Find out what your peers are saying about Datadog, Dynatrace, Splunk and others in Application Performance Monitoring (APM) and Observability.
Product | Market Share (%) |
---|---|
Sentry | 5.8% |
Apache SkyWalking | 0.8% |
Other | 93.4% |
Company Size | Count |
---|---|
Small Business | 7 |
Midsize Enterprise | 3 |
Large Enterprise | 3 |
Apache SkyWalking is a versatile open-source tool used for monitoring and analyzing the performance and behavior of applications in distributed systems. It enables tracking requests, identifying bottlenecks, and troubleshooting issues in real-time, while also monitoring microservices, logs, and server metrics.
With its comprehensive monitoring capabilities, flexible architecture, and powerful visualization tools, Apache SkyWalking provides actionable insights and enhances overall application performance.
Its user-friendly interface and intuitive dashboards make it easy to understand and analyze complex data sets.
Sentry is a robust error management system known for real-time error tracking and integration with tools like Slack, GitLab, and Jira, benefiting those seeking comprehensive application performance insights.
Sentry offers a seamless platform to monitor errors in both front-end and back-end applications, providing real-time alerts and comprehensive event log context. With its integration capabilities, teams effectively track application metrics and access performance data without direct production access, ensuring enhanced reliability. Sentry's features such as event grouping and code trace logs linked to Git repositories highlight its utility in maintaining application efficiency. Enhanced security and regular updates make it a preferred choice over competitors. Despite some requests for improvements in automation and UI enhancements, Sentry remains invaluable for error management and application performance monitoring.
What are the key features of Sentry?In industries like technology, Sentry is crucial for monitoring errors in web applications, offering real-time alerts and performance tracking. It is frequently used in ETL processes to detect failures without direct developer access, benefiting teams who manage large-scale applications and databases efficiently.
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