OpenTelemetry and Prometheus are both open-source projects under Cloud Native Computing Foundation. In this article, let us understand the key differences between the two projects and explore their advantages and shortcomings.
OpenTelemetry is a vendor-agnostic instrumentation library. It provides a set of tools, APIs, and SDKs to create and manage telemetry data(logs, metrics, and traces). OpenTelemetry follows a specification driven development and has implementations in all major programming languages.
Prometheus is a time-series metrics monitoring tool. Prometheus enables you to capture time-series data as metrics. These metrics can be aggregated to give insights into the behavior of your systems.
What is OpenTelemetry?​
OpenTelemetry is a set of API, SDKs, libraries, and integrations that aims to standardize the generation, collection, and management of telemetry data(logs, metrics, and traces). OpenTelemetry is a Cloud Native Computing Foundation project created after the merger of OpenCensus(from Google) and OpenTracing(from Uber). CNCF is the same foundation which incubated Kubernetes too.
OpenTelemetry provides a vendor-agnostic method of collecting telemetry data. Telemetry data has become critical to observe the state of distributed systems. With microservices and polyglot architectures, there was a need to have a global standard. OpenTelemetry aims to fill that space and is doing a great job at it thus far.
What are the origins of OpenTelemetry?​
In early 2019, OpenTelemetry was announced as an open-source project under Cloud Native Computing Foundation (CNCF) after the merger of two open-source projects - OpenCensus and OpenTracing.
What is CNCF?
CNCF is a vendor-neutral foundation that works on critical cloud-native open-source technologies like Kubernetes, Prometheus, and Envoy. It is a part of the nonprofit Linux Foundation.
OpenCensus was an internal project at Google that was open-sourced later. It grew popular within the community as it provided libraries to generate and collect both traces and metrics.
The OpenTracing project was started in 2016 and was aimed at increasing the adoption of distributed tracing. It focused on providing an API that could solve the lack of consistent quality instrumentation.
Both these projects were trying to solve the same problem of monitoring and observability in cloud-native applications. But having two standards was not good for the cloud-native community, and hence it was decided to merge these projects and create a single standard for generating and managing telemetry data now known as OpenTelemetry.
The OpenTelemetry Architecture​
The OpenTelemetry architecture consist of following three main components:
OpenTelemetry API
The OpenTelemetry API is used to instrument libraries, frameworks, and applications.
OpenTelemetry SDK
The OpenTelemetry SDK implements the API.
OpenTelemetry Collector
The OpenTelemetry Collector or the OTel collector enables a vendor-netrual way to collect, process and export the collected telemetry data. The collector has receivers, processors and exporters to perform these functions.
OpenTelemetry Collector - architecture and configuration guide
Advantages of OpenTelemetry​
OpenTelemetry is quietly becoming the world-standard for generating telemetry data. Observability has become a critical component to gauge the health of distributed systems. And telemetry data powers observability. OpenTelemetry removes the need to depend on multiple vendors for generating telemetry data.
Some of the key advantages of using OpenTelemetry are:
- Reduces performance overhead on your application to generate and manage telemetry data
- Supports multiple popular programming languages like Java, Javascript, C++, Go, Python, etc.
- Provides libraries and agents to auto-instrument popular libraries and frameworks requiring minimal changes to your codebase
- Provides OpenTelemetry Collector, which can receive, process, and export data in multiple formats
- Backed by technology giants like Google, Microsoft, and other big cloud vendors.
- Freedom to switch to new backend analysis tools by using relevant exporters
- Instrumentation support for new frameworks and technologies
Disadvantages of OpenTelemetry​
Some of the key disadvantages of using OpenTelemetry are:
- Project has a lot of scope in improving documentation and support
- It does not provide backend storage and a visualization layer
But OpenTelemetry project is intentional about not providing a backend analysis tool as it aims to be vendor-neutral. You can use a tool like SigNoz to send your telemetry data. SigNoz is a full-stack open-source application monitoring and observability platform which comes with a great out of box visualization layer. It is also an open-source project.
What is Prometheus?​
Prometheus is used as a metrics monitoring tool. It was initially developed at SoundCloud in 2012 before being released as an open-source project. It got accepted into the CloudNative Computing Foundation in 2016 and was the second project to graduate from the foundation, following Kubernetes.
Prometheus is a good tool for monitoring any kind of time-series data. By time-series data, we mean metrics that change over time. For example, requests per second on an endpoint.
Key features of Prometheus​
Some of the key features of Prometheus are:
- multi-dimensional data model
- a query language called PromQL to query the metrics data collected
- pull model data collection over HTTP
- an alert manager to handle alerts
- Basic visualization layer but can be combined with Grafana to create rich visualizations
Disadvantages of Prometheus​
Prometheus is a great metrics monitoring tool, but that's it. It is not a full-stack application monitoring tool like SigNoz. Some of the disadvantages of using Prometheus are listed down below:
- Prometheus only captures metrics. For creating a robust monitoring framework, you will need to track metrics, logs, and traces. For example, a tool like SigNoz captures both metrics and traces(log management in product roadmap).
- Prometheus is designed for a single machine. It cannot be scaled horizontally.
- It takes time and effort to set up Prometheus for a great visualization. It involves setting up exporters and Grafana panels.
- Prometheus does not support root cause analysis as it does not support traces.
Key differences between OpenTelemetry and Prometheus​
Ease of Use​
OpenTelemetry:
- Provides flexibility with less vendor lock-in and greater interoperability.
- Offers auto-instrument frameworks and libraries, reducing the need for extensive codebase changes.
- However, it lacks a visualization layer or backend storage. You need to use a backend tool like SigNoz to send your OpenTelemetry data.
Prometheus:
- Comes with a basic visualization layer and an alert manager.
- Requires effort and time to set up exporters effectively.
- Designed for a single machine, limiting its scalability.
Pricing​
Both OpenTelemetry and Prometheus are open-source projects, implying that they are free to use. However, the costs associated with infrastructure, storage, and any additional integrations or tools should be considered.
Use Cases​
OpenTelemetry:
- Ideal for organizations looking for a comprehensive solution for logging, metrics, and tracing.
- Suitable for microservices architectures requiring high levels of observability.
- Best for companies aiming to avoid vendor lock-in and seeking flexibility in choosing backend analysis tools.
Prometheus:
- Perfect for monitoring time-series data in applications and infrastructure.
- Suitable for organizations that already have tools in place for logging and tracing and need a robust solution for metrics.
- Best for scenarios where data reliability is prioritized over absolute accuracy.
OpenTelemetry and SigNoz - the combo fit to replace Prometheus​
With Prometheus, you can monitor metrics. But your engineering teams will never be able to identify the root cause of issues in your application using just metrics. For that, you also need distributed tracing and logs.
OpenTelemetry is becoming the world standard for instrumenting application code due to its multi-language support and ease of use. But OpenTelemetry helps only to generate and collect telemetry data. You need to export the telemetry data to a backend analysis tool so that your teams can store, query, and visualize the collected data.
And that's where SigNoz comes into the picture. SigNoz is built to support OpenTelemetry natively. Once you instrument your application with OpenTelemetry libraries, you can send the collected data to SigNoz.
SigNoz comes with out of box visualization of things like RED metrics. There is a unified UI of logs, metrics, and traces so that you can easily identify the root cause of issues causing things like latency in your apps.
SigNoz also provides log management. Using logs, you can dive deeper into your application issues. Logs can also be intelligently correlated to other telemetry signals like traces and metrics.
Getting started with SigNoz​
SigNoz cloud is the easiest way to run SigNoz. You can sign up here for a free account and get 30 days of free uncapped usage.
You can also install and self-host SigNoz yourself. It can be installed on macOS or Linux computers in just three steps by using a simple install script.
The install script automatically installs Docker Engine on Linux. However, on macOS, you must manually install Docker Engine before running the install script.
git clone -b main https://github.com/SigNoz/signoz.git
cd signoz/deploy/
./install.sh
You can visit our documentation for more installation option.
If you liked what you read, then check out our GitHub repo 👇
Related Content​
OpenTelemetry Collector - Complete Guide
OpenTelemetry Tracing - things you need to know