Enabling the Full-Host Profiler
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The Full-Host Profiler is an eBPF-based profiling solution built on OpenTelemetry that sends profiling data to Datadog using the Datadog Agent. It supports symbolication for compiled languages and is optimized for containerized environments such as Docker and Kubernetes.
Use cases
The Full-Host Profiler is particularly valuable for:
- Profiling open source software components that aren’t instrumented with Datadog’s tracing libraries.
- Analyzing performance across multi-language processes and runtimes.
- Identifying resource bottlenecks at the host level, including detection of noisy neighbor processes.
Requirements
For a summary of the minimum and recommended runtime and tracer versions across all languages, read Supported Language and Tracer Versions.
- Supported operating systems
- Linux
- Supported architecture
amd64
or arm64
processors- Serverless
full host
is not supported on serverless platforms, such as AWS Lambda.- Debugging information
- Symbols should be available locally or can be uploaded in CI with
datadog-ci
Installation
The Full-Host Profiler is distributed as a standalone executable.
Container environments
For hosts running containerized workloads, Datadog recommends running the profiler inside a container:
Non-container environments
For hosts without container runtimes, follow the instructions for running directly on the host.
Configuration
Local symbol upload (Experimental)
For compiled languages (C/C++/Rust/Go), the profiler can upload local symbols to Datadog for symbolication when unstripped binaries are available.
To enable local symbol upload:
- Set the
DD_HOST_PROFILING_EXPERIMENTAL_UPLOAD_SYMBOLS=true
. - Provide a Datadog API key through the
DD_API_KEY
environment variable. - Provide a Datadog application key through the
DD_APP_KEY
environment variable. - Set the
DD_SITE
environment variable to your Datadog site. Your site is:
Build
To build the Full-Host Profiler directly on your machine, run:
What’s next?
After installing the Full-Host Profiler, see the Getting Started with Profiler to learn how to use Continuous Profiler to identify and fix performance problems.
Further reading
Additional helpful documentation, links, and articles: