ഫാൽക്കോ പതിപ്പിന്റെ ഡോക്യൂമെന്റഷൻ ആണ് നിങ്ങൾ കാണുന്നത്: v0.36.2

Falco v0.36.2 ഈ ഡോക്യുമെന്റേഷൻ സജീവമായി പരിപാലിക്കപ്പെടുന്നില്ല. നിങ്ങൾ നിലവിൽ കാണുന്ന പതിപ്പ് ഒരു സ്റ്റാറ്റിക് സ്നാപ്പ്ഷോട്ടാണ്. ഏറ്റവും പുതിയ ഡോക്യൂമെന്റഷന് വേണ്ടി latest version.

Deployment

Installing Falco on a Kubernetes Cluster

The guides - Download, Install, Running - focused on the systemd service deployment method, detailing how to primarily install and run Falco directly on the host. Additionally, these guides explored the alternative options of installing and running Falco within a container, with a driver installed on the underlying host.

The container deployment option is particularly enticing for Kubernetes settings, which will be discussed in more detail now.

Falco is designed to run once per instance of the Linux kernel, regardless of whether the deployment is on a bare-metal host or a virtual machine (VM). In third-party managed Kubernetes platforms (EKS, GKS, AKS, etc.), the latter option (VM) is prevalent.

Falco leverages the shared kernel in containerized environments like Kubernetes by installing a kernel driver on the underlying host.

This means that deploying Falco within a container, with the kernel driver installed on the host, is functionally equivalent to deploying it directly on the Linux host. This setup allows seamless monitoring of both host and container workloads without the need for sidecars.

Kubernetes

Falco can be deployed in Kubernetes as a DaemonSet to monitor the system events of every container in each pod and the underlying host itself on each node of your cluster.

Helm

One of the easiest ways to install Falco in Kubernetes is by using Helm. The Falco community supports an official helm chart, and documentation on how to use it can be found here. The chart can be easily configured to fit the most common installation requirements.

DaemonSet

Falco can also be installed in Kubernetes manually. In this case, you are in charge of providing the DaemonSet object YAML definition and deploying it in your cluster. For further details, you can find an example here.

Docker Deprecation in Kubernetes

Since version 1.20, Kubernetes started deprecating the Docker runtime in favor of runtimes that use the Container Runtime Interface (CRI). You can find further details on kubernetes.io. In the versions of Kubernetes where Docker has been deprecated, Falco will not be able to obtain container information from the Docker socket anymore.

Starting from version 0.15.0, Falco supports CRI-compatible runtimes such as containerd or CRI-O. A custom container runtime socket path can be specified by using --cri command line argument of Falco, or by setting the containerd.socket parameter in the official Helm chart. By default, Falco tries to use the containerd socket at /run/containerd/containerd.sock.

Falco attempts to use all the supported container runtimes it finds on the system, and queries all of them in cascade when trying to resolve container information. If Falco somehow fails to retrieve the required information, it will keep running as usual but some container-related fields might be shown as not available (<NA>). For example, in a scenario where Kubernetes uses containerd but dockerd is also running on the same machine, Falco will first query dockerd, and will eventually fallback to containerd if the required information is not found.

Accordingly, if you run a recent version of Falco you should not be affected by the Docker deprecation. If you use a CRI runtime and notice that container-related fields are shown as <NA> in Falco alerts, make sure that the --cri argument is properly set. If you run a version of Falco prior to v0.15.0, and wish to use it with a CRI-compatible runtime, you might consider updating Falco to a newer version.

As many Falco use cases are out of the scope of Kubernetes, Falco will keep supporting Docker as a container runtime. Generally, Falco will keep looking for the Docker socket to obtain container information. If not available, it will automatically attempt using the other supported container runtimes, which include the CRI-compatible ones.