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Kibana vs Sysdig: What are the differences?
Kibana vs. Sysdig:
<Write Introduction here>
1. **Data Sources**: Kibana primarily uses Elasticsearch as its data source, whereas Sysdig relies on its own agent and system instrumentation to collect data directly from the host and containers.
2. **User Interface**: Kibana offers a more visually appealing and user-friendly interface with features like dashboards, visualizations, and search capabilities, while Sysdig provides a more technical interface focused on monitoring and troubleshooting system performance.
3. **Focus**: Kibana is commonly used for log analysis and visualization, making it ideal for application monitoring and troubleshooting, whereas Sysdig is specifically designed for monitoring containerized environments, offering detailed insights into container performance and security.
4. **Alerting Capabilities**: Kibana supports alerting functionality through its Watcher feature, allowing users to set up conditions and actions based on data, while Sysdig offers more robust alerting capabilities, including out-of-the-box alerts for common issues in containerized environments.
5. **Integration**: Kibana integrates seamlessly with the entire Elastic Stack, including Elasticsearch, Logstash, and Beats, enabling comprehensive data analysis and visualization, whereas Sysdig can be integrated with various monitoring tools but does not have the same level of integration as Kibana.
6. **Community Support**: Kibana has a larger community of users, developers, and resources available for support and customization, making it easier to find solutions and best practices, while Sysdig's community is smaller but more focused on container monitoring and security.
In Summary, Kibana and Sysdig differ in terms of data sources, user interface, focus, alerting capabilities, integration options, and community support.
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.
The objective of this work was to develop a system to monitor the materials of a production line using IoT technology. Currently, the process of monitoring and replacing parts depends on manual services. For this, load cells, microcontroller, Broker MQTT, Telegraf, InfluxDB, and Grafana were used. It was implemented in a workflow that had the function of collecting sensor data, storing it in a database, and visualizing it in the form of weight and quantity. With these developed solutions, he hopes to contribute to the logistics area, in the replacement and control of materials.
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
Pros of Sysdig
- Powerful web app5
- Easy setup5
- Monitoring5
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Cons of Kibana
- Unintuituve7
- Works on top of elastic only4
- Elasticsearch is huge4
- Hardweight UI3
Cons of Sysdig
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