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Kapacitor vs Prometheus: What are the differences?
Differences Between Kapacitor and Prometheus
Kapacitor and Prometheus are both popular open-source systems used for monitoring and alerting in a distributed environment. However, they differ in some key aspects.
Data Storage and Retrieval: Kapacitor serves as a processing engine that streams data from external systems, performs calculations or transformations on the data, and stores results in a separate database. In contrast, Prometheus directly stores collected data in its own time-series database, without the need for external storage.
Query Language: Kapacitor utilizes TICKscript, a domain-specific language, to define data processing tasks and alerts. On the other hand, Prometheus uses PromQL, a powerful query language specifically designed for querying and analyzing time-series data. PromQL offers a more expressive and flexible way to query and aggregate data.
Alerting and Notifications: Kapacitor provides more advanced alerting capabilities compared to Prometheus. It supports complex event processing, anomaly detection, and can integrate with various notification services to send alerts. Prometheus, while capable of basic alerting, relies on external tools like Alertmanager to handle more advanced alerting and notification functionalities.
Scalability and Federation: Both Kapacitor and Prometheus are designed to handle large-scale monitoring. However, Prometheus offers native support for federation, allowing multiple instances to be connected and form a federated cluster for scalability and redundancy. Kapacitor, on the other hand, can only scale vertically by increasing the resources of the host machine.
Data Source Support: Prometheus is primarily focused on metrics monitoring and has built-in support for collecting data from various popular data sources, including applications, databases, and infrastructure components. Kapacitor, on the other hand, is more flexible and can ingest data from a wider range of sources, including streams, logs, and databases.
Integration with Other Tools: Prometheus has excellent integration with the entire Prometheus ecosystem, including Grafana for visualization, Alertmanager for alert routing, and exporters for collecting metrics from different systems. Kapacitor, on the other hand, integrates well with the InfluxData TICK Stack, which includes InfluxDB for storage and Chronograf for visualization, but may require additional configuration for integrating with other monitoring tools.
In summary, while both Kapacitor and Prometheus are capable monitoring systems, they differ in terms of data storage and retrieval, query language, alerting capabilities, scalability, data source support, and integrations with other tools. Understanding these differences can help in choosing the right monitoring system based on specific requirements and use cases.
Looking for a tool which can be used for mainly dashboard purposes, but here are the main requirements:
- Must be able to get custom data from AS400,
- Able to display automation test results,
- System monitoring / Nginx API,
- Able to get data from 3rd parties DB.
Grafana is almost solving all the problems, except AS400 and no database to get automation test results.
You can look out for Prometheus Instrumentation (https://prometheus.io/docs/practices/instrumentation/) Client Library available in various languages https://prometheus.io/docs/instrumenting/clientlibs/ to create the custom metric you need for AS4000 and then Grafana can query the newly instrumented metric to show on the dashboard.
Hi, We have a situation, where we are using Prometheus to get system metrics from PCF (Pivotal Cloud Foundry) platform. We send that as time-series data to Cortex via a Prometheus server and built a dashboard using Grafana. There is another pipeline where we need to read metrics from a Linux server using Metricbeat, CPU, memory, and Disk. That will be sent to Elasticsearch and Grafana will pull and show the data in a dashboard.
Is it OK to use Metricbeat for Linux server or can we use Prometheus?
What is the difference in system metrics sent by Metricbeat and Prometheus node exporters?
Regards, Sunil.
If you're already using Prometheus for your system metrics, then it seems like standing up Elasticsearch just for Linux host monitoring is excessive. The node_exporter is probably sufficient if you'e looking for standard system metrics.
Another thing to consider is that Metricbeat / ELK use a push model for metrics delivery, whereas Prometheus pulls metrics from each node it is monitoring. Depending on how you manage your network security, opting for one solution over two may make things simpler.
Hi Sunil! Unfortunately, I don´t have much experience with Metricbeat so I can´t advise on the diffs with Prometheus...for Linux server, I encourage you to use Prometheus node exporter and for PCF, I would recommend using the instana tile (https://www.instana.com/supported-technologies/pivotal-cloud-foundry/). Let me know if you have further questions! Regards Jose
We're looking for a Monitoring and Logging tool. It has to support AWS (mostly 100% serverless, Lambdas, SNS, SQS, API GW, CloudFront, Autora, etc.), as well as Azure and GCP (for now mostly used as pure IaaS, with a lot of cognitive services, and mostly managed DB). Hopefully, something not as expensive as Datadog or New relic, as our SRE team could support the tool inhouse. At the moment, we primarily use CloudWatch for AWS and Pandora for most on-prem.
this is quite affordable and provides what you seem to be looking for. you can see a whole thing about the APM space here https://www.apmexperts.com/observability/ranking-the-observability-offerings/
I worked with Datadog at least one year and my position is that commercial tools like Datadog are the best option to consolidate and analyze your metrics. Obviously, if you can't pay the tool, the best free options are the mix of Prometheus with their Alert Manager and Grafana to visualize (that are complementary not substitutable). But I think that no use a good tool it's finally more expensive that use a not really good implementation of free tools and you will pay also to maintain its.
Pros of Kapacitor
Pros of Prometheus
- Powerful easy to use monitoring47
- Flexible query language38
- Dimensional data model32
- Alerts27
- Active and responsive community23
- Extensive integrations22
- Easy to setup19
- Beautiful Model and Query language12
- Easy to extend7
- Nice6
- Written in Go3
- Good for experimentation2
- Easy for monitoring1
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Cons of Kapacitor
Cons of Prometheus
- Just for metrics12
- Bad UI6
- Needs monitoring to access metrics endpoints6
- Not easy to configure and use4
- Supports only active agents3
- Written in Go2
- TLS is quite difficult to understand2
- Requires multiple applications and tools2
- Single point of failure1