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Graylog vs Kibana vs Sentry: What are the differences?
Introduction:
In the world of log management and analytics, Graylog, Kibana, and Sentry are three popular tools used by developers and system administrators. While all three tools serve the purpose of monitoring and analyzing logs, there are key differences that set them apart.
1. Key Difference: Integration and Data Sources Graylog is known for its wide range of integrations and supports various data sources such as syslog, SNMP, GELF, and more. It provides flexible options for collecting and processing logs from multiple systems and applications.
On the other hand, Kibana primarily works with Elasticsearch as its data source. It is tightly integrated with Elasticsearch, and users can leverage its powerful querying and filtering capabilities. Kibana also offers integration with Beats for log collection.
Sentry, in contrast, is mainly focused on tracking and monitoring errors in software applications. It collects data directly from the application code rather than relying on external log sources.
2. Key Difference: User Interface and Visualization Graylog provides a user-friendly interface with various visualization options to analyze logs effectively. It offers dashboards, custom widgets, and search capabilities to explore log data efficiently. Users can visualize data using charts, graphs, and heatmaps.
Kibana, being part of the Elastic Stack, provides a robust and feature-rich interface for log analytics. It offers powerful visualization tools like graphs, maps, and time series visualizations. Kibana allows users to build complex dashboards and create customized visualizations.
Sentry focuses more on error tracking rather than log analysis, so its user interface is primarily designed for error monitoring and debugging, with features like issue tracking, error stack traces, and error frequency analysis.
3. Key Difference: Alerting and Notification Graylog offers built-in alerting functionality where users can define conditions based on log events and receive notifications via various channels such as email, Slack, PagerDuty, etc. It provides flexibility in creating complex alert rules and actions.
Kibana, on the other hand, does not have native alerting capabilities. Users need to leverage other tools or Elastic's X-Pack plugin to enable alerting functionality in their Kibana and Elasticsearch stack.
Sentry provides alerting and notification features specifically for error tracking and monitoring. Users can define rules to trigger alerts based on error patterns and receive notifications via email, chat platforms, or SMS.
4. Key Difference: Logs vs. Errors Graylog and Kibana primarily focus on log management and analysis, covering a broader scope of system logs, application logs, and other log sources. They provide a centralized platform for log aggregation, search, and analysis.
However, Sentry is specifically designed for error tracking and monitoring in software applications. It excels in identifying and resolving errors, collecting stack traces, and providing real-time error notifications.
5. Key Difference: Scalability Graylog is known for its distributed architecture, allowing horizontal scalability by adding more nodes to handle larger log volumes. It can efficiently handle high log inflow and storage requirements.
Kibana, being part of the Elastic Stack, also offers scalability options. It can scale horizontally by adding more Elasticsearch nodes to handle larger log volumes and concurrent users.
Sentry, being more focused on error tracking and monitoring, may not have the same scalability as Graylog or Kibana in terms of handling large log volumes. However, it provides adequate scalability for error monitoring in medium to large-scale applications.
6. Key Difference: Community and Ecosystem Graylog and Kibana have a strong community and extensive ecosystem support. They have active developer communities, plugins/extensions, and integrations with a wide range of tools and platforms. This allows users to customize and extend the functionality of these tools according to their specific needs.
Sentry also has a growing community and ecosystem support. It provides integrations with popular programming languages and frameworks, making it easier to integrate error tracking into different applications.
In Summary, Graylog stands out with its wide range of integrations and flexible log collection capabilities, while Kibana offers powerful visualization tools and seamless integration with Elasticsearch. Sentry focuses on error tracking and monitoring, providing targeted features for resolving software errors.
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.
I essentially inherited a Shopify theme that was originally created by an agency. After discovering a number of errors being thrown in the Dev Console just by scrolling through the website, I needed more visibility over any errors happening in the field. Having used both Sentry and TrackJS, I always got lost in the TrackJS interface, so I felt more comfortable introducing Sentry. The Sentry free tier is also very generous, although it turns out the theme threw over 15k errors in less than a week.
I highly recommend setting up error tracking from day one. Theoretically, you should never need to upgrade from the free tier if you're keeping on top of the errors...
Pros of Graylog
- Open source19
- Powerfull13
- Well documented8
- Alerts6
- User authentification5
- Flexibel query and parsing language5
- Alerts and dashboards3
- User management3
- Easy query language and english parsing3
- Easy to install2
- Manage users and permissions1
- A large community1
- Free Version1
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 Sentry
- Consolidates similar errors and makes resolution easy238
- Email Notifications121
- Open source108
- Slack integration84
- Github integration71
- Easy49
- User-friendly interface44
- The most important tool we use in production28
- Hipchat integration18
- Heroku Integration17
- Good documentation15
- Free tier14
- Self-hosted11
- Easy setup9
- Realiable7
- Provides context, and great stack trace6
- Feedback form on error pages4
- Love it baby4
- Gitlab integration3
- Filter by custom tags3
- Super user friendly3
- Captures local variables at each frame in backtraces3
- Easy Integration3
- Performance measurements1
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Cons of Graylog
- Does not handle frozen indices at all1
Cons of Kibana
- Unintuituve7
- Works on top of elastic only4
- Elasticsearch is huge4
- Hardweight UI3
Cons of Sentry
- Confusing UI12
- Bundle size4