Astro by Astronomer can be improved; they are doing a lot of progress on observability. How to see how all the pipelines and all the steps of the DAGs connect to each other is something that they improved recently, so we can see this, but as we have another process running outside of Astro by Astronomer, we could not use this for everything. Also, if we wanted to import data from outside, the price that they shared with us was higher than the actual tool that we are using right now. On a scale of one to ten, I would rate Astro by Astronomer an eight; there are some things that could be improved, perhaps in performance, perhaps in some areas of the web interface that could be more straightforward, but I think it is a solid eight.
Arquitecto De Datos at a retailer with 10,001+ employees
Real User
Top 20
Jul 27, 2026
I think Astro by Astronomer could be improved by having more clarity in cost topics and how the cost associated with the tool works.I think there is an aspect of the tool that has caused me some difficulty, which is the scheduler, and I think it could be more intuitive or efficient. The scheduler's latency, which I know is not sub-second and is not suitable for sub-second latency, is more for batch and minutes is recommended; in seconds it can become intensive. In the future, having something a bit more in seconds would be interesting. I also think there is an issue that it tends to be a bit slow; sometimes the tool does not reflect changes quickly, especially when I want to see something refreshed automatically.
Senior Data Platform Engineer at a retailer with 10,001+ employees
Real User
Top 10
Jul 26, 2026
Astro by Astronomer is doing great, and while improvement opportunities exist, particularly around the cost model, which can occasionally feel steep, I generally find it quite favorable. For smaller teams, the cost can be quite high; self-hosted Airflow or AWS MWAA options are cheaper. For larger companies, it seems acceptable. Aside from that, I do not have any other concerns, but perhaps adding advanced governance such as streamlining RBAC directly into the UI could be beneficial, which may not currently be available.
Engenheiro De Dados at a financial services firm with 51-200 employees
Real User
Top 20
Jul 22, 2026
I believe one area for improvement for Astro by Astronomer would be to further expand the documentation and examples for more advanced scenarios, especially involving integrations with AWS, Amazon ECS, AWS Fargate, and Astronomer Cosmos. Although the documentation is good, some more complex use cases require additional research or testing until you find the best approach. It would also be interesting to offer more templates and ready-made best practices for modern architectures with dbt, Airflow, and Kubernetes, making it easier for teams that are just getting started. This would reduce the learning curve and further speed up the implementation of production environments. The main point would be to provide more content and reference architectures for large-scale corporate environments, especially involving Airflow, dbt, Kubernetes, and AWS. This would help teams adopt best practices more quickly and reduce the time spent on architecture decisions. Otherwise, I consider the experience very positive, and Astro by Astronomer platform meets the needs of development and orchestration of data pipelines very well.
Consultant at a tech vendor with 10,001+ employees
Real User
Top 20
Jul 10, 2026
The current version of Astro by Astronomer is good enough for our needs. The documentation part of Astro by Astronomer can be made easier and more generic, not specific to the integration with each of the services. There are a few areas where improvement would be helpful. While it integrates well with Airflow and cloud services, configuring some third-party agents can require additional setup and troubleshooting.
Data & AI Engineer at a retailer with 10,001+ employees
Real User
Top 20
Jul 10, 2026
Astro by Astronomer's CLI might be a little challenging, and having the CLI commands along with the documentation more readily available would be great.
Data Engineer Customer Analytics at Lastminute.com
Real User
Top 20
Jul 8, 2026
Last year, as I shared with the product manager, I thought that it would be great to have a slower response time with Astro by Astronomer. I used to wait a few minutes to get a response and to see that the DAG was created completely, which I think is annoying when you work and need to wait until the suggestions were made after a few minutes. The speed, I think, was the part to improve, but the quality, for instance, was amazing. I think that one year ago, Astro by Astronomer needed to improve in reliability because it was a bit slow to develop and sometimes it crashed. As I said, it was before the launching date, so if they give me the opportunity to try it again, I will do that and test again. But the pain points were there.
I would say it would be much more helpful if Astro by Astronomer can provide an MCP to use and integrate with Astro by Astronomer and their AI agent Auto, so that we can use our tools like Claude, Code, or Cursor to have a central location where we integrate that MCP in Databricks via the AI gateway, and then we can have a place where we can connect to Astro by Astronomer, Databricks, other tools such as Jira and DataDog, and then have a much more comprehensive analysis and overview and monitoring of the entire data ecosystem. Having an MCP integration would tremendously help us to have a more comprehensive data platform that is more AI-ready. That is one of the features that I can think of. Another thought would be having an integration with Kubernetes instead of just scheduling everything on Astro by Astronomer workers. That would be helpful. One thing I can think of is that the Astro by Astronomer local developer environment can be improved further, but perhaps that is a very niche use case that I have in mind, and it may not be useful for others. There is room for improvement around having an improved UI and also integration with other tools. On governance, I would say we can have a more granular level of governance even inside workspaces. Having much more granular control over people belonging to the same team in Astro by Astronomer could have different access to different DAGs, depending upon our tagging strategy. That is one of the areas I can suggest in terms of improvement. The AI capabilities can be improved further. I would compare the current AI capabilities to newer models provided by Claude such as Opus or Codex.
Level One Data Analytics Analyst at a insurance company with 1,001-5,000 employees
Real User
Top 5
Jul 7, 2026
I think any further refinements as far as anything major is going to be on the user's side. Everybody's got a different need, so trying to build an overfit solution is only going to hurt other people. The reason I choose eight for Astro by Astronomer is that it is useful for learning and for companies, small to large. There is still a barrier for people who are not familiar with some of the prerequisite knowledge, but I do also think that is not something that needs to be fixed. It is just the nature of how this works. As I said before, if you try to tailor it too much where people were getting almost a no-code experience with it, I think due to the nature of the services it provides, it would cause more trouble than it would fix. An eight means you're doing great.
Data Engineer at a outsourcing company with 201-500 employees
Real User
Top 10
Jul 6, 2026
We want to explore how to deal with multi-tenancy while using Astro by Astronomer, as it is something really important for us because it enhances user experience. Additionally, we aim to resolve some bugs that Airflow has in managed AWS, such as isolated environments, and in general, we want to optimize DevOps around local instances, which is really something cool that Astro by Astronomer provides. I think Astro by Astronomer could improve its pricing, as it is really expensive, especially if you want to have large use in a large-scale enterprise edition, which requires you to create a VPC hosted instance that significantly increases expenses. I believe they should work on this to provide more affordable solutions. I chose 8 out of 10 because there are deployment issues, at least initially, regarding VPC hosting and many other networking issues. Second is pricing, which is really expensive even just to start experimenting, as they also provide you a developer package for this. The total plan needs improvement, but other than that, it is acceptable.
Data Engineer at a university with 5,001-10,000 employees
Real User
Jul 5, 2026
Astro by Astronomer can be improved by adding managed infrastructure with zero setup deliverable developer tools. It can include a high-performance executor, which eliminates manual Airflow maintenance through cloud-hosted or remote execution deployment models. Key improvements for Astro by Astronomer include integrating with Terraform provider and multiple other tools. Regarding Astro by Astronomer's AI capabilities, I think its governance and security need to improve, but currently it can be used quite well, though there are some improvements needed for governance and security related to AI.
Manager, Project Development at a tech vendor with 10,001+ employees
Real User
Top 5
Jul 5, 2026
I believe there are several areas where Astro by Astronomer can improve. The pricing has become a little expensive because I have very large and always-running workloads. The enterprise configuration sometimes requires a learning curve that could be easier. Advanced customizations could be improved, and the documentation of complex topics needs enhancement. In enterprise scenarios, better documentation would help me more. I believe support is strong. Whenever I reach out to find issues or root causes, I get a very timely response from the support team. Integration is definitely an area that could be much better because of advanced enterprise requirements that need more configurable learning curves. If integration were easier, it would be simpler to deploy to different teams.
Astro by Astronomer is a cutting-edge data orchestration platform designed to simplify and streamline data workflows. It enhances productivity by transforming complex tasks into manageable processes, offering robust solutions for modern data engineering challenges.Astro by Astronomer empowers users with a comprehensive suite for managing and orchestrating data pipelines. It stands out for its scalable infrastructure and seamless integrations, enabling organizations to efficiently process and...
Astro by Astronomer can be improved; they are doing a lot of progress on observability. How to see how all the pipelines and all the steps of the DAGs connect to each other is something that they improved recently, so we can see this, but as we have another process running outside of Astro by Astronomer, we could not use this for everything. Also, if we wanted to import data from outside, the price that they shared with us was higher than the actual tool that we are using right now. On a scale of one to ten, I would rate Astro by Astronomer an eight; there are some things that could be improved, perhaps in performance, perhaps in some areas of the web interface that could be more straightforward, but I think it is a solid eight.
I think Astro by Astronomer could be improved by having more clarity in cost topics and how the cost associated with the tool works.I think there is an aspect of the tool that has caused me some difficulty, which is the scheduler, and I think it could be more intuitive or efficient. The scheduler's latency, which I know is not sub-second and is not suitable for sub-second latency, is more for batch and minutes is recommended; in seconds it can become intensive. In the future, having something a bit more in seconds would be interesting. I also think there is an issue that it tends to be a bit slow; sometimes the tool does not reflect changes quickly, especially when I want to see something refreshed automatically.
Astro by Astronomer is doing great, and while improvement opportunities exist, particularly around the cost model, which can occasionally feel steep, I generally find it quite favorable. For smaller teams, the cost can be quite high; self-hosted Airflow or AWS MWAA options are cheaper. For larger companies, it seems acceptable. Aside from that, I do not have any other concerns, but perhaps adding advanced governance such as streamlining RBAC directly into the UI could be beneficial, which may not currently be available.
I believe one area for improvement for Astro by Astronomer would be to further expand the documentation and examples for more advanced scenarios, especially involving integrations with AWS, Amazon ECS, AWS Fargate, and Astronomer Cosmos. Although the documentation is good, some more complex use cases require additional research or testing until you find the best approach. It would also be interesting to offer more templates and ready-made best practices for modern architectures with dbt, Airflow, and Kubernetes, making it easier for teams that are just getting started. This would reduce the learning curve and further speed up the implementation of production environments. The main point would be to provide more content and reference architectures for large-scale corporate environments, especially involving Airflow, dbt, Kubernetes, and AWS. This would help teams adopt best practices more quickly and reduce the time spent on architecture decisions. Otherwise, I consider the experience very positive, and Astro by Astronomer platform meets the needs of development and orchestration of data pipelines very well.
The current version of Astro by Astronomer is good enough for our needs. The documentation part of Astro by Astronomer can be made easier and more generic, not specific to the integration with each of the services. There are a few areas where improvement would be helpful. While it integrates well with Airflow and cloud services, configuring some third-party agents can require additional setup and troubleshooting.
Astro by Astronomer's CLI might be a little challenging, and having the CLI commands along with the documentation more readily available would be great.
Last year, as I shared with the product manager, I thought that it would be great to have a slower response time with Astro by Astronomer. I used to wait a few minutes to get a response and to see that the DAG was created completely, which I think is annoying when you work and need to wait until the suggestions were made after a few minutes. The speed, I think, was the part to improve, but the quality, for instance, was amazing. I think that one year ago, Astro by Astronomer needed to improve in reliability because it was a bit slow to develop and sometimes it crashed. As I said, it was before the launching date, so if they give me the opportunity to try it again, I will do that and test again. But the pain points were there.
I would say it would be much more helpful if Astro by Astronomer can provide an MCP to use and integrate with Astro by Astronomer and their AI agent Auto, so that we can use our tools like Claude, Code, or Cursor to have a central location where we integrate that MCP in Databricks via the AI gateway, and then we can have a place where we can connect to Astro by Astronomer, Databricks, other tools such as Jira and DataDog, and then have a much more comprehensive analysis and overview and monitoring of the entire data ecosystem. Having an MCP integration would tremendously help us to have a more comprehensive data platform that is more AI-ready. That is one of the features that I can think of. Another thought would be having an integration with Kubernetes instead of just scheduling everything on Astro by Astronomer workers. That would be helpful. One thing I can think of is that the Astro by Astronomer local developer environment can be improved further, but perhaps that is a very niche use case that I have in mind, and it may not be useful for others. There is room for improvement around having an improved UI and also integration with other tools. On governance, I would say we can have a more granular level of governance even inside workspaces. Having much more granular control over people belonging to the same team in Astro by Astronomer could have different access to different DAGs, depending upon our tagging strategy. That is one of the areas I can suggest in terms of improvement. The AI capabilities can be improved further. I would compare the current AI capabilities to newer models provided by Claude such as Opus or Codex.
I think any further refinements as far as anything major is going to be on the user's side. Everybody's got a different need, so trying to build an overfit solution is only going to hurt other people. The reason I choose eight for Astro by Astronomer is that it is useful for learning and for companies, small to large. There is still a barrier for people who are not familiar with some of the prerequisite knowledge, but I do also think that is not something that needs to be fixed. It is just the nature of how this works. As I said before, if you try to tailor it too much where people were getting almost a no-code experience with it, I think due to the nature of the services it provides, it would cause more trouble than it would fix. An eight means you're doing great.
We want to explore how to deal with multi-tenancy while using Astro by Astronomer, as it is something really important for us because it enhances user experience. Additionally, we aim to resolve some bugs that Airflow has in managed AWS, such as isolated environments, and in general, we want to optimize DevOps around local instances, which is really something cool that Astro by Astronomer provides. I think Astro by Astronomer could improve its pricing, as it is really expensive, especially if you want to have large use in a large-scale enterprise edition, which requires you to create a VPC hosted instance that significantly increases expenses. I believe they should work on this to provide more affordable solutions. I chose 8 out of 10 because there are deployment issues, at least initially, regarding VPC hosting and many other networking issues. Second is pricing, which is really expensive even just to start experimenting, as they also provide you a developer package for this. The total plan needs improvement, but other than that, it is acceptable.
Astro by Astronomer can be improved by adding managed infrastructure with zero setup deliverable developer tools. It can include a high-performance executor, which eliminates manual Airflow maintenance through cloud-hosted or remote execution deployment models. Key improvements for Astro by Astronomer include integrating with Terraform provider and multiple other tools. Regarding Astro by Astronomer's AI capabilities, I think its governance and security need to improve, but currently it can be used quite well, though there are some improvements needed for governance and security related to AI.
I believe there are several areas where Astro by Astronomer can improve. The pricing has become a little expensive because I have very large and always-running workloads. The enterprise configuration sometimes requires a learning curve that could be easier. Advanced customizations could be improved, and the documentation of complex topics needs enhancement. In enterprise scenarios, better documentation would help me more. I believe support is strong. Whenever I reach out to find issues or root causes, I get a very timely response from the support team. Integration is definitely an area that could be much better because of advanced enterprise requirements that need more configurable learning curves. If integration were easier, it would be simpler to deploy to different teams.