Prometheus vs Telegraf

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Prometheus vs Telegraf: What are the differences?

Prometheus and Telegraf are both widely used tools in the field of monitoring and metrics collection. While they serve a similar purpose, there are key differences between them that make each tool unique and suitable for specific use cases.

  1. Data Collection: Prometheus is a pull-based system where it collects data by pulling metrics from targets. On the other hand, Telegraf is a versatile agent that supports both pull and push mechanisms. It can collect data by pulling metrics from various sources as well as pushing metrics to different destinations.

  2. Scalability: Prometheus is designed to be highly scalable and can handle large amounts of data. It achieves scalability through a federated architecture where multiple Prometheus servers can be federated together. Telegraf, on the other hand, is a lightweight collector that can be deployed on a large number of machines, making it highly scalable as well.

  3. Data Processing: Prometheus comes with its own query language called PromQL, which allows advanced querying and processing of metrics. With PromQL, users can perform aggregations, filtering, and math operations on the collected data. Telegraf, on the other hand, focuses more on data collection and routing, leaving the data processing task to other tools in the stack.

  4. Plugin Ecosystem: Telegraf has a rich plugin ecosystem, which allows easy integration with various systems and technologies. It supports a wide range of input and output plugins, making it flexible and extensible. Prometheus, on the other hand, focuses more on the core monitoring and alerting functions and has a limited number of official plugins.

  5. Alerting: Prometheus has a built-in alerting system that allows users to define alert rules based on the collected metrics. It supports various notification channels, such as email, Slack, and PagerDuty, to send alerts when certain conditions are met. Telegraf, on the other hand, does not have a built-in alerting system and relies on other tools in the monitoring stack for alerting functionality.

In summary, Prometheus is a powerful pull-based monitoring tool with advanced data processing capabilities and built-in alerting, while Telegraf is a versatile agent that supports both pull and push mechanisms and focuses more on data collection and routing.

Advice on Prometheus and Telegraf
Susmita Meher
Senior SRE at African Bank · | 4 upvotes · 823.3K 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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Sakti Behera
Technical Specialist, Software Engineering at AT&T · | 3 upvotes · 608.7K 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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Replies (2)
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 · 751.4K 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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Replies (2)
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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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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Pros of Prometheus
Pros of Telegraf
  • 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
  • 5
    One agent can work as multiple exporter with min hndlng
  • 5
    Cohesioned stack for monitoring
  • 2
    Open Source
  • 2
    Metrics
  • 1
    Supports custom plugins in any language
  • 1
    Many hundreds of plugins

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Cons of Prometheus
Cons of Telegraf
  • 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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    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.

    What is Telegraf?

    It is an agent for collecting, processing, aggregating, and writing metrics. Design goals are to have a minimal memory footprint with a plugin system so that developers in the community can easily add support for collecting metrics.

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    What are some alternatives to Prometheus and Telegraf?
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    Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!
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