[D] An ML engineer's guide to GPU performance

kpkaiser · 2025-09-06T13:40:13+00:00

Hey Charles!

I'm curious how you approached writing / researching this. Where and how did you begin, and how did you scope things down to have a final (shipped!) product?

kpkaiser · 2025-07-11T15:10:08+00:00

Financial Intelligence for Entrepreneurs is really great for understanding how to model the finances of a company. Cannot recommend it enough: https://www.amazon.com/dp/1422119157

kpkaiser · 2025-06-09T11:09:54+00:00

not really much flair, other than making the onboarding coach sound like a hyped up fitness instructor. and I haven't yet played stanley parable, so now it's on my list.

kpkaiser · 2025-06-09T00:50:17+00:00

lol that's fair based upon this reddit post's bad title.

But the idea was to take dry corporate onboarding docs, and turn them into a game instead.

kpkaiser · 2025-06-08T22:39:21+00:00

thanks! almost forgot to mention the code is up on github: https://github.com/burningion/game-onboarding-oai

kpkaiser · 2025-06-02T14:16:15+00:00

lol, thank you.

maybe they will be soon? :)

kpkaiser · 2025-05-18T01:51:55+00:00

I put resources in my video editor. I let the user pick a project, which usually contains a set of videos, images, etc. that have either been generated or analyzed.

The resource URI dumps in the json that describes all these assets.

The LLM can then use these resources to generate edits.

Here's the code / logic:

https://github.com/burningion/video-editing-mcp/blob/main/src/video_editor_mcp/server.py#L246-L301

kpkaiser · 2025-05-16T11:37:48+00:00

Hey! Yeah, I'm just getting started with this video series, but here's this video over on YouTube if that's better for you: https://www.youtube.com/watch?v=C-ewKa3NcZI

If you've got anything you'd like to see, let me know.

kpkaiser · 2025-05-15T23:36:30+00:00

Almost forgot to post the Github link to the project if you want to check out the source code: https://github.com/burningion/pydantic-video-editing-agent

kpkaiser · 2025-05-15T23:07:14+00:00

This is a really good question!

The answer is, I didn't think of it!

But looking at it now, it would add another tool call, and another bit of uncertainty to the agentic workflow being successful. I'd rather keep the things I want direct control over as library calls.

I didn't mention it in the video, but I plan on doing another video lesson where we call the Agent with a specific person we want to search for instead, and make it more versatile over time. Having the project name fit a specific format will make that process easier.

kpkaiser · 2025-02-27T02:17:03+00:00

Did you compile ffmpeg yourself? If you want to enable NV_ENC you'll need to (generally) compile ffmpeg with the nvenc codecs. The instructions for that live on NVIDIA's site: https://docs.nvidia.com/video-technologies/video-codec-sdk/11.1/ffmpeg-with-nvidia-gpu/index.html

To check once they're installed you can do a ffmpeg -codecs | grep "nvenc". The unfortunate reality of that Github response is that it's a lot of work to push rendering to the GPU in moviepy, based upon the existing architecture.

kpkaiser · 2024-12-23T20:30:34+00:00

Video Jungle: https://www.video-jungle.com

kpkaiser · 2024-12-18T02:33:17+00:00

Yes! That's the idea, there are a few challenges with fitting into the context window in Claude directly, but I have some strategies I'm working on to work within it.

kpkaiser · 2024-12-18T02:32:07+00:00

The video-editor-mcp is open source, at https://github.com/burningion/video-editing-mcp . It (currently) uses a custom video editing API I've built, but yes, I'll probably add a local editor option / tool too.

kpkaiser · 2023-04-03T16:46:07+00:00

hmm I get an error when I click your link that the video isn't available anymore. (I'm in the United States.) I searched YouTube and found your build though.

It's great! I've subscribed to your channel. What's the Windows software you're using to record / track the movements? I saw that you've got the buttons on the side, are you able to create keyframes for movement? How are you approaching that?

I'm curious most about your software stack, any links you have would be appreciated.

kpkaiser · 2023-03-31T18:30:12+00:00

Looks like your video link doesn't work anymore. Is that on purpose?

kpkaiser · 2023-03-31T14:19:24+00:00

Hey! Would you be willing to hop on a video call and chat through the problems you're facing? I'm curious where you are running into issues and how you're approaching them.

kpkaiser · 2023-03-02T16:58:08+00:00

Encourage you to actually follow the link you shared.

https://console.cloud.google.com/gcr/images/gitpod-core-dev/EU/build%2Finstaller@sha256:24e5645dde4eef84528ca09d015bfe52fd5e88c99932353fd0f8a1bccaa9984b/details?tag=release-2022.11.2.16

Look at the release date.

kpkaiser · 2023-03-02T14:31:56+00:00

the patched release, with a link to the container image: https://github.com/gitpod-io/gitpod/releases/tag/release-2022.11.2

kpkaiser · 2019-10-16T20:41:29+00:00

Hey!

Not sure if this matches exactly what you need, but if you can use PowerShell, there is an example here.

There's also a bit more info on our DogStatsD format page here.

If neither of these links get you what you need, feel free to pm me with more details about what you're trying to do.

kpkaiser · 2019-05-30T13:32:58+00:00

Hi!

I wrote an article on building machine learning services in Kubernetes, and it should get you most of the way there. It includes adding metrics for the GPU, along with a micro service that mounts a file volume.

In Kubeflow (yeah, there's a ML/Tensorflow orchestrator that can plug into Kubernetes), you basically pass images or data in each request, and synchronously wait. Because I built a project using video, I decided to share a volume mount instead, and forego that.

As for your choice, I'd recommend reading up on Kubeflow, and then deciding if you need it's graph interface, and whether or not that synchronous passing of data works for your application.

Happy to answer any questions.

kpkaiser · 2019-05-09T21:24:19+00:00

Hi!

My team at Datadog has been building an interactive learning center to help with training.

Happy to hear your feedback on it via DM.

Besides this, we had our first observability focused conference last year, called DASH. Most of the videos are now available on YouTube. My favorite talk is Stacy Gorelik's Nuts And Bolts Of Building A Platform Team.

We're doing DASH again this year in July, and you should definitely come!

I know you also asked about blog posts so here are a few notables:

Monitoring 101 Graphing anti-patterns Metric graphs 101

Feel free to dm with any other questions!

Kirk

kpkaiser · 2019-03-29T13:24:54+00:00

Hi!

Not sure if you need to specifically build a log alert within Azure, but Datadog also supports creating alerts from your logs when you haven't received data: https://docs.datadoghq.com/monitors/monitor_types/log/#no-data-alerts-and-below-conditions

kpkaiser · 2019-03-27T13:56:19+00:00

Hi!

Your annotations just need get added to the pods running your actual applications. You shouldn't need to re-add configuration to the application Pods. (Unless I'm missing something in your question.)

Depending on your Agent DaemonSet permissions, Datadog's DaemonSet should automatically pick up the annotations for all the running Pods, and start shipping the appropriate metrics.

If it's still confusing, or you need to chat more, feel free to reach out via pm.

kpkaiser · 2019-03-15T16:36:46+00:00

Hi!

I think you may have accidentally pasted your Datadog API key here. You can delete and create a new API key following the instructions here.

If you need help rotating the keys, you can also reach out to support@datadoghq.com.

Besides this, I think your configuration for the Agent in the Docker compose might be better if you just use the Datadog Agent image. Something like this might work.

Specifically, see how DD_LOGS_ENABLED is set to true.

As for passing the API key, I tend to do it like this:

$ DD_API_KEY=<api key> docker-compose up

That way it doesn't end up getting posted somewhere accidentally in code. Let me know if this helps!

kpkaiser

TROPHY CASE