Docker
dagster
Our great sponsors
Docker | dagster | |
---|---|---|
4 | 46 | |
3,176 | 10,173 | |
0.8% | 4.8% | |
2.5 | 10.0 | |
10 days ago | 6 days ago | |
Go | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Docker
-
Dagger: a new way to build CI/CD pipelines
I'm not touching anything Docker anymore.
Here's the scenario: you're the unfortunate soul who received the first M1 as a new employee, and nothing Docker-related works. Cue multi-arch builds; what a rotten mess. I spent more than a week figuring out the careful orchestration that any build involving `docker manifest` needs. If you aren't within the very fine line that buildx assumes, good luck pal. How long has `docker manifest` been "experimental?" It's abandonware.
Then I decided it would be smart to point out that we don't sign our images, and so I had to figure out how to combine the `docker manifest` mess with `docker trust`, another piece of abandonware. Eventually I figured out that the way to do it was with notary[1], another (poorly documented) piece of abandonware. The new shiny thing is notation[2], which does exactly the same thing, but is nowhere near complete.
At least Google clearly signals that they are killing something, Docker just lets projects go quiet.
How long before this project lands up like the rest of them? Coincidentally, we were talking about decoupling our CI from proprietary CI, seeing this was a rollercoaster of emotions.
[1]: https://github.com/notaryproject/notary
- Notary
- Notary is a project that allows anyone to have trust over arbitrary collections of data
dagster
- Experience with Dagster.io?
-
Dagster tutorials
My recommendation is to continue on with the tutorial, then look at one of the larger example projects especially the ones named “project_”, and you should understand most of it. Of what you don't understand and you're curious about, look into the relevant concept page for the functions in the docs.
-
The Dagster Master Plan
I found this example that helped me - https://github.com/dagster-io/dagster/tree/master/examples/project_fully_featured/project_fully_featured
-
What are some open-source ML pipeline managers that are easy to use?
I would recommend the following: - https://www.mage.ai/ - https://dagster.io/ - https://www.prefect.io/ - https://metaflow.org/ - https://zenml.io/home
-
The Why and How of Dagster User Code Deployment Automation
In Helm terms: there are 2 charts, namely the system: dagster/dagster (values.yaml), and the user code: dagster/dagster-user-deployments (values.yaml). Note that you have to set dagster-user-deployments.enabled: true in the dagster/dagster values-yaml to enable this.
-
Best Orchestration Tool to run dbt projects?
Dagster seemed really cool when I looked into it as an alternative to airflow. I especially like the software defined assets and built-in lineage which I haven't seen in any other tool. However it seems it does not support RBAC which is a pretty big issue if you want a self-service type of architecture, see https://github.com/dagster-io/dagster/issues/2219. It does seem like it's available in their hosted version, but I wanted to run it myself on k8s.
-
dbt Cloud Alternatives?
Dagster? https://dagster.io
-
What's the best thing/library you learned this year ?
One that I haven't seen on here yet: dagster
- Anyone have an example of a project where a handful of the more popular Python tools are used? (E.g. airbyte, airflow, dbt, and pandas)
- Can we take a moment to appreciate how much of dataengineering is open source?
What are some alternatives?
Postman - CLI tool for batch-sending email via any SMTP server.
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
snap - The open telemetry framework
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Juju - Orchestration engine that enables the deployment, integration and lifecycle management of applications at any scale, on any infrastructure (Kubernetes or otherwise).
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
Seaweed File System - SeaweedFS is a fast distributed storage system for blobs, objects, files, and data lake, for billions of files! Blob store has O(1) disk seek, cloud tiering. Filer supports Cloud Drive, cross-DC active-active replication, Kubernetes, POSIX FUSE mount, S3 API, S3 Gateway, Hadoop, WebDAV, encryption, Erasure Coding. [Moved to: https://github.com/seaweedfs/seaweedfs]
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
Dokku - A docker-powered PaaS that helps you build and manage the lifecycle of applications
MLflow - Open source platform for the machine learning lifecycle
Documize - Modern Confluence alternative designed for internal & external docs, built with Go + EmberJS
meltano