Start at the foundation - what a container actually is - then meet the tool that made them ubiquitous, see where they run in production on a serverless cloud platform, how the same platform handles run-to-completion tasks, two comparisons to help you pick, and how each side actually auto-scales.
The runtime-agnostic foundation - what's inside one, how it differs from a virtual machine, and the Linux primitives (namespaces, cgroups, layered filesystems) that make it work.
Read it →The platform that turned containers usable - Engine, CLI, Desktop, Hub, Compose, and Buildx, plus the build-ship-run cycle every developer learns first.
Read it →Serverless containers as long-lived services - HTTPS, autoscaling, rolling revisions, and a managed environment, without a Kubernetes cluster to operate underneath.
Read it →Serverless containers that start, do work, and exit - scheduled by cron, triggered by a queue, or kicked off on demand, on the same platform that runs your services.
Read it →Same platform, same image, two contracts. The dividing line between Apps and Jobs, the billing implications, and a four-question decision tree for picking the right one.
Read it →Two serverless ways to run bounded work on Azure - one ships a container, one ships a handler. Duration, programming model, billing, and which one fits the task.
Read it →Both auto-scale - but through different machinery and different units. The scale signal, the scale controller vs KEDA, scale to zero, and a worked burst.
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