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We can then use the Google Cloud SDK to deploy the app:. - Source: dev.to / 11 months ago
I made a fresh install of gcloud for ubuntu as instructed here. I want to use the additional components offered by gcloud like kubectl and docker. Source: about 1 year ago
To add more context, if you are developing containers in a local dev environment, the minimum you should have is the Google Cloud SDK and Skaffold. The SDK will allow you to programmatically interact with Googleapis e.g. auth, services, resources. Skaffold will allow you to build and deploy to the cloud similar to working with a local dev environment. Source: about 1 year ago
For Google Cloud, you should be familiar Google Cloud SDK (gcloud tool) with setting up an account, project, and provisioning resources. This is important as there are cost factors involved in setting these things up. - Source: dev.to / over 1 year ago
You'll also need to install the Google Cloud SDK (a command line tool for interacting with GCP; SDK stands for 'software development kit') on your computer. Once you have downloaded and installed it, run gcloud init to set it up. This is the point at which your computer becomes trusted to do things to your GCP account. - Source: dev.to / over 1 year ago
For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules. - Source: dev.to / 2 months ago
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows. Source: 6 months ago
Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring. - Source: dev.to / 6 months ago
AIRFLOW This is more of a library in my opinion, but Airflow has become an essential tool for scheduling in my work. All our ML training pipelines are ordered and scheduled with Airflow and it works seamlessly. The dashboard provided is also fantastic! Source: 7 months ago
I agree there are many options in this space. Two others to consider: - https://airflow.apache.org/ - https://github.com/spotify/luigi There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file... - Source: Hacker News / 7 months ago
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