There are often questions surrounding the ideal Apache HTTPD Web Server configuration for HealthShare. The contents of this article will outline the initial recommended web server configuration for any HealthShare product.

As a starting point, Apache HTTPD version 2.4.x (64-bit) is recommended. Earlier versions such as 2.2.x are available, however version 2.2 is not recommended for performance and scalability of HealthShare.

We are experimenting with IIS, as the PWS will be gone in newer versions.

The code which is executed, takes 15ms to run. If we execute it through PWS (REST), there is some overhead and the total execution time is 40ms, which is acceptable. However, if we go through IIS, it takes 150ms or sometimes even more.

Both PWS and IIS are running on the same server as IRIS in this case. No optimisations have been done on IIS.

Any suggestions on where to look/what to optimize on IIS?

You may have heard about our mg-dbx-napi interface for IRIS which provides insanely fast access from Node.js. If you've been following recent developments in the server-side JavaScript world, you'll be excited to know that mg-dbx-napi also works with Bun.js, the latter proving to be significantly faster than Node.js for many/most purposes.

Of course, if you're a Node.js user, you'll probably wonder how mg-dbx-napi compares with the Native API for Node.js that is included with IRIS.

It seems like yesterday when we did a small project in Java to test the performance of IRIS, PostgreSQL and MySQL (you can review the article we wrote back in June at the end of this article). If you remember, IRIS was superior to PostgreSQL and clearly superior to MySQL in insertions, with no big difference in queries.

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.

InterSystems IRIS offers various ways how to profile your code, in most cases it produces enough information to find the places where the most time is spent or where the most global sets. But sometimes it's difficult to understand the execution flow and how it ended at that point.

To solve this, I've decided to implement a way to build a report in a way, so, it's possible to dive by stack down

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.

Hey Developers,

Enjoy watching the new video on InterSystems Developers YouTube:

⏯ System Performance Review for InterSystems IRIS Applications @ Global Summit 2022

https://www.youtube.com/embed/lGnJS3VMFUA
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A good writer is supposed to draw you in with the title and bury the answer somewhere in the article. I suppose this makes me a bad writer – don’t think less of me, my whole feeling of self-worth comes from the opinions of internet strangers!

In terms of general through-put design and long term support, I'm considering what would be a "best approach" for needing to create multiple batch files in a few different layouts from the same data-sets.

Your application is deployed and everything is running fine. Great, hi-five! Then out of the blue the phone starts to ring off the hook – it’s users complaining that the application is sometimes ‘slow’. But what does that mean? Sometimes? What tools do you have and what statistics should you be looking at to find and resolve this slowness? Is your system infrastructure up to the task of the user load? What infrastructure design questions should you have asked before you went into production? How can you capacity plan for new hardware with confidence and without over-spec'ing? How can you stop the phone ringing? How could you have stopped it ringing in the first place?

While reviewing our documentation for our ^pButtons (in IRIS renamed as ^SystemPerformance) performance monitoring utility, a customer told me: "I understand all of this, but I wish it could be simpler… easier to define profiles, manage them etc.".

After this session I thought it would be a nice exercise to try and provide some easier human interface for this.

The first step in this was to wrap a class-based API to the existing pButtons routine.

I was also able to add some more "features" like showing what profiles are currently running, their time remaining to run, previously running processes and more.

The next step was to add on top of this API, a REST API class.

With this artifact (a pButtons REST API) in hand, one can go ahead and build a modern UI on top of that.

For example -

Could anyone please explain why Caché has a %STARTSWITH function while it supports ANSI SQL "LIKE"?

thank you very much.

Since Caché 2017 the SQL engine has included new set of statistics. These record the number of times a query is executed and the time it takes to run.