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Grafana vs Zipkin: What are the differences?
Key Differences between Grafana and Zipkin
Grafana and Zipkin are both popular tools used for monitoring and analyzing application performance and metrics. Despite having some similarities, they also have distinct differences.
Data Visualization Capabilities: Grafana is known for its powerful data visualization capabilities, allowing users to create interactive and customizable dashboards. It supports a wide range of data sources and provides a variety of options for data visualization, such as graphs, tables, and heatmaps. On the other hand, Zipkin primarily focuses on distributed tracing and provides limited options for data visualization.
Scope of Monitoring: Grafana is a comprehensive monitoring tool that can monitor various aspects of an application, including performance metrics, logs, and infrastructure monitoring. It can integrate with different monitoring systems and provide an all-in-one solution for monitoring and analysis. In contrast, Zipkin primarily focuses on distributed tracing, which involves monitoring requests as they move through a distributed system, making it more specialized for tracing specific issues.
Data Collection Approach: Grafana collects data through agents or plugins that are installed on the servers or applications being monitored. It supports a wide range of data collection methods, including pulling data from databases, APIs, or other data sources. On the other hand, Zipkin collects data through instrumentation, where specific code snippets are added to the application's codebase to capture tracing data.
Tracing Capability: While both Grafana and Zipkin can trace requests in a distributed system, they have different approaches to tracing. Grafana focuses on providing a high-level overview of an application's performance and dependencies, allowing users to identify bottlenecks and performance issues. Zipkin, on the other hand, specializes in detailed distributed tracing, providing insights into individual requests' paths through a system and enabling users to identify specific issues.
Community and Ecosystem: Grafana has a larger and more active community, which translates to a wider range of plugins, integrations, and community support available. It has a rich ecosystem, allowing users to extend its functionality and integrate with various data sources easily. Zipkin also has a community but is relatively smaller with fewer integrations and plugins available.
Use Case: Due to their differences, Grafana and Zipkin are often used in different use cases. Grafana is commonly used for monitoring and visualizing metrics from various data sources, including databases, APIs, and sensors. It is widely used in operations and DevOps teams for infrastructure and application monitoring. Zipkin, on the other hand, is widely used for distributed tracing and is more suitable for troubleshooting and debugging latency problems in microservices or distributed systems.
In summary, Grafana is a comprehensive monitoring and visualization tool with a focus on data visualization capabilities and a wide range of monitoring options. Zipkin, on the other hand, specializes in distributed tracing and provides detailed insights into individual requests' paths through a system.
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.
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/
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.
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 Zipkin
- Open Source10
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Cons of Grafana
- No interactive query builder1