Dependency Hygiene & Scaling Alignment
Whether interacting systems are configured and versioned in ways that scale safely together.
Identify services approaching dependency-imposed scaling limits before their own compute limits. Examples: database max connections, queue partition throughput, API rate limits, disk IOPS caps, load balancer target limits.
2. Which components are configured incompatibly with the systems they depend on?Identify components configured incompatibly with the systems they depend on. Examples: timeout mismatches, retry storms, oversized connection pools, memory limits below runtime behavior, cache TTLs that amplify database load.
3. Where are client-side concurrency settings out of proportion to downstream capacity?Detect client-side concurrency settings out of proportion to downstream capacity; include affected service pair, current settings, observed utilization, and risk.
4. Which dependencies run deprecated versions that could affect performance or resilience?Identify dependencies on deprecated or soon-to-be-unsupported infrastructure versions that could affect performance or resilience; include version inventory and operational risk context.
5. Are shared dependencies aligned with current growth and access patterns?Identify shared dependencies serving workloads whose growth or access patterns are no longer aligned with current shard, partition, or replica design. Examples: database shards with skewed key distribution, Kafka topics with hot partitions, search clusters with unbalanced index sizes.