getting-started VS meltano

You should do docker’s getting-started container it’ll help fill gaps.

I have docker installed but im having issues with it im too dumb to follow this tutorial https://youtu.be/B134jvhO8yk i have no idea what hes it doing at around the 3 minute mark where he is creating a "clone" im getting this message at the Tutorial part in docker I went and removed the container and tried it again but im getting the same issue. I PS C:\Users\user> docker run --name repo alpine/git clone https://github.com/docker/getting-started.git

C:\Windows\system32>docker run --name repo alpine/git clone \ https://github.com/docker/getting-started.git Unable to find image 'alpine/git:latest' locally latest: Pulling from alpine/git 97518928ae5f: Pull complete b8d269ae55e3: Pull complete b863f4504196: Pull complete b90e122235c6: Pull complete Digest: sha256:d4740deff7f05d2d48771ff66d9d9c26dfb76f0db0aa833b1ea0ee346fa1e48f Status: Downloaded newer image for alpine/git:latest docker: Error response from daemon: failed to start service utility VM (createreadwrite): hcsshim::CreateComputeSystem 94a61d6c784cb6e83c57feb0292ca424a482ef80c97ee7ec76e1d1b403b3f23b_svm: The virtual machine could not be started because a required feature is not installed. See 'docker run --help'.

docker run --name repo alpine/git clone \ https://github.com/docker/getting-started.git docker cp repo:/git/getting-started/ .

I would use something like meltano or airbyte, but if you really want to use Lambda for extraction I'd say there is no point spinning up a Redshift cluster just for that, Athena would be the way to go and you can use dbt pretty nicely with it and it would keep costs down.

Airbyte and Singer/Meltano if you want to learn more about ingestion pipelines. Airbyte and Meltano teams are very welcoming. SQLfluff a shiny SQL linter. Beautiful project with awesome maintainers.

I know really sure if this is what are you looking for, but take a look at Meltano

I'm not aware of any. I did just open this issue[0] in the Meltano project to open discussion with the team/community. It could be an interesting iteration on the Singer Spec[1] if we find that users are interested in it and it helps solve some bottleneck challenges.

[0] https://gitlab.com/meltano/meltano/-/issues/2616

Good point! As expected, there's an issue about adding it already: https://gitlab.com/meltano/meltano/-/issues/1175

At GitLab, we're not ready to give up on the Singer spec, community, and ecosystem yet, which is why I've been working on Meltano for the past year: https://meltano.com/

We think that the biggest things holding back Singer are the lack of documentation and tooling around taking existing taps and targets to production, and around building, debugging, maintaining, and testing new or existing high-quality taps and targets.

Meltano itself addresses the first problem, and provides a robust and reliable platform for building, running & orchestrating Singer- and dbt-based ELT pipelines.

At the same time, we have been working with some members of the community on a new framework for building taps and targets: https://gitlab.com/meltano/meltano/-/issues/2401, which we have decided to call the Singer SDK: https://gitlab.com/meltano/singer-sdk