If you run your own infrastructure in a private cloud with one of the larger operators such as AWS or Azure, you may have noticed some time ago came support for ARM64 processors.
The DecisionRules cloud runs partially in some locations on AWS T4g instances, which are available in many locations. T4g instance types use AWS Graviton 2 processors. We try to combine different types of AWS instances that suit a given site.
Why do we use ARM64? - Cheaper operation of infrastructure while maintaining comparable performance. That's why we decided to publish ARM compatible containers for our On-Premise customers as well.
AWS promises 40% savings over other Intel-based instances. In our case, the savings are lower, but still noticeable on the larger number of instances that we run or need to create on-demand with increased traffic to our APIs.
DecisionRules docker containers are published on DockerHub. Here, as with other containers, you see the supported architecture.
Our customers and their technology scouts often use Apple M1 processors, and without ARM compliant containers, DecisionRules was slower to run as instructed because emulation via Rosetta 2 was required. This issue is now resolved and you can easily run DecisionRules showcase on your Apple M1 chip.
We are bringing a series of articles describing the application of DecisionRules to real-world situations. In this article, we present a case from the financial world.
DecisionRules is constantly improving its collection of advanced functions which can be used for custom computation within decision tables and decision trees. In this article, we shall look at a specific and very useful type of functions treating arrays.