Companies competing in Application monitoring
| company | description | stage |
|---|---|---|
| Better Stack | Observability and log management. | private (series A) |
| Checkly | Code-based monitoring. | private (series B) |
| Datadog | Application monitoring, security and observability. | public (NASDAQ: DDOG) |
| Dynatrace | Infrastructure monitoring and security. | public (NYSE: DT) |
| Grafana Labs | Operational dashboards for data. | private (series D) |
| Highlight.io | Open source infrastructure monitoring. | private (seed) |
| Instabug | Mobile app testing and feedback. | private (series B) |
| Logz.io | Cloud observability platform. | private (series E) |
| New Relic | Application monitoring & infrastructure observability. | private (private equity) |
| Rollbar | Error monitoring and remediation. | private (series B) |
| Sleuth | Continuous delivery metrics and control software. | private (series A) |
What is application monitoring?
Application monitoring refers to the process of observing and analyzing the behavior and performance of software applications in order to detect and diagnose issues, improve performance, and optimize user experience. It involves collecting data from various sources, such as logs, metrics, traces, and user feedback, and using this data to gain insights into application performance, identify bottlenecks, and troubleshoot problems.
Some common features of application monitoring tools include:
- Performance metrics: Measurements of application performance, such as response time, throughput, and resource utilization.
- Error tracking: Detection and reporting of errors, exceptions, and failures within the application.
- Log analysis: Analysis of log data to identify issues, troubleshoot problems, and understand user behavior.
- User experience monitoring: Measurement of user satisfaction, such as response time, error rates, and user feedback.
- Traceability: Ability to trace requests and interactions across multiple services and systems.
- Real-time analytics: Real-time analysis of data to identify trends, patterns, and anomalies in application performance.
- Alerting and notifications: Automated alerts and notifications when certain thresholds are met or when issues are detected.
- Root cause analysis: Identification of the underlying causes of issues and problems.
- Capacity planning: Planning for future capacity requirements based on historical data and growth trends.
- Compliance monitoring: Monitoring of application performance and security to ensure compliance with regulatory requirements and industry standards.