Airflow
Docker Compose
Airflow | Docker Compose | |
---|---|---|
171 | 392 | |
35,036 | 32,780 | |
1.6% | 1.3% | |
10.0 | 9.6 | |
4 days ago | 5 days ago | |
Python | Go | |
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.
Airflow
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10 Open Source Tools for Building MLOps Pipelines
An integral part of an ML project is data acquisition and data transformation into the required format. This involves creating ETL (extract, transform, load) pipelines and running them periodically. Airflow is an open source platform that helps engineers create and manage complex data pipelines. Furthermore, the support for Python programming language makes it easy for ML teams to adopt Airflow.
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AI Strategy Guide: How to Scale AI Across Your Business
Level 1 of MLOps is when you've put each lifecycle stage and their intefaces in an automated pipeline. The pipeline could be a python or bash script, or it could be a directed acyclic graph run by some orchestration framework like Airflow, dagster or one of the cloud-provider offerings. AI- or data-specific platforms like MLflow, ClearML and dvc also feature pipeline capabilities.
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Building in Public: Leveraging Tublian's AI Copilot for My Open Source Contributions
Contributing to Apache Airflow's open-source project immersed me in collaborative coding. Experienced maintainers rigorously reviewed my contributions, providing constructive feedback. This ongoing dialogue refined the codebase and honed my understanding of best practices.
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Navigating Week Two: Insights and Experiences from My Tublian Internship Journey
In week Two, I contributed to the Apache Airflow repository.
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Airflow VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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Best ETL Tools And Why To Choose
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.
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Simplifying Data Transformation in Redshift: An Approach with DBT and Airflow
Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring.
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Share Your favorite python related software!
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!
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Ask HN: What is the correct way to deal with pipelines?
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 showing up in a directory…
- "Você veio protestar para ter acesso ao código fonte da urnas. O que é o código fonte?" "Não sei" 🤡
Docker Compose
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Essential Docker Commands for Developers
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:
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Llama3 Implemented from Scratch
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.
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Docker and WSL2 without Docker Desktop
To install docker compose tool, download the latest version of the plugin by visiting https://github.com/docker/compose/releases. Find the most recent release, go to the “Assets” section, and expand the list of assets. Download the file that ends with windows-x86_64.exe, like docker-compose-windows-w86_64.exe. Place the downloaded file in the cli-plugins folder you created earlier, and rename it to docker-compose.exe. Now, we can use the command docker compose.
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Deploy a Grafana dashboard with Docker on AWS EC2
sudo curl -L https://github.com/docker/compose/releases/latest/download/docker-compose-$(uname -s)-$(uname -m) -o /usr/local/bin/docker-compose sudo chmod +x /usr/local/bin/docker-compose
- Docker Compose: `version` is obsolete
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12 Factor: 13 years later
Solutions are many, and could include Docker Compose, VS Code dev containers, Telepresence, Localstack or setting up temporary AWS accounts as a development environment for serverless applications.
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Let's write a simple microservice in Clojure
Using Docker Compose to run Postgres and any third-party services locally provides a streamlined and consistent development environment. Developers can define services in a docker-compose.yml file, which enables them to configure and launch an entire stack with a single command. In this case, Postgres is encapsulated within a container with predefined configurations. Docker Compose also facilitates easy scaling, updates, and isolation of services, enhancing development efficiency and reducing the setup time for new team members or transitioning between projects. It encapsulates complex configurations, such as Postgres' performance monitoring and logging settings, in a manageable, version-controlled file, simplifying and replicating the service setup across different environments.
- Live reload em Go com docker e compile daemon
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Docker compose, orchestrating and automating services
“Compose simplifies the control of your entire application stack, making it easy to manage services, networks, and volumes in a single, comprehensible YAML configuration file. Then, with a single command, you create and start all the services from your configuration file.” - Docker documentation
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Hosting a simple docker-compose app with Nginx and generate a SSL with certbot on digitalocean droplet
curl -fsSL https://get.docker.com -o get-docker.sh sudo sh get-docker.sh # Install docker compose sudo curl -L "https://github.com/docker/compose/releases/download/1.29.2/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose # Apply executable permissions to the binary sudo chmod +x /usr/local/bin/docker-compose # Run Project docker-compose up -d
What are some alternatives?
Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
supervisor - Supervisor process control system for Unix (supervisord)
dagster - An orchestration platform for the development, production, and observation of data assets.
LibreNMS-docker - LibreNMS Docker image
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
Portainer - Making Docker and Kubernetes management easy.
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
terraform - Terraform enables you to safely and predictably create, change, and improve infrastructure. It is a source-available tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Cloud-Init - unofficial mirror of Ubuntu's cloud-init
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
k3s - Lightweight Kubernetes