Now more than ever, customers expect relevant and personalized digital experiences, no matter where they are, and on the device of their choosing. That’s why technology leaders around the world tell us that there’s no greater priority than digital transformation. The reasons are clear: Digital technologies represent radically new ways of delivering value to customers, disrupting competitive landscapes, and changing the underlying economics of markets.
Rapid innovation prompts the need for better solutions
Technological change is nothing new, but this round of change is happening at a rate faster than ever before. To deliver on these digital transformations, new approaches have emerged to enable faster innovation, such as Cloud technologies, containers, and orchestration engines like Kubernetes, microservices, serverless, and DevOps with CI/CD automation, SRE, and on-call developers to name a few.
Technology complexity reaches new heights
A consequence of these rapid changes is increased technical complexity, which is why making sense of such highly dynamic and distributed systems presents new challenges. This was the bedrock for the recent emergence of Observability and where OpenTelemetry comes in to help.
OpenTelemetry will manage that complexity and diversity
OpenTelemetry is a vendor-neutral standard way to collect telemetry data for applications, their supporting infrastructures, and services. It’s been incubating as a Cloud Native Computing Foundation sandbox project since May 2019 with the merger of OpenCensus and OpenTracing projects. Some components reached the beta stage in March 2020 and others are expected to reach a 1.0 GA status by the end of the year. Spans and traces are the most advanced for now, automated instrumentation, metrics, and additional languages are in active development, and logs are planned for a later date.
OpenTelemetry is an important milestone, making it easier for providers and users alike to collect data from a broader set of systems and get a more complete picture of how applications behave and why. Today’s challenge shouldn’t be about getting telemetry data –whether that’s metrics, events, logs, or traces (also known as MELT) — but to relate how the infrastructure (whether compute, storage, or network) and supporting services (as service meshes) influence the application’s health, and ultimately, the user experiences delivered and the impact they have on business.
That’s what AppDynamics has been focusing on for years: understanding where problems come from, why they happen, and relate how technical problems impact user experiences and business outcomes to set the right priorities of actions. As a consequence, we welcome OpenTelemetry as a data ingestion standard which will make it even easier to get visibility into a broader set of systems, and enrich our traditional AI and ML capabilities to help make sense of that vast array of data.
How does OpenTelemetry work (in a nutshell)?
OpenTelemetry covers many components, including the following:
- APIs are used to instrument your code to generate traces, i.e. the components parts that make calls and exchange information with other parts. This can be performed via code change or auto-instrumentation agents (which is less mature for now). Most libraries are expected to come with OpenTelemetry capabilities out of the box in the not-too-distant future.
- SDKs to collect such data and pass it to the processing and export stages.
- In-process exporters, running with the application, can translate the telemetry data into custom formats and send directly or through a collector to back-ends, whether Open Source as Jaeger or Zipkin, or from commercial providers. The in-process exporter approach is language-specific and is the main approach used so far since was the first one to be mature.
- The out-of-process collector is used for data filtering, aggregation, batching, and communication with various telemetry backends. This communication is performed either via vendor-specific exporters or standard OpenTelemetry OTLP exporters.
We’re working on making AppDynamics’ backend OTLP compliant and support both:
- Our recommended out-of-process collector standard so our customers can use the bundled OpenTelemetry OTLP exporters to minimize the risk of relying on multiple specific in-process exporters which might get out of sync with the rapidly evolving OpenTelemetry standard and to support all existing and upcoming languages at once.
- In-process standard OTLP exporters if you don’t have the possibility to deploy a dedicated collector.
This is obviously an oversimplified introduction; see the OpenTelemetry documentation for more details.
OpenTelemetry will accelerate innovation through standardization
By alleviating the burden of collecting data from diverse technologies, OpenTelemetry will allow observability and monitoring solution providers to focus more of their efforts on capabilities to relate the data across domains (i.e., understand how a compute element interacts with the storage and network ones), understand the impact on the application health, and ultimately, the delivered user experiences and business outcomes.
We’re excited to partner with AWS because we believe AWS Distro for OpenTelemetry will enable customers to make the leap to OpenTelemetry thanks to AWS’ secure, production-ready, AWS-supported distribution of the CNCF OpenTelemetry project. Customers can now use AWS Distro for OpenTelemetry to collect traces and metrics and send them to compliant monitoring back-ends, including AppDynamics, Amazon CloudWatch and AWS X-Ray. This further reinforces a very bright future for OpenTelemetry as it will help accelerate the adoption of community-driven common standards and a shared open-source implementation for the benefits of all customers.
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