Continuing on with providing some examples of various storage technologies and their performance profiles, this time we looked at the growing trend of leveraging internal commodity-based server storage, specifically the new HPE Cloudline 3150 Gen10 AMD processor-based single socket servers with two 3.2TB Samsung PM1725a NVMe drives.

Some Usage cases

1. A deployment may consist of two high availability instances and two disaster recovery instances in a different data center.

The corresponding UAT environment could replicate this giving a total of 8 instances. How do you confirm CPF and Scheduled task alignment across ALL instances.

InterSystems products (IRIS, Caché, Ensemble) already include a built-in Apache web server. But the built-in server is designed for the development and administration tasks and thus has certain limitations. Though you may find some useful workarounds for these limitations, the more common approach is to deploy a full-scale web server for your production environment. This article describes how to set up Apache to work with InterSystems products and how to provide HTTPS access. We will be using Ubuntu, but the configuration process is almost the same for all Linux distributions.

During startup a Caché/Ensemble/HealthShare instance must consult a parameter file to get some information it needs at the early stages of startup. By default it uses the file called cache.cpf, but by adding an extra argument to the ccontrol start command you can make it use an alternative file.

Introduction

Like hardware hosts, virtual hosts in public and private clouds can develop resource bottlenecks as workloads increase. If you are using and managing InterSystems IRIS instances deployed in public or private clouds, you may have encountered a situation in which addressing performance or other issues requires increasing the capacity of an instance's host (that is, vertically scaling).

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.

InterSystems FAQ rubric

You can set the maximum size of the IRISTemp database at IRIS startup by setting a configuration parameter called MaxIRISTempSizeAtStart.

After setting, the system will truncate IRISTemp to the set value (MB) at the next IRIS startup. If the current size is less than the specified MaxIRISTempSizeAtStart, no truncation will occur. Also, if 0 is specified, truncation will not be performed, so the size will start without changing. (Default) Settings are made from the menu below.

InterSystems FAQ rubric

The attached code package provides a simple implementation of a web service client that utilizes the USPS Shipping API to normalize an address.

This code requires the developer to obtain a USPS Shipping API user ID which can be obtained from the USPS shipping API website. The assigned User Id can either be passed into the web service call as a parameter or can be coded as a parameter into the Request object.

YASPE is the successor to YAPE (Yet Another pButtons Extractor). YASPE has been written from the ground up with many internal changes to allow easier maintenance and enhancements.

YASPE functions:

• Parse and chart InterSystems Caché pButtons and InterSystems IRIS SystemPerformance files for quick performance analysis of Operating System and IRIS metrics.
• Allow a deeper dive by creating ad-hoc charts and by creating charts combining the Operating System and IRIS metrics with the "Pretty Performance" option.
• The "System Overview" option saves you from searching your SystemPerformance files for system details or common configuration options.

YASPE is written in Python and is available on GitHub as source code or for Docker containers at:

• https://github.com/murrayo/yaspe

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.

What is Journaling?

Journaling is a critical IRIS feature and a part of what makes IRIS a reliable database. While journaling is fundamental to IRIS, there are nuances, so I wrote this article to summarize (more briefly than our documentation which has all the details) what you need to know. I realize the irony of saying the 27 minute read is brief.

There are two great WRC best practice articles Ensemble Orphaned Messages | InterSystems Developer Community | Best
and the delete helper post DeleteHelper - A Class to Help with Deleting Referenced Persistent Classes (intersystems.com)