OpenTelemetry (link resides outside ibm.com) is an open-source observability framework with a collection of software development kits (SDKs), vendor-neutral or vendor-agnostic APIs, and tools for instrumentation. This technology can generate, collect, export, and instrument telemetry data to analyze your platform’s behavior and performance. Opentelemetry is also known as OTel.
IT groups and DevOps professionals must use instrumentation to create an observable system in cloud-native applications. Instrumentation code used to be varied, making it difficult for companies to change backends. It was hard to switch tools because they would need to reinstrument their code and reconfigure new agents to send telemetry data to their new devices.
After seeing the need for a standardized system, Cloud Native Computing Foundation (CNCF) (link resides outside ibm.com) sponsored the OpenTelemetry project to create a standardized way to send, collect, and transfer telemetry data to backend observability platforms. OpenTelemetry was born from combining the distributed tracing technology of OpenCensus (link resides outside ibm.com) and OpenTracing (link resides outside ibm.com) into one tool.
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To gain a deeper understanding of OpenTelemetry, let’s deep dive into what telemetry data is and how your organization can utilize it.
A key part of successful application performance is having observability through access to data. IT professionals use telemetry data to determine the health and performance of your application.
OpenTelemetry creates a standard for collecting and transferring telemetry data in cloud-native applications. These metrics can then be analyzed and monitored by your organization to improve your platforms.
Telemetry data is composed primarily of outputs collected from logs, metrics, and traces. These are often referred to as the three pillars of observability.
Metrics: Metrics are typically where you’ll see the first sign of an issue occurring in your system. These give you numerical values or sets of measurements that show your resource utilization and application performance. The three main types of metrics are delta, gauge, and cumulative.
Traces: Traces evaluate how requests move through a server in distributed cloud environments. It looks at this by monitoring how an operation transfers from node to node. Traces can only provide limited visibility into application health because it is solely focused on application layers. To get a complete picture of what is going on in your system, it’s also essential to monitor your metrics and logs.
Collecting telemetry data is an important step in the OpenTelemetry and observability process. Next, we’ll discuss how OpenTelemetry is used for in a dispersed cloud environment.
OpenTelemetry’s primary goal is to collect and export telemetry data. OTel assists DevOps professionals in debugging and managing applications. Once they have this data, they can make informed coding decisions and adjust as their organization continues to change and grow.
There are three main ways OpenTelemetry is used in DevOps to solve application problems:
Prioritizes Requests: OpenTelemetry has the unique ability to create a tier system for requests within your system. This is important because competing requests will be correctly prioritized.
Track Resource Usage: Capture requests between microservers to attribute resource usage by groups. IT professionals can track this resource usage between shared systems.
Observability of Microservices: Monitor the health of your application by recording telemetry data from applications in distributed systems. Having this information will help your team optimize and run your application correctly.
Each of these features helps organizations solve common errors when running applications across cloud-native systems.
There are many benefits to using OpenTelemetry for your open-source projects. Each of these benefits will help improve observability and monitoring. These benefits explain why OTel is the future of application performance monitoring (APM).
Consistency: The main benefit of OpenTelemetry is the consistency of collecting OpenTelemetry data across different applications. A lack of a unified standard creates problems for Dev Ops professionals and SREs. OTel now saves you time, gives you more observability, and collects telemetry data without changing your code. The broad adoption of this technology across organizations has made it easier to implement container deployment. This is similar to the mass embracement of Kubernetes as the standard for container orchestration.
Simplified Observability: OTel simplifies observability because it can collect telemetry data without changing code or metadata. Now developers don’t have to stick to specific backends or vendors.
Flexibility: Developers can monitor performance metrics and usage from any web browser or device. The convenience of observing your application from any location makes it easier to track your analytics in real-time.
Overall, OpenTelemetry's primary benefit is that it can help you achieve your optimal business goals. This software enables your organization to understand and fix issues that could negatively impact your customer experience. OpenTelemetry gives you the data needed to stop a problem in its tracks before your service is interrupted.
In a nutshell, OpenTelemetry works by combining an API, SDK, Collector, and automatic instrumentation to pull data and send it to its target system. In order to make your system more agnostic, there are several steps it needs to take using these components.
An API will create traces by instrumenting your code and dictating which metrics need to be collected. Your SDK will then gather, translate, and sends that data to the next stage. The OpenTelemetry Collector processes the data, filters it, and exports it to a supported backend.
There are many moving pieces when it comes to making Otel’s data collection successful. Here is an in-depth explanation of the four major components of OpenTelemetry:
SDK: DevOps professionals can use language SDKs to allow OTel APIs to generate telemetry data in the language of their choice. After they have generated this data, you can export the information to your desired backend. OpenTelemetry SDKs make it possible to connect common libraries' manual instrumentation with applications’ manual instrumentation. SDKs are the bridge between APIs and collectors. It stands for software development kit.
Collector: The OpenTelemetry Collector is made up of exporters, processors, aggregates, and receivers for telemetry data. It can support Prometheus, OpenTelemetry Protocol (OTLP), Jaeger, Zipkin and other proprietary tools. The collector can take telemetry data and send it to multiple observability backends. Lastly, it can assist your organization as a processing pipeline and with filtering your data before exporting. This helps with troubleshooting potential issues more quickly.
Automatic Instrumentation: It’s important to note that automatic instrumentation differs between varying programming languages. Auto-instrumentation takes a lot of tedious manual coding out of the equation.
Each of these components makes up the framework for why OpenTelemetry is a winning addition to monitoring your application.
OpenTracing is an open-source project that assists developers in instrumenting code for distributed tracing through vendor-neutral APIs. This is beneficial because it doesn’t force you to stick with one particular vendor or product.
This project is available in nine different languages, including Ruby, Java, and Python. DevOps and IT professionals can use distributed tracing to optimize and debug software architecture code. It is especially useful when dealing with microservices.
The CNCF created OpenTelemetry by merging OpenTracing and OpenCensus into one platform. There have been over 10,000 contributions from 300 companies since the project was deployed. The encouragement of broad collaboration and additions has created access to a large set of instrumentation that is unmatched in the industry.
If you were going to choose between the two open-source platforms, it would be wise to go with OpenTelemetry since it has more capabilities.
OpenTelemetry is changing the landscape of observability. Similar to Kubernetes becoming the standard for container orchestration, OpenTelemetry is becoming widely adopted for observability. Opentelemetry’s adoption and popularity will continue to soar because of the OpenTelemetry benefits we stated above.
The OpenTelemetry project teams continue to work on stabilizing the software’s core components and creating automated instrumentation. Once it is out of the beta stage, it’s projected to take over the observability framework in cloud-native ecosystems.
The bottom line is that OpenTelemetry is not an observability backend but a tool that makes collecting and sending telemetry data more streamlined. Instana is the final piece of this equation as the observability tool. OpenTelemetry formats and SDKs can be a migration path for legacy systems and unsupported technologies.
Our organization is committed to fully embracing OTel to help you achieve business goals through simplified data collection. We are working on giving end users the same visibility that they get with Instana’s AutoTrace through our integration with OpenTelemetry. Try our Sandbox for free today.
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