Adding upstream version 1.29.0.upstream/1.29.0

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

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+<!--
+title: "Monitor, troubleshoot, and debug applications with eBPF metrics"
+description: "Use Netdata's built-in eBPF metrics collector to monitor, troubleshoot, and debug your custom application using low-level kernel feedback."
+image: /img/seo/guides/troubleshoot/monitor-debug-applications-ebpf.png
+custom_edit_url: https://github.com/netdata/netdata/edit/master/docs/guides/troubleshoot/monitor-debug-applications-ebpf.md
+-->
+
+# Monitor, troubleshoot, and debug applications with eBPF metrics
+
+When trying to troubleshoot or debug a finicky application, there's no such thing as too much information. At Netdata,
+we developed programs that connect to the [_extended Berkeley Packet Filter_ (eBPF) virtual
+machine](/collectors/ebpf.plugin/README.md) to help you see exactly how specific applications are interacting with the
+Linux kernel. With these charts, you can root out bugs, discover optimizations, diagnose memory leaks, and much more.
+
+This means you can see exactly how often, and in what volume, the application creates processes, opens files, writes to
+filesystem using virtual filesystem (VFS) functions, and much more. Even better, the eBPF collector gathers metrics at
+an _event frequency_, which is even faster than Netdata's beloved 1-second granularity. When you troubleshoot and debug
+applications with eBPF, rest assured you miss not even the smallest meaningful event.
+
+Using this guide, you'll learn the fundamentals of setting up Netdata to give you kernel-level metrics from your
+application so that you can monitor, troubleshoot, and debug to your heart's content.
+
+## Configure `apps.plugin` to recognize your custom application
+
+To start troubleshooting an application with eBPF metrics, you need to ensure your Netdata dashboard collects and
+displays those metrics independent from any other process.
+
+You can use the `apps_groups.conf` file to configure which applications appear in charts generated by
+[`apps.plugin`](/collectors/apps.plugin/README.md). Once you edit this file and create a new group for the application
+you want to monitor, you can see how it's interacting with the Linux kernel via real-time eBPF metrics.
+
+Let's assume you have an application that runs on the process `custom-app`. To monitor eBPF metrics for that application
+separate from any others, you need to create a new group in `apps_groups.conf` and associate that process name with it.
+
+Open the `apps_groups.conf` file in your Netdata configuration directory.
+
+```bash
+cd /etc/netdata   # Replace this path with your Netdata config directory
+sudo ./edit-config apps_groups.conf
+```
+
+Scroll down past the explanatory comments and stop when you see `# NETDATA processes accounting`. Above that, paste in
+the following text, which creates a new `dev` group with the `custom-app` process. Replace `custom-app` with the name of
+your application's process name.
+
+Your file should now look like this:
+
+```conf
+...
+# -----------------------------------------------------------------------------
+# Custom applications to monitor with apps.plugin and ebpf.plugin
+
+dev: custom-app
+
+# -----------------------------------------------------------------------------
+# NETDATA processes accounting
+...
+```
+
+Restart Netdata with `sudo service netdata restart` or the appropriate method for your system to begin seeing metrics
+for this particular group+process. You can also add additional processes to the same group.
+
+You can set up `apps_groups.conf` to more show more precise eBPF metrics for any application or service running on your
+system, even if it's a standard package like Redis, Apache, or any other [application/service Netdata collects
+from](/collectors/COLLECTORS.md).
+
+```conf
+# -----------------------------------------------------------------------------
+# Custom applications to monitor with apps.plugin and ebpf.plugin
+
+dev: custom-app
+database: *redis*
+apache: *apache*
+
+# -----------------------------------------------------------------------------
+# NETDATA processes accounting
+...
+```
+
+Now that you have `apps_groups.conf` set up to monitor your application/service, you can also set up the eBPF collector
+to show other charts that will help you debug and troubleshoot how it interacts with the Linux kernel.
+
+## Configure the eBPF collector to monitor errors
+
+The eBPF collector has [two possible modes](/collectors/ebpf.plugin#ebpf-load-mode): `entry` and `return`. The default
+is `entry`, and only monitors calls to kernel functions, but the `return` also monitors and charts _whether these calls
+return in error_.
+
+Let's turn on the `return` mode for more granularity when debugging Firefox's behavior.
+
+```bash
+cd /etc/netdata   # Replace this path with your Netdata config directory
+sudo ./edit-config ebpf.conf
+```
+
+Replace `entry` with `return`:
+
+```conf
+[global]
+    ebpf load mode = return
+    disable apps = no
+
+[ebpf programs]
+    process = yes
+    network viewer = yes
+```
+
+Restart Netdata with `sudo service netdata restart` or the appropriate method for your system.
+
+## Get familiar with per-application eBPF metrics and charts
+
+Visit the Netdata dashboard at `http://NODE:19999`, replacing `NODE` with the hostname or IP of the system you're using
+to monitor this application. Scroll down to the **Applications** section. These charts now feature a `firefox` dimension
+with metrics specific to that process.
+
+Pay particular attention to the charts in the **ebpf file**, **ebpf syscall**, **ebpf process**, and **ebpf net**
+sub-sections. These charts are populated by low-level Linux kernel metrics thanks to eBPF, and showcase the volume of
+calls to open/close files, call functions like `do_fork`, IO activity on the VFS, and much more.
+
+See the [eBPF collector documentation](/collectors/ebpf.plugin/README.md#integration-with-appsplugin) for the full list
+of per-application charts.
+
+Let's show some examples of how you can first identify normal eBPF patterns, then use that knowledge to identify
+anomalies in a few simulated scenarios.
+
+For example, the following screenshot shows the number of open files, failures to open files, and closed files on a
+Debian 10 system. The first spike is from configuring/compiling a small C program, then from running Apache's `ab` tool
+to benchmark an Apache web server.
+
+![An example of eBPF
+charts](https://user-images.githubusercontent.com/1153921/85311677-a8380c80-b46a-11ea-9735-babaedc22fdb.png)
+
+In these charts, you can see first a spike in syscalls to open and close files from the configure/build process,
+followed by a similar spike from the Apache benchmark.
+
+> 👋 Don't forget that you can view chart data directly via Netdata's API!
+> 
+> For example, open your browser and navigate to `http://NODE:19999/api/v1/data?chart=apps.file_open`, replacing `NODE`
+> with the IP address or hostname of your Agent. The API returns JSON of that chart's dimensions and metrics, which you
+> can use in other operations.
+>
+> To see other charts, replace `apps.file_open` with the context of the chart you want to see data for.
+>
+> To see all the API options, visit our [Swagger
+> documentation](https://editor.swagger.io/?url=https://raw.githubusercontent.com/netdata/netdata/master/web/api/netdata-swagger.yaml)
+> and look under the **/data** section.
+
+## Troubleshoot and debug applications with eBPF
+
+The actual method of troubleshooting and debugging any application with Netdata's eBPF metrics depends on the
+application, its place within your stack, and the type of issue you're trying to root cause. This guide won't be able to
+explain how to troubleshoot _any_ application with eBPF metrics, but it should give you some ideas on how to start with
+your own systems.
+
+The value of using Netdata to collect and visualize eBPF metrics is that you don't have to rely on existing (complex)
+command line eBPF programs or, even worse, write your own eBPF program to get the information you need.
+
+Let's walk through some scenarios where you might find value in eBPF metrics.
+
+### Benchmark application performance
+
+You can use eBPF metrics to profile the performance of your applications, whether they're custom or a standard Linux
+service, like a web server or database.
+
+For example, look at the charts below. The first spike represents running a Redis benchmark _without_ pipelining
+(`redis-benchmark -n 1000000 -t set,get -q`). The second spike represents the same benchmark _with_ pipelining
+(`redis-benchmark -n 1000000 -t set,get -q -P 16`).
+
+![Screenshot of eBPF metrics during a Redis
+benchmark](https://user-images.githubusercontent.com/1153921/84916168-91607700-b072-11ea-8fec-b76df89315aa.png)
+
+The performance optimization is clear from the speed at which the benchmark finished (the horizontal length of the
+spike) and the reduced write/read syscalls and bytes written to disk.
+
+You can run similar performance benchmarks against any application, view the results on a Linux kernel level, and
+continuously improve the performance of your infrastructure.
+
+### Inspect for leaking file descriptors
+
+If your application runs fine and then only crashes after a few hours, leaking file descriptors may be to blame.
+
+Check the **Number of open files (apps.file_open)** and **Files closed (apps.file_closed)** for discrepancies. These
+metrics should be more or less equal. If they diverge, with more open files than closed, your application may not be
+closing file descriptors properly.
+
+See, for example, the volume of files opened and closed by `apps.plugin` itself. Because the eBPF collector is
+monitoring these syscalls at an event level, you can see at any given second that the open and closed numbers as equal.
+
+This isn't to say Netdata is _perfect_, but at least `apps.plugin` doesn't have a file descriptor problem.
+
+![Screenshot of open and closed file
+descriptors](https://user-images.githubusercontent.com/1153921/84816048-c57f5d80-afc8-11ea-9684-d2b923d5d2b2.png)
+
+### Pin down syscall failures
+
+If you enabled the eBPF collector's `return` mode as mentioned [in a previous
+step](#configure-the-ebpf-collector-to-monitor-errors), you can view charts related to how often a given application's
+syscalls return in failure.
+
+By understanding when these failures happen, and when, you might be able to diagnose a bug in your application.
+
+To diagnose potential issues with an application, look at the **Fails to open files (apps.file_open_error)**, **Fails to
+close files (apps.file_close_error)**, **Fails to write (apps.vfs_write_error)**, and **Fails to read
+(apps.vfs_read_error)** charts for failed syscalls coming from your application. If you see any, look to the surrounding
+charts for anomalies at the same time frame, or correlate with other activity in the application or on the system to get
+closer to the root cause.
+
+### Investigate zombie processes
+
+Look for the trio of **Process started (apps.process_create)**, **Threads started (apps.thread_create)**, and **Tasks
+closed (apps.task_close)** charts to investigate situations where an application inadvertently leaves [zombie
+processes](https://en.wikipedia.org/wiki/Zombie_process).
+
+These processes, which are terminated and don't use up system resources, can still cause issues if your system runs out
+of available PIDs to allocate.
+
+For example, the chart below demonstrates a [zombie factory
+program](https://www.refining-linux.org/archives/7-Dr.-Frankenlinux-or-how-to-create-zombie-processes.html) in action.
+
+![Screenshot of eBPF showing evidence of a zombie
+process](https://user-images.githubusercontent.com/1153921/84831957-27e45800-afe1-11ea-9fe2-fdd910915366.png)
+
+Starting at 14:51:49, Netdata sees the `zombie` group creating one new process every second, but no closed tasks. This
+continues for roughly 30 seconds, at which point the factory program was killed with `SIGINT`, which results in the 31
+closed tasks in the subsequent second.
+
+Zombie processes may not be catastrophic, but if you're developing an application on Linux, you should eliminate them.
+If a service in your stack creates them, you should consider filing a bug report.
+
+## View eBPF metrics in Netdata Cloud
+
+You can also show per-application eBPF metrics in Netdata Cloud. This could be particularly useful if you're running the
+same application on multiple systems and want to correlate how it performs on each target, or if you want to share your
+findings with someone else on your team.
+
+If you don't already have a Netdata Cloud account, go [sign in](https://app.netdata.cloud) and get started for free.
+Read the [get started with Cloud guide](https://learn.netdata.cloud/docs/cloud/get-started) for a walkthrough of node
+claiming and other fundamentals.
+
+Once you've added one or more nodes to a Space in Netdata Cloud, you can see aggregated eBPF metrics in the [Overview
+dashboard](/docs/visualize/overview-infrastructure.md) under the same **Applications** or **eBPF** sections that you
+find on the local Agent dashboard. Or, [create new dashboards](/docs/visualize/create-dashboards.md) using eBPF metrics
+from any number of distributed nodes to see how your application interacts with multiple Linux kernels on multiple Linux
+systems. 
+
+Now that you can see eBPF metrics in Netdata Cloud, you can [invite your
+team](https://learn.netdata.cloud/docs/cloud/manage/invite-your-team) and share your findings with others.
+
+## What's next?
+
+Debugging and troubleshooting an application takes a special combination of practice, experience, and sheer luck. With
+Netdata's eBPF metrics to back you up, you can rest assured that you see every minute detail of how your application
+interacts with the Linux kernel.
+
+If you're still trying to wrap your head around what we offer, be sure to read up on our accompanying documentation and
+other resources on eBPF monitoring with Netdata:
+
+-   [eBPF collector](/collectors/ebpf.plugin/README.md)
+-   [eBPF's integration with `apps.plugin`](/collectors/apps.plugin/README.md#integration-with-ebpf)
+-   [Linux eBPF monitoring with Netdata](https://www.netdata.cloud/blog/linux-ebpf-monitoring-with-netdata/)
+
+The scenarios described above are just the beginning when it comes to troubleshooting with eBPF metrics. We're excited
+to explore others and see what our community dreams up. If you have other use cases, whether simulated or real-world,
+we'd love to hear them: [info@netdata.cloud](mailto:info@netdata.cloud).
+
+Happy troubleshooting!
+
+[![analytics](https://www.google-analytics.com/collect?v=1&aip=1&t=pageview&_s=1&ds=github&dr=https%3A%2F%2Fgithub.com%2Fnetdata%2Fnetdata&dl=https%3A%2F%2Fmy-netdata.io%2Fgithub%2Fdocs%2Fguides%troubleshoot%2Fmonitor-debug-applications-ebpf.md&_u=MAC~&cid=5792dfd7-8dc4-476b-af31-da2fdb9f93d2&tid=UA-64295674-3)](<>)