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Thursday, June 30, 2022
Wednesday, June 29, 2022
New top story on Hacker News: Show HN: Ploomber Cloud (YC W22) – run notebooks at scale without infrastructure
Show HN: Ploomber Cloud (YC W22) – run notebooks at scale without infrastructure
25 by idomi | 3 comments on Hacker News.
Hi, we’re Ido & Eduardo, the founders of Ploomber. We’re launching Ploomber Cloud today, a service that allows data scientists to scale their work from their laptops to the cloud. Our open-source users ( https://ift.tt/ejsi5SZ ) usually start their work on their laptops; however, often, their local environment falls short, and they need more resources. Typical use cases run out of memory or optimize models to squeeze out the best performance. Ploomber Cloud eases this transition by allowing users to quickly move their existing projects into the cloud without extra configurations. Furthermore, users can request custom resources for specific tasks (vCPUs, GPUs, RAM). Both of us experienced this challenge firsthand. Analysis usually starts in a local notebook or script, and whenever we wanted to run our code on a larger infrastructure we had to refactor the code (i.e. rewrite our notebooks using Kubeflow’s SDK) and add a bunch of cloud configurations. Ploomber Cloud is a lot simpler, if your notebook or script runs locally, you can run it in the cloud with no code changes and no extra configuration. Furthermore, you can go back and forth between your local/interactive environment and the cloud. We built Ploomber Cloud on top of AWS. Users only need to declare their dependencies via a requirements.txt file, and Ploomber Cloud will take care of making the Docker image and storing it on ECR. Part of this implementation is open-source and available at: https://ift.tt/cUjKkXN Once the Docker image is ready, we spin up EC2 instances to run the user’s pipeline distributively (for example, to run hundreds of ML experiments in parallel) and store the results in S3. Users can monitor execution through the logs and download artifacts. If source code hasn’t changed for a given pipeline task, we use cached artifacts and skip redundant computations, severely cutting each run's cost, especially for pipelines that require GPUs. Users can sign up to Ploomber Cloud for free and get started quickly. We made a significant effort to simplify the experience ( https://ift.tt/qUrQOb1 ). There are three plans ( https://ift.tt/uh4dY25 ): the first is the Community plan, which is free with limited computing. The Teams plan has a flat $50 monthly and usage-based billing, and the Enterprise plan includes SLAs and custom pricing. We’re thrilled to share Ploomber Cloud with you! So if you’re a data scientist who has experienced these endless cycles of getting a machine and going through an ops team, an ML engineer who helps data scientists scale their work, or you have any feedback, please share your thoughts! We love discussing these problems since exchanging ideas sparks exciting discussions and brings our attention to issues we haven’t considered before! You may also reach out to me at ido@ploomber.io.
25 by idomi | 3 comments on Hacker News.
Hi, we’re Ido & Eduardo, the founders of Ploomber. We’re launching Ploomber Cloud today, a service that allows data scientists to scale their work from their laptops to the cloud. Our open-source users ( https://ift.tt/ejsi5SZ ) usually start their work on their laptops; however, often, their local environment falls short, and they need more resources. Typical use cases run out of memory or optimize models to squeeze out the best performance. Ploomber Cloud eases this transition by allowing users to quickly move their existing projects into the cloud without extra configurations. Furthermore, users can request custom resources for specific tasks (vCPUs, GPUs, RAM). Both of us experienced this challenge firsthand. Analysis usually starts in a local notebook or script, and whenever we wanted to run our code on a larger infrastructure we had to refactor the code (i.e. rewrite our notebooks using Kubeflow’s SDK) and add a bunch of cloud configurations. Ploomber Cloud is a lot simpler, if your notebook or script runs locally, you can run it in the cloud with no code changes and no extra configuration. Furthermore, you can go back and forth between your local/interactive environment and the cloud. We built Ploomber Cloud on top of AWS. Users only need to declare their dependencies via a requirements.txt file, and Ploomber Cloud will take care of making the Docker image and storing it on ECR. Part of this implementation is open-source and available at: https://ift.tt/cUjKkXN Once the Docker image is ready, we spin up EC2 instances to run the user’s pipeline distributively (for example, to run hundreds of ML experiments in parallel) and store the results in S3. Users can monitor execution through the logs and download artifacts. If source code hasn’t changed for a given pipeline task, we use cached artifacts and skip redundant computations, severely cutting each run's cost, especially for pipelines that require GPUs. Users can sign up to Ploomber Cloud for free and get started quickly. We made a significant effort to simplify the experience ( https://ift.tt/qUrQOb1 ). There are three plans ( https://ift.tt/uh4dY25 ): the first is the Community plan, which is free with limited computing. The Teams plan has a flat $50 monthly and usage-based billing, and the Enterprise plan includes SLAs and custom pricing. We’re thrilled to share Ploomber Cloud with you! So if you’re a data scientist who has experienced these endless cycles of getting a machine and going through an ops team, an ML engineer who helps data scientists scale their work, or you have any feedback, please share your thoughts! We love discussing these problems since exchanging ideas sparks exciting discussions and brings our attention to issues we haven’t considered before! You may also reach out to me at ido@ploomber.io.
Tuesday, June 28, 2022
Monday, June 27, 2022
Sunday, June 26, 2022
Saturday, June 25, 2022
Friday, June 24, 2022
As states ban abortions, many women will need to drive hundreds of miles to reach a clinic.
By BY MARGOT SANGER-KATZ, QUOCTRUNG BUI AND CLAIRE CAIN MILLER from NYT U.S. https://ift.tt/MDqvIhT
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Thursday, June 23, 2022
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Saturday, June 18, 2022
New top story on Hacker News: Ask HN: Why are Git submodules so bad?
Ask HN: Why are Git submodules so bad?
38 by ghoward | 27 comments on Hacker News.
I have been a git user for a long time, but I've never used Subversion or any other VCS more than a little. I also hardly use Git submodules, but when I do, I don't struggle. Yet people talk about Git submodules as though they are really hard. I presume I'm just not using them as much as other people, or that my use case for them happens to be on their happy path. So why are Git submodules so bad?
38 by ghoward | 27 comments on Hacker News.
I have been a git user for a long time, but I've never used Subversion or any other VCS more than a little. I also hardly use Git submodules, but when I do, I don't struggle. Yet people talk about Git submodules as though they are really hard. I presume I'm just not using them as much as other people, or that my use case for them happens to be on their happy path. So why are Git submodules so bad?
A vaccine for young children? U.S. parents’ reactions remain mixed.
By BY ELIZA FAWCETT, KIMIKO DE FREYTAS-TAMURA, CHRISTINA CAPECCHI, ELLEN B. MEACHAM, KEVIN WILLIAMS AND ADAM BEDNAR from NYT U.S. https://ift.tt/CbuTpDy
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Friday, June 17, 2022
Thursday, June 16, 2022
Wednesday, June 15, 2022
New top story on Hacker News: Are V8 isolates the future of computing?
Are V8 isolates the future of computing?
12 by pranay01 | 4 comments on Hacker News.
I was reading this article on Cloudflare workers https://ift.tt/1zxDvup and seemed like isolates have significant advantage over serverless technology like lambda etc. What are the downsides of v8? Is it poor security isolation?
12 by pranay01 | 4 comments on Hacker News.
I was reading this article on Cloudflare workers https://ift.tt/1zxDvup and seemed like isolates have significant advantage over serverless technology like lambda etc. What are the downsides of v8? Is it poor security isolation?
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