowed us to scale transactions confidently. From AWS-to-GCP migration to DevSecOps pipelines, their work cut deployment time and strengthened compliance. What impressed us most was how they delivered cost optimisation while ensuring zero downtime.”
“The GYSP team completely transformed our infrastructure. Moving from a monolith to microservices, full observability, compliance. All while keeping costs predictable, which I honestly didn't think was possible at the same time. Teachers and students got faster, more reliable access and our dev team finally had real velocity. More partner than vendor.”
“We needed a partner who could modernise our platform without cutting corners on compliance. GYSP delivered on both. Their work across cloud migration, security, and automation gave us a foundation that actually scales. The platform runs faster, more securely, and with far less maintenance overhead than before. That's all we were asking for.”
FAQs
Common questions
Everything buyers typically ask before starting a cloud & devops engagement.
Ask us anythingHow long does a cloud migration typically take?
A lift-and-shift migration for a medium-complexity workload takes 8–12 weeks. A re-architecture migration (modernising to cloud-native services) runs 16–24 weeks. We always migrate in phases to protect uptime, and production never goes dark.
Can you reduce our cloud costs without a full re-architecture?
Yes, and this is where we start. A FinOps engagement identifies 20–40% spend reduction within 90 days by rightsizing, eliminating waste, optimising reserved capacity, and restructuring data transfer costs. No re-architecture required.
Our AI API and GPU costs are growing as fast as our cloud bill — can you help?
Yes. GenAI workloads introduce a cost layer most FinOps frameworks weren't built for: LLM token spend, vector database compute, GPU serving pipelines, and embedding generation at scale. We apply the same FinOps rigour to AI infrastructure — auditing model selection, prompt efficiency, caching strategies, and right-sizing GPU instances — to identify where AI spend is leaking and how to bring it under control without sacrificing model quality.
What is Platform Engineering and do we need it?
Platform Engineering is building an Internal Developer Platform, a self-service layer that lets your engineers provision infrastructure, deploy, and run pipelines without tickets or DevOps bottlenecks. You need it when developer-to-platform-engineer friction is slowing delivery: long PR-to-deploy times, frequent environment issues, developers blocked on infra.
How do you handle zero-downtime migrations for production systems?
Blue/green deployments, canary releases, traffic shifting with automated rollback triggers, and feature flags for gradual exposure. We design the migration strategy before writing a single Terraform file, so cutover risk is engineered out, not managed during the event.
Which cloud provider do you recommend — AWS, Azure, or GCP?
It depends on your workload, team expertise, and existing investments. AWS leads for breadth of services. Azure is the natural choice for Microsoft-heavy organisations. GCP is strongest for ML/data workloads. We're certified across all three and advise based on your specific context, not vendor preference.
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