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.

AI agents increasingly drive demand for deployable, scalable application runtimes, background jobs, secure sandboxes, and developer tooling, making them materially relevant to containerized hosting decisions.

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

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.

Kubernetes is a foundational container orchestration technology that directly shapes deployment, scaling, networking, and operations choices for containerized application hosting.