performance-tuning

name	performance-tuning
description	Optimize performance of the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration for AEMaaCS cloud workflows only, with cloud-specific baseline and runtime verification.
license	Apache-2.0
compatibility	Requires Dispatcher MCP configured for cloud variant (`AEM_DEPLOYMENT_MODE=cloud`).
allowed-tools	["validate","lint","sdk","trace_request","inspect_cache","monitor_metrics","tail_logs"]
metadata	{"mcp-tool-contract":"core-7-tools"}

Dispatcher Performance Tuning (Cloud)

Improve cache efficiency, latency, and throughput for cloud deployments that use the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration.

Variant Scope

• This skill is cloud-service-only.
• Scope is fixed by this skill directory; do not ask the user to choose deployment variant.

MCP Tool Contract

Use only these Dispatcher MCP tools:

• validate
• lint
• sdk
• trace_request
• inspect_cache
• monitor_metrics
• tail_logs

Workflow

1. Capture baseline metrics and cache evidence.
2. Apply cloud guardrails (immutable/default includes, reserved probe paths, and CDN-vs-Dispatcher ownership) before proposing changes.
3. Prioritize low-risk/high-impact changes.
4. Apply minimal edits.
5. Verify with validate, lint, and sdk.
6. Compare before/after runtime evidence.

Verification Scope Selection

Use shared references to select optimization evidence depth:

• mode-specific-verification-matrix.md
• test-case-catalog.md

Output Contract

Always return:

• baseline metrics snapshot
• prioritized optimization list with impact/risk
• changed files and intent
• executed checks + before/after evidence
• selected test IDs and outcomes
• rollback plan and open risks

Guardrails

• Do not claim improvement without measurable comparison.
• Keep high-risk tuning opt-in unless user explicitly requests it.
• Keep cloud assumptions explicit for each recommendation batch.
• Route edge/WAF/CDN-only concerns to CDN layer guidance instead of Dispatcher config changes.

References

• optimization-patterns.md
• performance-scenario-playbooks.md – scenario-driven tuning flows adapted from broader MCP prompt surfaces
• load-testing-guidance.md
• performance-monitoring-setup.md
• quick-start-execution-path.md – fast entry path for optimization requests
• repo-layout-workflows.md – map performance findings to cache, farm, vhost, and rewrite file families
• playbook-command-linkage.md – exact MCP command chains for tuning playbooks
• mode-specific-verification-matrix.md
• cloud-service-aemaacs-guardrails.md – cloud-service-only immutable/include/runtime boundary checks from AEMaaCS patterns
• test-case-catalog.md
• change-risk-and-rollback-template.md
• public-docs-index.md
• public-doc-citation-rules.md