Initially, in version 3, Jiffy.ai did not have support for containerization. In our environment, we are heavy users of containers and container illustrators. So, the initial deployment option was running based on individual hosts that we deployed in the cloud. That created a singularity in the way that we deployed services in our system. However, in the latest version release (4), they have full support for containerization. This has been a great improvement and one of the driving factors for switching from version 3 to version 4 very soon. The containerization capability will make a huge difference in our deployment process, because it doesn't create exceptions in the way we would deploy services. All the rest of the system is containers, so if you now have a product from a vendor that doesn't support containerization that means you must have a different process of deploying services, then accompany it with corresponding policies, because we have policies on how systems need to be configured to be reliable, secure, etc. Also, there are the BCDR aspects of it: the disaster recovery and business continuity. So, if you're introducing a new way of deploying services, now you need to have a BCDR plan dedicated to that as well, as opposed to deploying everything using a single model of deployment (mainly containers). Therefore, this will simplify a lot of things, in terms of DevOps.
