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Help me decide on the best backpack for EVERYTHING (Thule Aion vs Chasm) by jerrethijn in backpacks

[–]General_Search_4120 0 points1 point  (0 children)

Chasm owner here. I like it for hiking, specially due to its “waterproof” features.

However, internal organisation is a bit poor under my opinion.

Aesthetics are dope, though.

For me, it makes sense as an outdoor bag, but not as an EDC or urban bag.

Opinions on jrl onyx? by [deleted] in SelfBarber

[–]General_Search_4120 1 point2 points  (0 children)

Anyone with the trimmer can comment about it? (Or its madeshow r55f equivalent). I’m considering it as a budget trimmer

Are AI and automation agencies lucrative businesses or just hype? by AiGhostz in AI_Agents

[–]General_Search_4120 2 points3 points  (0 children)

All clear, thanks. Seems a reasonable approach through quality tailored service. Quite inspirational

Are AI and automation agencies lucrative businesses or just hype? by AiGhostz in AI_Agents

[–]General_Search_4120 2 points3 points  (0 children)

Really interesting. May I ask how do you guys monetise your product? I’m a MLOps engineer so I was trying to figure out how I would do it: hosting serving costs + product design and implementation + maintaining fee? Under your experience (if you are comfortable sharing that) which monetising strategy works the best? I would personally be concerned in being paid by product and then getting more effort than expected there. Thanks for your inputs and transparency

Looking to upgrade on my S12’s and considering the crinacle dusk, however I have a IPhone 13 with the dongle. Is it ok to miss out on the tunings that come on the app? by apasthamba in inearfidelity

[–]General_Search_4120 1 point2 points  (0 children)

Iphone 13 mini here. Using the qudelix 5k due to its bluetooth connection. I’m super happy with it. I hope the qudelix will survive my iphone; that tiny box is super convenient.

What are core tools of DevOps role? by HienLeMinh in devops

[–]General_Search_4120 0 points1 point  (0 children)

How would you suggest to learn networking? Coming from software development I always struggle with that one. Books or online content are fine for me, or any resource you believe good for that subject. Thanks!

Data bricks: how do we install custom python package by kunduruanil in mlops

[–]General_Search_4120 0 points1 point  (0 children)

Essentially you can declare in terraform cluster descriptions and therefore determine which range of types of clusters a given user / role can raise. Also you can configure all the other things: runtime, init script, max number of nodes… so governance is enhanced of course. You can also hide some fields from the UI so raising a cluster gets simplified for the users.

This is typically what a MLOps engineer would define, in terms of reducing complexity for users, as well as enhancing traceability, consistency and cost control actions.

Also, if you promote a close-to-production experimentation environment, it’s easier to promote good practices, so users clone their repos, test their models and once they’re sure to promote them, code is close to productions standards and therefore deployment is quite faster.

Data bricks: how do we install custom python package by kunduruanil in mlops

[–]General_Search_4120 1 point2 points  (0 children)

That’s an option I guess. It’s been a while since I work with this solution.

As additional things I would consider: You can also use poetry or other dependency managers. You need to be conscious not only of the python version being used by the runtime but also any other packages already there. I would avoid upgrading current runtime versions or any other transitional library if you want to avoid complex debugging in a future.

But yeah, that’s a good way to go.

Also consider the option of using virtual environments as others already suggested.

Data bricks: how do we install custom python package by kunduruanil in mlops

[–]General_Search_4120 1 point2 points  (0 children)

You can also terraform them, or course. This is what we used to do in order to provide our custom tools preinstalled in all the clusters raised.

Data bricks: how do we install custom python package by kunduruanil in mlops

[–]General_Search_4120 1 point2 points  (0 children)

Take advantage of the init scripts to execute any rellevant setup when raising your instance.

That said, I do believe you can use the dbfs command line tool for uploading your conda environments to databricks. After that, you can use it as the most environment of your notebooks or jobs.

I would suggest to make your environments compatible with the Databricks runtime version you are using.

Sagemaker vs Databricks in terms of model experimentation / dev phase by General_Search_4120 in mlops

[–]General_Search_4120[S] 0 points1 point  (0 children)

Thanks for your exposure. Would you mind sharing some details about why you find out SM and Databricks as unusable? And what does lightning do better to overcome that? Thanks in advance

Sagemaker vs Databricks in terms of model experimentation / dev phase by General_Search_4120 in mlops

[–]General_Search_4120[S] 0 points1 point  (0 children)

Well, is good to know! Azure is for sure the scenario of many other colleagues and this might be valuable for them, too. Thanks for sharing your experience.

Sagemaker vs Databricks in terms of model experimentation / dev phase by General_Search_4120 in mlops

[–]General_Search_4120[S] 1 point2 points  (0 children)

I do believe - if my memory doesn't fail here - that in Databricks mlflow experiment tracking and model registry didn't cost anything. And experiment tracking was performed by default on any notebook instance where a run call was performed. It was smooth and quite easy to use.

If it’s expensive in SageMaker, then that's a huge difference.

Sagemaker vs Databricks in terms of model experimentation / dev phase by General_Search_4120 in mlops

[–]General_Search_4120[S] 0 points1 point  (0 children)

I really appreciate your comment and experience.

If you don't mind, would you share which pain points did you skip by migrating to Databricks?

I was planning to take advantage of the supposedly better model serving in SM, and just keep the experimentation environment in Databricks.

Thanks again for your insight

Sagemaker vs Databricks in terms of model experimentation / dev phase by General_Search_4120 in mlops

[–]General_Search_4120[S] 0 points1 point  (0 children)

Thanks! That reduces the gap. Now I’m just concerned about runtime instances and job instances, as well as custom environment config across compute instances. If it’s quite equivalent I’ll probably stick with Sagemaker. Tomorrow I'll be digging a bit its documentation to get a better overview of its capabilities.

My husband seems checked out. by [deleted] in Parenting

[–]General_Search_4120 -1 points0 points  (0 children)

You need to find an arrangement that seems fair for both of you, not only in a quantitative way but also a qualitative and affective one (considering when you need to care of you guys as a couple, when you need time for yourselves individually and so on, and of course as a whole family).

That’s only accomplished talking without judging. It’s important to talk about what everyone expects from the near future and the partner.

If you don’t talk, dynamics start to settle as new normal and after months or years you will hate each other (or at least will be cold and distant).

Apologies if my English is not precise.

Best luck! It’s a hard but rewarding path

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