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Grok Bot+18 agentsMicroservices Dependency Impact Analyzer
Map microservice dependencies, trace transitive blast radius, and generate safe deployment sequences.
$39.99
Microservices Dependency Impact Analyzer
Example session with this skill installed
Analyze the impact of adding a required 'tax_id' field to the Order Service POST /orders endpoint. We have an API Gateway, an Inventory Service (Sync), and a Billing Service (Kafka).
- Read your context and instructions
- Compiled the microservices dependency impact
Analysis complete. Adding a required field to a core synchronous endpoint without a phased rollout will break the API Gateway and upstream clients.
Impact Report: Order Service Change
Dependency Map
Client -> API Gateway
└──sync──> Order Service (TARGET)
├──sync──> Inventory Service
└──async──> Kafka (Topic: orders.created)
└──> Billing Service
Affected Services
| Component | Impact | Criticality | Confidence | Priority |
|---|---|---|---|---|
| API Gateway | Breaking | Critical | Confirmed | P0 |
| Billing Service | Potential | Medium | Likely | P1 |
| Inventory Service | None | Low | Confirmed | P2 |
Failure Propagation
The API Gateway currently sends payloads without tax_id. Making this field required in Order Service will cause immediate 400 Bad Request errors for all incoming traffic. If the Billing Service consumes the entire order object from Kafka, it may fail during deserialization if its schema is not updated simultaneously.
Deployment Sequence
- Update Order Service: Add
tax_idas an optional field to the API and Kafka producer. - Update Billing Service: Update consumer to handle the new field (if applicable).
- Update Clients/Gateway: Begin sending
tax_idin requests. - Finalize Order Service: Change
tax_idfrom optional to required once 100% of traffic includes it.
Next steps
- Verify if the
Billing Serviceuses a schema registry (e.g., Confluent) for Kafka validation. - Run a contract test between the API Gateway and Order Service using the updated spec.
- Check if historical order data in the database requires a backfill for the new field.
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About this skill
The problem
Changes to a single microservice often cause unexpected cascading failures in downstream systems. Developers frequently lack visibility into the transitive blast radius, leading to broken API contracts and deployment order errors.
What it does
- Maps direct and transitive service dependencies across HTTP, gRPC, Kafka, and shared databases.
- Identifies critical business paths and traces how failures propagate through retries, timeouts, and circuit breakers.
- Classifies API and event schema changes as backward-compatible or breaking based on consumer analysis.
- Generates dependency-aware deployment sequences and rollback strategies to prevent service outages.
Frameworks & tools
Kubernetes, Docker Compose, Terraform, OpenAPI/Swagger, Kafka, gRPC, and GraphQL.
Why this beats prompting it yourself
Generic LLMs often hallucinate service relationships or overlook transitive dependencies. This skill enforces a strict MAP-TRACE-ASSESS workflow that distinguishes between confirmed evidence and inference, ensuring you never miss a hidden data dependency or deployment constraint.
Use cases
- Pre-deployment blast radius assessment for infrastructure or code changes.
- Designing expand-and-contract migration patterns for shared database schemas.
- Mapping critical paths to determine where to implement circuit breakers.
- Validating deployment order for complex, multi-service releases.
Known limitations
Does not monitor real-time traffic; analysis is based strictly on provided manifests, specs, and logs. Cannot prove runtime failure where evidence of circuit-breaker configuration is missing.
Core Features Microservice dependency mapping Direct dependency analysis Transitive dependency tracing Blast-radius analysis Critical-path identification Dependency criticality scoring Synchronous dependency analysis Event-driven dependency analysis API consumer impact analysis Event schema impact analysis Shared-database dependency detection Database migration impact analysis Infrastructure dependency analysis Failure propagation analysis Retry-storm detection Cascading-timeout analysis Queue/backlog risk analysis Circuit-breaker analysis Change compatibility assessment Deployment sequencing Rollout strategy planning Rollback planning Targeted test planning Observability requirements Evidence/confidence tracking Production change-risk reportingRequires architectural inputs like manifests or API specs. Analysis is static based on provided data and does not involve active runtime probing.
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