CLOUD & DEVOPS ENGINEERING

Cloud DevOps Engineering for Enterprise Infrastructure

Cloud DevOps engineering is the infrastructure layer that determines whether enterprise AI systems perform in production or break under load. MetaSys designs and builds cloud environments, CI/CD pipelines, and Kubernetes clusters that give your AI systems the compute, scalability, and uptime they require. We also migrate legacy on-premise infrastructure to cloud without downtime.

Talk to a Cloud Architect See what we build

AWS, GCP and Azure|Zero-downtime migration|99.99% uptime SLA

CLUSTER STATUS / PRODUCTION
─────────────────────────────────────
Provider:AWS EKS (us-east-1)
Nodes:12 running / 12 healthy
Pods:847 running / 0 failed
─────────────────────────────────────
[✓]AI inference: healthy
[✓]Data pipeline: healthy
[✓]API gateway: healthy
[✓]Autoscaler: active (8 triggers)
[→]Rolling deploy: 94% complete
[ ]Canary release: queued
Uptime (30d)99.97%
Deployments142 this month
Avg deploy time4m 12s
Last incident23 days ago

WHY IT MATTERS

AI systems make new demands on infrastructure.

AI workloads need elastic compute

Training runs, inference bursts, and batch processing jobs require infrastructure that scales on demand and scales back down. Fixed-size servers from 2018 cannot handle this.

Security requirements are non-negotiable

AI systems process sensitive business data. Network isolation, secrets management, RBAC, and encryption at rest and in transit are baseline requirements, not optional add-ons.

Slow deploys kill iteration speed

If deploying a new model version takes two days and three approvals, your AI team will stop shipping. CI/CD built for AI workflows is a competitive advantage.

WHAT WE BUILD

Six cloud and DevOps capabilities we deliver.

Cloud architecture and migration

Design and execution of cloud migration from on-premise or legacy environments. AWS, GCP, and Azure. Zero-downtime migration strategies with rollback capability at every stage.

AWS, GCP, Azure

Kubernetes and container orchestration

EKS, GKE, and AKS cluster design, deployment, and management. Auto-scaling, pod scheduling, network policies, and resource optimization for AI workloads.

EKS, GKE, AKS, Helm

CI/CD pipeline engineering

Automated build, test, and deploy pipelines using GitHub Actions, GitLab CI, or Jenkins. Canary releases, blue/green deployments, and automated rollback for zero-risk shipping.

GitHub Actions, ArgoCD, Jenkins

Cloud security and compliance

IAM policies, network segmentation, secrets management with Vault or AWS Secrets Manager, security scanning in CI/CD, and compliance frameworks for SOC 2 and HIPAA environments.

Vault, AWS IAM, Security Hub

Observability and monitoring

Full-stack observability with Datadog, Grafana, and Prometheus. Distributed tracing, log aggregation, custom dashboards, and alert routing that reaches the right person immediately.

Datadog, Grafana, Prometheus

Cloud cost optimization

Right-sizing, reserved instance planning, spot instance strategies, and automated cost anomaly detection. We reduce cloud spend without reducing performance.

AWS Cost Explorer, Spot, Reserved

MIGRATION METHODOLOGY

Zero-downtime migration is not a promise. It is a process.

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Week 1

Infrastructure audit

We document your current environment completely. Every service, dependency, data store, and integration. Nothing moves until we understand everything that touches it.

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Week 1-2

Target architecture design

We design the cloud target state: compute, network, storage, security, and observability. You approve the architecture before a single resource is created.

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