What are the basics of eBPF and Beyla?

What do these two technologies have to do with one another, and what’s the difference between Beyla and something like the prometheus node exporter?

eBPF (Extended Berkeley Packet Filter) and Grafana Beyla are closely related technologies, with eBPF serving as the foundational technology that enables Beyla's functionality.

Basics of eBPF

  • eBPF Overview: eBPF is a technology that allows you to run custom programs in the Linux kernel without changing kernel source code or loading kernel modules. It provides a way to attach programs to various points in the kernel, such as system calls, network events, and more.
  • Safety and Efficiency: eBPF programs are verified for safety, ensuring they do not crash the kernel. They are compiled Just-In-Time (JIT) for efficient execution on the host architecture.
  • Use Cases: eBPF is used for a variety of purposes, including observability, security, and networking. It can monitor system performance, enforce security policies, and more.

Basics of Grafana Beyla

  • What is Beyla?: Grafana Beyla is an open-source tool that leverages eBPF for auto-instrumentation of applications. It provides observability by capturing metrics and traces without requiring changes to application code.
  • Functionality: Beyla can automatically instrument applications written in various languages (e.g., Go, C/C++, Rust, Python, Java) to collect metrics like requests per second, errors, and durations. It exports data in OpenTelemetry and Prometheus formats.
  • Deployment: Beyla can be deployed as a DaemonSet in Kubernetes, allowing it to instrument all services on a node with minimal setup.

Difference Between Beyla and Prometheus Node Exporter

  • Purpose: The Prometheus Node Exporter is designed to expose hardware and OS-level metrics (e.g., CPU, memory, disk usage) for Prometheus to scrape. It focuses on infrastructure monitoring.
  • Scope: Beyla, on the other hand, focuses on application-level observability. It captures application-specific metrics and traces, providing insights into application performance and behavior.
  • Implementation: While Node Exporter collects metrics from the system, Beyla uses eBPF to hook into application and kernel events, providing a deeper level of observability without modifying application code.

In summary, eBPF is the underlying technology that enables Beyla to perform its auto-instrumentation magic, while Beyla itself is a tool that provides application-level observability. The Prometheus Node Exporter is more focused on infrastructure metrics, making it complementary to Beyla's application-centric approach.

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What’s the status of eBPF implementations across various operating systems, and are there any details on Beyla’s support of these?

eBPF is primarily a Linux-based technology, and its implementation is most mature on Linux systems. Here's a breakdown of its status across various operating systems and how it relates to Grafana Beyla:

eBPF Implementations Across Operating Systems

  1. Linux:
  2. eBPF is natively supported in Linux and has been integrated into the kernel for several years. It is widely used for observability, security, and networking tasks. The Linux kernel version 5.8 or higher is generally required for full eBPF functionality, with BPF Type Format (BTF) enabled for enhanced capabilities.
  3. Grafana Beyla is designed to work on Linux systems, leveraging eBPF to provide application-level observability without modifying application code.

  4. Windows:

  5. eBPF on Windows is still in development. There is an ongoing project to bring eBPF capabilities to the Windows platform, but it is not yet as mature or widely adopted as on Linux.
  6. As of now, Grafana Beyla does not support Windows, as it relies on the Linux kernel's eBPF capabilities.

  7. Other Operating Systems:

  8. eBPF is not natively supported on other operating systems like macOS or BSD. Efforts to port eBPF to these systems are limited and not as advanced as on Linux.
  9. Consequently, Grafana Beyla is not available for these platforms.

Beyla’s Support and Deployment

  • Linux Focus: Beyla is specifically designed for Linux environments, taking advantage of the robust eBPF support in the Linux kernel to provide zero-code instrumentation for applications.
  • Kubernetes and Docker: Beyla can be deployed as a DaemonSet in Kubernetes clusters or used in Docker containers, making it versatile for cloud-native environments.
  • Open Source and Vendor Neutral: Beyla is open source and uses the OpenTelemetry protocol, allowing it to integrate with various observability backends, including Grafana Cloud.

In summary, while eBPF is primarily a Linux technology, ongoing efforts may expand its reach to other operating systems in the future. For now, Grafana Beyla is focused on leveraging eBPF on Linux to provide powerful, no-code observability solutions.

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Give me a quick rundown of how to instrument a python app with Beyla

To instrument a Python application with Grafana Beyla, you can follow these general steps. Beyla leverages eBPF to provide auto-instrumentation, which means you don't need to modify your application code. Here's a quick rundown:

Prerequisites

  1. Linux Environment: Ensure your application is running on a Linux system with a kernel version 5.8 or higher, as eBPF is primarily supported on Linux.
  2. Beyla Installation: Install Grafana Beyla on your system. This can be done by deploying it as a DaemonSet in Kubernetes or running it directly on your Linux host.

Steps to Instrument a Python App

  1. Deploy Beyla:
  2. If you're using Kubernetes, deploy Beyla as a DaemonSet. This will allow it to automatically instrument all services running on the nodes.
  3. For standalone Linux systems, you can run Beyla directly on the host where your Python application is running.

  4. Configure Beyla:

  5. Ensure Beyla is configured to capture the necessary metrics and traces. This typically involves setting up Beyla to listen for HTTP/gRPC traffic and other relevant events in your application.

  6. Run Your Application:

  7. Start your Python application as you normally would. Beyla will automatically attach eBPF probes to capture metrics and traces related to your application's network interactions and other events.

  8. Export and Visualize Data:

  9. Beyla exports data in OpenTelemetry and Prometheus formats. You can configure it to send this data to a backend like Grafana Cloud or any other observability platform that supports these formats.
  10. Use Grafana dashboards to visualize the collected metrics and traces, providing insights into your application's performance and behavior.

Key Benefits

  • No Code Changes: Beyla provides zero-code instrumentation, meaning you don't need to modify your Python application's source code.
  • Vendor Neutral: The data is exported in standard formats, allowing integration with various observability backends.
  • Comprehensive Metrics: Capture RED (Rate, Errors, Duration) metrics and traces to monitor your application's health and performance.

By following these steps, you can quickly set up observability for your Python applications using Grafana Beyla, leveraging the power of eBPF for efficient and effective monitoring.

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how to install beyla on a linux host such as a VM and enable as a system service?

To install Grafana Beyla on a Linux host, such as a virtual machine (VM), and enable it as a system service, you can follow these steps:

Prerequisites

  1. Linux Environment: Ensure your Linux system is running a kernel version 5.8 or higher, as eBPF requires this for full functionality.
  2. Administrative Privileges: You will need sudo privileges or CAP_SYS_ADMIN permissions to install and run Beyla.

Installation Steps

  1. Download and Install Beyla:
  2. You can install Beyla using Docker, Helm, or directly from the Grafana Cloud integrations tile. For a standalone Linux host, using Docker is a straightforward approach.

Using Docker: sh docker run -e BEYLA_PROMETHEUS_PORT=9090 -e BEYLA_EXECUTABLE_NAME=./your_app_executable \ -p 9090:9090 --privileged --pid host grafana/beyla:latest

  1. Enable Beyla as a System Service:
  2. To run Beyla as a system service, you can create a systemd service file.

Create a systemd service file: sh sudo nano /etc/systemd/system/beyla.service

Add the following content to the file: ```ini [Unit] Description=Grafana Beyla Service After=network.target

[Service] ExecStart=/usr/bin/docker run -e BEYLA_PROMETHEUS_PORT=9090 -e BEYLA_EXECUTABLE_NAME=./your_app_executable \ -p 9090:9090 --privileged --pid host grafana/beyla:latest Restart=always User=root

[Install] WantedBy=multi-user.target ```

  1. Start and Enable the Service:
  2. Reload the systemd daemon to recognize the new service file: sh sudo systemctl daemon-reload

  3. Start the Beyla service: sh sudo systemctl start beyla

  4. Enable the service to start on boot: sh sudo systemctl enable beyla

Verification

  • To verify that Beyla is running, you can check the status of the service: sh sudo systemctl status beyla

  • You can also test the metrics endpoint to ensure Beyla is capturing data: sh curl http://localhost:9090/metrics

This setup will allow Beyla to run as a system service on your Linux host, automatically starting on boot and providing continuous observability for your applications.

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