Apache Airflow is an open source tool that can be used to programmatically author, schedule and monitor data pipelines using Python and SQL. Created at Airbnb as an open-source project in 2014, Airflow was brought into the Apache Software Foundation’s Incubator Program 2016 and announced as Top-Level Apache Project in 2019. It is used as a data orchestration solution, with over 140 integrations and community support.
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Azure Logic Apps
Score 8.8 out of 10
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Microsoft offers the Azure Logic Apps as a cloud-based integration service, supporting data and application integration.
For a quick job scanning of status and deep-diving into job issues, details, and flows, AirFlow does a good job. No fuss, no muss. The low learning curve as the UI is very straightforward, and navigating it will be familiar after spending some time using it. Our requirements are pretty simple. Job scheduler, workflows, and monitoring. The jobs we run are >100, but still is a lot to review and troubleshoot when jobs don't run. So when managing large jobs, AirFlow dated UI can be a bit of a drawback.
Microsoft Azure Logic Apps was a perfect solution for us to integrate the apps and products we used in our business to create automated workflows which were also complex and very advanced. This was a very new feature for us, and also it reduced our software costs massively and also saved us a lot of time. With the crisis, we were in back then Azure turned out to be the best cost-friendly solution because we only had to pay for what we used!
Microsoft Azure should be unclouded with its pricing. We don't always know how much an inclusion will affect the monthly price. So we have to speculate where we are with the price and if we can afford to include another asset.
I found them easy to use and adapt to different scenarios, from Azure management to link processes between REST APIs. Together with Function Apps, they're probably the most useful resource type for Azure. Today, I use them in production, and that's a key component: stable, secure, easy to manage, and maintain.
Azure Logic Apps are backed by Azure and Microsoft. There is a wealth of information on the internet about both of these platforms. In addition to this Microsoft has a huge bush to using this platform and have offered many solutions and support options to the user. The only drawback is that it is a fairly new platform so the 3rd party information tends to be lacking.
There are a number of reasons to choose Apache Airflow over other similar platforms- Integrations—ready-to-use operators allow you to integrate Airflow with cloud platforms (Google, AWS, Azure, etc) Apache Airflow helps with backups and other DevOps tasks, such as submitting a Spark job and storing the resulting data on a Hadoop cluster It has machine learning model training, such as triggering a Sage maker job.
This is very dependent on the line of work you are in and the unique company requirements, as is the case with everything. We utilize Azure Logic Apps for all of our computing solutions within our domain, and it has always worked flawlessly. One of the simplest clouds to set up and use is by far the most popular.
Moving to Serverless Computing obviously makes the organization get rid of dependent Infra.
ROI can be seen immediately as the required infra can be decommissioned after a successful quarter run.
Being deployed as a single entity or single app on Azure Logic Apps, Organizations need to be more careful with controls applied to meet compliance and security posture.