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Prometheus vs Zipkin: What are the differences?
Prometheus and Zipkin are two popular monitoring and tracing tools used in the field of software development. Let's explore the key differences between them.
Scalability and Data Storage: Prometheus is designed as a time-series database that allows users to collect and store metrics data over extended periods. It uses a "pull" model, where clients pull metrics data from the server. On the other hand, Zipkin focuses more on distributed tracing and relies on storing and indexing traces rather than raw metrics. It uses a "push" model, where the traced data is sent to the server asynchronously.
Querying and Alerting: Prometheus provides a powerful and flexible query language called PromQL, which allows users to perform complex queries and aggregations on the collected metrics data. Additionally, Prometheus supports alerting rules that enable users to define thresholds and triggers for alert notifications based on metrics data. In contrast, Zipkin focuses more on distributed tracing and does not offer extensive querying or alerting functionalities.
Data Collection: Prometheus employs an agentless architecture, where clients (also known as exporters) expose metrics data over HTTP or other protocols directly to the Prometheus server. It supports various popular exporters for collecting metrics from different systems. On the other hand, Zipkin relies on instrumentation libraries or SDKs integrated into the application codebase to collect tracing data. These libraries automatically propagate trace context across various systems and collect information about request flows and latency.
Visualization and User Interface: Prometheus includes a built-in expression browser and graphing tool called Grafana. It offers a wide range of visualization options and is well-suited for exploring and visualizing time-series metrics data. Zipkin, on the other hand, has a user interface focused on distributed tracing. It provides a detailed view of traces, showing the flow of requests across various services and their respective durations.
Purpose and Use Case: Prometheus is mainly used for monitoring and alerting in a microservices environment. It excels at collecting and analyzing metrics data, enabling users to gain insights into the performance and health of their applications and infrastructure. Zipkin, on the other hand, is primarily used for distributed tracing to understand and troubleshoot latency issues and service dependencies in complex distributed systems.
Community and Ecosystem: Prometheus has a large and active open-source community, with a wide range of exporters, integrations, and extensions available. It integrates well with other tools in the monitoring ecosystem, such as Grafana and Alertmanager. Zipkin also has an active community, but its ecosystem is more focused on distributed tracing. It has integrations with other tracing tools like Jaeger, and there are various tracing libraries available for different programming languages.
In summary, Prometheus is a robust monitoring and alerting tool widely used for collecting and querying time series data, providing insights into system performance and health metrics. In contrast, Zipkin is a distributed tracing system that helps in troubleshooting and understanding the latency and flow of requests across microservices architectures, facilitating efficient diagnosis of performance issues and bottlenecks.
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.
Hi, We have a situation, where we are using Prometheus to get system metrics from PCF (Pivotal Cloud Foundry) platform. We send that as time-series data to Cortex via a Prometheus server and built a dashboard using Grafana. There is another pipeline where we need to read metrics from a Linux server using Metricbeat, CPU, memory, and Disk. That will be sent to Elasticsearch and Grafana will pull and show the data in a dashboard.
Is it OK to use Metricbeat for Linux server or can we use Prometheus?
What is the difference in system metrics sent by Metricbeat and Prometheus node exporters?
Regards, Sunil.
If you're already using Prometheus for your system metrics, then it seems like standing up Elasticsearch just for Linux host monitoring is excessive. The node_exporter is probably sufficient if you'e looking for standard system metrics.
Another thing to consider is that Metricbeat / ELK use a push model for metrics delivery, whereas Prometheus pulls metrics from each node it is monitoring. Depending on how you manage your network security, opting for one solution over two may make things simpler.
Hi Sunil! Unfortunately, I don´t have much experience with Metricbeat so I can´t advise on the diffs with Prometheus...for Linux server, I encourage you to use Prometheus node exporter and for PCF, I would recommend using the instana tile (https://www.instana.com/supported-technologies/pivotal-cloud-foundry/). Let me know if you have further questions! Regards Jose
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.
Pros of Prometheus
- Powerful easy to use monitoring47
- Flexible query language38
- Dimensional data model32
- Alerts27
- Active and responsive community23
- Extensive integrations22
- Easy to setup19
- Beautiful Model and Query language12
- Easy to extend7
- Nice6
- Written in Go3
- Good for experimentation2
- Easy for monitoring1
Pros of Zipkin
- Open Source10
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Cons of Prometheus
- Just for metrics12
- Bad UI6
- Needs monitoring to access metrics endpoints6
- Not easy to configure and use4
- Supports only active agents3
- Written in Go2
- TLS is quite difficult to understand2
- Requires multiple applications and tools2
- Single point of failure1