creating-amazon-aurora-db-cluster-with-instances
Creating Amazon Aurora DB Cluster with Instances
Overview
Domain expertise for creating complete Amazon Aurora database setups including cluster creation, instance provisioning, and managed password configuration via AWS Secrets Manager. Supports both Aurora MySQL and Aurora PostgreSQL engines.
Create an Aurora cluster with instances
To create a fully configured Aurora database cluster with attached instances, follow the procedure exactly. See Aurora cluster creation procedure.
The procedure creates an empty Aurora cluster first, then adds a database instance to make it queryable. It uses AWS Secrets Manager for password management and includes proper status monitoring with retry logic.
Troubleshooting
Cluster creation fails
Verify the engine version is supported in your region and that you have sufficient permissions for RDS and Secrets Manager operations.
Instance creation fails
Check that the instance class is compatible with the Aurora engine and available in your region's availability zones.
Long creation times
Aurora cluster and instance creation can take 10-20 minutes. Extended wait times are normal for Aurora resources.
More from aws/agent-toolkit-for-aws
aws-iam
Verified corrections for IAM behaviors that AI agents frequently get\
341amazon-bedrock
Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore. Use when invoking models, setting up Knowledge Bases, creating agents, applying guardrails, deploying to AgentCore, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedException), or choosing models (Claude, Llama, Nova, Titan). ALSO USE for prompt caching setup and debugging, quota health checks and throttling diagnosis, cost attribution and tracking, migrating between Claude model generations (4.5 to 4.6 to 4.7), chunking strategies, API selection (Converse vs InvokeModel), guardrail capabilities, and model selection. NOT for custom model training, Rekognition, or Comprehend.
323aws-serverless
Builds, deploys, manages, debugs, configures, and optimizes serverless applications on AWS using Lambda, API Gateway, Step Functions, EventBridge, and SAM/CDK. Covers cold starts, CORS debugging, event source mappings, troubleshooting, concurrency, SnapStart, Powertools, function URLs, EventBridge Scheduler, Lambda layers, Durable Functions, durable execution, checkpoint-and-replay, and production readiness. Use when the user mentions Lambda, API Gateway, Step Functions, SAM templates, CDK serverless stacks, DynamoDB stream triggers, SQS event sources, cold starts, timeouts, 502/504 errors, throttling, concurrency, CORS, Powertools, Durable Functions, durable execution, checkpoint-and-replay, or any event-driven architecture on AWS, even if they don't say "serverless." Do NOT use for EC2, ECS/Fargate containers, or Amplify hosting.
312aws-cdk
Authors, deploys, and troubleshoots AWS infrastructure using CDK with TypeScript or Python. Covers best practices, stack architecture, and construct patterns. Always use when writing CDK constructs, bootstrapping environments, running cdk deploy/synth/diff, fixing CDK or CloudFormation errors, planning stack structure, importing existing resources, resolving drift, or refactoring stacks without resource replacement.
304aws-cloudformation
Author, validate, and troubleshoot AWS CloudFormation templates. Covers template authoring with secure defaults, pre-deployment validation (cfn-lint, cfn-guard, change sets), and root-cause diagnosis of failed stacks using CloudFormation events and CloudTrail correlation.
299aws-observability
Builds, configures, debugs, and optimizes AWS observability using CloudWatch (Logs Insights, Metrics, Alarms, Dashboards, EMF), X-Ray, CloudTrail, and ADOT. Covers Log Insights query syntax (fields, filter, stats, parse, pattern, join, subqueries), alarm configuration (metric, composite, anomaly detection, missing data treatment), dashboard design, custom metrics (PutMetricData, EMF, metric filters), X-Ray tracing (ADOT, sampling rules, annotations vs metadata), ADOT collector config, and CloudTrail auditing. Use when the user mentions CloudWatch, Log Insights, alarms, INSUFFICIENT_DATA, dashboards, custom metrics, EMF, X-Ray, traces, sampling, CloudTrail, who deleted, ADOT, OpenTelemetry, observability, monitoring, synthetics, canaries, or troubleshooting alarm behavior. Do NOT use for application logging setup, container log drivers, or security threat detection.
299