plugins/faos-architect/skills/workflow-orchestration-patterns/SKILL.md
<!-- AUTO-GENERATED by export-plugins.py — DO NOT EDIT --> --- name: workflow-orchestration-patterns description: Design durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running business processes or distributed transactions. tags: [workflow, temporal, orchestration] --- # Workflow Orchestration Patterns Master workflow orchestration architecture with Temporal, c
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Master workflow orchestration architecture with Temporal, covering fundamental design decisions, resilience patterns, and best practices for building reliable distributed systems.
The Fundamental Rule (Source: temporal.io/blog/workflow-engine-principles):
Characteristics:
Example workflow tasks:
Characteristics:
Example activity tasks:
Does it touch external systems? -> Activity
Is it orchestration/decision logic? -> Workflow
Purpose: Implement distributed transactions with rollback capability
Pattern (Source: temporal.io/blog/compensating-actions-part-of-a-complete-breakfast-with-sagas):
For each step:
1. Register compensation BEFORE executing
2. Execute the step (via activity)
3. On failure, run all compensations in reverse order (LIFO)
Example: Payment Workflow
Critical Requirements:
Purpose: Long-lived workflow representing single entity instance
Pattern (Source: docs.temporal.io/evaluate/use-cases-design-patterns):
Example Use Cases:
Benefits:
Purpose: Execute multiple tasks in parallel, aggregate results
Pattern:
Scaling Rule (Source: temporal.io/blog/workflow-engine-principles):
Purpose: Wait for external event or human approval
Pattern:
Use Cases:
How Temporal Works (Source: docs.temporal.io/workflows):
Workflows Execute as State Machines:
Prohibited in Workflows (Source: docs.temporal.io/workflows):
random())datetime.now())Allowed in Workflows:
workflow.now() (deterministic time)workflow.random() (deterministic random)Challenge: Changing workflow code while old executions still running
Solutions:
workflow.get_version() for safe changesDefault Behavior: Temporal retries activities forever
Configure Retry:
Non-Retryable Errors:
Why Critical (Source: docs.temporal.io/activities):
Implementation Strategies:
Purpose: Detect stalled long-running activities
Pattern:
Workflow Violations:
datetime.now() instead of workflow.now()Activity Mistakes:
Monitoring:
Scalability:
Official Documentation:
Key Principles:
development
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<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-lakebase-provisioned --- # Lakebase Provisioned Patterns and best practices for using Lakebase Provisioned (Databricks managed PostgreSQL) for OLTP workloads. ## When to Use Use this skill when: - Building applications that need a PostgreSQL database for transactional workloads - Adding persistent state to Databricks Apps - Implementing reverse ETL from Delta Lake to an operational database - Storing chat/agent m
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<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-jobs --- # Databricks Lakeflow Jobs ## Overview Databricks Jobs orchestrate data workflows with multi-task DAGs, flexible triggers, and comprehensive monitoring. Jobs support diverse task types and can be managed via Python SDK, CLI, or Asset Bundles. ## Reference Files | Use Case | Reference File | | ----------------------
development
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-genie --- # Databricks Genie Create and query Databricks Genie Spaces - natural language interfaces for SQL-based data exploration. ## Overview Genie Spaces allow users to ask natural language questions about structured data in Unity Catalog. The system translates questions into SQL queries, executes them on a SQL warehouse, and presents results conversationally. ## When to Use This Skill Use this skill when: -