Review the AWS database engine recommended for each access pattern in your source database, the estimated cost of running it, and the trade-offs each design accepts.
The target architecture recommended for this database, its projected monthly cost, and the workload it covers.
Analyzed 50 source tables and 107 query patterns across 3 target database(s). Workload split: dynamodb handles 58 queries (54.2%), aurora_mysql handles 49 queries (45.8%). Cache layer: elasticache fronts 20 hot reads (83.4% of calls) cache-aside and owns no queries. Estimated monthly cost: $582.76. 2 open migration risks (overall: HIGH); 6 more were resolved by the assignment. Other targets evaluated: documentdb (consolidated into aurora_mysql by the reality check), opensearch (consolidated into aurora_mysql by the reality check).
The incremental migration waves computed from this assessment. One suggested adoption path, not the only one — to modernize in one step instead, adopt the target architecture in Executive Summary above directly.
Estimated monthly cost of running each recommended engine at your current workload volume.
How your access patterns distribute across the recommended engines, from source table to target.
Browse every access pattern by pattern or by source table. Filter by engine, operation, or text to narrow the list, then select a row to see its target design.
What each target design gains, what it gives up, and the reasoning behind the decision.
Observations raised while reviewing each design, including the decisions to validate with your team before you commit to them.