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Apache Airflow Room for Improvement

Engineering Manager - OTT Platform at Amagi

One specific feature that is missing from Airflow is that the steps of your workflow are not pipelined, meaning the stageless steps of any workflow. Not every workflow can be implemented within Airflow. For example, Step 1 of my workflow will have output which I definitely want to automatically be provided as an input to my Step 2. At the workflow level, we want to have common state management where, across steps, we'll be able to reach the state information. Right now, we're using an external state repository to maintain the state.

If Airflow could come up with some kind of implementation, where not every step of the pipeline is an independent step, that would be helpful. I would like it if a part of the output of your previous steps could be Apache input for your next step. That kind of pipeline is missing. When we consider other products like jBPM, Camunda, or Cadence, they have the concept of pipelining.

I would also like to see support for more platforms, in terms of programming BPMs. Cadence supports Golang and Java. Legacy components can be from any platform, so if they could provide more client support for Java client library and Golang, that would be helpful. I want it to program in Java.

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JP
Senior Solutions Architect/ Software Architect at a comms service provider with 51-200 employees

The graphics in the past have not been ideal.

We have several areas where we feel they could improve in terms of being a little bit more flexible. One is implementation. Even though we customized it, there were some specific things we had to do with the image by itself.

The management integration was challenging as well. It requires a lot of work on our end. We were creating our own way to integrate things specifically with specific tools. There's not really an ease of management out-of-the-box option for integration. We needed to become a little bit creative to solve that ourselves.

The scalability of the solution itself is not as we expected. Being on the cloud, it should be easy to scale, however, it's not.

There is no SDC versioning. There's no virtual control for pipelines. We have to build several pipelines for several flows, yet there's not a virtual control to generate them.

There's no Python SDK. We need to generate our own scripts and upload them and put them there. However, there's not a realistic case that we can get connected to them. On top of that, the API sets that are provided are very limited. They are not as rich as others. You cannot do much with them.

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MW
Assistant Manager at a comms service provider with 10,001+ employees

We're currently using version 1.10, but I understand that there's a lot of improvements in version 2. In the earlier version that we're using, we sometimes have problems with maintenance complexity. Actually using Airflow is okay, but maintaining it has been difficult.

When something fails, it's not that easy to troubleshoot what went wrong. Sometimes the UI becomes really slow and there's no easy way to diagnose the problem. For the most part, we have had to learn through trial and error how to operate it properly. 

The UI is also not that attractive, and I feel that the user experience isn't that nice. Version 2 is supposedly better, but without having tried it, I could suggest more improvements in the visual UI. We want to do the ETL as code, but having a nice visual UI to facilitate this process would be great. Because that means we can also rely on non-technical staff, rather than just the three solid technical staff we have here. If there were better features for the UI, like drag-and-drop, then we could expand its use to more of our team.

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Learn what your peers think about Apache Airflow. Get advice and tips from experienced pros sharing their opinions. Updated: November 2021.
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JR
Senior Software Engineer at a pharma/biotech company with 1,001-5,000 employees

I am using a Celery Executor and I find that it crashes and I can't see any logs. I can only assume that it's a memory issue and have to blindly restart until eventually, it starts up again.

One of the use cases is triggered by input rather than a batch process. For example, we receive a batch of data, it goes through tasks one, two, and three, and a new batch comes in, each subsequent task should be operating on just that data from the prior task.

I am used to working on it as the output gets written to a table and then the next task selects all from that upstream table. It could be coded where you are only writing the data for that portion of the task. It could handle state machines and state changes as opposed to the batch proxy.

I would like to see it more friendly for other use cases.

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AJ
Associate Director - Technologies at a tech services company with 51-200 employees

Technical support is an area that needs improvement. The contact numbers should be readily available so that we can call to get support as required.

In the future, I would like to see a single-click installation.

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CP
Virksomhedskonsulent - Digitalisering, Forretningsudvikling, BPM, Teknologi & Innovation at a consultancy with 51-200 employees

The dashboard is connected into the BPM flow that could be improved.

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Learn what your peers think about Apache Airflow. Get advice and tips from experienced pros sharing their opinions. Updated: November 2021.
554,529 professionals have used our research since 2012.