Kiali vs Prometheus: What are the differences?

Introduction Kiali and Prometheus are two popular observability tools used in monitoring and managing applications. While both tools serve the same general purpose of monitoring, there are several key differences that set them apart. This article will highlight and explain the major differences between Kiali and Prometheus.

1. Data Collection and Metrics: Kiali is primarily designed to be used with Istio, a service mesh, and it collects metrics specifically related to Istio components and services. Kiali provides detailed insights into the health and performance of microservices within an Istio network. On the other hand, Prometheus is a general-purpose monitoring tool that can be used with a wide range of systems. It collects metrics using an HTTP pull model, allowing it to scrape and monitor various endpoints directly.

2. Data Storage and Querying: Kiali uses a time-series database called Jaeger, which is optimized for high-velocity data ingestion and query performance. It allows users to query and visualize Istio-related metrics efficiently. In contrast, Prometheus stores data in its custom time-series database called TSDB. It offers advanced querying capabilities, including PromQL, a powerful query language that allows for complex analysis and aggregation of metrics.

3. Alerting and Notification: Prometheus provides built-in alerting functionalities, allowing users to set up rules and thresholds for different metrics. It can send notifications through multiple channels, such as emails, Slack, or PagerDuty. Kiali, on the other hand, does not have native alerting capabilities. Users need to integrate Kiali with other alerting systems, such as Prometheus Alertmanager or third-party tools, to enable alerting and notification features.

4. Visualization and UI: Kiali offers a user-friendly web interface that provides graphical representations of the Istio service mesh, including the topology of services, traffic flows, and components. It allows users to visualize and navigate through the service mesh architecture easily. Prometheus, although it has a built-in UI called Prometheus Expression Browser, lacks a comprehensive graphical interface for visualizing metrics. Users typically rely on third-party tools, such as Grafana, to create dashboards and visualize Prometheus data.

5. Adoption and Ecosystem: Prometheus has a broader adoption and a more extensive ecosystem compared to Kiali. It is widely used in the Kubernetes community and has become the de facto standard for monitoring microservices. Prometheus has an active community, offering numerous integrations, plugins, and exporters. Kiali, being more specific to Istio and service mesh monitoring, has a smaller user base and a less extensive ecosystem in terms of integrations and third-party support.

6. Scalability and Performance: Both Kiali and Prometheus are scalable and performant tools, but there are some differences in their scaling capabilities. Kiali's scalability is mainly tied to the scale of the Istio service mesh it is monitoring. As the number of microservices and network traffic increases, additional Kiali instances may be required to handle the load. Prometheus, on the other hand, can scale horizontally by deploying multiple instances and using federation and sharding techniques to distribute the load across them.

In Summary, Kiali and Prometheus differ in terms of data collection, storage, querying, alerting, visualization, adoption, and scalability. While Kiali focuses on specifically monitoring Istio service mesh, Prometheus is a more general-purpose monitoring tool with a broader adoption and ecosystem.