Sentry

Track custom metrics alongside error and performance data for holistic application insights.

Track the rate of new errors to identify sudden spikes or regressions.

Build custom queries to search and filter events based on any attribute.

Automatically detect sudden increases in error rates or performance degradation.

Monitor server-side errors, exceptions, and performance in Python, Java, Node.js, and other backends.

Monitor scheduled jobs and background tasks to detect failures and performance issues.

Share insights, assign issues to team members, and collaborate on error resolution.

Automatic detection and aggregation of errors across your application with full stack traces.

Create personalized dashboards to visualize specific metrics and KPIs.

Centralized view of errors across multiple projects and teams.

Configure how long error data is retained to meet compliance and cost requirements.

Automatically adjust sampling rates based on transaction type and error likelihood to optimize data costs.

Filter and sample events to control costs and focus on critical errors.

Prevent certain errors from being reported based on URLs, error messages, or other criteria.

Track user actions and system events leading up to an error for better debugging context.

Attach screenshots, logs, and other files to error events for better context.

View network requests, responses, and console logs alongside session replays.

Upload source maps to map minified/compiled code back to original source for accurate error reporting.

Identify which commits likely introduced errors to speed up debugging.

Deploy Sentry on-premises for complete data control and compliance.

Separate and track errors across multiple environments like staging, development, and production.

Track JavaScript errors, resource loading issues, and user interactions in web applications.

REST and GraphQL APIs for programmatic access to error data and project management.

Create custom integrations with webhooks to send Sentry data to any external system.

Predict future error trends and potential system failures using machine learning.

AI-powered automatic grouping of similar errors to reduce noise and improve signal.

AI-powered suggestions for common fixes based on error patterns and best practices.

Monitor crashes and performance issues in iOS and Android applications.

Real-time monitoring of application error rates with alerting on threshold violations.

Configurable alerts sent to team members via email, Slack, or webhooks when issues are detected.

Monitor application performance metrics including transaction duration, throughput, and error rates.

Analyze CPU and memory usage patterns to identify performance bottlenecks in production.

Trace requests across distributed systems to identify where performance issues occur.

Monitor the health and adoption of releases with crash-free user sessions metrics.

Track errors and issues associated with specific application releases.

Track all administrative actions and changes for compliance and security auditing.

Role-based access control to manage team member permissions across projects.

Single sign-on support for enterprise authentication via SAML, OAuth, and other protocols.

Replay user sessions to understand the context behind errors and crashes.

Collect user feedback when errors occur to understand impact and improve support.

Triage, assign, and resolve issues with workflow management and custom status tracking.

View complete history of issue state changes, comments, and activities.