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Ganglia vs Prometheus vs collectd: What are the differences?
Introduction
In the world of monitoring and performance management, there are various tools available for system administrators to choose from. Ganglia, Prometheus, and collectd are three popular tools that serve this purpose. Each tool has its unique features and capabilities, making them suitable for different use cases.
Data Collection Method: Ganglia primarily uses a hierarchical design to collect and send metrics to a central server for analysis. On the other hand, Prometheus utilizes a pull-based model where each target exposes a metrics endpoint that Prometheus scrapes periodically. In comparison, collectd employs a plugin-based architecture to collect various types of system metrics and statistics.
Data Storage and Querying: Prometheus has a built-in time-series database that stores all collected metrics locally, providing powerful querying capabilities using its PromQL language. Ganglia relies on RRDTool for storing historical data, making it less flexible for advanced querying. Collectd, on the other hand, lacks built-in data storage capabilities and typically forwards metrics to other tools like Prometheus.
Alerting and Notification: Prometheus comes with built-in alerting features that allow users to set up rules for alert notifications based on specified conditions. Ganglia does not have native alerting capabilities and usually requires integration with third-party tools for this functionality. Similarly, collectd does not provide native alerting features and relies on external tools for setting up alerts.
Community and Ecosystem: Prometheus has a rapidly growing community and a rich ecosystem of integrations with various third-party tools and platforms, making it a popular choice for monitoring in modern environments. Ganglia has a well-established community but may lack some of the modern features and integrations available in Prometheus. Collectd has a smaller community compared to Prometheus and Ganglia, which can affect the availability of plugins and support resources.
Scalability and Performance: Ganglia is known for its scalability and efficiency in large-scale deployments, making it a preferred choice for monitoring clusters and distributed systems. Prometheus, while capable of handling large volumes of metrics, may require additional resources for optimal performance in high-traffic environments. Collectd is lightweight and designed for minimal resource consumption, making it suitable for monitoring individual systems or small-scale deployments.
Architecture and Flexibility: Ganglia follows a client-server architecture where data is sent to a central collector for processing, while Prometheus and collectd can operate in standalone modes without the need for centralized servers. Prometheus offers more flexibility in terms of metric collection and monitoring configurations, with support for dynamic service discovery and auto-scaling environments. Collectd, on the other hand, is more focused on system-level metrics collection and may require additional tools for advanced monitoring use cases.
In Summary, Ganglia, Prometheus, and collectd each offer unique features and capabilities for monitoring and performance management, catering to different requirements in terms of data collection, storage, querying, alerting, community support, scalability, and flexibility.
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.
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.
Pros of collectd
- Open Source2
- Modular, plugins2
- KISS1
Pros of Ganglia
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
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Cons of collectd
Cons of Ganglia
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