Jaeger vs Kiali: What are the differences?

## Key Differences between Jaeger and Kiali

1. **Data Collection and Analysis**: Jaeger is primarily focused on distributed tracing, providing deep visibility into end-to-end transactions and their latency across microservices. It collects and analyzes trace data to provide insights into system behavior, performance optimizations, and latency tracking. Kiali, on the other hand, is a management console for Istio, a popular service mesh framework. Kiali provides a comprehensive view of the service mesh topology, health, and metrics, enabling administrators to visualize and monitor the status of services and their interactions.
2. **Scope**: Jaeger focuses on tracing individual requests and tracking their progress through different microservices. It captures and records traces, spans, and tags for analysis and troubleshooting. Kiali, on the other hand, provides a broader scope by visualizing the entire service mesh, including service dependencies, traffic flows, and ingress and egress points. It offers insights into the overall health and performance of the service mesh environment.
3. **User Interface and Visualization**: Jaeger provides a user-friendly interface for visualizing and exploring trace data, allowing users to view individual traces, analyze latency, and identify bottlenecks. It offers tools for searching traces and filtering data based on different criteria. Kiali, on the other hand, offers a comprehensive graphical user interface (GUI) that provides visualizations of the service mesh topology, traffic flows, and request/response rates. It allows users to understand the relationships between services and identify potential issues in the mesh.
4. **Integration**: Jaeger can integrate with various frameworks, libraries, and platforms to collect trace data. It has integrations with popular observability tools, service mesh frameworks, and cloud platforms. Kiali, on the other hand, is specifically designed for Istio and integrates seamlessly with Istio's control plane components. It relies on the data collected by Istio's sidecars and envoy proxies to generate its visualizations and insights.
5. **Alerting and Notifications**: Jaeger does not offer built-in alerting and notification features. However, it can be integrated with external monitoring and alerting tools to provide alerts based on specific metrics or conditions. Kiali, on the other hand, offers built-in alerting capabilities that allow administrators to define rules and notifications based on various metrics, such as error rates, latency thresholds, or service health. It provides proactive monitoring and notification of issues within the service mesh.
6. **Deployment and Scalability**: Jaeger can be deployed as a standalone service or in a distributed architecture. It supports scalability through its ability to distribute trace collection and storage across multiple instances. Kiali, on the other hand, is typically deployed as part of the Istio control plane and scales along with the service mesh. It leverages Istio's scalability features to handle the increasing complexity and volume of data in large-scale deployments.

In summary, Jaeger is a distributed tracing system focused on analyzing individual request traces to optimize system performance, while Kiali is a management console for Istio that provides visualizations and monitoring of service mesh topology and metrics.