What problem does it solve?
This Skill eliminates the complex, time-consuming work of manually instrumenting Java applications to send observability data (traces, logs, metrics) to Maple's OpenTelemetry-based backend, removing the need for extensive custom code for standard framework instrumentation.
Core Features & Use Cases
- Zero-code auto-instrumentation: Uses the OpenTelemetry Java Agent to automatically instrument common Java frameworks including Spring Boot, JDBC, Kafka, and gRPC with no application code changes required.
- Manual SDK implementation: Provides guidance for edge cases where the agent cannot run, such as GraalVM native images or sealed module paths, with full control over span creation and configuration.
- Log context bridging: Configures existing Logback/SLF4J logging setups to carry trace and span context, so logs are correlated with traces in Maple.
- Use Case: A Java backend team running an orders API can deploy the OpenTelemetry Java Agent with inline Maple endpoint and ingest key configuration to start sending full observability data to Maple in minutes, or use manual instrumentation to add custom business spans for order submission workflows.
Quick Start
Use the maple-java-style skill to configure your Java application to send OpenTelemetry traces, logs, and metrics to your Maple ingest endpoint using either the zero-code Java agent or manual SDK setup based on your runtime requirements.
