Lucee CFML Server (Windows 2019+Boncode+Tomcat)

My main use case for Lucee CFML Server is to build websites for clients, and we do that on top of Lucee CFML Server. We do consultancy on a client patient filing system, which is built on top of Lucee CFML Server. We maintain an open source content management system, which supports all three CFML engines, including Lucee CFML Server. We have been helping clients with various CFML work. In general, over the last few years, our preference has always been to use Lucee CFML Server as the first choice when we pick a CFML engine.

A specific example of a project I have built recently using Lucee CFML Server is for one of our clients in the healthcare industry. They have a filing system to file reports and information about clients and patients in small healthcare organizations, and that has historically been a product built on top of Lucee CFML Server. For the last five to six years, we have been helping the company provide support and maintenance on their application. We migrated it from Lucee 5 to Lucee 6 and moved to Docker containers, Lucee Docker containers for hosting, and performed various work around Lucee CFML Server to ensure the system runs smoothly.

Lucee CFML Server positively impacts my organization by allowing us to easily and quickly develop new functionality within the application. Lucee CFML Server is part of a rapid application development ecosystem, so we have been able to deliver functionality and value for our clients and their customers quickly.

I do not have any hard metrics to share regarding specific outcomes such as time saved, improved client satisfaction, or anything measurable.

Lucee CFML Server offers strong features, particularly that it is a very strong open source alternative in the CFML community. The fact that it is open source is a huge benefit. Beyond that, it has a strong core with a good foundation, which results in good performance, and it is very extensible throughout the CFML ecosystem as well as the underlying Java ecosystem.

Lucee CFML Server's extensibility helps my team and projects. For example, if we need to integrate with some third-party solution, in many of the cases we have dealt with, Java libraries are available for that integration. Instead of needing a dedicated CFML library, which most of the time does not exist, we can use a Java library and plug that into our application and use that Java library within our CFML code to integrate with a third party.

Lucee CFML Server has been in a position over the last few years of pushing the CFML world forward by introducing more modern syntax and techniques.

Lucee CFML Server can be improved by staying up to date. Good documentation is necessary and already available, but that documentation should receive a lot of attention, especially in a world where we move more and more to AI-assisted development. I think it is very important that the documentation provides the right information that AI receives and works with whenever it helps us or writes code for us.

Regarding the governance and security of Lucee CFML Server's AI capabilities, I think they are good. One area it could improve in, due to the changing landscape over the last few months, is to make sure that it stays very up to date with its dependencies. That is not only something for Lucee CFML Server; it is a general thing in all of IT, considering the speed at which vulnerabilities emerge and how fast things need to be patched. It is very important for a product like Lucee CFML Server to be very responsive to any dependencies that have been fixed for security-related issues.

I have been using Lucee CFML Server since around 2013.

Lucee CFML Server is stable.

Lucee CFML Server's scalability is good; it runs on a relatively low memory footprint, which makes it easy to run multiple containers next to each other and scale in that sense.

In terms of customer support, we have not used any customer support from Lucee CFML Server. Personally, I am friends with some team members behind the open source project, and when we reach out to them, we have generally had very good feedback and responses. However, there is no contractual relation.

We did not really switch to Lucee CFML Server; we alongside Lucee CFML Server also use Adobe ColdFusion and BoxLang. It all depends on the use case and what the client requires. In some cases, we have clients that are on Adobe ColdFusion, so we support them with that. In other cases, we are looking into BoxLang ourselves to see what we can do with that for some of the use cases we come across. The main reason we mainly use Lucee CFML Server right now is its open source nature, which really drives costs down for us, and we are a big fan of the open source movement, so we prefer working with open source solutions.

I cannot share any hard numbers regarding return on investment, but we have definitely seen a return. Lucee CFML Server allows us to do the same amount of work with fewer employees, which basically means that we save time and money.

My experience with the pricing, setup cost, and licensing of Lucee CFML Server is that since it is an open source product, the licensing has worked very well in my organization. We have not had any issues with that; it fits well. There is no real pricing involved since it is open source, and we do not have any SLA contracts with the team behind Lucee CFML Server. The setup costs are pretty low; we do the setup ourselves, and we have a lot of experience doing that, so it goes quickly.

I think I already addressed the question about evaluating other options before choosing Lucee CFML Server.

Lucee CFML Server is a very stable and mature solution that really delivers value. There is still some room for improvement, but it is definitely doing the job and it is not the bottleneck in our work, which is a compliment.

Concerning the accuracy and reliability of output in Lucee CFML Server's AI capabilities, I have not used a lot of the AI capabilities yet. I think that is something that will come, but what I see is that not only Lucee CFML Server but the other CFML servers as well provide easy integrations with third parties, AI being one of them. Often, it is as easy to do that integration yourself. I need to look more into it; I do not have a lot of experience with it, but I also have not immediately had the need for it either. One thing I do really appreciate, but again I need to play a little bit more with it, is the way they integrate AI in their error handling. If you enable it, the stack trace comes with AI-powered information, which is very useful.

Lucee CFML Server is deployed in my organization using public cloud supported by AWS. We are heavy users of Fargate to run Lucee CFML Server within containers, and we build those containers using the container images provided by Lucee CFML Server.

I did not purchase Lucee CFML Server through the AWS Marketplace.

My advice for others looking into using Lucee CFML Server is to use it, try it, play with it, and see how it can benefit your use case. I rate Lucee CFML Server an eight out of ten.