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* Add Java SDK reference files (11 files) Create complete Java reference documentation covering: - java.md: Entry point with quick start tutorial, key concepts - patterns.md: 17 patterns (signals, queries, updates, child workflows, saga, cancellation scopes, heartbeating, etc.) - determinism.md: Safe alternatives table, forbidden operations - determinism-protection.md: Convention-based enforcement (no sandbox) - error-handling.md: ApplicationFailure, retry/timeout config - gotchas.md: Non-deterministic operations, cancellation, heartbeating - testing.md: TestWorkflowEnvironment, Mockito mocking, replay testing - versioning.md: Workflow.getVersion(), worker versioning - data-handling.md: Jackson, PayloadConverter, encryption, search attributes - observability.md: SLF4J logging, Micrometer metrics - advanced-features.md: Schedules, async completion, worker tuning Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Fix Java alignment issues from self-review - Reduce gotchas.md Non-Deterministic Operations from ~94 lines to ~12 (reference determinism.md instead of duplicating) - Remove Workflow Failure Exception Types duplication from error-handling.md (keep only in advanced-features.md) - Expand versioning.md Worker Versioning with Key Concepts, PINNED vs AUTO_UPGRADE, Deployment Strategies subsections - Fix section names to match Python reference style: Activity Heartbeat Details, Handling Activity Errors, Retry Policy Configuration, Workflow Test Environment, Mocking Activities, Workflow Replay Testing - Reduce data-handling.md Payload Encryption verbosity - Reduce observability.md Logger Customization verbosity - Reduce testing.md to single approach per section - Rename determinism.md "Convention-Based Enforcement" to "SDK Protection" - Fix handler guidance in patterns.md to match Python Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Fix correctness issues in Java reference files - patterns.md: Fix Queries section — ActivityStub → typed interface (Workflow.newActivityStub returns the typed interface, not ActivityStub) - data-handling.md: Add missing ProtobufPayloadConverter to default converter chain (4th of 5 converters) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Add Java to SKILL.md and core/determinism.md - SKILL.md: Add "Temporal Java" trigger phrase, update Overview to list Java, add Java entry to Getting Started references - core/determinism.md: Add Java entry to SDK Protection Mechanisms (no sandbox, convention-based, NonDeterministicException at replay) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Apply manual editorial fixes to Java references - java.md: Remove "Understanding Replay" section (covered by Overview), simplify File Organization note (no sandbox rationale) - gotchas.md: Move Heartbeating before Cancellation, make Wrong Retry Classification brief with reference (not inline examples) - error-handling.md: Remove editorializing from Workflow Failure note - determinism-protection.md: Remove cross-language comparison paragraph (state Java's approach on its own terms) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Add temporal-workflowcheck static analysis to Java determinism docs - determinism-protection.md: Add "Static Analysis with temporal-workflowcheck" section with Gradle/Maven setup, manual run, and suppression instructions. Beta warning included. - determinism.md: Update overview and SDK Protection to reference workflowcheck - core/determinism.md: Update Java entry in SDK Protection Mechanisms Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Integrate feedback from Go PR into Java patterns - Updates: Add validator note — validators must not mutate state or block (matches note added to Python, TypeScript, Go, and core) - Saga Pattern: Use Workflow.newDetachedCancellationScope() for compensations so they execute even if the workflow is cancelled (mirrors Go's workflow.NewDisconnectedContext pattern) Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com> * docs: add @WorkflowInit description to java.md Key Concepts Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * mark java as supported * Apply suggestions from code review Co-authored-by: Brian Strauch <brian@brianstrauch.com> * strongly recommend java 21+ * Softened stance on static checker and replay testing. * address python/typescript sandboxing comment --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: Brian Strauch <brian.strauch@temporal.io> Co-authored-by: Brian Strauch <brian@brianstrauch.com>
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Java SDK Observability
Overview
The Java SDK provides observability through replay-safe logging, Micrometer-based metrics, and visibility (Search Attributes).
Logging
Workflow Logging (Replay-Safe)
Use Workflow.getLogger() for replay-safe logging that suppresses duplicate messages during replay:
public class OrderWorkflowImpl implements OrderWorkflow {
private static final Logger logger = Workflow.getLogger(OrderWorkflowImpl.class);
@Override
public String run(Order order) {
logger.info("Workflow started for order {}", order.getId());
String result = Workflow.newActivityStub(OrderActivities.class,
ActivityOptions.newBuilder()
.setStartToCloseTimeout(Duration.ofMinutes(5))
.build()
).processOrder(order);
logger.info("Activity completed with result {}", result);
return result;
}
}
The workflow logger automatically:
- Suppresses duplicate logs during replay
- Includes workflow context (workflow ID, run ID, etc.)
- Uses SLF4J under the hood
Activity Logging
Use standard SLF4J loggers in activities. Activity context is available via Activity.getExecutionContext():
public class OrderActivitiesImpl implements OrderActivities {
private static final Logger logger =
LoggerFactory.getLogger(OrderActivitiesImpl.class);
@Override
public String processOrder(Order order) {
logger.info("Processing order {}", order.getId());
// Access activity context for metadata
ActivityExecutionContext ctx = Activity.getExecutionContext();
logger.info("Activity ID: {}, attempt: {}",
ctx.getInfo().getActivityId(),
ctx.getInfo().getAttempt());
// Perform work...
logger.info("Order processed successfully");
return "completed";
}
}
Customizing the Logger
The Java SDK uses SLF4J. Configure your preferred backend:
Logback (logback.xml)
<configuration>
<appender name="STDOUT" class="ch.qos.logback.core.ConsoleAppender">
<encoder>
<pattern>%d{HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n</pattern>
</encoder>
</appender>
<!-- Suppress noisy Temporal internals -->
<logger name="io.temporal.internal" level="WARN"/>
<root level="INFO">
<appender-ref ref="STDOUT"/>
</root>
</configuration>
Log4j2 is also supported as an SLF4J backend with equivalent configuration.
Metrics
Micrometer with Prometheus
The Java SDK uses Micrometer for metrics collection. Configure with MicrometerClientStatsReporter:
import io.micrometer.prometheus.PrometheusConfig;
import io.micrometer.prometheus.PrometheusMeterRegistry;
import io.temporal.common.reporter.MicrometerClientStatsReporter;
import com.uber.m3.tally.RootScopeBuilder;
import com.uber.m3.tally.Scope;
import com.uber.m3.util.Duration;
// Set up Prometheus registry
PrometheusMeterRegistry registry = new PrometheusMeterRegistry(PrometheusConfig.DEFAULT);
// Create the Temporal metrics scope
Scope scope = new RootScopeBuilder()
.reporter(new MicrometerClientStatsReporter(registry))
.reportEvery(Duration.ofSeconds(10));
// Apply to service stubs
WorkflowServiceStubs service = WorkflowServiceStubs.newServiceStubs(
WorkflowServiceStubsOptions.newBuilder()
.setMetricsScope(scope)
.build()
);
// Expose Prometheus endpoint (e.g., via HTTP server)
// registry.scrape() returns the metrics in Prometheus format
Key SDK Metrics
temporal_request— Client requests to servertemporal_workflow_task_execution_latency— Workflow task processing timetemporal_activity_execution_latency— Activity execution timetemporal_workflow_task_replay_latency— Replay duration
Best Practices
- Use
Workflow.getLogger()in workflows, standard SLF4J loggers in activities - Do not use
System.out.println()in workflows — it produces duplicate output on replay - Configure Micrometer metrics for production monitoring
- Use Search Attributes for business-level visibility — see
references/java/data-handling.md