What problem does it solve? Developers face slow API responses, database read bottlenecks, DynamoDB throttling, and Bedrock latency or cost issues, and they lack guided expertise for choosing, provisioning, securing, and operating AWS ElastiCache across Valkey, Redis OSS, and Memcached engines. ## Core Features & Use Cases - Sub-skill routing: A registry of six sub-skills (requirements, setup, data-modeling, genai, monitoring, migration) matches user intent to the right workflow, with shared state tracked in .elasticache/requirements.json. - Provisioning and connectivity: Guides engine selection, serverless vs node-based deployment, VPC connectivity, TLS, RBAC/IAM auth, and IaC via CloudFormation, CDK, or Terraform, including SSM tunnel setup for local development. - GenAI and vector workloads: Classifies AI caching into plain cache, semantic response cache, or full vector search modes, enforcing node-based Valkey 8.2+ for vector similarity search, RAG, and agent memory. - Operations and migration: Generates CloudWatch dashboards and alarms, estimates serverless ECPU costs, and runs migration preflight checks for moving self-managed Redis to ElastiCache. - Use Case: A team with an RDS-backed application suffering read bottlenecks uses the skill to evaluate ElastiCache fit, provision a Valkey serverless cache, implement cache-aside patterns, and deploy monitoring alarms. ## Quick Start Ask the assistant to help you set up an ElastiCache Valkey cache for your application and recommend the right engine and deployment model.
