Containerized app hosting

Real-time and streaming workloads are a meaningful deployment use case for container platforms, influencing requirements for low latency, persistent connections, scaling, and event-driven architecture.

Observability and distributed tracing are directly relevant to operating containerized applications, where distributed services, ephemeral workloads, and deployment complexity make diagnosis and performance management essential.

Serverless and functions-as-a-service are a durable adjacent deployment model that directly shapes how developers choose to package, run, scale, and pay for applications.

Developer experience directly shapes platform selection, onboarding speed, deployment workflows, and operational productivity for containerized application hosting.

LLM workloads and AI-enabled applications increasingly shape deployment, scaling, GPU access, observability, and runtime requirements for container hosting.