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Grafana vs Runbook: What are the differences?
Integration and Compatibility: Grafana is primarily a visualization tool that integrates with a wide range of data sources, including databases, cloud services, and APIs. It can be easily integrated with various monitoring systems, such as Prometheus and Graphite, allowing users to create customizable dashboards. On the other hand, Runbook is a tool specifically designed for incident management and runbook automation. It integrates with popular incident management platforms like PagerDuty and ServiceNow, providing a seamless workflow for incident response and resolution.
User Interface and Dashboards: Grafana offers a highly customizable and visually appealing user interface (UI) for building dashboards. It provides a wide range of options for data visualization, including charts, graphs, tables, and heatmaps. Users can easily create and arrange panels, add annotations, and apply styling options to design the perfect dashboard. In contrast, Runbook focuses more on predefined incident response workflows and does not provide extensive customization options for UI and dashboards. The emphasis is on providing a streamlined interface to guide users through predefined actions during an incident.
Alerting and Notifications: Grafana allows users to set up alerts based on specific conditions and thresholds in their data. It provides flexible options for configuring alert rules and actions, such as sending notifications via email, Slack, or other messaging platforms. Additionally, Grafana supports alerting on data from multiple sources, making it suitable for complex monitoring scenarios. Runbook, on the other hand, primarily relies on integrations with incident management platforms for alerting and notifications. It leverages the existing infrastructure of these platforms to trigger notifications and escalate incidents to the appropriate stakeholders.
Collaboration and Documentation: Grafana provides limited built-in capabilities for collaboration and documentation. It allows users to share dashboards with others and provides basic version control functionality. However, it lacks advanced features like real-time collaborative editing and comprehensive documentation management. In contrast, Runbook offers features specifically tailored for collaboration and documentation during incident management. It allows teams to create and maintain runbooks, document incident response procedures, and collaborate in real-time to resolve incidents more efficiently.
Automation and Orchestration: Grafana primarily focuses on data visualization and analysis and does not provide extensive automation capabilities. It relies on integrations with other tools, such as alerting and notification systems, for automation and orchestration. Runbook, on the other hand, excels in automation and orchestration of incident response tasks. It provides predefined incident response workflows and automation capabilities, allowing users to execute specific actions automatically during an incident, reducing manual effort and improving response times.
Scalability and Performance: Grafana is known for its scalability and performance, handling large amounts of data and supporting high-frequency data updates. It can handle complex queries and visualizations efficiently, making it suitable for demanding monitoring environments. Runbook, although not primarily focused on scalability and performance like Grafana, provides a reliable and performant platform for incident management. It ensures that incident response tasks can be executed quickly and effectively, without impacting the overall incident resolution process.
In summary, Grafana is a highly flexible and customizable visualization tool that integrates with various data sources, while Runbook is a specialized incident management tool focused on automation and collaboration during incident response. Grafana offers extensive UI customization and supports data alerting, while Runbook provides predefined incident response workflows and real-time collaboration features.
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.
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.
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.
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.
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/
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.
Pros of Grafana
- Beautiful89
- Graphs are interactive68
- Free57
- Easy56
- Nicer than the Graphite web interface34
- Many integrations26
- Can build dashboards18
- Easy to specify time window10
- Can collaborate on dashboards10
- Dashboards contain number tiles9
- Open Source5
- Integration with InfluxDB5
- Click and drag to zoom in5
- Authentification and users management4
- Threshold limits in graphs4
- Alerts3
- It is open to cloud watch and many database3
- Simple and native support to Prometheus3
- Great community support2
- You can use this for development to check memcache2
- You can visualize real time data to put alerts2
- Grapsh as code0
- Plugin visualizationa0
Pros of Runbook
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Cons of Grafana
- No interactive query builder1