Best Practices recommendations on how to develop, test, deploy and manage solutions on InterSystems Data Platforms better.
Hi All
I am an avid user of ZEN for over 10 years now and it works for me.
But it seems that Intersystems are no longer actively developing it (or ZEN Mojo), the only published reference to this is here
As an aside, Intersystems makes fine products (I have been using the technology for 35 years) and has great support BUT they are not good at being open with their product road map/retirement plans. This is very embarrassing to me when talking with my end user clients.
Database systems have very specific backup requirements that in enterprise deployments require forethought and planning. For database systems, the operational goal of a backup solution is to create a copy of the data in a state that is equivalent to when application is shut down gracefully. Application consistent backups meet these requirements and Caché provides a set of APIs that facilitate the integration with external solutions to achieve this level of backup consistency.
A few years ago, I was teaching the basics of our %UnitTest framework during Caché Foundations class (now called Developing Using InterSystems Objects and SQL). A student asked if it was possible to collect performance statistics while running unit tests. A few weeks later, I added some additional code to the %UnitTest examples to answer this question. I’m finally sharing it on the Community.
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:
This post is dedicated to the task of monitoring a Caché instance using SNMP. Some users of Caché are probably doing it already in some way or another. Monitoring via SNMP has been supported by the standard Caché package for a long time now, but not all the necessary parameters are available “out of the box”. For example, it would be nice to monitor the number of CSP sessions, get detailed information about the use of the license, particular KPI’s of the system being used and such. After reading this article, you will know how to add your parameters to Caché monitoring using SNMP.
If you’ve ever wondered whether there is a way to regulate access to resources in Caché, wonder no more. In version 2014.2 special classes were added that allow developers to work with semaphores.
The newer dynamic SQL classes (%SQL.Statement and %StatementResult) perform better than %ResultSet, but I did not adopt them for some time because I had learned how to use %ResultSet. Finally, I made a cheat sheet, which I find useful when writing new code or rewriting old code. I thought other people might find it useful.
First, here is a somewhat more verbose adaptation of my cheat sheet:
Hello everyone,
I was first introduced to TDD almost 9 year ago, and I immediately fell in love with it.
Nowadays it's become very popular but, unfortunately, I see that many companies don't use it. Moreover, many developers don't even know what it is exactly or how to use it, mainly beginners.
My goal with this article is to show how to use TDD with %UnitTest. I will show my workflow and explain how to use cosFaker, one of my first projects, which I created using Caché and recently uploaded to OpenExchange.
So buckle up and let's go.
In this article we are going to compare $Increment and $Sequence functions.
First of all, a note for readers who have never heard of $Increment. $Increment is a Caché ObjectScript function which performs an atomic operation to increment its argument by 1 and return the resulting value. You can only pass a global or local variable node as a parameter to $Increment, not an arbitrary expression. $Increment is heavily used when assigning sequential IDs. In such cases parameter of $Increment is usually a global node. $Increment guarantees that each process using it gets a unique ID.
As a developer, you have probably spent at least some time writing repetetive code. You may have even found yourself wishing you could generate the code programmatically. If this sounds familiar, this article is for you!
We'll start with an example. Note: the following examples use the %DynamicObject interface, which requires Caché 2016.2 or later. If you are unfamiliar with this class, check out the documentation here: Using JSON in Caché. It's really cool!
##Example
For each defined property, query or an index, several corresponding methods would be automatically generated on a class compilation. These methods can be very useful. In this article, I would describe some of them.
This series of articles would cover Python Gateway for InterSystems Data Platforms. Leverage modern AI/ML tools and execute Python code and more from InterSystems IRIS. This project brings you the power of Python right into your InterSystems IRIS environment:
The plan for the series so far (subject to change).
I' have done some tests with Caché and Apache Zeppelin. I want to share my experince to use both systems together. I'll try to describe all steps that are required to config Zeppelin to connect to Caché.
For all who think: What the heck is Apache Zeppelin?, here some details what the project site (http://zeppelin.apache.org) says:
Hi all. Today we are going to upload a ML model into IRIS Manager and test it.
Note: I have done the following on Ubuntu 18.04, Apache Zeppelin 0.8.0, Python 3.6.5.
These days many available different tools for Data Mining enable you to develop predictive models and analyze the data you have with unprecedented ease. InterSystems IRIS Data Platform provide a stable foundation for your big data and fast data applications, providing interoperability with modern DataMining tools.
The last time that I created a playground for experimenting with machine learning using Apache Spark and an InterSystems data platform, see Machine Learning with Spark and Caché, I installed and configured everything directly on my laptop: Caché, Python, Apache Spark, Java, some Hadoop libraries, to name a few. It required some effort, but eventually it worked. Paradise. But, I worried. Would I ever be able to reproduce all those steps? Maybe. Would it be possible for a random Windows or Java update to wreck the whole thing in an instant? Almost certainly.
Have some free text fields in your application that you wish you could search efficiently? Tried using some methods before but found out that they just cannot match the performance needs of your customers? Do I have one weird trick that will solve all your problems? Don’t you already know!? All I do is bring great solutions to your performance pitfalls!
As usual, if you want the TL;DR (too long; didn’t read) version, skip to the end. Just know you are hurting my feelings.
I needed to know programmatically if last ran failed or not.
After some exploring, here's the code:
ClassMethod isLastTestOk() As %Boolean{ set in = ##class(%UnitTest.Result.TestInstance).%OpenId(^UnitTest.Result) for i=1:1:in.TestSuites.Count() { #dim suite As %UnitTest.Result.TestSuite set suite = in.TestSuites.GetAt(i) return:suite.Status=0 $$$NO } quit $$$YES}I am planning to implement Business Intelligence based on the data in my instances. What is the best way to set up my databases and environment to use DeepSee?
InterSystems Data Platform includes utilities and tools for system monitoring and alerting, however System Administrators new to solutions built on the InterSystems Data Platform (a.k.a Caché) need to know where to start and what to configure.
This guide shows the path to a minimum monitoring and alerting solution using references from online documentation and developer community posts to show you how to enable and configure the following;
Caché Monitor: Scans the console log and sends emails alerts.
System Monitor: Monitors system status and resources, generating notifications (alerts and warnings) based on fixed parameters and also tracks overall system health.
Health Monitor: Samples key system and user-defined metrics and compares them to user-configurable parameters and established normal values, generating notifications when samples exceed applicable or learned thresholds.
History Monitor: Maintains a historical database of performance and system usage metrics.
pButtons: Operating system and Caché metrics collection scheduled daily.
Remember this guide is a minimum configuration, the included tools are flexible and extensible so more functionality is available when needed. This guide skips through the documentation to get you up and going. You will need to dive deeper into the documentation to get the most out of the monitoring tools, in the meantime, think of this as a set of cheat sheets to get up and running.
In this series of articles, I'd like to present and discuss several possible approaches toward software development with InterSystems technologies and GitLab. I will cover such topics as:
I have a few cubes and numerous dashboards and I am ready to deploy them to our end users and administrators. How to configure DeepSee so that users don’t disrupt each other’s areas and are restricted from using functionalities specific to developers?
Hi,
This is a quick tutorial how to install and use TFS in Atelier. It is based on my self experience and some tricks that I 've noted.
If you are used to using visual studio maybe you feel that is a bit slow and heavy, but you have the same TFS panel as you have in Visual Studio, so don't need any special "training" to use it 
It's important don't store the file .buildpath because it has the server definition that you are working in a team, each one have the personal configuration, so the name of the server could be different.
To prevent it, create a file called .tfignore with this content
This is a posting about a particular feature of Caché which I find useful but is probably not well known or used. I am referring to the feature of Language Extensions.
This feature allows you to extend the commands, special variables and functions available in Caché Object Script with commands, special variables and functions of your own. This functionality also applies to other languages the Caché supports at the server, including Caché Basic and Multivalue Basic.
Why would I need or want to add new commands ?
When working at the Caché command prompt I sometimes want to run an operating system command on the server host. By prefixing my command line with ! or $ I can do this with ease. The following examples are from 2017.1 on Windows, but the feature is available on all versions and platforms:
The goal of this “DeepSee Troubleshooting Guide” is to help you track down and fix problems in your DeepSee project.
If the problem can’t be fixed by following the guidelines, you will at least have enough information to submit a WRC issue with DeepSee Support and provide all the evidence to us, so we can continue the investigation together and resolve it faster!
Please NOTE: If you are unfamiliar with the consequences of a given action or command, please don’t run it as it might have an effect on your production system. In this case contact DeepSee Support for further assistance.
Everybody has a testing environment.
Some people are lucky enough to have a totally separate environment to run production in.
-- Unknown
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In this series of articles, I'd like to present and discuss several possible approaches toward software development with InterSystems technologies and GitLab. I will cover such topics as:
This first part deals with the cornerstone of modern software development - Git version control system and various Git flows.
With the launch of InterSystems IRIS Data Platform, we provide our product even in a Docker container. But what is a container?
The fundamental container definition is that of a sandbox for a process.
Containers are software-defined packages that have some similarities to virtual machines (VM) like for example they can be executed.
Containers provide isolation without a full OS emulation. Containers are therefore much lighter than a VM.
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.
Google Cloud Platform (GCP) provides a feature rich environment for Infrastructure-as-a-Service (IaaS) as a cloud offering fully capable of supporting all of InterSystems products including the latest InterSystems IRIS Data Platform. Care must be taken, as with any platform or deployment model, to ensure all aspects of an environment are considered such as performance, availability, operations, and management procedures. Specifics of each of those areas will be covered in this article.