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AI for Jenkins Difficulty: Advanced ClaudeChatGPT

Jenkins Migrate to Ephemeral Agents Prompt

Move from long-lived static Jenkins agents to ephemeral, provisioned-on-demand agents (cloud VMs or containers) — so every build starts from a clean image, capacity scales to zero, and snowflake nodes disappear.

Target user
Teams retiring pet Jenkins build servers
Difficulty
Advanced
Tools
Claude, ChatGPT

The prompt

You are a platform engineer who retires pet build servers in favor of ephemeral agents that spin up clean and tear down after each build.

I will provide:
- My current static agents (OS, installed tools, how builds depend on local state)
- My target cloud/platform (Kubernetes, EC2, GCE, Azure) and the plugin available
- Build volume/patterns (steady vs bursty) and cost concerns

Your job:

1. **Find the hidden state** — inventory what builds silently depend on today: pre-installed tools, local caches, credentials on disk, files left by previous builds. This is what breaks when agents become clean-per-build.

2. **Bake images** — define golden agent images (VM image or container) with the required toolchain baked in, versioned and rebuilt from code (Packer/Dockerfile), so provisioning is fast and reproducible.

3. **Cloud provisioning** — configure the cloud plugin (Kubernetes/EC2/etc.): templates, labels, min/max instances, idle timeout, and scale-to-zero when idle.

4. **Externalize caches** — replace on-agent caches with an external cache/registry (dependency cache, artifact store) since ephemeral agents start empty; tie into a caching strategy.

5. **Cost & burst** — size min/max and idle timeouts to balance cold-start latency against cost; consider spot/preemptible with retry for cheap burst capacity.

6. **Cutover** — run static and ephemeral in parallel, migrate one job family at a time, fix each hidden-state break, then decommission the static nodes.

Output: (a) the hidden-state inventory, (b) the golden-image definition, (c) the cloud-plugin provisioning config, (d) the external-cache + cutover plan.

Bias toward: reproducible golden images, external caches, and a gradual per-job cutover that surfaces hidden state.

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