Article
Igor Titarenko · Sep 10, 2020 3m read
How To Create "Write-Only" Code

One of the leading benefits of ObjectScript is the speed and efficiency it allows for an experienced developer. Let's look at an example of how you can benefit from ObjectScript today.

Suppose you have a class that stores the names of your users. We'll call the class Data.User, and give it a string property Name. Next, we will need a method to create a new user or update an existing one. A naive, simplistic approach might look like this example:

 

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Hello,

This package may be of interest...

Link: https://github.com/litesolutions/cachedb-import

I have programmed this over a hunch, in order to facilitate the retrieval of source code from a Caché installation. It makes use of the Java API provided by Caché.

Right now, I use it as a means to salvage sources in order to analyze them using the SonarQube plugin I develop for my employer. Unfortunately this plugin is not open source.

I am calling for help here, on two fronts:

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In the last post we scheduled 24-hour collections of performance metrics using pButtons. In this post we are going to be looking at a few of the key metrics that are being collected and how they relate to the underlying system hardware. We will also start to explore the relationship between Caché (or any of the InterSystems Data Platforms) metrics and system metrics. And how you can use these metrics to understand the daily beat rate of your systems and diagnose performance problems.

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This is the third post of a series explaining how to create an end-to-end Machine Learning system.

Training a Machine Learning Model

When you work with machine learning is common to hear this work: training. Do you what training mean in a ML Pipeline?
Training could mean all the development process of a machine learning model OR the specific point in all development process
that uses training data and results in a machine learning model.

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Article
David Reche · Dec 22, 2015 1m read
Sign and verify in SMIME format

In some project, I found the need to use SMIME format https://www.ietf.org/rfc/rfc3851.txt, basically is an standard used to wrap a message together with its signature using a certificate (usually X509). Ensemble don't have a single class to do that but inside the Ensemble installation we have the openssl utility, so in this example I use the "openssl smime" command to sign or verify a message.

The example has two Business Process that able to sign or verify and in order to test I made a simple production.

Hope this helps

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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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Article
Evgeny Shvarov · Mar 31, 2018 1m read
What Are You Using For Issue Tracking?

Hi, Community!

What is your favorite issue tracking system for projects with InterSystems Data Platform? What did you use and what are you using now?

In projects with InterSystems Data Platform, I worked with Redmine, JIRA, Trello. A lot of code versioning systems now have this feature too (Gitlab, Github).

Now my favorite for small and medium projects is Github, because it is simple, is very close to code (commit-issue linkage) and it has kanban).

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InterSystems IRIS currently limits classes to 999 properties.

But what to do if you need to store more data per object?

This article would answer this question (with the additional cameo of Community Python Gateway and how you can transfer wide datasets into Python).

The answer is very simple actually - InterSystems IRIS currently limits classes to 999 properties, but not to 999 primitives. The property in InterSystems IRIS can be an object with 999 properties and so on - the limit can be easily disregarded.

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Developing a Full-Stack JavaScript web app with Caché requires you to bring together the right building blocks. In the previous part, we created a basic front-end React application. In the second part of this article series I will show how to choose the right back-end technology for your application. You will see Caché allows you to use many different approaches to link your front-end to your Caché server, depending on your application's needs. In this part we will set up a back-end with Node.js/QEWD and CSP/REST. In the next part we will enhance our basic web app and connect it to Caché using these technologies.

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Article
Timur Safin · Apr 1, 2019 3m read
Closures in ObjectScript

After many sleepless nights it's a pleasure to announce the newer, better, moderner ObjectScript compiler which implemented pretty much everything you ever wanted to have in modern ObjectScript:

  • Design objective of this new compiler is to parse reasonable subset of current ObjectScript syntax which will look readable for stranger, and not scare them with 1 letter syntax. The good start for compiler was the old-good COS Guidelines from here https://github.com/intersystems-ru/cos-guidelines
  • For reasons we mentioned above we do not parse 1 letter syntax. It's declared evil;
  • We do not handle dotted syntax for the same reason - modern syntax with {} is proper replacement for dotted syntax blocks;

But we not only parse the modern ObjectScript syntax, we have implemented finally the long-standing request which we always dreamed about. Closures!

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Article
Eduard Lebedyuk · Dec 7, 2017 3m read
Asynchronous REST

In this article I'd like to discuss asynchronous REST and approaches to implementing it.

Why do we need asynchronous REST? Simply put - answering the request takes too much time. While most requests usually can be satisfied immediately, some can't. The reasons are varied:

  • You need to perform time-consuming calculations
  • Performing action actually takes time (for example container creation)
  • etc.

The solution to these problems is asynchronous REST. Asynchronous REST works by separating request and real response. Here's an example, let's consider the following simple async REST broker:

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Article
David Loveluck · Jan 15, 2016 1m read
Activity Monitor in Ensemble 2016.1

Has anyone tried the new Activity Volume Statistics and Monitoring  in Ensembel 2016.1? I would love to get some feedback.

If you haven't read about this, there is a dashboard that provides counts and response times for messages sent and received by each configuration item. Alternatively the underlying data is arranged in tables that should make it easy for you to use your favorite SQL reporting tools to generate reports for short term performance monitoring or longer term capacity planning.

Dave

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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:

  • Git 101
  • Git flow (development process)
  • GitLab installation
  • GitLab Workflow
  • Continuous Delivery
  • GitLab installation and configuration
  • GitLab CI/CD
  • Why containers?
  • Containers infrastructure
  • CD using containers

In the first article, we covered Git basics, why a high-level understanding of Git concepts is important for modern software development, and how Git can be used to develop software.

In the second article, we covered GitLab Workflow - a complete software life cycle process and Continuous Delivery.

In the third article, we covered GitLab installation and configuration and connecting your environments to GitLab

In the fourth article, we wrote a CD configuration.

In the fifth article, we talked about containers and how (and why) they can be used.

In the sixth article let's discuss main components you'll need to run a continuous delivery pipeline with containers and how they all work together.

In this article, we'll build Continuous Delivery configuration discussed in the previous articles.

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Article
Mike Kadow · Jun 20, 2016 4m read
NewBie's Corner Session 8 Not

NewBie's Corner Session 8 Not

Welcome to NewBie's Corner, a weekly or biweekly post covering basic Caché Material.

Click on the Caché Cube in your system tray and select Terminal to try out these commands.

NOT operator ('), single quote or apostrophe 

The "NOT" operator reverses the truth-value and is intended for numeric operands, however it can be used on alphanumeric operands.

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Hi Community!

I think everyone keeps the source code of the project in the repository nowadays: Github, GitLab, bitbucket, etc. Same for InterSystems IRIS projects  check any on Open Exchange.

What do we do every time when start or continue working with a certain repository with InterSystems Data Platform?

We need a local InterSystems IRIS machine, have the environment for the project set up and the source code imported.

So every developer performs the following:

  1. Check out the code from repo
  2. Install/Run local IRIS installation
  3. Create a new namespace/database for a project
  4. Import the code into this new namespace
  5. Setup all the rest environment
  6. Start/continue coding the project 

If you dockerize your repository this steps line could be shortened to this 3 steps:

  1. Check out the code from repo
  2. Run docker-compose build 
  3. Start/continue coding the project 

Profit - no any hands-on for 3-4-5 steps which could take minutes and bring head ache sometime.

You can dockerize (almost) any your InterSystems repo with a few following steps. Let’s go!

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The following steps show you how to display a sample list of metrics available from the /api/monitor service.

In the last post, I gave an overview of the service that exposes IRIS metrics in Prometheus format. The post shows how to set up and run IRIS preview release 2019.4 in a container and then list the metrics.


This post assumes you have Docker installed. If not, go and do that now for your platform :)

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