BaseRock's integration testing validates how services, modules, and APIs work together, using OpenTelemetry-based discovery or source code analysis to map real dependencies - automatically, without manually scripted test scenarios.
Yes. BaseRock validates the underlying API calls and system interactions across both mono-repo and multi-repo architectures, confirming services communicate correctly as your system grows.
Continuous monitoring of code and telemetry flags contract or logic changes as they happen, automatically updating affected tests so breaking changes are caught before they reach production.
Source code learning typically completes in under a day. OpenTelemetry-based learning takes 2–3 days after one full regression run, after which BaseRock has a working map of your real dependencies.
Yes. BaseRock integrates with GitHub, GitLab, Bitbucket, Jenkins, and Azure DevOps, and failing integration tests can be configured to block a merge or deployment automatically.
Not directly - UI flows themselves aren't automated by this capability yet, but the underlying API calls and system interactions those UI flows depend on are fully testable.
Integration testing validates that services and APIs work together correctly at the system level; functional testing validates a full feature or user workflow against requirements. See Functional Testing FAQs below for the distinction.
Functional testing validates a feature or workflow from a user or business perspective across multiple components, generated from requirements, code, and acceptance criteria together -not just from service-to-service communication.
Yes. BaseRock reads Jira tickets, PRDs, and Figma files alongside code context to generate functional tests that reflect actual product requirements, not just what the code currently does.
Yes. Scenario-based and edge-case paths are included and benchmarked against historical regression failures, so coverage goes beyond happy-path checks.
Coverage is auditable through the BaseRock dashboard, where teams can review generated tests directly against requirements and flag any gaps before release.
Yes. Tests are fully editable in the BaseRock portal, and the Playbook feature lets QA guide test generation using plain natural language, no scripting required.
Yes. It's designed to validate complete feature workflows spanning multiple modules or services, not a single isolated function or endpoint.
BaseRock supports major frameworks including NestJS, Next.js, Vue.js, React.js, Django, Spring Boot, Go, and TypeScript-based stacks, with automatic project structure detection.
Business Use Case Testing validates the customer journeys and revenue-critical workflows - like checkout, signup, or billing -beyond the individual code paths a developer thought to test, catching failures and traditional testing misses.
Functional testing checks that one feature works as specified. B.U.C.T. validates that entire business-critical journeys spanning multiple features deliver the outcome the business actually depends on.
BaseRock combines code analysis, requirements, and usage patterns to map and prioritize the workflows most tied to revenue or customer experience, without requiring a manual audit.
Not necessarily - critical flows can be inferred automatically, though teams can guide and refine prioritization using the Playbook feature if they want more control.
Yes. Reports are framed around business outcomes and release readiness, so they're directly usable by product managers and business leaders, not just engineers.
Yes. It's designed to validate complete feature workflows spanning multiple modules or services, not a single isolated function or endpoint.
Code can be technically correct - passing every syntax or unit-level check - while still being business incorrect if it fails the customer's actual journey. B.U.C.T. is built specifically to catch that gap.
BaseRock's control plane deploys inside your own Kubernetes namespace, VPC, or on-premise environment, so processing happens locally and your source code and proprietary requirements never leave your approved security perimeter.
BaseRock can be deployed on Azure, AWS, GCP, or any other major cloud provider, as well as fully on-premise or in a private cloud, giving teams flexibility to match their existing infrastructure.
Yes, BaseRock has achieved SOC 2 compliance, reflecting independently audited controls for security, availability, and confidentiality; a SOC 2 report is available to partners under NDA.
Depending on the integration approach, BaseRock accesses either telemetry metadata (OpenTelemetry-based) or read-only source code and metadata (GitHub-based) - never write access — and all data is stored in your own environment with a configurable retention duration.
Yes. BaseRock supports bring-your-own-LLM through providers like Anthropic, OpenAI, Azure OpenAI, and AWS Bedrock, or you can deploy BaseRock's fine-tuned model directly inside your own environment.
Yes. It's designed to validate complete feature workflows spanning multiple modules or services, not a single isolated function or endpoint.
