菜单
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.
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基于 SOC 职业分类
| 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"} |
Improve cache efficiency, latency, and throughput for cloud deployments that use the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration.
Use only these Dispatcher MCP tools:
validatelintsdktrace_requestinspect_cachemonitor_metricstail_logsvalidate, lint, and sdk.Use shared references to select optimization evidence depth:
Always return:
Single entry point for all AEM as a Cloud Service Workflow skills. Covers workflow model design, custom process step and participant chooser development, launcher configuration, workflow triggering, and production support including debugging stuck/failed workflows, triaging incidents with Cloud Manager logs, thread pool analysis, and Sling Job diagnostics for the Granite Workflow Engine.
Debug AEM Workflow issues on AEM as a Cloud Service including stuck workflows, failed steps, missing Inbox tasks, launcher failures, stale instances, thread pool exhaustion, queue backlogs, purge failures, and permissions errors. Use when the user reports workflow problems on Cloud Service, asks why a workflow is stuck or failed, needs step-by-step troubleshooting, or provides thread dumps, configuration output, or Sling Job console output for analysis.
Implement custom AEM Workflow Java components on AEM as a Cloud Service. Use when writing WorkflowProcess steps, ParticipantStepChooser implementations, registering services via OSGi DS R6 annotations, reading step arguments from MetaDataMap, accessing JCR payload via WorkflowSession adapter, reading and writing workflow metadata and variables, and handling errors with WorkflowException for retry behavior.
Design and create AEM Workflow models on AEM as a Cloud Service. Use when creating workflow models via the Workflow Model Editor or content package XML, defining step types (PROCESS, PARTICIPANT, DYNAMIC_PARTICIPANT, OR_SPLIT, AND_SPLIT), configuring step properties, declaring workflow variables, and deploying models through the Cloud Manager pipeline.
Triage AEM Workflow issues on AEM as a Cloud Service by classifying symptoms, gathering the right logs and metrics, and mapping to runbooks or Splunk searches. Use when the user asks for workflow activity/errors on a Cloud Service host, needs to classify a Jira ticket, or wants to know what to collect for workflow debugging.
Start AEM Workflows on AEM as a Cloud Service using all available triggering mechanisms. Use when starting workflows manually via the Timeline UI, programmatically via WorkflowSession.startWorkflow(), via the HTTP Workflow API, through Manage Publication, or passing initial metadata and payload to a workflow instance.