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NetData vs Prometheus: What are the differences?

NetData and Prometheus are two popular monitoring tools that provide insights into the performance and health of systems, applications, and networks. Let's explore the key differences between them.

  1. Data Collection Method: NetData uses a streaming-based approach to collect data in real-time, continuously polling system metrics at high frequencies. On the other hand, Prometheus follows a pull-based model, where it regularly scrapes metrics from endpoint targets. This fundamental difference in data collection methods can affect the accuracy and responsiveness of the monitoring data.

  2. Architecture: NetData has an agent-based architecture, which means that individual agents need to be installed and configured on each target machine. In contrast, Prometheus operates as a standalone server that collects metrics from various exporters and targets through HTTP or other protocols. This architectural difference can impact the deployment and scalability of the monitoring setup.

  3. Alerting and Notification: NetData supports basic alerting capabilities but relies on external tools like email or SMS gateways for notifications. Prometheus, on the other hand, provides a built-in alerting system that can trigger notifications based on user-defined rules and thresholds. This native alerting feature makes Prometheus more self-contained and convenient for managing alerts.

  4. Data Storage: NetData stores metrics in memory by default, allowing for real-time visualization and analysis. However, for long-term storage or historical analysis, NetData relies on third-party tools like Elasticsearch or InfluxDB. In contrast, Prometheus has its own time-series database that stores metrics persistently, making it easier to perform time-based queries and generate historical reports.

  5. Service Discovery: NetData does not have built-in service discovery mechanisms and relies on manual configuration of targets. On the other hand, Prometheus has robust service discovery capabilities that automatically identify and monitor new instances as they come online or go offline. This automatic service discovery simplifies the management of dynamic environments and facilitates scaling.

  6. Ecosystem and Integrations: Prometheus has a vibrant ecosystem with a wide range of integrations, exporters, and community-contributed plugins, making it easy to collect metrics from different systems and applications. NetData, while extensible through various collectors and plugins, has a less extensive ecosystem and may require more custom development for integrating with specific technologies.

In summary, NetData provides real-time, per-second monitoring with a user-friendly interface, making it easy to visualize system metrics and troubleshoot issues quickly. In contrast, Prometheus offers powerful querying and alerting capabilities, along with a robust ecosystem of exporters and integrations, making it suitable for large-scale, multi-dimensional monitoring setups.

Advice on Netdata and Prometheus
Susmita Meher
Senior SRE at African Bank · | 4 upvotes · 832.1K views
Needs advice
on
GrafanaGrafanaGraphiteGraphite
and
PrometheusPrometheus

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.

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Replies (1)
Sakti Behera
Technical Specialist, Software Engineering at AT&T · | 3 upvotes · 617.7K views
Recommends
on
GrafanaGrafanaPrometheusPrometheus

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.

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Sunil Chaudhari
Needs advice
on
MetricbeatMetricbeat
and
PrometheusPrometheus

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.

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Matthew Rothstein
Recommends
on
PrometheusPrometheus

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.

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Recommends
on
InstanaInstana

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

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Mat Jovanovic
Head of Cloud at Mats Cloud · | 3 upvotes · 759.9K views
Needs advice
on
DatadogDatadogGrafanaGrafana
and
PrometheusPrometheus

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.

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Lucas Rincon
Recommends
on
InstanaInstana

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/

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Recommends
on
DatadogDatadog

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.

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Decisions about Netdata and Prometheus
Leonardo Henrique da Paixão
Junior QA Tester at SolarMarket · | 15 upvotes · 382.1K 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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Pros of Netdata
Pros of Prometheus
  • 17
    Free
  • 14
    Easy setup
  • 12
    Graphs are interactive
  • 9
    Montiors datasbases
  • 9
    Well maintained on github
  • 8
    Monitors nginx, redis, logs
  • 4
    Can submit metrics to Time Series databases
  • 3
    Open source
  • 2
    Easy Alert Setop
  • 2
    Netdata is also a statsd server
  • 1
    Written in C
  • 1
    GPLv3
  • 0
    Zabbix
  • 47
    Powerful easy to use monitoring
  • 38
    Flexible query language
  • 32
    Dimensional data model
  • 27
    Alerts
  • 23
    Active and responsive community
  • 22
    Extensive integrations
  • 19
    Easy to setup
  • 12
    Beautiful Model and Query language
  • 7
    Easy to extend
  • 6
    Nice
  • 3
    Written in Go
  • 2
    Good for experimentation
  • 1
    Easy for monitoring

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Cons of Netdata
Cons of Prometheus
    Be the first to leave a con
    • 12
      Just for metrics
    • 6
      Bad UI
    • 6
      Needs monitoring to access metrics endpoints
    • 4
      Not easy to configure and use
    • 3
      Supports only active agents
    • 2
      Written in Go
    • 2
      TLS is quite difficult to understand
    • 2
      Requires multiple applications and tools
    • 1
      Single point of failure

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    - No public GitHub repository available -

    What is Netdata?

    Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps

    What is 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.

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    What are some alternatives to Netdata and Prometheus?
    Grafana
    Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.
    Zabbix
    Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.
    Nagios
    Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.
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    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.
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    It is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.
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