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You need to understand how renderPlot works. It uses the R png function first to create a png and then sends it to the client browser. When the data of the plot changes, this png is recreated. So, replot part of the png is not possible. So adding points to an existing plot will always use the time of slow points + new points, so under the current shiny mechanism, it is not possible not to recalculate these slow points. A possible option is to use plotly with proxy . It is made of HTML and Javascript, so yes, you can do it with partial updating. See the link for details, not repeating here. For my personal experience, it is fast not so fast as milliseconds-level as you want.

So here I have a smart trick for you: why do we update on the same plot? We can use one plot as background and it is slow, but we only render it one time, and we will never touch it again. Then we update another plot that has only a few points and we stack this plot on top of the slow plot.

Here is how:

1. add some CSS tricks to do the stacking
2. rendering the slow plot
3. rendering the the quick plot with transparency

First note that if you apply base function diff to the months columns, you will get one column less but transposed.

Does it make sense to iterate through layers like this and keep adding files (to some target, does not matter for now) and deleting the added files in case they are found with a .wh prefix? Or am I totally off and is there a much better way?

There is a much better way, you do not want to reimplement (with worse performances) what Docker already does. The main reason is that Docker uses a mount filesystem called overlay2 by default that allows the creation of images and containers leveraging the concepts of a Union Filesystem: lowerdir, upperdir, workdir and mergeddir.

What you might not expect is that you can reproduce an image or container building process using the mount command available in almost any Unix-like machine.

I found a very interesting article that explains how the overlay storage system works and how Docker internally uses it, I highly recommend the reading.

Actually, if you have read the article, the solution is there: you can mount the image data you have by docker inspecting its LowerDir, UpperDir, WorkDir and by setting the merged dir to a custom path. To make the process simpler, you can run a script like:

An approach could be the following:

Try adding a JS aggregate function callback, instead of using the built-in aggregation:

Adding all your items to the price list is going to cause them all to be in one column. Instead, store separate lists for each column, in a dict, like this (name them whatever you want):

It depends on whether you want requests to be routed through your ingress controller or not.

Requests sent to the full URL configured in your Ingress resource will be processed by your ingress controller. The controller itself — NGINX in this case — will proxy the request to the Service. The request will then be routed to a Pod.

Sending the request directly to the Service’s URL simply skips your ingress controller. The request is directly routed to a Pod.

The trade offs between the two options depend on your setup.

Sending requests through your ingress controller will increase request latency and resource consumption. If your ingress controller does nothing other than route requests, I would recommend sending requests directly to the Service.

However, if you use your ingress controller for other purposes, like authentication, monitoring, logging, or tracing, then you may prefer that the controller process internal requests.

For example, on some of my clusters I use the NGINX ingress controller to measure request latency and track HTTP response statuses. I route requests between apps running in the same cluster through the ingress controller in order to have that information available. I pay the cost of increased latency and resource usage in order to have improved observability.

Whether the trade offs are worth it in your case depends on you. If your ingress controller does nothing more that basic routing, then my recommendation is to skip it entirely. If it does more, then you need to weigh the pros and cons of routing requests through it.

Posting comment as the community wiki answer for better visibility

This issue was due to kubelet certificate expired and fixed following these steps. If someone faces this issue, make sure /var/lib/kubelet/pki/kubelet-client-current.pem certificate and key values are base64 encoded when placing on /etc/kubernetes/kubelet.conf

the solution to my problem was answered in this article about all PWA strategies: https://jakearchibald.com/2014/offline-cookbook/#network-falling-back-to-cache

and what I had to do was add this piece of code to the end of my service-worker.js file: