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Alerta vs Kibana: What are the differences?
Introduction
Alerta and Kibana are two popular tools used in the field of monitoring and visualization of logs and events. While both are designed to handle large amounts of data and provide insights for troubleshooting and analysis, there are some key differences between them.
Alerta: Alerta is an open-source monitoring system that focuses on alert management and visualization. It provides a unified view of alerts from different monitoring tools and allows for easy integration with various notification channels. Alerta offers a flexible and customizable alert filtering and categorization system, allowing users to prioritize and take actions on the most critical alerts. It also supports the creation of custom plugins for extending its functionality.
Kibana: Kibana is an open-source data visualization tool that is part of the Elastic Stack. It is primarily used for exploring, analyzing, and visualizing data stored in Elasticsearch. Kibana provides a user-friendly interface for creating interactive dashboards, visualizations, and charts. It supports various data types and offers powerful querying and filtering capabilities. It also allows for the creation of alerts and notifications based on predefined conditions.
Integration: One major difference between Alerta and Kibana is their integration capabilities. Alerta is designed to integrate with multiple monitoring tools, allowing for the consolidation of alerts from various sources. On the other hand, Kibana is tightly integrated with Elasticsearch, which serves as the data source for visualization and analysis. While Kibana can ingest data from various sources, its primary focus is on Elasticsearch.
Focus: Alerta primarily focuses on alert management and visualization, providing a centralized platform for managing alerts from different sources. It offers features like alert deduplication, escalation, and suppression. On the other hand, Kibana focuses on data exploration, visualization, and analysis. It provides a wide range of tools and options for creating interactive visualizations and dashboards.
Customization: Alerta offers a high level of customization, allowing users to define their own alert rules, filters, and notification channels. It also provides an API for programmatic access and integration with external systems. Kibana, on the other hand, provides a more user-friendly and intuitive interface for visualization and analysis, but it may have limitations in terms of customization and flexibility.
Data Source: Another significant difference lies in their data sources. Alerta can receive alerts from various monitoring tools and systems, including Nagios, Zabbix, Prometheus, and more. It acts as a central aggregator and provides a unified view of all the alerts. Kibana, on the other hand, relies on Elasticsearch as its data source. It is designed to work specifically with Elasticsearch indices and does not have direct integration with other monitoring systems.
In summary, Alerta is a flexible and customizable alert management system with integration capabilities for multiple monitoring tools, while Kibana is a visualization tool tightly integrated with Elasticsearch, focusing on data exploration and analysis.
From a StackShare Community member: “We need better analytics & insights into our Elasticsearch cluster. Grafana, which ships with advanced support for Elasticsearch, looks great but isn’t officially supported/endorsed by Elastic. Kibana, on the other hand, is made and supported by Elastic. I’m wondering what people suggest in this situation."
For our Predictive Analytics platform, we have used both Grafana and Kibana
- Grafana based demo video: https://www.youtube.com/watch?v=tdTB2AcU4Sg
- Kibana based reporting screenshot: https://imgur.com/vuVvZKN
Kibana has predictions
and ML algorithms support, so if you need them, you may be better off with Kibana . The multi-variate analysis features it provide are very unique (not available in Grafana).
For everything else, definitely Grafana . Especially the number of supported data sources, and plugins clearly makes Grafana a winner (in just visualization and reporting sense). Creating your own plugin is also very easy. The top pros of Grafana (which it does better than Kibana ) are:
- Creating and organizing visualization panels
- Templating the panels on dashboards for repetetive tasks
- Realtime monitoring, filtering of charts based on conditions and variables
- Export / Import in JSON format (that allows you to version and save your dashboard as part of git)
I use both Kibana and Grafana on my workplace: Kibana for logging and Grafana for monitoring. Since you already work with Elasticsearch, I think Kibana is the safest choice in terms of ease of use and variety of messages it can manage, while Grafana has still (in my opinion) a strong link to metrics
After looking for a way to monitor or at least get a better overview of our infrastructure, we found out that Grafana (which I previously only used in ELK stacks) has a plugin available to fully integrate with Amazon CloudWatch . Which makes it way better for our use-case than the offer of the different competitors (most of them are even paid). There is also a CloudFlare plugin available, the platform we use to serve our DNS requests. Although we are a big fan of https://smashing.github.io/ (previously dashing), for now we are starting with Grafana .
I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.
Kibana should be sufficient in this architecture for decent analytics, if stronger metrics is needed then combine with Grafana. Datadog also offers nice overview but there's no need for it in this case unless you need more monitoring and alerting (and more technicalities).
@Kibana, of course, because @Grafana looks like amateur sort of solution, crammed with query builder grouping aggregates, but in essence, as recommended by CERN - KIbana is the corporate (startup vectored) decision.
Furthermore, @Kibana comes with complexity adhering ELK stack, whereas @InfluxDB + @Grafana & co. recently have become sophisticated development conglomerate instead of advancing towards a understandable installation step by step inheritance.
Pros of Alerta
Pros of Kibana
- Easy to setup88
- Free65
- Can search text45
- Has pie chart21
- X-axis is not restricted to timestamp13
- Easy queries and is a good way to view logs9
- Supports Plugins6
- Dev Tools4
- More "user-friendly"3
- Can build dashboards3
- Out-of-Box Dashboards/Analytics for Metrics/Heartbeat2
- Easy to drill-down2
- Up and running1
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Cons of Alerta
Cons of Kibana
- Unintuituve7
- Works on top of elastic only4
- Elasticsearch is huge4
- Hardweight UI3