Gain complete visibility into your PHP logs with real-time monitoring and advanced error tracking to optimize PHP performance and minimize downtime.
Capture and parse PHP fatal errors, warnings, deprecation notices, and exceptions from error_log, Monolog channels, and framework-specific handlers. Correlate log events with request traces for complete failure context.
Automatically structure Laravel channel logs, Symfony messenger queues, and WordPress debug output. Extract context like Eloquent queries, middleware execution, and Composer dependency failures from native PHP formats.
Track logs through complete PHP execution flow—from nginx/Apache access, PHP-FPM pool processing, application bootstrap, to response generation. Identify bottlenecks in slow database queries or heavy ORM operations.
Monitor PHP memory_limit violations, execution time exceeded errors, and max_input_vars overflows. Surface slow Composer autoloads and circular references causing production OOM conditions.
Capture Guzzle HTTP client errors, Redis connection timeouts, MySQL deadlocks, and Elasticsearch indexing failures logged by PHP applications. Link external dependency issues to specific application code paths.
Connect unstructured PHP logs directly to source code lines, PHPUnit test failures, and Artisan command outputs. Navigate from log events to exact controller methods, service classes, or trait implementations.
Detect PHP ini setting mismatches between environments, unsafe opcache configurations, and disabled error reporting that hide production issues from development logs.
Monitor worker process crashes, slow request queues, pm.max_children exhaustion, and status page metrics alongside application logs for complete PHP execution visibility.
Atatus understands Laravel, Symfony, Monolog, and PHP-FPM logs out of the box with zero setup complexity.
Atatus structures PHP logs automatically to surface errors and exceptions in real time.
Atatus correlates application errors with worker performance and system metrics instantly.
Atatus collects logs reliably at scale without impacting application performance.
Atatus enables fast querying across stack traces, messages, and custom fields.
Atatus keeps production, staging, and multi-tenant logs cleanly isolated.
Atatus uses intelligent retention to control storage while preserving critical logs.
Atatus adapts to how engineering teams work across development, operations, and reliability.
Debug errors and slow paths with the full context of what happened.
Atatus for developersTrack deployments and see how each release affects stability.
Atatus for DevOpsWatch latency and error rates to ship with less production risk.
Atatus for release engineersPricing, deployment, data and the agent. If something is missing, a person will answer it on a demo call.
PHP Logs Monitoring in Atatus is a comprehensive solution that allows users to track, analyze, and troubleshoot logs generated by PHP applications. It provides real-time visibility into log data, helping to identify issues, improve performance, and ensure the health of your PHP applications.
Atatus's PHP Logs Monitoring integrates seamlessly with your PHP 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, PHP 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, PHP Logs Monitoring seamlessly integrates with other Atatus products, such as APM (Application Performance Monitoring). This integration allows for a holistic view of your PHP 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 PHP 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 PHP 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.
