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Grafana vs Shinken: What are the differences?

Introduction

Grafana and Shinken are both software tools used for monitoring and visualizing metrics in an IT environment. While they share some similarities, there are key differences that set them apart.

  1. Architecture: Grafana is primarily a visualization tool that connects to various data sources and presents the collected data in customizable dashboards. It does not have built-in monitoring capabilities but can integrate with other monitoring tools. On the other hand, Shinken is a complete monitoring solution that includes data collection, alerting, and visualization components. It is designed to monitor various types of infrastructure and services from a central server.

  2. Data Visualization: Grafana provides a wide range of options for visualizing data, including charts, graphs, tables, and maps. It offers a highly flexible and customizable interface, allowing users to create visually appealing and informative dashboards. Shinken, on the other hand, does not have as extensive visualization capabilities as Grafana. It focuses more on the monitoring aspect, providing basic visualization options such as tables and graphs.

  3. Alerting and Notification: Shinken excels in alerting and notification capabilities. It allows users to set up complex alerting rules based on predefined thresholds or custom criteria. It provides multiple notification options, such as email, SMS, and integration with third-party tools like Slack. Grafana, on the other hand, relies on integrations with alerting tools like Prometheus or InfluxDB for alerting and notification functionalities.

  4. Community and Ecosystem: Grafana has a larger and more active community compared to Shinken. This allows for a wider range of community-developed plugins, extensions, and integrations. Grafana also has extensive documentation and online resources available, making it easy for users to find help and support. Shinken has a smaller community and a more limited ecosystem of plugins and extensions.

  5. Ease of Use: Grafana offers a user-friendly and intuitive interface, making it easy for both beginners and experienced users to create dashboards and visualizations. It provides drag-and-drop functionality and a rich set of pre-built panels and templates. Shinken, on the other hand, has a steeper learning curve and requires more configuration and setup to get started. It is more suited for experienced users or organizations with specific monitoring requirements.

  6. Scalability: Shinken is designed to handle large-scale monitoring environments with thousands of hosts and services. It supports distributed monitoring, allowing for the deployment of multiple servers for load balancing and fault tolerance. Grafana, on the other hand, relies on external data sources for data collection and does not have built-in scalability features. Scalability in Grafana depends on the scalability of the underlying data sources.

In summary, Grafana is a powerful data visualization tool with flexible dashboards and a large community, while Shinken is a comprehensive monitoring solution with strong alerting capabilities and scalability for large deployments.

Advice on Grafana and Shinken
Susmita Meher
Senior SRE at African Bank · | 4 upvotes · 783.4K views
Needs advice
on
GrafanaGrafanaGraphiteGraphite
and
PrometheusPrometheus

Looking for a tool which can be used for mainly dashboard purposes, but here are the main requirements:

  • Must be able to get custom data from AS400,
  • Able to display automation test results,
  • System monitoring / Nginx API,
  • Able to get data from 3rd parties DB.

Grafana is almost solving all the problems, except AS400 and no database to get automation test results.

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Replies (1)
Sakti Behera
Technical Specialist, Software Engineering at AT&T · | 3 upvotes · 568.7K views
Recommends
on
GrafanaGrafanaPrometheusPrometheus

You can look out for Prometheus Instrumentation (https://prometheus.io/docs/practices/instrumentation/) Client Library available in various languages https://prometheus.io/docs/instrumenting/clientlibs/ to create the custom metric you need for AS4000 and then Grafana can query the newly instrumented metric to show on the dashboard.

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Mat Jovanovic
Head of Cloud at Mats Cloud · | 3 upvotes · 712.7K views
Needs advice
on
DatadogDatadogGrafanaGrafana
and
PrometheusPrometheus

We're looking for a Monitoring and Logging tool. It has to support AWS (mostly 100% serverless, Lambdas, SNS, SQS, API GW, CloudFront, Autora, etc.), as well as Azure and GCP (for now mostly used as pure IaaS, with a lot of cognitive services, and mostly managed DB). Hopefully, something not as expensive as Datadog or New relic, as our SRE team could support the tool inhouse. At the moment, we primarily use CloudWatch for AWS and Pandora for most on-prem.

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Replies (2)
Lucas Rincon
Recommends
on
InstanaInstana

this is quite affordable and provides what you seem to be looking for. you can see a whole thing about the APM space here https://www.apmexperts.com/observability/ranking-the-observability-offerings/

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Recommends
on
DatadogDatadog

I worked with Datadog at least one year and my position is that commercial tools like Datadog are the best option to consolidate and analyze your metrics. Obviously, if you can't pay the tool, the best free options are the mix of Prometheus with their Alert Manager and Grafana to visualize (that are complementary not substitutable). But I think that no use a good tool it's finally more expensive that use a not really good implementation of free tools and you will pay also to maintain its.

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Needs advice
on
GrafanaGrafana
and
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
on
GrafanaGrafana
at

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
on
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
Recommends
on
GrafanaGrafana
at

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
on
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
on
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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Recommends
on
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 · 593.4K views
Recommends
on
KibanaKibana
at

@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 Grafana and Shinken
Leonardo Henrique da Paixão
Junior QA Tester at SolarMarket · | 2 upvotes · 174.7K views

I learned a lot from Grafana, especially the issue of data monitoring, as it is easy to use, I learned how to create quick and simple dashboards. InfluxDB, I didn't know any other types of DBMS, I only knew about relational DBMS or not, but the difference was the scalability of both, but with influxDB, I knew how a time series DBMS works and finally, Telegraf, which is from the same company as InfluxDB, as I used the Windows Operating System, Telegraf tools was the first in the industry, in addition, it has complete documentation, facilitating its use, I learned a lot about connections, without having to make scripts to collect the data.

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Leonardo Henrique da Paixão
Junior QA Tester at SolarMarket · | 15 upvotes · 353.5K 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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Pros of Grafana
Pros of Shinken
  • 89
    Beautiful
  • 68
    Graphs are interactive
  • 57
    Free
  • 56
    Easy
  • 34
    Nicer than the Graphite web interface
  • 26
    Many integrations
  • 18
    Can build dashboards
  • 10
    Easy to specify time window
  • 10
    Can collaborate on dashboards
  • 9
    Dashboards contain number tiles
  • 5
    Open Source
  • 5
    Integration with InfluxDB
  • 5
    Click and drag to zoom in
  • 4
    Authentification and users management
  • 4
    Threshold limits in graphs
  • 3
    Alerts
  • 3
    It is open to cloud watch and many database
  • 3
    Simple and native support to Prometheus
  • 2
    Great community support
  • 2
    You can use this for development to check memcache
  • 2
    You can visualize real time data to put alerts
  • 0
    Grapsh as code
  • 0
    Plugin visualizationa
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    Cons of Grafana
    Cons of Shinken
    • 1
      No interactive query builder
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      - No public GitHub repository available -

      What is 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.

      What is Shinken?

      Shinken's main goal is to give users a flexible architecture for their monitoring system that is designed to scale to large environments. Shinken is backwards-compatible with the Nagios configuration standard and plugins. It works on any operating system and architecture that supports Python, which includes Windows, GNU/Linux and FreeBSD.

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      Jobs that mention Grafana and Shinken as a desired skillset
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      San Francisco, United States
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      What are some alternatives to Grafana and Shinken?
      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!
      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.
      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.
      Graphite
      Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand
      Splunk
      It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
      See all alternatives