This week I am going to look at CPU, one of the primary hardware food groups :) A customer asked me to advise on the following scenario; Their production servers are approaching end of life and its time for a hardware refresh. They are also thinking of consolidating servers by virtualising and want to right-size capacity either bare-metal or virtualized. Today we will look at CPU, in later posts I will explain the approach for right-sizing other key food groups - memory and IO.

So the questions are:

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"Telegram" is a well-known instant messenger, which provides an API for creating bots. The features of this API allow you to create bots with a wide range of functionality including receiving payments.
With the help of the telegram bot, I solved a simple task - sending Alerts from Ensemble to Telegram.

Advantages: Alerts come to the mobile phone, a notification appears, so there is no need to install any additional applications (in contrast to the solution https://community.intersystems.com/post/sending-alerts-mobile-phone-using-pushover- httpoutboundadapter).

The bot can be extended by adding new commands, for example, for managing the Production or for solving other tasks in Iris, Ensemble or Cache.

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Article
· Feb 16, 2018 2m read
Adopted Bitmap

The base class Bmap.Person defines persons within an organization distributed
by various countries. All records are indexed by (Country, PersonalId).
this structure doesn't allow use of bitmaps.

So a wrapper class Bmap.PersonQ around the data eliminates the top level of
the index (Country) and isolates the PersonalId (%Integer, MINVAL=1).
We are ready to use a Bitmap index.

A few performance figures on 300010 generated records.
You see that Relative Cost are sometimes quite misleading.

base

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Article
· Nov 11, 2017 3m read
Summary on Local Variable Scoping

This should be an overview over a subject that pops up over several places in online documentation mostly as remarks and never as dedicated chapter.

Once upon a time ... No it's not a fairy tale.
In the beginning of Caché (and before) you had your partition to run your code. Part of that partition was a space with all your local variables nicely sorted by %,A,..Z,a,...z

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Globals, these magic swords for storing data, have been around for a while, but not many people can use them efficiently or know about this super-weapon altogether.

If you use globals for tasks where they truly shine, the results may be amazing, either in terms of increased performance or dramatic simplification of the overall solution (1, 2).

Globals offer a special way of storing and processing data, which is completely different from SQL tables. They were first introduced in 1966 in the M(UMPS) programming language, which was initially used in medical databases. It is still used in the same way, but has also been adopted by some other industries where reliability and high performance are top priorities: finance, trading, etc.

Later M(UMPS) evolved into Caché ObjectScript (COS). COS was developed by InterSystems as a superset of M. The original language is still accepted by developers' community and alive in a few implementations. There are several signs of activity around the web: MUMPS Google group, Mumps User's group), effective ISO Standard, etc.

Modern global based DBMS supports transactions, journaling, replication, partitioning. It means that they can be used for building modern, reliable and fast distributed systems.

Globals do not restrict you to the boundaries of the relational model. They give you the freedom of creating data structures optimized for particular tasks. For many applications reasonable use of globals can be a real silver bullet offering speeds that developers of conventional relational applications can only dream of.

Globals as a method of storing data can be used in many modern programming languages, both high- and low-level. Therefore, this article will focus specifically on globals and not the language they once came from.

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Index

This is a list of all the posts in the Data Platforms’ capacity planning and performance series in order. Also a general list of my other posts. I will update as new posts in the series are added.


You will notice that I wrote some posts before IRIS was released and refer to Caché. I will revisit the posts over time, but in the meantime, Generally, the advice for configuration is the same for Caché and IRIS. Some command names may have changed; the most obvious example is that anywhere you see the ^pButtons command, you can replace it with ^SystemPerformance.


While some posts are updated to preserve links, others will be marked as strikethrough to indicate that the post is legacy. Generally, I will say, "See: some other post" if it is appropriate.


Capacity Planning and Performance Series

Generally, posts build on previous ones, but you can also just dive into subjects that look interesting.


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Killer presentations are essential for opening doors, doing business and delighting customers. These types of presentations move away from the traditional and tiring topics and portions of texts, or even pictures of happy people to get closer to the interests of their audience.The best presentations materialize what customers are looking for into something they can see working. Instead of promises, examples in execution and the ability to be very close to what you want to do.

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Article
· Aug 16, 2023 11m read
Http request response time monitoring

Hi developers!

Today I would like to address a subject that has given me a hard time. I am sure this must have been the case for quite a number of you already (so-called “the bottleneck”). Since this is a broad topic, this article will only focus on identifying incoming HTTP requests that could be causing slowness issues. I will also provide you with a small tool I have developed to help identify them.

Our software is becoming more and more complex, processing a large number of requests from different sources, be it front-end or third-party back-end applications. To ensure optimal performance, it is essential to have a logging system capable of taking a few key measurements, such as the response time, the number of global references and the number of lines of code executed for each HTTP response. As part of my work, I get involved in the development of EMR software as well as incident analysis. Since user load comes mostly from HTTP requests (REST API or CSP application), the need to have this type of measurement when generalized slowness issues occur has become obvious.

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When there's a performance issue, whether for all users on the system or a single process, the shortest path to understanding the root cause is usually to understand what the processes in question are spending their time doing. Are they mostly using CPU to dutifully march through their algorithm (for better or worse); or are they mostly reading database blocks from disk; or mostly waiting for something else, like LOCKs, ECP or database block collisions?

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Hi Developers,

The annual competition for InterSystems IRIS developers is fast approaching!

We're super excited to invite you all to join the Grand Prix contest for building open-source solutions using InterSystems IRIS data platform!

🏆 InterSystems Grand Prix Contest 2023 🏆

Duration: June 12th - July 9th, 2023

Prize pool: $26,000

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One of the reasons why I love Cache and Iris is that not only you can do anything you can imagine, also you can do it in a lot of different ways!!.

Imagine that you have an integration running with IRIS connected by ODBC you probably only run SQL queries but you can also create stored procedures and inside write the code to do everything you can imagine.

I'm going to give you some examples but the limit is your imagination!!

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Hi Developers!

Often when we develop some library, tool, package, whatever on InterSystems ObjectScript we have a question, how we deploy this package on the target machine?

Also, we often expect that some other libraries already installed, so our package depends on them, and often on some particular version of it.

When you code on javascript, python, etc the role of packages deployment with dependency management takes package manager.

So, I'm pleased to announce that InterSystems ObjectScript Package Manager available!

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Docker 20.10.14 (released March 23, 2022) changes the Linux capabilities given to containers in a manner that is incompatible with the Linux capability checker in InterSystems IRIS 2021.1 (and up) containers.

Users running Docker 20.10.14 on Linux will find that IRIS 2021.1+ containers will fail to start and the logs will incorrectly report that required Linux capabilities are missing. For example:

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Hello everyone!

We are Longevica (https://www.longevica.com/) Healthtech, a Boston-based healthy aging digital health startup. Longevica was born as a research company back in 2009; we pioneered the screening of chemicals, which would drastically extend the life span. With 1000 screened pharmaceuticals and 20 000 mice experiments, we have identified specific compounds that, if taken daily, could extend life by years. This discovery leads to two questions: how to measure the effect of aging progress in real-time and how to make this a lifelong habit. This led us to the digital health market to create a new company Longevica HealthTech.

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The InterSystems Iris Fhirserver running on a Raspberry Pi Raspberry running as a FHIRserver

Raspberry running as FHIRserver

About a year ago I wrote some articles about the installation of the HAPI FHIRserver on a Raspberry Pi. At that time, I only knew the basics of the FHIR standard, little about the technology behind FHIR-servers and not much more about the Raspberry. By trying, failing, giving up and trying again I learned a lot.

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The 2021.2 release of the InterSystems IRIS Data Platform includes many exciting new features for fast, flexible and secure development of your mission-critical applications. Embedded Python definitely takes the limelight (and for good reason!), but in SQL we've also made a massive step forward towards a more adaptive engine that gathers detailed statistical information about your table data and exploits it to deliver the best query plans. In this brief series of articles, we'll take a closer at three elements that are new in 2021.2 and work together towards this goal, starting with Run Time Plan Choice.

It's hard to figure out the right order to talk about these (you can't imagine how often I've reshuffled them in writing this article!) because they fit together in such a nice way. As such, feel free to go on a limb and read these in random order smiley.

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If a picture is worth a thousand words, what's a video worth? Certainly more than typing a post.

Please check out my "Coding talks" on InterSystems Developers YouTube:

1. Analysing InterSystems IRIS System Performance with Yape. Part 1: Installing Yape

https://www.youtube.com/embed/3KClL5zT6MY
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Running Yape in a container.

2. Yape Container SQLite iostat InterSystems

https://www.youtube.com/embed/cuMLSO9NQCM
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Extracting and plotting pButtons data including timeframes and iostat.

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Last week, we announced the InterSystems IRIS Data Platform, our new and comprehensive platform for all your data endeavours, whether transactional, analytics or both. We've included many of the features our customers know and loved from Caché and Ensemble, but in this article we'll shed a little more light on one of the new capabilities of the platform: SQL Sharding, a powerful new feature in our scalability story.

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[Background]

InterSystems IRIS family has a nice utility ^SystemPerformance (as known as ^pButtons in Caché and Ensemble) which outputs the database performance information into a readable HTML file. When you run ^SystemPerformance on IRIS for Windows, a HTML file is created where both our own performance log mgstat and Windows performance log are included.

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The IKO documentation is robust. A single web page, that consists of about 50 actual pages of documentation. For beginners that can be a bit overwhelming. As the saying goes: how do you eat an elephant? One bite at a time. Let's start with the first bite: helm.

What is Helm?

Helm is to Kubernetes what the InterSystems Package Manager (IPM, formerly ObjectScript Package Manager - ZPM) is to IRIS.

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iris-docker-multi-stage-script

A python script to keep your docker iris images in shape ;)

Witout changing your dockerfile or your code you can reduce the size of your image by 50% or more !

TL;DR

Name the builder image builder and the final image final and add this to end of your Dockerfile:

Modify your Dockerfile to use a multi-stage build:

ARG IMAGE=intersystemsdc/irishealth-community:latest
FROM $IMAGE as builder

Add this to end of your Dockerfile:

FROM $IMAGE as final

ADD --chown=${ISC_PACKAGE_MGRUSER}:${ISC_PACKAGE_IRISGROUP} https://github.com/grongierisc/iris-docker-multi-stage-script/releases/latest/download/copy-data.py /irisdev/app/copy-data.py

RUN --mount=type=bind,source=/,target=/builder/root,from=builder \
    cp -f /builder/root/usr/irissys/iris.cpf /usr/irissys/iris.cpf && \
    python3 /irisdev/app/copy-data.py -c /usr/irissys/iris.cpf -d /builder/root/ 

Boom! You're done!

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