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Found 93 Skills
Use this skill when designing event-driven systems, implementing event sourcing, applying CQRS patterns, selecting message brokers, or reasoning about eventual consistency. Triggers on tasks involving Kafka, RabbitMQ, event stores, command-query separation, domain events, sagas, compensating transactions, idempotency, message ordering, and any architecture where components communicate through asynchronous events rather than direct synchronous calls.
Event sourcing and CQRS expert for AI memory systemsUse when "event sourcing, event store, cqrs, nats jetstream, kafka events, event projection, replay events, event schema, event-sourcing, cqrs, nats, kafka, projections, event-driven, memory-architecture, ml-memory" mentioned.
Amazon SQS managed message queue service. Covers standard and FIFO queues, dead-letter queues, and integration patterns. Use for AWS-native serverless and microservices architectures. USE WHEN: user mentions "sqs", "aws queues", "fifo queue", "lambda trigger", "sns to sqs", asks about "aws messaging", "serverless queues", "standard queue", "visibility timeout" DO NOT USE FOR: event streaming - use `kafka` or AWS Kinesis; Azure-native - use `azure-service-bus`; GCP-native - use `google-pubsub`; on-premise - use `rabbitmq` or `activemq`; complex routing - use `rabbitmq`
Routes PubNub events to external systems with no code via Events & Actions (E&A). Covers event listeners (Messages, Users, Channels, Push, Memberships), action targets (Webhook, SQS, Kinesis, S3, Kafka, IFTTT, AMQP), filter types (basic vs JSONPath), retry policy, envelopes, and batching. Use when integrating PubNub with Lambda, Kafka, SQS, S3, EventBridge, an analytics pipeline, or any external system.
Selects, investigates, and compares AWS object, file, and block storage services, and answers cost, performance, configuration, security, and troubleshooting questions about storage services. Applies when a user asks where to store or archive data based on their usage patterns; which storage service to choose or how two compare; how to migrate data from on-premises or between AWS services; how to protect, replicate, or recover data; how to optimize storage costs; where to deploy shared NFS, SMB, or POSIX file systems; where to store vector embeddings or tabular data; what storage backs enterprise file shares, self-managed databases on EC2, VMware, or stateful containers; or asks what an AWS storage service can do or how it works. Relevant for storage needs for workloads such as AI/ML, analytics, EDA, HPC, media, genomics, or financial trading. Not applicable for SQL query engines (Athena, Spark, Redshift, EMR), ETL (Glue), streaming (Kafka, MSK, Kinesis), or managed database services (RDS, Aurora, DynamoDB).
Hookdeck Outpost — open-source infrastructure for sending webhooks and events to user-preferred destinations (HTTP, SQS, RabbitMQ, Pub/Sub, EventBridge, Kafka). Use when building a SaaS platform that needs to deliver events to customers.
Creates Robot Framework test cases for SnapLogic account creation. Use when the user wants to create accounts (Oracle, PostgreSQL, Snowflake, Kafka, S3, etc.), needs to know what environment variables to configure, or wants to see account test case examples.
Event-driven architecture patterns including message queues, pub/sub, event sourcing, CQRS, and sagas. Use for async messaging, distributed transactions, event stores, domain/integration events, data streaming, choreography/orchestration, or integrating with Kafka, RabbitMQ, Pulsar, SQS/SNS, or NATS.
Implement distributed transactions using the Saga Pattern in Spring Boot microservices. Use when building microservices requiring transaction management across multiple services, handling compensating transactions, ensuring eventual consistency, or implementing choreography or orchestration-based sagas with Spring Boot, Kafka, or Axon Framework.
Implements OpenTelemetry (OTEL) logging with trace context correlation and structured logging. Use when setting up production logging with OTEL exporters, structlog/loguru integration, trace context propagation, and comprehensive test patterns. Covers Python implementations for FastAPI, Kafka consumers, and background jobs. Includes OTLP, Jaeger, and console exporters.
Monitor hosts, Docker containers, Kubernetes clusters, database/queue/cache servers, and cloud-provider metrics with Pydantic Logfire — no application code required. Use this skill whenever the user asks to "monitor my host/server/VM", "monitor my Docker containers", "monitor my Kubernetes cluster", "send infrastructure metrics to Logfire", "watch my database/Postgres/Redis/MongoDB/Kafka", "collect cloud metrics" (AWS/GCP), or mentions the OpenTelemetry Collector in the context of Logfire. This is infrastructure only — for instrumenting APPLICATION CODE (traces, logs, AI/agent spans) use the logfire-instrumentation skill instead.
Use when user explicitly asks Flink/Ververica/Realtime Compute Console workspace operations: 草稿(draft), SQL校验/执行, 部署(deployment), 作业(job), Session Cluster, namespace, 表(table), 成员(member), 变量(variable), 或 checkpoint timeout 诊断, especially with workspace/deployment/job IDs (w-*, d-*, j-*, sc-*, draft-*). Also use when prompt asks to test/verify Flink Console lifecycle flow, safety guardrails, or parameter validation for these operations. This includes prompts such as create draft, deploy draft, list deployments, start/stop job, create/list session cluster, get tables, list variables. Also use when prompt explicitly asks to run `python scripts/flink_ververica_ops.py` for Flink Console workspace operations. Do not trigger for unrelated "workspace" contexts or generic cloud/platform tasks (ECS, OSS, RDS, Kafka, Spark, Kubernetes, billing, weather). Do not trigger for Flink instance lifecycle operations (create/scale/delete/renew); those belong to alibabacloud-flink-instance-manage.