OpenTelemetry vs. Prometheus: You can’t fix what you can’t see

Monitoring and optimizing software efficiency is essential for software program builders and enterprises at giant. The extra functions that an enterprise deploys, the extra knowledge that exists for gathering and analyzing. But, this knowledge isn’t price a lot with out the proper instruments for monitoring, optimizing, storing and—crucially—placing the info into context.

Organizations can benefit from software knowledge by deploying monitoring and observability options that assist enhance software well being by figuring out points earlier than they come up, flagging bottlenecks, distributing community visitors and extra. These options assist scale back software downtime, present extra dependable software efficiency and enhance consumer expertise.

OpenTelemetry and Prometheus are each open-source initiatives underneath the Cloud Native Computing Basis (CNCF) that provide observability instruments for software monitoring. Various kinds of knowledge and operations require distinct options that depend upon a company’s targets and software specs. Understanding the important thing variations between platforms like OpenTelemetry and Prometheus and what every resolution gives, is essential earlier than you select one for implementation.

Additionally it is priceless to notice that OpenTelemetry and Prometheus combine and may work collectively as a strong duo for monitoring functions. OpenTelemetry and Prometheus allow the gathering and transformation of metrics, which permits DevOps and IT groups to generate and act on efficiency insights.

What’s OpenTelemetry?

OpenTelemetry or OTel, is a platform that’s designed to create a centralized location for producing, gathering, exporting and managing telemetry knowledge, together with logs, metrics and traces. OTel was born from the merger of OpenCensus and OpenTracing with the objective of offering APIs, SDKs, libraries and integrations that standardize the gathering of disparate knowledge. With OTel, the needed monitoring outputs will be constructed into your code to simplify knowledge processing and be sure that knowledge is exported to the suitable again finish.

Analyzing telemetry knowledge is vital in understanding system efficiency and well being. Any such optimized observability permits organizations to troubleshoot sooner, enhance system reliability, deal with latency points and scale back software downtime.

Right here’s a fast break down the important thing elements of the OpenTelemetry ecosystem:

APIs: OpenTelemetry APIs (application programming interfaces) universally translate programming languages. This functionality allows the APIs to gather telemetry knowledge. These APIs play a key function in standardizing the gathering of OpenTelemetry metrics.

SDKs: Software program improvement kits are instruments for constructing software program. They embody the framework, code libraries and debuggers which are the constructing blocks of software program improvement. OTel SDKs implement OpenTelemetry APIs and provide the instruments which are wanted to generate and gather telemetry knowledge.

OpenTelemetry collector: The OTel collector receives, processes and exports, telemetry knowledge. OTel collectors will be configured to filter particular knowledge sorts to the designated again finish.  

Instrumentation library: OTel offers an instrumentation mannequin that runs on all platforms. The instrumentation libraries make it doable for OTel to combine with any programming language.

Advantages of OpenTelemetry

The OpenTelemetry protocol (OTLP) simplifies observability by gathering telemetry knowledge, like metrics, logs and traces, with out altering code or metadata.

Metrics: Metrics outline a high-level overview of system efficiency and well being. Builders, IT and enterprise administration groups decide what metrics are most helpful to trace to take care of a stage of software efficiency that meets enterprise targets. Metrics differ relying on the info {that a} staff deems essential and may embody community visitors, latency and CPU storage. Metrics may also be used to trace patterns and developments in software efficiency.

Logs: Logs are a file of occasions that happen inside a software program or software element. Logs will be created round particular elements of a element that DevOps groups need to monitor. They function historic knowledge that may current normal efficiency data, present when set thresholds are surpassed, or show errors. Logs assist monitor the general well being of an software ecosystem.

Traces: Traces provide a extra zoomed out view of software efficiency than logs and assist with optimization. They’re additionally extra centered than logs and comply with the end-to-end journey of a single request because it strikes by means of the applying stack. Traces enable builders to seek out the precise second errors or bottlenecks happen, how lengthy they final and the way they have an effect on the consumer journey. This data helps handle microservices and enhance general software efficiency.

OTel can take these three various kinds of telemetry knowledge and export them to numerous again ends, together with Prometheus. This functionality prevents vendor or back-end lock-in and permits builders to decide on their most well-liked evaluation instruments. OpenTelemetry helps a spread of integrations with different platforms, together with Prometheus, which give larger alternatives for observability. OTel helps Java, Python, JavaScript and Go, making it an more and more versatile resolution. It additionally permits builders and IT groups to observe efficiency from any net browser or location.

The best strengths of OpenTelemetry come from its means to persistently gather and export knowledge throughout many functions and its standardization of the gathering course of. OTel is a strong software for observability into distributed methods and microservices.

What’s Prometheus?

Prometheus is a toolkit for monitoring and alerting that was created to gather and arrange software metrics. The Prometheus server was initially developed at SoundCloud earlier than it turned an open-source software.

Prometheus is a time-series database for end-to-end monitoring of time-series knowledge. Time-series metrics are a group of information that’s taken at common intervals equivalent to month-to-month gross sales knowledge, or day by day software visitors. Clear visibility into this sort of knowledge gives insights into patterns, developments and predictions for enterprise planning. As soon as built-in with a number, Prometheus gathers software metrics which are associated to devoted features that DevOps groups need to monitor.

Prometheus metrics present knowledge factors that encompass the metric identify, label, timestamp and worth by utilizing a question language referred to as PromQL. PromQL permits builders and IT departments to mixture knowledge metrics and switch them into histograms–graphs and dashboards for larger visualization. Prometheus can entry knowledge from enterprise databases or from exporters. Exporters are software program that’s associated to functions that work to tug metrics from numerous apps and endpoints.

Prometheus collects 4 forms of metrics:

Counters: Countersmeasure cumulative numerical values that solely enhance. Counters are used to measure accomplished duties, the variety of errors that occurred throughout an outlined interval, or the variety of operating processes or microservices.

Gauges: Gauges monitor numerical values that rise and fall relying on exterior elements. They will monitor CPU and reminiscence utilization, temperature, or the dimensions of a queue.

Histograms: Histograms measure the period of specified occasions equivalent to request period or response dimension. They then divide the vary of those measurements into intervals which are referred to as buckets and decide what number of of those measurements fall into every respective bucket.

Summaries: Like histograms, summaries additionally measure request durations and response dimension, but additionally present a complete depend of all observations and a complete of all noticed values.

One other priceless facet of Prometheus is that it could possibly create accessible dashboards and graphs based mostly on the collected knowledge.

Advantages of Prometheus

Prometheus allows real-time software monitoring that provides you correct insights and facilitates fast troubleshooting. It additionally permits for the creation of thresholds which are associated to particular features. When these thresholds are met or surpassed, it triggers alerts that may scale back the time that it takes to resolve points. Prometheus can deal with and retailer giant volumes of metrics knowledge and make the info out there for analytics groups as wanted. It’s not meant to be a long-term storage resolution however a software for storing knowledge that’s wanted for instant evaluation. The usual window for knowledge storage with Prometheus is between two hours and fifteen days.

Prometheus seamlessly integrates with Kubernetes, an open-source container orchestration platform for scheduling and automating the deployment, administration and scaling of containerized functions. Kubernetes permits enterprises to construct advanced hybrid and multicloud environments that deploy a spread of companies and microservices. Integrating Prometheus with Kubernetes brings full-stack observability and oversight into these advanced methods.

Prometheus can also be appropriate with Grafana, a strong visualization software that helps rework knowledge into dashboards, charts, graphs and alerts. When paired with Prometheus, Grafana can take metrics and create clear visualizations. The compatibility between these two platforms makes advanced knowledge extra accessible and sharable amongst totally different groups. 

Key variations between OpenTelemetry and Prometheus

Prometheus gives instruments for metrics monitoring, storage and visualization, however doesn’t observe logs or assist traces, that are used for root trigger evaluation. Total, Prometheus has extra restricted use instances than OpenTelemetry.

OpenTelemetry can course of and hint extra advanced metrics than Prometheus by means of programming language-agnostic integrations. OTel is very scalable and has larger extensibility than Prometheus by providing automated instrumentation fashions. Not like Prometheus, OpenTelemetry doesn’t provide a storage resolution and should be paired with a separate back-end system.

A fast breakdown:

• Prometheus can measure cumulative metrics, supplying you with a sum, whereas OpenTelemetry can signify metrics as deltas.
• Prometheus offers short-term knowledge and metrics storage whereas OTel doesn’t natively assist storage however will be paired with a separate storage resolution.
• OpenTelemetry collects metrics, logs and traces by utilizing a consolidated API through push or pull, and interprets them into a standard language, which Prometheus can not obtain. Prometheus gathers metrics by pulling knowledge from hosts and is primarily involved with gathering and storing time-series metrics.
• OTel is language agonistic and may translate metrics, giving builders extra flexibility. Prometheus makes use of PromQL to mixture knowledge and metrics.
• Prometheus offers net visualization for monitoring metrics coupled with customizable alerts. OpenTelemetry should be built-in with separate instruments for visualization.
• OTel permits metric values to be expressed as integers quite than floating-point numbers, which give extra correct worth representations and are simpler to know. Prometheus can not specific metrics as integers.

Your group’s wants will dictate which of those options is best for you. Should you want a extra holistic understanding of your knowledge, are working in advanced environments with distributed methods, and need extra flexibility, OpenTelemetry may be a extra acceptable resolution. That is additionally the case if it’s essential monitor logs and traces.

If it’s essential monitor particular person methods or operations, and are in search of alerting, storage and visualization fashions, Prometheus may be the proper possibility.

OpenTelemetry and Prometheus integration

The excellent news is that you just don’t essentially have to decide on one or the opposite; OpenTelemetry and Prometheus are appropriate platforms. OTel SDKs can gather metrics from Prometheus knowledge fashions and Prometheus helps OpenTelemetry metrics. Utilizing these platforms collectively offers you the perfect of each worlds and superior monitoring choices. For instance:

• When coupled, OTel and Prometheus present monitoring into advanced methods with real-time insights into your software environments.
• You’ll be able to pair OTel’s tracing and monitoring instruments with Prometheus’ alerting capabilities.
• Prometheus can deal with giant volumes of information. This characteristic coupled with OTel’s means to consolidate metrics, traces and logs right into a single interface creates larger effectivity when scaling methods and functions.
• PromQL can analyze the info that’s collected from OpenTelemetry’s knowledge captures and use it to create visualization fashions.

As well as, OpenTelemetry and Prometheus combine with IBM® Instana and IBM® Turbonomic to supply extra monitoring instruments. With Instana’s highly effective dependency map, upstream/downstream service correlation and full-stack visibility, OTel’s capabilities are optimized to be sure that all companies are instrumented. Instana delivers the identical nice expertise with OTel knowledge because it offers for each different knowledge supply, supplying you with the context that it’s essential rapidly discover and repair software points. With Turbonomic, you need to use Prometheus’ knowledge monitoring instruments to automate resourcing selections based mostly on real-time knowledge assortment. These integrations are optimized methods to advertise the well being of your software ecosystem and enhance general efficiency.

Explore IBM Instana OpenTelemetry

Explore Prometheus integration with IBM Turbonomic