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fixed some review comments
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Signed-off-by: Alexander Wert <[email protected]>
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AlexanderWert committed Jun 7, 2024
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Expand Up @@ -10,36 +10,34 @@ author:
Wert](https://github.com/AlexanderWert) (Elastic), [Morgan
McLean](https://github.com/mtwo) (Splunk), [Ryan
Perry](https://github.com/Rperry2174) (Grafana)
draft: true # TODO: remove this line once your post is ready to be published
# canonical_url: http://somewhere.else/ # TODO: if this blog post has been posted somewhere else already, uncomment & provide the canonical URL here.
issue: https://github.com/open-telemetry/community/issues/1918
sig: Profiling SIG
---

Following significant collaboration between
[Elastic](https://www.elastic.co/observability-labs/blog/elastic-donation-proposal-to-contribute-profiling-agent-to-opentelemetry)
and [OpenTelemetry's profiling community](/blog/2024/profiling/), which included a
thorough review process, we’re excited to announce that the OpenTelemetry
and [OpenTelemetry's profiling community](/blog/2024/profiling/), which included
a thorough review process, we’re excited to announce that the OpenTelemetry
project has accepted
[Elastic's donation of its continuous profiling agent](https://github.com/open-telemetry/community/issues/1918).

This marks a significant milestone in establishing profiling as a core telemetry
signal in OpenTelemetry. Elastic’s [eBPF based](https://ebpf.io/) profiling agent
observes code across different programming languages and runtimes, third-party
libraries, kernel operations, and system resources with low CPU and memory
overhead in production. Both, SREs and developers can now benefit from these
capabilities: quickly identifying performance bottlenecks, maximizing resource
utilization, reducing carbon footprint, and optimizing cloud spend.
signal in OpenTelemetry. Elastic’s [eBPF based](https://ebpf.io/) profiling
agent observes code across different programming languages and runtimes,
third-party libraries, kernel operations, and system resources with low CPU and
memory overhead in production. Both, SREs and developers can now benefit from
these capabilities: quickly identifying performance bottlenecks, maximizing
resource utilization, reducing carbon footprint, and optimizing cloud spend.

Elastic’s decision to contribute the project to OpenTelemetry was made to
accelerate OpenTelemetry’s mission and enable effective observability through
high-quality, portable telemetry. This collaboration also shows the commitment
to vendor neutrality and community-driven development enhancing the overall
profiling and observability ecosystems.

The Elastic team would like to thank the OpenTelemetry community for the great
and constructive cooperation on the donation proposal. We look forward to
jointly establishing continuous profiling as an integral part of OpenTelemetry.
The donation happened through a great and constructive cooperation between
Elastic and the OpenTelemetry community. We look forward to jointly establishing
continuous profiling as an integral part of OpenTelemetry.

With today’s acceptance, Elastic’s continuous profiling agent will be
contributed to OpenTelemetry. This agent will now be jointly supported by both
Expand All @@ -55,9 +53,9 @@ companies:

[Continuous profiling](https://www.cncf.io/blog/2022/05/31/what-is-continuous-profiling/)
is a technique used to understand the behavior of a software application by
collecting information about its execution. This includes tracking the duration
of function calls, memory usage, CPU usage, and other system resources along
with associated metadata.
collecting information about its execution over time. This includes tracking the
duration of function calls, memory usage, CPU usage, and other system resources
along with associated metadata.

## Benefits of Continuous Profiling

Expand All @@ -77,16 +75,17 @@ cost, making code and infrastructure improvements easier.

## Contribution of comprehensive profiling abilities

The continuous profiling agent, that Elastic is donating, is [based on eBPF](https://ebpf.io/) and by that a
whole system, always-on solution that observes code and third-party libraries,
kernel operations, and other code you don't own. It eliminates the need for code
instrumentation (run-time/bytecode), recompilation, or service restarts with low
overhead, low CPU (~1%), and memory usage in production environments.
The continuous profiling agent, that Elastic is donating, is
[based on eBPF](https://ebpf.io/) and by that a whole system, always-on solution
that observes code and third-party libraries, kernel operations, and other code
you don't own. It eliminates the need for code instrumentation
(run-time/bytecode), recompilation, or service restarts with low overhead, low
CPU (~1%), and memory usage in production environments.

The Elastic profiling agent facilitates identifying non-optimal code paths,
The donated profiling agent facilitates identifying non-optimal code paths,
uncovering "unknown unknowns", and provides comprehensive visibility into the
runtime behavior of all applications. Elastic’s continuous profiling agent
provides support for a wide range of runtimes and languages, such as:
runtime behavior of all applications. The continuous profiling agent provides
support for a wide range of runtimes and languages, such as:

- C/C++
- Rust
Expand Down Expand Up @@ -144,7 +143,7 @@ With these benefits, SREs, developers, and DevOps, can now manage the overall
application’s efficiency on the cloud while ensuring their engineering teams
optimize it.

As the next step, Elastic and the OpenTelemetry profiling SIG will jointly work
on integrating the donated agent into OpenTelemetry's components ecosystem. We
look forward to providing a fully integrated and usable version of the new
OpenTelemetry eBPF profiling agent to the users, soon.
As the next step, the OpenTelemetry profiling SIG, that Elastic is a part of,
will jointly work on integrating the donated agent into OpenTelemetry's
components ecosystem. We look forward to providing a fully integrated and usable
version of the new OpenTelemetry eBPF profiling agent to the users, soon.

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