overcommit | A fully configurable and extendable Git hook manager | Frontend Utils library

I'm new at Kubernetes and trying to do a simple project to connect MySQL and PhpMyAdmin using Kubernetes on my Ubuntu 20.04. I created the components needed and here is the components.

mysql.yaml

I am trying to determine a reliable setup to use with K8S to scale one of my deployments using an HPA and an autoscaler. I want to minimize the amount of resources overcommitted but allow it to scale up as needed.

I have a deployment that is managing a REST API service. Most of the time the service will have very low usage (0m-5m cpu). But periodically through the day or week it will spike to much higher usage on the order of 5-10 CPUs (5000m-10000m).

My initial pass as configuring this is:

• Deployment: 1 replica

I was trying out my cluster in EKS with managed node group. I am able to attach CSI to the cluster and able to create storageClass and persistentVolumeClaim, but when ever I try to deploy a deployment. The pods seems to be not associating with the specified nodes.

the pod file

I am currently coding a server application that basically processes workloads for clients. Based on the actual workload, the server could use huge amounts of memory. Target Platforms are Windows and Linux, the code is written in c++.

However, i am not very familiar with linux programming and during some testing today i run into some strange crashes. As it turns out, those were related to overcommited memory.

The code i have written is fairly robust and can handle out-of-memory situations (at least on Windows systems) by splitting and queueing its workloads whenever it runs into bad_alloc exceptions. Refactoring all the code to cope with errors that could occur due to overcommited memory would be a complete nightmare.

So, i was wondering if i could turn off overcommit for my process and child threads. I already found an old question here Link (at stackoverflow) that answers this as no, but realizing that this is a 10 year old answer i was wondering if that might have changed?

If its still not possible to turn this of application wise, is there at least a way of detecting the current setting for it inside my application?

Thanks in advance!

I have some function which uses image processing functions which are itself multithreaded. I distribute many of those function calls on a dask cluster. First, I started a scheduler on a host: dask-scheduler. The I started the workers: dask-worker --nthreads 1 --memory-limit 0.9 tcp://scheduler:8786.

The python code looks similar to this:

I'm trying to deploy a Prometheus nodeexporter Daemonset in my AWS EKS K8s cluster.

I have overcommitted (based on my current development skill) to deliver to a volunteer group I'm involved with some code that I originally thought was going to be a simple task. In essence, because of COVID, a "raffle drawing" that we used to do in-person is now being done electronically. What I was hoping to do was simulate a "wheel-of-fortune" approach that would pull names from the list of raffle ticket holders into a second list — but only momentarily (300 ms) as a 'visible' teaser — and then remove it and then add another name, again, as a teaser, and so on until a set number of iterations has taken place (let's say 60). I've been successful in getting this to work but the "data removal" setTimeout function is operating in an odd manner. Basically, sometimes one item appears and then disappears but sometimes two items end up on the list before they both disappear. I am trying to make this a 1:1 relationship: one item appears as the previous item disappears.

Am I going about this the wrong way and, if so, what suggestions would you make to set me on the right track? Thank you for any help you can provide. I know this is just a "game" but I've actually learned a lot along the way. Here is my code so far ...

My local machine kubernetes cluster running fine yesterday util I install some component, my slave1 and slave2 only have 4G for each, and I check the free memory only have 100MB+, then I stop the VM and increase the KVM virtual machine memory to 8GB. And recheck the free memory to make sure it have 2GB+ free for each node. Now the slave1 and slave2 node not running fine,this is the node status:

After clean installation of Kubernetes cluster with 3 nodes (2 Master & 3 Node) i.e., Masters are also assigned to be worker node.

After successful installation, I got the below roles for the node. Where Node role is missing for the masters as shown.