antho | jsonnet package manager written in go | Continuous Deployment library

This is the first time I have been trying to install managed Anthos into one of the clusters in GKE. I admit I do not fully understand the full process of installation and troubleshooting I have already done.

It looks like a managed service has failed to install. When I run:

I am trying to load an apparmor profile I created using GKE and some of the following instructions.

To apply the created app armor profile I followed this instructions:

https://cloud.google.com/container-optimized-os/docs/how-to/secure-apparmor#creating_a_custom_security_profile

which is just the apparmor parser applied to the node[s], and some follow up instructions to apply this same profile creation during restart of the node. Basically is running the following line:

I'm running a 2 GKE private cluster set up in europe-west2. I have a dedicated config cluster for MCI and a worker cluster for workloads. Both clusters are registered to Anthos hub and ingress feat enabled on config cluster. In addition worker cluster runs latest ASM 1.12.2.

As far as MCI is concerned my deployment is 'standard' as in based on available docs (ie https://cloud.google.com/architecture/distributed-services-on-gke-private-using-anthos-service-mesh#configure-multi-cluster-ingress, terraform-example-foundation repo etc).

Everything works but I'm hitting an intermittent connectivity issue no matter how many times I redeploy entire stack. My eyes are bleeding from staring at logging dashboard. I ran out of dots to connect.

I'm probing some endpoints presented from my cluster which most of the time returns 200 with following logged under resource.type="http_load_balancer":

We are using GKE to host our apps with Anthos, our default node pool ils set to autoscale but I noticed that out of 5 running pods, only 2 are hosting our actual services.

All the others are running internal services like this:

The issue with that is that there's not enough room for running our own services. I guess these are vital for the cluster otherwise the cluster would autoscale and the nodes would get removed.

What would be the best approach to solve this issue? I thought of upgrading the nodes machine type to allow more resources per node and have more room within them and thus have less running nodes, but I wanted to make sure I was not simply missing something on how GKE works.

I've been now digging for quite some time but it seems that would be my only option.

I'm trying to close the browser then reopen it without getting any errors.
I tried doing driver.close() then webdriver.Chrome(executable_path=driver_path, options=option) to reopen it, but it brings up selenium.common.exceptions.InvalidSessionIdException: Message: invalid session id
If you're wondering why I want to do this, I'm tyring to clear all cache and cookies. I thought maybe delete_all_cookies might work but it doesn't.

You should be able to recreative everything with this:

I've been reading the Google Cloud documentation about hybrid GKE cluster with Connect or completely on prem with GKE on-prem and VMWare.

However, I see that GKE with Connect you can manage the on-prem Kubernetes cluster from Google Cloud dashboard.

But, what I am trying to find, is, to mantain a hybrid cluster with GKE mixing on-prem and cloud nodes. Graphical example:

For the above solution, the master node is managed by GCloud, but the ideal solution is to manage multiple node masters (High availability) on cloud and nodes on prem. Graphical example:

Is it possible to apply some or both of the proposed solutions on Google Cloud with GKE?

For instance, if I do something like

I have a list of items with the same class and a button for each that toggles offline class when clicked. I've used the for loop and forEach loop to iterate through the list using an event listener "click" then check if the item class list contains "offline".If it contains offline the button innerText changes to offline as well as the styling. Now the issue is when I reload the page everything resets. I've tried using local storage but it restores the offline class to every item.

When I open an ipynb file, I just see a json file. I tested with all files of :
https://github.com/MicrosoftLearning/mslearn-ai900.git

I have on my machine :

• Python 3.9.6 installed
• Installed with pip command : jupyterlab, notebook and voila

On Visual Studio Code (version 1.59.0) :

• Python 3.9.6 64-bit is the current interpreter.
• I can create a new notebook : "CTRL+SHIFT+P --> Jupyter : Create new blank notebook" and I saw on the down-right "Jupyter Server:local". I can execute code : print("Hello, Python!"), but when I try to save file, I have this error :
  Failed to register 'Untitled-1' : File name file:///*ThePathToSave*/Test.ipynb is not supported by Jupyter.

Extensions installed :

• Jupyter v2021.8.1195043623
• Pylance v2021.8.1
• Python v2021.8.1105858891

List of kernel : (command) jupyter kernelspec list