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Kibana vs Sentry: What are the differences?

Kibana and Sentry are both popular tools used for monitoring and analyzing software logs and errors. Here are the key differences between the two.

  1. Integration Capabilities: Kibana is a part of the ELK stack (Elasticsearch, Logstash, and Kibana) and is specifically designed to work with Elasticsearch. It provides a wide range of integration options with various systems and data sources. In contrast, Sentry is a standalone error monitoring platform that can integrate with different programming languages and frameworks.

  2. Real-time Monitoring vs. Exception Tracking: Kibana is primarily focused on real-time monitoring and log analysis. It enables users to visualize and analyze log data in real time, making it ideal for monitoring system performance and detecting anomalies. On the other hand, Sentry is mainly used for exception tracking and error reporting. It captures and aggregates application errors, providing detailed information about the root causes and allowing developers to fix them efficiently.

  3. Search and Query Capabilities: Kibana offers advanced search and query capabilities due to its integration with Elasticsearch. Users can perform complex queries, filter data, and create dashboards and visualizations based on the data stored in Elasticsearch. Sentry, though it provides some search capabilities, is more focused on providing detailed error information and stack traces rather than broader search functionality.

  4. Alerting and Notification: Kibana provides flexible alerting and notification options, allowing users to define conditions and thresholds for triggering alerts based on specific log events or metrics. It can send notifications via various channels like email, Slack, or PagerDuty. On the other hand, Sentry offers a comprehensive email notification system but provides limited options for defining custom alerts and integrating with external notification services.

  5. Data Retention and Scalability: Kibana, being a part of the ELK stack, can handle large volumes of data by leveraging the scalability and distributed nature of Elasticsearch. It allows users to configure data retention policies, balancing storage requirements with historical data analysis needs. Sentry, on the other hand, has a defined retention policy and offers storage options based on the selected plan. It includes a set retention period for error data and provides automatic data pruning after that period.

In summary, Kibana is an integration-focused tool designed for real-time log analysis, with strong search capabilities and flexible alerting options. On the other hand, Sentry is a specialized exception tracking platform that provides detailed error information, stack traces, and notifications but with limited custom alerting and search functionality.

Advice on Kibana and Sentry
Needs advice
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GrafanaGrafana
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KibanaKibana

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."

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Replies (7)
Recommends
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GrafanaGrafana
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For our Predictive Analytics platform, we have used both Grafana and Kibana

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)
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Recommends
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KibanaKibana

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

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Bram Verdonck
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GrafanaGrafana
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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 .

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Recommends
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KibanaKibana

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.

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Recommends
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KibanaKibana

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).

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GrafanaGrafana

I use Grafana because it is without a doubt the best way to visualize metrics

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Povilas Brilius
PHP Web Developer at GroundIn Software · | 0 upvotes · 604.4K views
Recommends
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@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.

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Decisions about Kibana and Sentry
Leonardo Henrique da Paixão
Junior QA Tester at SolarMarket · | 15 upvotes · 362.1K views

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.

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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...

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Pros of Kibana
Pros of Sentry
  • 88
    Easy to setup
  • 65
    Free
  • 45
    Can search text
  • 21
    Has pie chart
  • 13
    X-axis is not restricted to timestamp
  • 9
    Easy queries and is a good way to view logs
  • 6
    Supports Plugins
  • 4
    Dev Tools
  • 3
    More "user-friendly"
  • 3
    Can build dashboards
  • 2
    Out-of-Box Dashboards/Analytics for Metrics/Heartbeat
  • 2
    Easy to drill-down
  • 1
    Up and running
  • 237
    Consolidates similar errors and makes resolution easy
  • 121
    Email Notifications
  • 108
    Open source
  • 84
    Slack integration
  • 71
    Github integration
  • 49
    Easy
  • 44
    User-friendly interface
  • 28
    The most important tool we use in production
  • 18
    Hipchat integration
  • 17
    Heroku Integration
  • 15
    Good documentation
  • 14
    Free tier
  • 11
    Self-hosted
  • 9
    Easy setup
  • 7
    Realiable
  • 6
    Provides context, and great stack trace
  • 4
    Feedback form on error pages
  • 4
    Love it baby
  • 3
    Gitlab integration
  • 3
    Filter by custom tags
  • 3
    Super user friendly
  • 3
    Captures local variables at each frame in backtraces
  • 3
    Easy Integration
  • 1
    Performance measurements

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Cons of Kibana
Cons of Sentry
  • 6
    Unintuituve
  • 4
    Elasticsearch is huge
  • 3
    Hardweight UI
  • 3
    Works on top of elastic only
  • 12
    Confusing UI
  • 4
    Bundle size

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What is Kibana?

Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.

What is Sentry?

Sentry’s Application Monitoring platform helps developers see performance issues, fix errors faster, and optimize their code health.

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What are some alternatives to Kibana and Sentry?
Datadog
Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!
Grafana
Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.
Loggly
It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.
Graylog
Centralize and aggregate all your log files for 100% visibility. Use our powerful query language to search through terabytes of log data to discover and analyze important information.
Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
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