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@@ -113,6 +113,7 @@ words: | |
- overridable | ||
- outro | ||
- packagist | ||
- pageinfo | ||
- Paixão | ||
- parentbased | ||
- Pavol | ||
|
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name: i18n | ||
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on: | ||
pull_request: | ||
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jobs: | ||
i18n-check: | ||
name: I18N check | ||
runs-on: ubuntu-latest | ||
steps: | ||
- uses: actions/checkout@v4 | ||
with: | ||
fetch-depth: 0 # all | ||
- run: scripts/i18n-check.sh -u | ||
- run: .github/workflows/scripts/i18n-check-helper.sh |
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#!/bin/bash -e | ||
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echo "For localization docs, see https://opentelemetry.io/docs/contributing/localization" | ||
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CHANGES=`git status --porcelain` | ||
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if [[ -z $CHANGES ]]; then | ||
echo "All localization pages have the requisit commit hash. <3" | ||
exit; | ||
fi | ||
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cat <<EOS | ||
Some i18n pages are missing the 'default_lang_commit' front matter field. | ||
To fix this in your local development environment, run | ||
scripts/i18n-check.sh -u | ||
and commit the changes for your locale. Here are the list of pages that | ||
need to be updated: | ||
--- | ||
EOS | ||
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echo "$CHANGES" | ||
echo "---" | ||
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exit 1 |
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--- | ||
title: {{ replaceRE "[-_]" " " .Name | title }} | ||
date: {{ .Date | time.Format "2006-01-02" }} # Start date (optional) | ||
expiryDate: {{ dateFormat "2006-01-02" .Date }} # End date (optional) | ||
--- | ||
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||
<!-- For more detail about announcements, see | ||
https://opentelemetry.io/docs/contributing/#announcement-management | ||
Erase this comment once you are done including the announcement text below. --> |
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--- | ||
title: Announcements | ||
cascade: | ||
type: docs | ||
--- |
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--- | ||
title: eBPF | ||
date: 2024-06-07 | ||
expiryDate: 2024-07-25 | ||
--- | ||
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Elastic's **eBPF profiling agent** is now part of OTel. | ||
[Learn more](/blog/2024/elastic-contributes-continuous-profiling-agent) |
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--- | ||
title: OTel Community Day | ||
date: 2024-04-05 | ||
expiryDate: 2024-06-25 | ||
weight: -1 # top | ||
--- | ||
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<i class="fas fa-bullhorn"></i> Join us for | ||
[**OTel Community Day**](https://events.linuxfoundation.org/open-telemetry-community-day/) | ||
on June 25th |
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6
content/en/blog/2024/cve-2024-36129/index.md → content/en/blog/2024/cve-2024-36129.md
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140 changes: 140 additions & 0 deletions
140
content/en/blog/2024/elastic-contributes-continuous-profiling-agent.md
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--- | ||
title: Elastic Contributes its Continuous Profiling Agent to OpenTelemetry | ||
linkTitle: Elastic Contributes Profiling Agent | ||
date: 2024-06-07 | ||
# prettier-ignore | ||
cSpell:ignore: Bahubali Christos Dmitry Filimonov Geisendörfer Halliday Kalkanis Shetti | ||
author: > | ||
[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 | ||
--- | ||
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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). | ||
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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. | ||
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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. | ||
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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. | ||
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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: | ||
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- Dmitry Filimonov (Grafana Labs) | ||
- Felix Geisendörfer (Datadog) | ||
- Jonathan Halliday (Red Hat) | ||
- Christos Kalkanis (Elastic) | ||
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## What is continuous profiling? | ||
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[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. | ||
|
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## Benefits of Continuous Profiling | ||
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Traditional profiling solutions, typically used for one-off, development time | ||
optimizations, can have significant drawbacks limiting adoption in production | ||
environments: | ||
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- Significant cost and performance overhead due to code instrumentation | ||
- Disruptive service restarts | ||
- Inability to get visibility into third-party libraries | ||
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Continuous profiling, however, runs in the background with minimal overhead, | ||
providing real-time, actionable insights without the need to replicate issues in | ||
separate environments. | ||
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This allows SREs, DevOps, and developers to see how code affects performance and | ||
cost, making code and infrastructure improvements easier. | ||
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## Contribution of comprehensive profiling abilities | ||
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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. | ||
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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: | ||
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- C/C++ | ||
- Rust | ||
- Zig | ||
- Go | ||
- Java | ||
- Python | ||
- Ruby | ||
- PHP | ||
- Node.js / V8 | ||
- Perl | ||
- .NET | ||
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## Benefits to OpenTelemetry | ||
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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. | ||
|
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### User benefits of OpenTelemetry Profiling | ||
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OpenTelemetry-based continuous profiling unlocks the following possibilities for | ||
users: | ||
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- Continuous profiling data compliments the existing signals (traces, metrics | ||
and logs) by providing detailed, code-level insights on the services' | ||
behavior. | ||
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- Seamless correlation with other OpenTelemetry signals such as traces, | ||
increasing fidelity and investigatory depth. | ||
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- Estimate environmental impact: Combining profiling data with OpenTelemetry's | ||
resource information (i.e. resource attributes) allows to derive insights into | ||
the services' carbon footprint. | ||
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- Through a detailed breakdown of services' resource utilization, profiling data | ||
provides actionable information on performance optimization opportunities. | ||
|
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- Improved vendor neutrality: a vendor-agnostic eBPF-based profiling agent | ||
removes the need to rely on proprietary agents to collect profiling telemetry. | ||
|
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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. | ||
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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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