A more robust solution for development involves using Docker Compose to manage both your application container and your PostgreSQL service in separate containers. It's generally better to handle services like databases with separate containers or services, especially in production environments. - Source: dev.to / about 15 hours ago

Docker Compose is a tool for defining and running multi-container Docker applications. Define your services in a docker-compose.yml file, and then use the following commands:. - Source: dev.to / 27 days ago

https://github.com/docker/compose This seems to really just be "old0man-yelling-at-clouds-syndrome" I for one welcome anime girls in readmes and hope to see more of it in the future if only because it seems to bother some of the old hoagies in the world for some reason. - Source: Hacker News / about 1 month ago

Docker and docker compose: We will use docker as a container manager and docker-compose as a tool to configure and start a redis container. If you have not used them so far, refer to the links to install them. - Source: dev.to / 8 months ago

To get the latest release of Docker Compose, go to https://github.com/docker/compose and download the release for your OS. - Source: dev.to / about 1 year ago

There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: over 1 year ago

I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago

This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: about 2 years ago

Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago

Check out https://aws.amazon.com/emr/. Source: about 2 years ago