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Found 83 Skills
Apply cloud-native architecture patterns. Use when designing for scalability, resilience, or cloud deployment. Covers microservices, containers, and distributed systems.
Chaos engineering principles, controlled failure injection, resilience testing, and system recovery validation. Use when testing distributed systems, building confidence in fault tolerance, or validating disaster recovery.
When designing distributed systems for scalability, reliability, and consistency. Covers CAP/PACELC theorems, consistency models (strong, eventual, causal), replication patterns (leader-follower, multi-leader, leaderless), partitioning strategies (hash, range, geographic), transaction patterns (saga, event sourcing, CQRS), resilience patterns (circuit breaker, bulkhead), service discovery, and caching strategies for building fault-tolerant distributed architectures.
Standardized error handling patterns with classification, recovery, and logging strategies. error handling, error recovery, graceful degradation, resilience.
Resilience patterns with Spring Cloud Circuit Breaker and Resilience4j. Covers circuit breaker, retry, rate limiter, bulkhead, and fallback patterns. USE WHEN: user mentions "circuit breaker", "resilience4j", "fallback", "retry pattern", "rate limiter", "bulkhead", "fault tolerance Spring" DO NOT USE FOR: basic HTTP errors - handle in code, Hystrix (deprecated) - use Resilience4j instead
Guides microservice design and delivery—bounded contexts, service boundaries, REST/gRPC/event APIs, sync vs async tradeoffs, resilience (timeouts, retries, circuit breakers, bulkheads), per-service data ownership, saga and outbox patterns, twelve-factor containers, observability (logs, metrics, trace propagation), API versioning at gateways/meshes, and contract testing. Use for microservices developer, service boundary, bounded context, gRPC between services, circuit breaker, saga pattern, outbox pattern, twelve-factor, contract testing microservices, service decomposition, or event-driven microservice—not K8s platform ops (platform-engineer, site-reliability-engineer), enterprise iPaaS (enterprise-integration-api-developer), monolith-first apps (senior-software-engineer), or classified pipelines (classified-software-devsecops-engineer).
Create and manage chaos experiments using Harness Chaos Engineering via MCP. Run resilience tests like pod deletion, CPU stress, and network faults. Use when user says "chaos experiment", "chaos engineering", "resilience test", "chaos test", or wants to test system reliability.
Comprehensive microservices patterns skill covering service mesh, traffic management, circuit breakers, resilience patterns, Istio, and production microservices architecture
Comprehensive microservices architecture patterns covering service decomposition, communication, data management, and resilience strategies. Use when designing distributed systems, breaking down monoliths, or implementing service-to-service communication.
Design state machines, orchestration workflows, saga patterns, and resilience strategies for distributed systems, AI agents, and complex async processes. Use when asking for a workflow, state machine, orchestration design, saga, HITL checkpoint, or process resilience strategy.
Sets up AWS Resilience Hub v2 from scratch: creates resilience policies with SLO targets, registers systems and user journeys, onboards services with input sources, and runs a first failure mode assessment. Applies when the user wants to get started with Resilience Hub v2, create a policy, onboard a service, or run an assessment — including creating one concrete policy with specific availability/RTO/RPO targets and a DR approach for a single service (even a tier-1 one). Does not apply to FIS experiments or ARC routing controls.
Guides the end-to-end AWS resilience lifecycle integrating Resilience Hub v2, Fault Injection Service, and Application Recovery Controller. Covers the Define → Test → Operate workflow: from policy creation through failure mode assessment, to FIS experiment validation, to ARC operational controls. Applicable when the user wants a complete resilience strategy, needs to connect findings to experiments to controls, or is planning a resilience program. Also applicable for the meta question of whether marking NGRH findings as resolved is enough, whether they are "done" after resolving findings, or how to validate findings before resolving them. Not applicable for resolving or remediating a specific individual finding (see resilience-hub-failure-mode-assessment), or when a single service is explicitly named (e.g. "what FIS experiment should I run").