Java Logs Monitoring & Observability
Effortlessly track Java logs, gaining instant insights into errors and refining logging for a more efficient and reliable application.
Monitor Java app logs across Spring Boot, Quarkus, and production servers
Collect all Java logs in one place
Collect Logback, Log4j2, and standard Java logging output emitted by Spring Boot applications, Hibernate operations, and reactive components into a centralized log view.
Parse structured log data
Parse JSON-formatted logs, MDC fields, and SLF4J markers to extract contextual attributes such as request identifiers and application-specific metadata.
Track Spring transactions end-to-end
Correlate logs generated across Spring-managed transactions, JPA operations, and Spring Security flows to help investigate slow queries and transactional delays.
Catch memory and GC problems
Ingest JVM garbage collection logs and error output to identify GC pauses, memory pressure, and OutOfMemoryError events when GC logging is enabled.
Keep distributed trace context
Preserve trace and request correlation identifiers propagated via OpenTelemetry or custom MDC fields across asynchronous execution, messaging, and remote service calls.
Link logs to source code
Map production stack traces to Java class and method names to help locate the originating @RestController, @Service, or application component.
Monitor dependency issues
Capture startup and runtime logs that reveal dependency conflicts, incompatible Spring Boot versions, or missing logging bindings during application initialization.
Debug reactive streams
Collect logs emitted by Project Reactor and RxJava pipelines to analyze reactive execution errors and request flow interruptions.
Get Actionable Insights From Your Java Application Logs in Atatus
Centralize and analyze your Java logs in real time so you can structure, filter, and correlate log data for faster troubleshooting and clearer visibility.
Raw Logs Lack Structure
Unstructured Java log lines make it hard to detect meaningful patterns, and parsing them into fields turns free text into searchable, actionable data.
Full-Text Search Across Logs Is Slow
Manually grepping log files is inefficient, and centralized search enables instant discovery by timestamp, field, or custom criteria.
Important Signals Get Lost in Volume
High log volume can bury critical events, and custom filters with pipelines help isolate what matters most to application behavior.
Context Switching Slows Debugging
Jumping between logs and other tools breaks investigation flow, and saved views keep relevant filters ready for focused debugging.
Correlate Logs With Performance Metrics
Logs alone provide limited insight, and correlating log entries with request or transaction data adds valuable troubleshooting context.
Why Choose Atatus for Java Logs Monitoring?
Simple Java log collection with Spring Boot support and production-ready monitoring
Works with Spring Boot out-of-the-box
Automatically collects application logs from Spring Boot services without requiring changes to logback-spring.xml configuration.
Shows thread activity together
View logs from thread pools and asynchronous tasks on a unified timeline using thread identifiers and timestamps for better execution tracing.
Safe async log delivery
Uses buffered asynchronous delivery with retry handling to reduce log loss during Kafka or RabbitMQ network interruptions.
Analyzes garbage collection logs
Ingest and correlate JVM garbage collection logs with application logs to help analyze memory behavior when GC logging is enabled.
Works across Kubernetes pods
Aggregates logs from Spring Boot containers running across multiple Kubernetes pods for centralized visibility.
Secure long-term log storage
Stores audit and application logs securely with configurable retention controls to support compliance requirements.
Unified Observability for Every Engineering Team
Atatus adapts to how engineering teams work across development, operations, and reliability.
Developers
Trace requests, debug errors, and identify performance issues at the code level with clear context.
DevOps
Track deployments, monitor infrastructure impact, and understand how releases affect application stability.
Release Engineer
Measure service health, latency, and error rates to maintain reliability and reduce production risk.
Unified Logs Monitoring & Observability Across Different Platforms
Frequently Asked Questions
Find answers to common questions about our platform