pitah1

8 ms·

1.
by pitah1 1y ago
I have a tool[1] that solely worked with docker before and was putting off supporting podman for a while because I thought it would take some time. But it turned out to work straight out of the box without tweaking. Essentially frictionless
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Show HN: Insta-infra – One click start any service(github.com)
1 points by pitah1 1y ago|0 comments
3.
by pitah1 1y ago
It leverages docker compose 'depends_on' for the dependencies ( https://docs.docker.com/compose/how-tos/startup-order/ ). For example, airflow depends on airflow-init container to be completed success
4.
by pitah1 1y ago
I have a small open-source project, that uses docker compose behind the scenes, to help startup any service. You can look to add it in (or I am also happy to add it in) and then users are one command away from running it (insta moose). Rece
5.
by pitah1 2y ago
This looks really cool. I'm surprised I didn't find this before when I was searching for something like this. I've been using jpackage[1] for a while now but this seems like it would be easier for me to manage using JReleaser
6.
by pitah1 2y ago
I've taken a stab at making a solution for it via https://github.com/data-catering/data-caterer . It focuses on making integration tests easier by generating data across batch and real-time data sources, whilst mai
7.
A year of getting paid from Medium articles(data.catering)
1 points by pitah1 2y ago|0 comments
8.
The ultimate test of your Docker image: Running in GitHub Actions(medium.com)
1 points by pitah1 2y ago|0 comments
9.
by pitah1 2y ago
This was also my philosophy behind creating insta-infra ( https://github.com/data-catering/insta-infra ). Single command to run any service. No additional thinking required. Too many times I've become very frustrate
10.
by pitah1 2y ago
The world of mock data generation is now flooded with ML/AI solutions generating data but this is a solution that understands it is better to generate metadata to help guide the data generation. I found this was the case given the form
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Data Contracts in Action: Tools(medium.com)
1 points by pitah1 2y ago|0 comments
12.
by pitah1 2y ago
I recently went down the rabbit hole of using PyScript for running a Python CLI app in the browser. It felt hacky the whole time, especially when dependencies were involved. I had to create wrapper classes to work around Pydantic 2.x not be
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Show HN: Data Contract Playground(data-catering.github.io)
1 points by pitah1 2y ago|0 comments
14.
by pitah1 2y ago
I've created a Docker image for it and onboarded it into my tool called insta-infra[1]. You should be able to run it via: ./run.sh maestro [1] https://github.com/data-catering/insta-infra
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Data Contracts in Action: Testing(medium.com)
1 points by pitah1 2y ago|0 comments
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Data Contracts in Action: Testing(medium.com)
1 points by pitah1 2y ago|0 comments
17.
by pitah1 2y ago
Would love to hear what people think or other approaches people have taken to help quickly spin up tools on your laptop.
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Show HN: Insta-infra – Single command quickstart for any tool(github.com)
2 points by pitah1 2y ago|1 comments
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Show HN: Insta-infra – Spin up any tool in your local laptop with one command(github.com)
2 points by pitah1 2y ago|0 comments
20.
by pitah1 2y ago
I've been keeping an eye on these kinds of Spark accelerator libraries for a while now. How does it compare to Blaze[1] and Gluten[2]? I'm interested in running some benchmarks soon against all three for my project to see how they
21.
by pitah1 2y ago
Thanks for sharing. Happy to see another solution that doesn't just slap on AI/ML to try to solve it. I am also among the many people who have created a solution similar[0] to this :). The approach I took though is being metadata-
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Difficulties of Test Environments(medium.com)
1 points by pitah1 2y ago|0 comments
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Generate Data for HTTP API from Swagger/OpenAPI Spec(youtube.com)
1 points by pitah1 2y ago|0 comments
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Automatic data generation and clean up in Postgres in 60 seconds(youtube.com)
1 points by pitah1 2y ago|0 comments
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Deploying a Spark-based application as a Windows application(medium.com)
1 points by pitah1 2y ago|0 comments
26.
Most Dangerous Button [video](youtube.com)
1 points by pitah1 2y ago|0 comments
27.
by pitah1 2y ago
Working on a data generation and validation tool called Data Caterer. The focus of it is being data source agnostic, fast and simple. Just last week, I released a UI for it. https://github.com/data-catering/data-caterer
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Show HN: Data Caterer – Data generation and validation tool(github.com)
1 points by pitah1 2y ago|0 comments
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Places you can find the Java version in Intellij(medium.com)
1 points by pitah1 3y ago|0 comments
30.
by pitah1 3y ago
I think they make the biggest difference when testing data pipelines (which have historically been difficult to test). You can now easily test out compatibility between different versions of databases, verify data types, embed as part of yo

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