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OpenStack
Apache AirflowOpenStack is particularly recommended for large enterprises, organizations with skilled IT teams, academic institutions, and service providers that need a highly customizable and scalable cloud solution. It's also a great fit for entities with specific compliance requirements or those that need to run a private cloud with tailored configurations.
Apache Airflow is recommended for data engineers, data scientists, and IT professionals who need to automate and manage workflows. It is particularly suited for organizations handling large-scale data processing tasks, requiring integration with various systems, and those looking to deploy machine learning pipelines or ETL processes.
Based on our record, Apache Airflow seems to be a lot more popular than OpenStack. While we know about 80 links to Apache Airflow, we've tracked only 2 mentions of OpenStack. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
In my first post, I looked into what is OpenStack and how, if done right, can be quite a powerful ally in our cloud deployment strategies. In this post, I want to start looking at how we can create an application to learn the basics and components of the system. - Source: dev.to / about 5 years ago
While searching for solutions and documentation on the various problems I've come across, I would often see references to OpenStack and it got my curiosity going. What is OpenStack? What services does it offer and who owns it? How do I learn to use it? What are it's costs and limitations? - Source: dev.to / about 5 years ago
General orchestrators โ Airflow, Prefect, AWS Step Functions, Azure Logic Apps. These treat Each LLM call as just another task in a DAG, and give you the heavyweight reliability Machinery: durable state, scheduling, checkpointing, audit trails, human approval. - Source: dev.to / 4 days ago
There is a lot of stuff for Python which follows the "express computation as a dag" approach, especially Apache Airflow https://airflow.apache.org/. - Source: Hacker News / 10 months ago
Doing ingestion or data processing with Airflow, a very popular open-source platform for developing and running workflows, is a fairly common setup. DataHub's automatic lineage extraction works great with Airflow - provided you configure the Airflow connection to DataHub correctly. - Source: dev.to / 11 months ago
Apache Airflow represents the open-source workflow orchestration approach to MongoDB ETL. By combining Airflow's powerful scheduling and dependency management with a Python library like PyMongo, you can build highly customized ETL workflows that integrate seamlessly with MongoDB. - Source: dev.to / 11 months ago
You appear to be making the mistake of assuming that the only valid definition for the term "workflow" is the definition used by software such as https://airflow.apache.org/ https://www.merriam-webster.com/dictionary/workflow thinks the word dates back to 1921. There no reason Anthropic can't take that word and present their own alternative definition for it in the context of LLM tool usage, which is what they've... - Source: Hacker News / about 1 year ago
Linode - We make it simple to develop, deploy, and scale cloud infrastructure at the best price-to-performance ratio in the market.
Make.com - Tool for workflow automation (Former Integromat)
DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.
ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.
Microsoft Azure - Windows Azure and SQL Azure enable you to build, host and scale applications in Microsoft datacenters.
Pushwoosh - Mobile-inspired customer engagement platform for high achievers