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Kibana
Kibana

5.4K
3.9K
+ 1
235
Sensu
Sensu

150
135
+ 1
54
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Kibana vs Sensu: What are the differences?

Developers describe Kibana as "Explore & Visualize Your Data". 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. On the other hand, Sensu is detailed as "Open source monitoring framework". A monitoring framework that aims to be simple, malleable, and scalable. Essentially, Sensu takes the results of “check” scripts run across many systems, and if certain conditions are met; passes their information to one or more “handlers”. Checks are used, for example, to determine if a service like Apache is up or down.

Kibana and Sensu can be categorized as "Monitoring" tools.

Some of the features offered by Kibana are:

  • Flexible analytics and visualization platform
  • Real-time summary and charting of streaming data
  • Intuitive interface for a variety of users

On the other hand, Sensu provides the following key features:

  • Execute service checks
  • Send notifications
  • Collect metrics

"Easy to setup" is the top reason why over 76 developers like Kibana, while over 11 developers mention "Support for almost anything" as the leading cause for choosing Sensu.

Kibana and Sensu are both open source tools. It seems that Kibana with 12.4K GitHub stars and 4.8K forks on GitHub has more adoption than Sensu with 2.96K GitHub stars and 389 GitHub forks.

According to the StackShare community, Kibana has a broader approval, being mentioned in 907 company stacks & 479 developers stacks; compared to Sensu, which is listed in 33 company stacks and 7 developer stacks.

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 Sensu?

Sensu is the future-proof solution for multi-cloud monitoring at scale. The Sensu monitoring event pipeline empowers businesses to automate their monitoring workflows and gain deep visibility into their multi-cloud environments.
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    What are some alternatives to Kibana and Sensu?
    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
    The world's most popular cloud-based log management service delivers application intelligence.
    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
    Splunk Inc. provides the leading platform for Operational Intelligence. Customers use Splunk to search, monitor, analyze and visualize machine data.
    Prometheus
    Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.
    See all alternatives
    Decisions about Kibana and Sensu
    StackShare Editors
    StackShare Editors
    Kibana
    Kibana
    Grafana
    Grafana
    Elasticsearch
    Elasticsearch
    Logstash
    Logstash
    Graphite
    Graphite
    Icinga
    Icinga

    One size definitely doesn’t fit all when it comes to open source monitoring solutions, and executing generally understood best practices in the context of unique distributed systems presents all sorts of problems. Megan Anctil, a senior engineer on the Technical Operations team at Slack gave a talk at an O’Reilly Velocity Conference sharing pain points and lessons learned at wrangling known technologies such as Icinga, Graphite, Grafana, and the Elastic Stack to best fit the company’s use cases.

    At the time, Slack used a few well-known monitoring tools since it’s Technical Operations team wasn’t large enough to build an in-house solution for all of these. Nor did the team think it’s sustainable to throw money at the problem, given the volume of information processed and the not-insignificant price and rigidity of many vendor solutions. With thousands of servers across multiple regions and millions of metrics and documents being processed and indexed per second, the team had to figure out how to scale these technologies to fit Slack’s needs.

    On the backend, they experimented with multiple clusters in both Graphite and ELK, distributed Icinga nodes, and more. At the same time, they’ve tried to build usability into Grafana that reflects the team’s mental models of the system and have found ways to make alerts from Icinga more insightful and actionable.

    See more
    Kibana
    Kibana
    Splunk
    Splunk
    Grafana
    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.

    See more
    Kibana
    Kibana
    Grafana
    Grafana
    Elasticsearch
    Elasticsearch

    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

    See more
    Grafana
    Grafana
    Kibana
    Kibana

    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)
    See more
    Interest over time
    Reviews of Kibana and Sensu
    No reviews found
    How developers use Kibana and Sensu
    Avatar of Clarabridge Engage
    Clarabridge Engage uses KibanaKibana

    Used for graphing internal logging data; including metrics related to how fast we serve pages and execute MySQL/ElasticSearch queries.

    Avatar of Wirkn Inc.
    Wirkn Inc. uses KibanaKibana

    Our Kibana instances uses our ElasticSearch search data to help answer any complicated questions we have about our data.

    Avatar of Hevelop
    Hevelop uses KibanaKibana

    Kibana is our tools to query data in Elasticsearch clusters set up as catalog search engine.

    Avatar of Diogo Silva
    Diogo Silva uses KibanaKibana

    Perfect for exploring and visualizing the data available at ElasticSearch

    Avatar of Tongliang Liu
    Tongliang Liu uses KibanaKibana

    Log visualization. Wish it could add built-in alert functionality.

    How much does Kibana cost?
    How much does Sensu cost?