oss-fuzz VS cluster-api

> because the ifunc code was breaking with all sorts of build options and obviously caused many problems with various sanitizers

for example, https://github.com/google/oss-fuzz/pull/10667

Have you tried Googles grpc fuzzer?

https://github.com/google/oss-fuzz/blob/master/projects/grpc...

https://www.fda.gov/medical-devices/digital-health-center-ex...

oss-fuzz: https://github.com/google/oss-fuzz :

> We support the libFuzzer, AFL++, and Honggfuzz fuzzing engines in combination with Sanitizers, as well as ClusterFuzz, a distributed fuzzer execution environment and reporting tool.

> Currently, OSS-Fuzz supports C/C++, Rust, Go, Python, Java/JVM, and JavaScript code. Other languages supported by LLVM may work too. OSS-Fuzz supports fuzzing x86_64 and i386 builds.

I love fuzzing as a technique and use it quite regularly, but running AFL++ on even a single program occupies all threads of a high end AMD server for weeks. I'm running it locally so only paying for the electricity. If it was a cloud instance it would cost a small fortune. I think this is a reason it is not used more widely.

I will note that Google have a programme for doing fuzz testing on open source projects using computer from their cloud: https://google.github.io/oss-fuzz/

Yes, mosh has fuzz tests in oss-fuzz [1].

[1] https://github.com/google/oss-fuzz/tree/master/projects/mosh

We will explore how Jazzer is used to automatically generate malicious inputs for Java programs, and how it compares to Symflower, which can automatically generate unit tests to uncover bugs and errors in your code. With the help of Jazzer, many bugs - some of them even in the OpenJDK - were found already. Also, as of March 2021, Jazzer is officially part of OSS-Fuzz, Google's cloud fuzzing engine. It should be noted that Jazzer is a pure "bug detection" utility that finds reproducers for errors in user code. Symflower can do the same, but provides additional functionalities to boost developer productivity, like generating high coverage unit tests and providing test templates for the software developer or tester.

In this blog post, we will demonstrate how easy and fast it is to deploy Sveltos on an RKE2 cluster with the help of ArgoCD, register two RKE2 Cluster API (CAPI) clusters and create a ClusterProfile to deploy Prometheus and Grafana Helm charts down the managed CAPI clusters.

4. Having moved to a container orchestrator, all of my nodes are immutable. Hardware and VM instances _can_ be born magically into existence. Nearly all infra providers support [cluster-api](https://cluster-api.sigs.k8s.io/). Network infrastructure can now be managed with TF, so I go that route.

## Linux curl -L https://github.com/kubernetes-sigs/cluster-api/releases/download/v1.4.4/clusterctl-linux-amd64 -o clusterctl sudo install -o root -g root -m 0755 clusterctl /usr/local/bin/clusterctl ## Mac brew install clusterctl

Did you ever try CAPI? https://github.com/kubernetes-sigs/cluster-api

You might find interesting the capi-rancher-import k8s operator we use in Sylva, it would adopt in Rancher server the Cluster API created k8s clusters (with bootstrap provider kubeadm or even rke2 - you can lookup CAPBR for the latter). I understand your clusters are not created by Cluster API, so if you could move the workloads/resources to new clusters created by Cluster API, this can come handy. (Adoption of non-CAPI clusters into CAPI is not yet a standard practice, more in https://github.com/kubernetes-sigs/cluster-api/issues/7776)

Most of the comments have mentioned older tools like kubespray, Ansible, Rancher etc. I would suggest the cloud native way using ClusterAPI or use a tool that relies on ClusterAPI in the backend called Talos

Cluster API

Sveltos is a powerful open source project that makes managing Kubernetes add-ons a breeze. It automatically discovers ClusterAPI powered clusters and allows you to easily register any other cluster (like GKE). Then, it seamlessly manages Kubernetes add-ons across all your clusters.