4 posts tagged with "Java Ecosystem"

TL;DR: Testing Spring Cloud OpenFeign clients is difficult to get right. Mocking the Java interface misses serialization and interceptor logic. WireMock tests the full HTTP stack but requires constant manual updates to JSON stubs. A more reliable alternative is runtime replay. You capture real HTTP exchanges from production and virtualize the Feign boundaries during your Spring Boot integration tests.

TL;DR: Your service compiles. Your unit tests pass. Your integration tests are green. But a single line in your ObjectMapper configuration just changed what every outgoing HTTP request looks like. The downstream service cannot parse the payload anymore, and you will find out in production. Here are five Jackson configuration changes that cause this, with exact before/after JSON for each.

We're excited to announce the release of BitDive 1.2.6, bringing new capabilities that make Runtime Observability (glossary) for JVM applications even more powerful and developer-friendly. This update expands protocol coverage, adds a new analytics view, and introduces flexible agent configuration - all designed to help teams move faster from problem detection to resolution using Real Runtime Data.

From Fragmented Traces to Confident Releases. BitDive eliminates "Mocking Hell" by turning real-world JVM traffic into Trace-Based Testing suites. By replacing handwritten test code with recorded Replay Plans, enterprise teams reduce test maintenance by 60% and establish the Real Runtime Data needed for AI-assisted development.

Testing for JVM applications, Java, Kotlin, Spring Boot, often struggles to keep up with distributed systems, asynchronous flows, and frequent code changes. Traditional methods rely on mocks and black‑box checks that don't reflect how the system really behaves. The result: flaky tests, missed bugs, and uncertainty before release.

BitDive provides a single platform for the entire testing lifecycle. It captures real execution data, curates meaningful scenarios, replays them across builds, and validates results where it matters most, at the level of API responses, database queries, and messaging flows.

JVM-first • Kafka/gRPC/JDBC support • CI/CD friendly • Flake-resistant • Zero infrastructure

The ROI of Trace-Based Verification​