Kubernetes
EKS environments with managed baseline capacity and workload-aware autoscaling.
The challenge
Many workloads, one operable platform
The client needed separate development, staging and production environments; controlled network and database boundaries; elastic compute for data and ML jobs; and a repeatable route from code to operations.
The platform also had to make reliability, security, cost and support ownership visible rather than leaving them as post-project concerns.
The operating platform
Data workflows
Orchestration, distributed SQL, notebooks, dashboards and ML lifecycle services.
Infrastructure as code
Repeatable Terraform modules and environment-aware deployment controls.
Observability
Metrics, logs, tracing, dashboards, alerts and operational runbooks.
Security
Private access, managed identity, secret handling and audit trails.
FinOps
Environment cost baselines, capacity review and prioritized optimization.
What this proves
Perception IT can design, automate and operate a cloud platform that connects infrastructure, data, ML and AI workloads—not just deploy isolated cloud resources.
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