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Ganglia vs collectd: What are the differences?

Introduction:

Ganglia and collectd are both monitoring tools used in system administration to collect and analyze system performance data. However, there are key differences between the two that make them suitable for different use cases.

  1. Data Collection Method: Ganglia uses a pull-based model where the data is collected from monitored hosts by a central gmond daemon running on the Ganglia server, while collectd uses a push-based model where the monitored hosts actively push data to a designated collectd server or service.

  2. Plugin Ecosystem: Ganglia provides a limited set of built-in monitoring capabilities and relies more on third-party plugins to extend its functionality, whereas collectd comes with a wide range of plugins covering various metrics like CPU, memory, disk, network, and even custom metrics.

  3. Scalability: Ganglia is known for its scalability and is commonly used in large-scale environments with thousands of hosts due to its efficient data aggregation and storage mechanisms, while collectd is more lightweight and suited for smaller environments or when a lesser number of metrics need to be monitored.

  4. Architecture: Ganglia follows a hierarchical architecture where data flows from hosts to gmond to gmetad for storage and analysis, while collectd implements a simpler architecture where data is directly sent from hosts to the central server or destination without the need for intermediate layers.

  5. Data Visualization: Ganglia provides a web-based interface for visualizing system metrics, creating graphs, and setting up alerts, whereas collectd does not come with a built-in graphical interface and relies on third-party tools or integration with other monitoring platforms for data visualization.

  6. Community Support: Ganglia has been around longer and has a more established community, making it easier to find documentation, plugins, and support, while collectd, although actively developed, may have a smaller user base and community resources available.

In Summary, Ganglia and collectd differ in key aspects such as data collection method, plugin ecosystem, scalability, architecture, data visualization, and community support.

Decisions about collectd and Ganglia
Leonardo Henrique da Paixão
Junior QA Tester at SolarMarket · | 15 upvotes · 349.8K 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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    - No public GitHub repository available -

    What is collectd?

    collectd gathers statistics about the system it is running on and stores this information. Those statistics can then be used to find current performance bottlenecks (i.e. performance analysis) and predict future system load (i.e. capacity planning). Or if you just want pretty graphs of your private server and are fed up with some homegrown solution you're at the right place, too.

    What is Ganglia?

    It is a scalable distributed monitoring system for high-performance computing systems such as clusters and Grids. It is based on a hierarchical design targeted at federations of clusters.

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    Jobs that mention collectd and Ganglia as a desired skillset
    Postman
    San Francisco, United States
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    What are some alternatives to collectd and Ganglia?
    StatsD
    It is a network daemon that runs on the Node.js platform and listens for statistics, like counters and timers, sent over UDP or TCP and sends aggregates to one or more pluggable backend services (e.g., Graphite).
    Nagios
    Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.
    Fluentd
    Fluentd collects events from various data sources and writes them to files, RDBMS, NoSQL, IaaS, SaaS, Hadoop and so on. Fluentd helps you unify your logging infrastructure.
    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.
    Munin
    Munin is a networked resource monitoring tool that can help analyze resource trends and "what just happened to kill our performance?" problems. It is designed to be very plug and play. A default installation provides a lot of graphs with almost no work.
    See all alternatives