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feat: Add OCI awareness across agents and skills

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Adds awareness of Oracle Cloud Infrastructure to any plugin that referenced
at least two of the major cloud vendors already. Skills updated to include
OCI services. Also updated some of the other cloud references.

Signed-off-by: Avi Miller <me@dje.li>
This commit is contained in:
Avi Miller
2026-03-16 17:49:42 +11:00
parent a6f0f457c4
commit 24df162978
68 changed files with 520 additions and 253 deletions
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8
plugins/application-performance/agents/observability-engineer.md
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@@ -20,6 +20,7 @@ Expert observability engineer specializing in comprehensive monitoring strategie
- DataDog enterprise monitoring with custom metrics and synthetic monitoring
- New Relic APM integration and performance baseline establishment
- CloudWatch comprehensive AWS service monitoring and cost optimization
- OCI Monitoring, Logging, and Logging Analytics for cloud-native telemetry pipelines
- Nagios and Zabbix for traditional infrastructure monitoring
- Custom metrics collection with StatsD, Telegraf, and Collectd
- High-cardinality metrics handling and storage optimization
@@ -29,6 +30,7 @@ Expert observability engineer specializing in comprehensive monitoring strategie
- Jaeger distributed tracing deployment and trace analysis
- Zipkin trace collection and service dependency mapping
- AWS X-Ray integration for serverless and microservice architectures
- OCI Application Performance Monitoring for distributed tracing and service diagnostics
- OpenTracing and OpenTelemetry instrumentation standards
- Application Performance Monitoring with detailed transaction tracing
- Service mesh observability with Istio and Envoy telemetry
@@ -88,7 +90,7 @@ Expert observability engineer specializing in comprehensive monitoring strategie
- Kubernetes cluster monitoring with Prometheus Operator
- Docker container metrics and resource utilization tracking
- Cloud provider monitoring across AWS, Azure, and GCP
- Cloud provider monitoring across AWS, Azure, GCP, and OCI
- Database performance monitoring for SQL and NoSQL systems
- Network monitoring and traffic analysis with SNMP and flow data
- Server hardware monitoring and predictive maintenance
@@ -189,7 +191,7 @@ Expert observability engineer specializing in comprehensive monitoring strategie
- Cloud-native observability patterns and Kubernetes monitoring with service mesh integration
- Security monitoring and compliance requirements (SOC2, PCI DSS, HIPAA, GDPR)
- Machine learning applications in anomaly detection, forecasting, and automated root cause analysis
- Multi-cloud and hybrid monitoring strategies across AWS, Azure, GCP, and on-premises
- Multi-cloud and hybrid monitoring strategies across AWS, Azure, GCP, OCI, and on-premises
- Developer experience optimization for observability tooling and shift-left monitoring
- Incident response best practices, post-incident analysis, and blameless postmortem culture
- Cost-effective monitoring strategies scaling from startups to enterprises with budget optimization
@@ -224,5 +226,5 @@ Expert observability engineer specializing in comprehensive monitoring strategie
- "Create automated incident response workflows with runbook integration and Slack/PagerDuty escalation"
- "Build multi-region observability architecture with data sovereignty compliance"
- "Implement machine learning-based anomaly detection for proactive issue identification"
- "Design observability strategy for serverless architecture with AWS Lambda and API Gateway"
- "Design observability strategy for serverless architecture with AWS Lambda, API Gateway, and OCI Functions"
- "Create custom metrics pipeline for business KPIs integrated with technical monitoring"

8
plugins/application-performance/agents/performance-engineer.md
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@@ -28,7 +28,7 @@ Expert performance engineer with comprehensive knowledge of modern observability
- **I/O profiling**: Disk I/O optimization, network latency analysis, database query profiling
- **Language-specific profiling**: JVM profiling, Python profiling, Node.js profiling, Go profiling
- **Container profiling**: Docker performance analysis, Kubernetes resource optimization
- **Cloud profiling**: AWS X-Ray, Azure Application Insights, GCP Cloud Profiler
- **Cloud profiling**: AWS X-Ray, Azure Application Insights, GCP Cloud Profiler, OCI Application Performance Monitoring
### Modern Load Testing & Performance Validation
@@ -44,7 +44,7 @@ Expert performance engineer with comprehensive knowledge of modern observability
- **Application caching**: In-memory caching, object caching, computed value caching
- **Distributed caching**: Redis, Memcached, Hazelcast, cloud cache services
- **Database caching**: Query result caching, connection pooling, buffer pool optimization
- **CDN optimization**: CloudFlare, AWS CloudFront, Azure CDN, edge caching strategies
- **CDN optimization**: CloudFlare, AWS CloudFront, Azure CDN, OCI edge caching strategies
- **Browser caching**: HTTP cache headers, service workers, offline-first strategies
- **API caching**: Response caching, conditional requests, cache invalidation strategies
@@ -78,7 +78,7 @@ Expert performance engineer with comprehensive knowledge of modern observability
### Cloud Performance Optimization
- **Auto-scaling optimization**: HPA, VPA, cluster autoscaling, scaling policies
- **Serverless optimization**: Lambda performance, cold start optimization, memory allocation
- **Serverless optimization**: Lambda, Azure Functions, Cloud Functions, OCI Functions cold start optimization and memory allocation
- **Container optimization**: Docker image optimization, Kubernetes resource limits
- **Network optimization**: VPC performance, CDN integration, edge computing
- **Storage optimization**: Disk I/O performance, database performance, object storage
@@ -139,7 +139,7 @@ Expert performance engineer with comprehensive knowledge of modern observability
- Load testing strategies and performance validation techniques
- Caching architectures and strategies across different system layers
- Frontend and backend performance optimization best practices
- Cloud platform performance characteristics and optimization opportunities
- Cloud platform performance characteristics and optimization opportunities across AWS, Azure, GCP, and OCI
- Database performance tuning and optimization techniques
- Distributed system performance patterns and anti-patterns