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.

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.

I want to try out iris-DataViz app to visualize my own data. I cloned the repo and docker-compose up -d in AWS. IRIS portal works, but on port 8051 I get nothing. I checked my AWS security groups. I reversed IRIS webserver port and 8051 and I can connect to Management portal using port 8051. I don't understand what is refusing connection on port 8051 running in iris-DataViz container.

Hi all, I need an advice (or a guide):

In an EC2 environment running RHEL, which memory management model makes sense to use. Standard Huge Pages or Transparent Huge Pages?

Hello Community,

I'd like to share with you our article with @Regilo Regilio Guedes de Souza on AWS Amazon blog Automating application-consistent Amazon EBS Snapshots for InterSystems IRIS databases. Our team has created this step-by-step instruction to create application-consistent snapshots for InterSystems IRIS databases. In this article, we outline how to automate pre-scripts to pause I/O and flush buffer to disk and post-scripts to thaw I/O, as shown in the following figure:

IRIS can use a KMS (Key Managment Service) as of release 2023.3. Intersystems documentation is a good resource on KMS implementation but does not go into details of the KMS set up on the system, nor provide an easily followable example of how one might set this up for basic testing.

The purpose of this article is to supplement the docs with a brief explanation of KMS, an example of its use in IRIS, and notes for setup of a testing system on AWS EC2 RedHat Linux system using the AWS KMS. It is assumed in this document that the reader/implementor already has access/knowledge to set up an AWS EC2 Linux system running IRIS (2023.3 or later), and that they have proper authority to access the AWS KMS and AWS IAM (for creating roles and polices), or that they will be able to get this access either on their own or via their organizations Security contact in charge of their AWS access.

This question is about calling AWS REST APIs. Based on:

http://docs.aws.amazon.com/general/latest/gr/sigv4_signing.html

AWS requires REST clients to call their APIs using Signature Version 4 which in case you don't know what I am talking about is a pain in the neck. Here comes the question:

Has anybody, by any chance implemented the v4 signing alg. in COS? If yes, would she or he have the kind heart to share?

Thanks,

Chris

Most transactional applications have a 70:30 RW profile. However, some special cases have extremely high write IO profiles.

I ran storage IO tests in the ap-southeast-2 (Sydney) AWS region to simulate IRIS database IO patterns and throughput similar to a very high write rate application.

The test aimed to determine whether the EC2 instance types and EBS volume types available in the AWS Australian regions will support the high IO rates and throughput required.

I'm trying to execute SQL on a EC2 via SSM:

import boto3

instanceid = "i-123456789"
sql = """SELECT path FROM Security.Applications WHERE ID = '/csp/sys'"""
template = """su - irisusr -c 'cat << EOF | iris sql iris -U %SYS
                """ + sql + """
                        q
                        EOF'
                       """
template = [line.strip() for line in template.splitlines()] 
template = """\n""".join(template) 
ssm_client = boto3.client('ssm') 
response = ssm_client.send_command(
            InstanceIds=[instanceid],
            DocumentName="AWS-RunShellScript",
            Comment=AWS,
            Parameters={'commands': template})

I am often asked to review customers' IRIS application performance data to understand if system resources are under or over-provisioned.

This recent example is interesting because it involves an application that has done a "lift and shift" migration of a large IRIS database application to the Cloud. AWS, in this case.

A key takeaway is that once you move to the Cloud, resources can be right-sized over time as needed. You do not have to buy and provision on-premises infrastructure for many years in the future that you expect to grow into.

Continuous monitoring is required. Your application transaction rate will change as your business changes, the application use or the application itself changes. This will change the system resource requirements. Planners should also consider seasonal peaks in activity. Of course, an advantage of the Cloud is resources can be scaled up or down as needed.

For more background information, there are several in-depth posts on AWS and IRIS in the community. A search for "AWS reference" is an excellent place to start. I have also added some helpful links at the end of this post.

AWS services are like Lego blocks, different sizes and shapes can be combined. I have ignored networking, security, and standing up a VPC for this post. I have focused on two of the Lego block components;
- Compute requirements.
- Storage requirements.

The Amazon Web Services (AWS) Cloud provides a broad set of infrastructure services, such as compute resources, storage options, and networking that are delivered as a utility: on-demand, available in seconds, with pay-as-you-go pricing. New services can be provisioned quickly, without upfront capital expense. This allows enterprises, start-ups, small and medium-sized businesses, and customers in the public sector to access the building blocks they need to respond quickly to changing business requirements.

Updated: 10-Jan, 2023

Overview

Predictable storage IO performance with low latency is vital to provide scalability and reliability for your applications. This set of benchmarks is to inform users of IRIS considering deploying applications in AWS about EBS gp3 volume performance.

Summary

• An LVM stripe can increase IOPS and throughput beyond single EBS volume performance limits.
• An LVM stripe lowers read latency.

Being interoperable is more and more important nowadays. InterSystems IRIS 2022.1 comes with a new messaging API to communicate with event streaming platforms like Kafka, AWS SQS/SNS, JMS and RabbitMQ.

This article shows how you can connect to Kafka and AWS SQS easily.
We start with a brief discussion of the basic concepts and terms of event streaming platforms.

Hi everyone, I'll be honest with you I don't have much idea how to do this, but I was asked to install IRIS for Health on an AWS ubuntu machine(ssh -i "teleker-net.pem" ubuntu@xx.xxx.xx.xxx(no I will put the real number)). My boss has sent me the .key and .pem files that I am supposed to need for the installation.