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Glossary

Observability Tools

Observability tools are software solutions designed to monitor, analyze, and provide insights into the performance, health, and behavior of systems and applications.

What are Observability Tools?

Observability tools are software solutions designed to provide visibility into the performance, health, and behavior of systems and applications. These tools collect, analyze, and present data, helping organizations to understand and manage complex software environments. 

1. Metrics

Numeric measurements that provide quantitative data about the performance and behavior of a system. Examples include CPU usage, memory usage, and response times.

2. Logs

Text-based records generated by applications and systems, capturing events, errors, and informational messages. Logs are crucial for troubleshooting and debugging.

3. Traces

A sequence of events or transactions that follow a request as it traverses through different components of a distributed system. Tracing helps identify bottlenecks and performance issues.

4. Monitoring

The continuous process of observing a system’s metrics, logs, and traces to detect and respond to anomalies, errors, or performance issues.

5. Alerting

A mechanism that notifies operators or administrators when predefined thresholds or conditions are met. Alerts help teams respond promptly to potential issues.

6. Dashboards

Visual representations of key metrics and performance indicators, providing a real-time overview of a system’s health and status.

7. APM (Application Performance Monitoring)

A subset of observability tools that specifically focuses on monitoring and optimizing the performance of software applications.

8. Distributed Tracing

The practice of tracing and monitoring requests as they travel through different components and services in a distributed system.

9. Log Aggregation

The process of collecting and consolidating log data from multiple sources into a centralized location for easier analysis and troubleshooting.

10. Anomaly Detection

The identification of unusual patterns or deviations from normal behavior in the data, helping to proactively address potential issues.

11. Incident Response

The coordinated process of identifying, managing, and resolving incidents or disruptions in a system’s normal operation.

12. Telemetry

The collection and transmission of data from various components within a system, including metrics, logs, and traces.

13. OpenTelemetry

An open-source project that provides a set of APIs, libraries, agents, instrumentation, and instrumentation standards for observability in software.

14. Agent

A software component installed on servers or within applications to collect and transmit observability data to a central monitoring system.

15. Data Retention

The duration for which observability data is stored and maintained for analysis and historical reference.

Switch It On With Split

The Split Feature Data Platform™ gives you the confidence to move fast without breaking things. Set up feature flags and safely deploy to production, controlling who sees which features and when. Connect every flag to contextual data, so you can know if your features are making things better or worse and act without hesitation. Effortlessly conduct feature experiments like A/B tests without slowing down. Whether you’re looking to increase your releases, to decrease your MTTR, or to ignite your dev team without burning them out–Split is both a feature management platform and partnership to revolutionize the way the work gets done. Schedule a demo or explore our feature flag solution at your own pace to learn more.

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