Blog post on Elastic's donation of the eBPF profiling agent

content/en/_index.md

@@ -12,16 +12,16 @@ developer_note:
 show_banner: true
 limit_banner: 2 # Default to 2, adjust as needed
 banners:
+  - message:
+      '<i class="fas fa-bullhorn"></i> We are happy to announce that Elastic''s
+      donation of the [**eBPF profiling agent has been
+      accepted**](/blog/2024/elastic-contributes-continuous-profiling-agent)!'
+    to: 2024-07-25
   - message:
       '<i class="fas fa-bullhorn"></i> Join us for [**OTel Community Day** on
       June
       25th](https://events.linuxfoundation.org/open-telemetry-community-day/)!'
     to: 2024-06-25
-  - message:
-      '<i class="fas fa-bullhorn"></i> Help improve OTel and Prometheus
-      interoperability: [complete our
-      survey](https://forms.gle/bZAG9f7udoJsjZUG9) by May 31'
-    to: 2024-05-31
 ---
 
 <div class="d-none"><a rel="me" href="https://fosstodon.org/@opentelemetry"></a></div>

content/en/blog/2024/elastic-contributes-continuous-profiling-agent.md

@@ -0,0 +1,141 @@
+---
+title: Elastic Contributes its Continuous Profiling Agent to OpenTelemetry
+linkTitle: Elastic Contributes Profiling Agent # Mandatory, make sure that your short title.
+date: 2024-06-06 # Put the current date, we will keep the date updated until your PR is merged
+# prettier-ignore
+cSpell:ignore: Bahubali Christos Dmitry Filimonov Geisendörfer Halliday Kalkanis Shetti
+author:
+  >- # If you have only one author, then add the single name on this line in quotes.
+  [Bahubali Shetti](https://github.com/bshetti) (Elastic), [Alexander
+  Wert](https://github.com/AlexanderWert) (Elastic), [Morgan
+  McLean](https://github.com/mtwo) (Splunk), [Ryan
+  Perry](https://github.com/Rperry2174) (Grafana)
+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
+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.
+
+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 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
+Elastic’s team as well as a diverse set of official maintainers from different
+companies:
+
+- Dmitry Filimonov (Grafana Labs)
+- Felix Geisendörfer (Datadog)
+- Jonathan Halliday (Red Hat)
+- Christos Kalkanis (Elastic)
+
+## What is continuous profiling?
+
+[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 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
+
+Traditional profiling solutions, typically used for one-off, development time
+optimizations, can have significant drawbacks limiting adoption in production
+environments:
+
+- Significant cost and performance overhead due to code instrumentation
+- Disruptive service restarts
+- Inability to get visibility into third-party libraries
+
+Continuous profiling, however, runs in the background with minimal overhead,
+providing real-time, actionable insights without the need to replicate issues in
+separate environments.
+
+This allows SREs, DevOps, and developers to see how code affects performance and
+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 donated profiling agent facilitates identifying non-optimal code paths,
+uncovering "unknown unknowns", and provides comprehensive visibility into the
+runtime behavior of all applications. The continuous profiling agent provides
+support for a wide range of runtimes and languages, such as:
+
+- C/C++
+- Rust
+- Zig
+- Go
+- Java
+- Python
+- Ruby
+- PHP
+- Node.js / V8
+- Perl
+- .NET
+
+## Benefits to OpenTelemetry
+
+This contribution not only boosts the standardization of continuous profiling
+for observability but also accelerates its adoption as a key signal in
+OpenTelemetry. Customers benefit from a vendor-agnostic method of collecting
+profiling data correlating it with existing signals, like tracing, metrics, and
+logs, opening new potential for observability insights and a more efficient
+troubleshooting experience.
+
+### User Benefits of OpenTelemetry Profiling
+
+OpenTelemetry-based continuous profiling unlocks the following possibilities for
+users:
+
+- Continuous profiling data compliments the existing signals (traces, metrics
+  and logs) by providing detailed, code-level insights on the services'
+  behavior.
+
+- Seamless correlation with other OpenTelemetry signals such as traces,
+  increasing fidelity and investigatory depth.
+
+- Estimate environmental impact: Combining profiling data with OpenTelemetry's
+  resource information (i.e. resource attributes) allows to derive insights into
+  the services' carbon footprint.
+
+- Through a detailed breakdown of services' resource utilization, profiling data
+  provides actionable information on performance optimization opportunities.
+
+- Improved vendor neutrality: a vendor-agnostic eBPF-based profiling agent
+  removes the need to rely on proprietary agents to collect profiling telemetry.
+
+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, 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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