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.
Java Logs Monitoring & Observability
Effortlessly track Java logs, gaining instant insights into errors and refining logging for a more efficient and reliable application.
Challenges
Monitor Java app logs across Spring Boot, Quarkus, and production servers
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.
JVM and Application Execution Logging
- Track log generation across application services, scheduled jobs, and transaction processing to understand execution behavior within the JVM environment.
- Correlate log entries with request context, service layers, and transaction flows to trace application execution paths.
- Identify execution failures during service initialization, dependency injection, and runtime processing affecting application stability.
- Detect disruptions in transaction handling, background processing, and service communication across Java workloads.
Exception and Stack Trace Diagnostics
- Capture Java exceptions, stack traces, and runtime errors generated across application components.
- Correlate exception logs with impacted services, endpoints, and deployment changes to identify failure sources.
- Identify recurring failures caused by configuration errors, dependency conflicts, and code-level regressions.
- Detect hidden runtime failures affecting transaction consistency and service reliability.
Thread, GC, and Performance Signals
- Analyze thread activity logs, garbage collection messages, and execution timing warnings affecting JVM performance.
- Correlate Java execution behavior with database latency, service calls, and infrastructure dependencies.
- Identify resource contention, thread blocking, and excessive logging impacting application performance.
- Detect performance degradation through abnormal GC activity, execution delays, and irregular runtime patterns.
Security and Access Monitoring
- Track authentication issues, authorization failures, and suspicious request activity captured in Java application logs.
- Identify abnormal behavior across services indicating misuse, access violations, or operational risks.
- Correlate application logs with infrastructure and network activity for incident investigation.
- Detect operational and security incidents affecting Java workloads through centralized log visibility.
Why Atatus
Why Choose Atatus for Java Logs Monitoring?
01
Spring Boot ready
Atatus automatically collects logs from Spring Boot applications without configuration changes.
02
Unified thread visibility
Atatus correlates thread pools and async task logs on a single timeline for clearer execution tracing.
03
Reliable async delivery
Atatus buffers and retries log forwarding to prevent data loss during network interruptions.
04
JVM memory insights
Atatus correlates garbage collection logs with application events to diagnose memory behavior.
05
Kubernetes-wide aggregation
Atatus centralizes logs across multiple pods and containers for complete visibility.
06
Secure log retention
Atatus stores application and audit logs securely with flexible retention controls.
Teams
Unified Observability for Every Engineering Team
Atatus adapts to how engineering teams work across development, operations, and reliability.
Developers
Debug errors and slow paths with the full context of what happened.
Atatus for developersDevOps
Track deployments and see how each release affects stability.
Atatus for DevOpsRelease engineers
Watch latency and error rates to ship with less production risk.
Atatus for release engineers
FAQ
Frequently Asked Questions
Pricing, deployment, data and the agent. If something is missing, a person will answer it on a demo call.
Java Logs Monitoring in Atatus is a comprehensive solution that allows users to track, analyze, and troubleshoot logs generated by Java applications. It provides real-time visibility into log data, helping to identify issues, improve performance, and ensure the health of your Java applications.
Atatus's Java Logs Monitoring integrates seamlessly with your Java applications, capturing log data and centralizing it for easy analysis. The solution offers powerful search and filter capabilities, making it simple to pinpoint specific events or issues within your logs. It also provides alerting features to notify you of critical events.
By offering real-time log streaming and advanced search capabilities, Java Logs Monitoring enables quicker issue identification and resolution. The ability to correlate logs with performance metrics provides a contextual understanding, streamlining the troubleshooting process.
Yes, Atatus provides powerful log filtering and searching capabilities. Users can filter logs based on specific criteria, such as log level, timestamp, or custom keywords. The search functionality allows for efficient navigation through large log datasets.
Yes, Java Logs Monitoring seamlessly integrates with other Atatus products, such as APM (Application Performance Monitoring). This integration allows for a holistic view of your Java applications, combining logs with performance metrics such as Distributed Traces to provide a comprehensive understanding of your application's health.
Log data parsing prioritizes customer security by meticulously anonymizing Personally Identifiable Information (PII) data. Sensitive fields can be completely excluded during the parsing process, ensuring the privacy and compliance of customer information.
In Java Logs Monitoring, log pipelines are customizable workflows that allow users to filter, parse, and fine-tune log data based on specific criteria.
Log pipelines can be customized by using diverse filters and defining custom parsing rules. Users have the flexibility to configure pipelines to meet their specific monitoring requirements, ensuring that log data is processed and organized according to their preferences.
Yes, log pipelines can be configured to filter log data based on various attributes such as log source, severity, timestamp, or any custom field. This customization allows users to focus on specific aspects of log data that are most relevant to their monitoring goals.
Saved Views in Java Logs Monitoring enable you to create and save custom configurations for different troubleshooting scenarios. This feature simplifies collaboration, allows for quick context switching, and automates repetitive tasks, significantly improving overall efficiency.
If you exceed your log ingestion limits, we would contact you to discuss on stopping further processing new log data or upgrade your subscription.
You can choose to store logs in Atatus for a limited time (e.g., 7 days) or export them to external storage solutions like Amazon S3 for long-term retention.
To access historical log data beyond the retention period, you can rely on log data exports from Amazon S3, where you can push the logs into Atatus for further analysis.
Yes, Atatus provides users with the flexibility to customize log retention settings. Users can adjust retention periods based on their specific needs, aligning with compliance standards or internal data management policies.