Airflow
terraform
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Airflow | terraform | |
---|---|---|
169 | 500 | |
34,485 | 41,118 | |
2.1% | 1.1% | |
10.0 | 9.9 | |
about 8 hours ago | 6 days ago | |
Python | Go | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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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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" 🤡
- Cómo construir tu propia data platform. From zero to hero.
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Is it impossible to contribute to open source as a data engineer?
You can try and contribute some new connectors/operators for workflow managers like Airflow or Airbyte
terraform
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Why CISA Is Warning CISOs About a Breach at Sisense
State Encryption was one of those long requested features[0] (I had it on my ideas list for years[1]) that Hashicorp didn't have much incentive to build. I don't think it has to with distancing opentofu as such, but the opentofu team prioritizing the right things that customers actually need.
[0]: https://github.com/hashicorp/terraform/issues/9556
[1]: https://github.com/captn3m0/ideas#-mars-terraform-remote-htt...
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OpenTofu Response to HashiCorp's Cease and Desist Letter
https://github.com/hashicorp/terraform/issues/34402
I’m not a lawyer and have no idea who is right or wrong but I understand why Hashicorp is scrutinizing this.
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The power of the CLI with Golang and Cobra CLI
Just to give an example of the power of Go for CLI builds, you may have already used or at least heard of Docker, Kubernetes, Prometheus, Terraform, but what do they all have in common? They all have a large part of their usability via CLI and are developed in Go 🐿.
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I Deployed My Own Cute Lil’ Private Internet (a.k.a. VPC)
Each app’s front end is built with Qwik and uses Tailwind for styling. The server-side is powered by Qwik City (Qwik’s official meta-framework) and runs on Node.js hosted on a shared Linode VPS. The apps also use PM2 for process management and Caddy as a reverse proxy and SSL provisioner. The data is stored in a PostgreSQL database that also runs on a shared Linode VPS. The apps interact with the database using Drizzle, an Object-Relational Mapper (ORM) for JavaScript. The entire infrastructure for both apps is managed with Terraform using the Terraform Linode provider, which was new to me, but made provisioning and destroying infrastructure really fast and easy (once I learned how it all worked).
- Configurar AWS Signer en lambda con terraform
- Cranelift code generation comes to Rust
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The Essential Guide to Internal Developer Platforms
For example, integrating Terraform for infrastructure as code (IaC) into the IDP can streamline updates and rollbacks.
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Experience Continuous Integration with Jenkins | Ansible | Artifactory | SonarQube | PHP
In this project, you will understand and get hands on experience around the entire concept around CI/CD from applications perspective. To fully gain real expertise around this idea, it is best to see it in action across different programming languages and from the platform perspective too. From the application perspective, we will be focusing on PHP here; there are more projects ahead that are based on Java, Node.js, .Net and Python. By the time you start working on Terraform, Docker and Kubernetes projects, you will get to see the platform perspective of CI/CD in action.
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The 2024 Web Hosting Report
Infrastructure as Code (IaC) is an important part of any true hosting operation in the public cloud. Each of these platforms has their own IaC solution, e.g. AWS CloudFormation. But they also support popular open-source IaC tools like Pulumi or Terraform. A category of tools that also needs to be discussed is API gateways and other app-specific load balancers. There are applications for internal consumption, which can be called microservices if you have a lot of them. And often microservices use advanced networking options such as a service mesh instead of just the native private network offered by a VPC.
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🦊 GitLab CI: Deploy a Majestic Single Server Runner on AWS
To quickly deploy the architecture, we will be using Terraform. With Terraform, we can automate the deployment process and have our infrastructure up and running in minutes.
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.
terragrunt - Terragrunt is a thin wrapper for Terraform that provides extra tools for working with multiple Terraform modules.
dagster - An orchestration platform for the development, production, and observation of data assets.
Docker Compose - Define and run multi-container applications with Docker
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
terraform-provider-restapi - A terraform provider to manage objects in a RESTful API
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.
crossplane - The Cloud Native Control Plane
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
boto3 - AWS SDK for Python
Dask - Parallel computing with task scheduling
nvim-lspconfig - Quickstart configs for Nvim LSP