Apache Airflow DAG Patterns
Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
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Validate production readiness of Vertex AI Agent Engine deployments across
--- name: validator-expert-c7b856f1df5b description: Validate production readiness of Vertex AI Agent Engine deployments across security, monitoring, performance, compliance, and best practices. Generates weighted scores (0-100%) with actionable recommendations. Use when asked to "validate deploymen... allowed-tools: Read, Grep, Glob, Bash license: MIT --- ## What This Skill Does Production validator for Vertex AI deployments. Performs comprehensive checks on security, compliance, monitoring, performance, and best practices before approving production deployment. ## When This Skill Activates Triggers: "validate deployment", "production readiness", "security audit vertex ai", "check compliance", "validate adk agent" ## Validation Checklist ### Security Validation - ✅ IAM roles follow least privilege - ✅ VPC Service Controls enabled - ✅ Encryption at rest configured - ✅ No hardcoded secrets - ✅ Service accounts properly configured - ✅ Model Armor enabled (for ADK) ### Monitoring Validation - ✅ Cloud Monitoring dashboards configured - ✅ Alerting policies set - ✅ Token usage tracking enabled - ✅ Error rate monitoring active - ✅ Latency SLOs defined ### Performance Validation - ✅ Auto-scaling configured - ✅ Resource limits appropriate - ✅ Caching strategy implemented - ✅ Code Execution sandbox TTL set - ✅ Memory Bank retention configured ### Compliance Validation - ✅ Audit logging enabled - ✅ Data residency requirements met - ✅ Privacy policies implemented - ✅ Backup/disaster recovery configured ## Tool Permissions Read, Grep, Glob, Bash - Read-only analysis for security ## References - Vertex AI Security: https://cloud.google.com/vertex-ai/docs/security--- name: validator-expert-c7b856f1df5b description: Validate production readiness of Vertex AI Agent Engine deployments across security, monitoring, performance, compliance, and best practices. Generates weighted scores (0-100%) with actionable recommendations. Use when asked to "validate deploymen... allowed-tools: Read, Grep, Glob, Bash license: MIT --- ## What This Skill Does Production validator for Vertex AI deployments. Performs comprehensive checks on security, compliance, monitoring, performance, and best practices before approving production deployment. ## When This Skill Activates Triggers: "validate deployment", "production readiness", "security audit vertex ai", "check compliance", "validate adk agent" ## Validation Checklist ### Security Validation - ✅ IAM roles follow least privilege - ✅ VPC Service Controls enabled - ✅ Encryption at rest configured - ✅ No hardcoded secrets - ✅ Service accounts properly configured - ✅ Model Armor enabled (for ADK) ### Monitoring Validation - ✅ Cloud Monitoring dashboards configured - ✅ Alerting policies set - ✅ Token usage tracking enabled - ✅ Error rate monitoring active - ✅ Latency SLOs defined ### Performance Validation - ✅ Auto-scaling configured - ✅ Resource limits appropriate - ✅ Caching strategy implemented - ✅ Code Execution sandbox TTL set - ✅ Memory Bank retention configured ### Compliance Validation - ✅ Audit logging enabled - ✅ Data residency requirements met - ✅ Privacy policies implemented - ✅ Backup/disaster recovery configured ## Tool Permissions Read, Grep, Glob, Bash - Read-only analysis for security ## References - Vertex AI Security: https://cloud.google.com/vertex-ai/docs/security
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