We didn't start with a big AI strategy.
We had a legacy InterSystems Caché 2018 application, a lot of old business logic, and a practical need: build a new UI and improve code that had been running for years. At first, I thought an AI coding agent would help only with a small part of the work. Maybe some boilerplate, some REST work around the system, and a bit of help reading old ObjectScript.
In practice, it became much more than that.
Introduction
In today's rapidly evolving threat landscape, organizations deploying mission-critical applications must implement robust security architectures that protect sensitive data while maintaining high availability and performance. This is especially crucial for enterprises utilizing advanced database management systems like InterSystems IRIS, which often powers applications handling highly sensitive healthcare, financial, or personal data.
As an IT and cloud team manager with 18 years of experience with InterSystems technologies, I recently led our team in the transformation of our traditional on-premises ERP system to a cloud-based solution. We embarked on deploying InterSystems IRIS within a Kubernetes environment on AWS EKS, aiming to achieve a scalable, performant, and secure system. Central to this endeavor was the utilization of the AWS Application Load Balancer (ALB) as our ingress controller.
I am currently using IKO 3.6 to deploy an irisCluster on EKS, but I am facing some challenges. Firstly, I need assistance in understanding how to connect to the Web Gateway sidecar. If anyone has experience with this, I would greatly appreciate any guidance or advice you can offer. Secondly, I am trying to utilize the 'seed: path' options of irisDatabases, but I am unsure of the best approach. If anyone has successfully implemented this feature, I would love to hear about your approach and any insights you can provide. Thank you in advance for any help you can offer!