Performance Tuning

adobe/skills/plugins/aem/cloud-service/skills/dispatcher/performance-tuning

作者 adobe940b8795c0df3e25de68ce3881dc90855129b215Apache-2.0197 个星标收录于 2026年10月9日更新于 2026年10月9日仓库今天更新

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.

仅含说明DevOps & Cloud
AI 生成的概览

使用 Dispatcher MCP 工具为 AEMaaCS 云部署调优 Adobe Dispatcher 与 HTTPD 配置性能。

功能
指导针对 AEM as a Cloud Service 部署的 Adobe Dispatcher Apache HTTP Server 模块及相关 HTTPD 配置进行性能调优。它会采集基线指标与缓存证据、应用云环境护栏、按优先级选择低风险改动、进行最小化编辑,并通过 validate、lint 和 sdk 检查进行验证。输出包括基线快照、带影响与风险的优化清单、变更文件、前后对比证据、所选测试 ID 以及回滚方案。
适用场景
适用于提升云服务 Dispatcher 与 HTTPD 配置的缓存效率、延迟或吞吐量。仅面向云部署,部署变体由技能目录固定。边缘、WAF 或纯 CDN 相关问题会转由其他指引处理,而不在此处理。
运行要求
需要配置为云变体的 Dispatcher MCP(AEM_DEPLOYMENT_MODE=cloud),以及 validate、lint、sdk、trace_request、inspect_cache、monitor_metrics 和 tail_logs 工具。不附带脚本,仅为指令与参考文档。

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
  • core-7-tools-reference.md

来源与署名

来源:adobe/skills位于plugins/aem/cloud-service/skills/dispatcher/performance-tuning提交940b879

许可证: Apache-2.0

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