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

In the previous 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. Still, our focus was on the implementation part of software development, but this part presents:

  • GitLab Workflow - a complete software life cycle process - from idea to user feedback
  • Continuous Delivery - software engineering approach in which teams produce software in short cycles, ensuring that the software can be reliably released at any time. It aims at building, testing, and releasing software faster and more frequently.

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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.

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This article was written as an attempt to share the experience of installing the InterSystems Caché DBMS for production environment.
We all know that the development configuration of a DBMS is very different from real-life conditions.
As a rule, development is carried out in “hothouse conditions” with a bare minimum of security measures, but when we publish our project online, we must ensure its reliable and uninterrupted operation in a very aggressive environment.

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Article
· Nov 8, 2016 4m read
Returning Disk Space to File Systems

This is the first article in a series discussing how to regain disk space from Caché databases at the operating system level. This introductory article discusses Caché database growth and gives an overview of various methods you can use to return unused disk space that is allocated to database files back to the file system. But before we talk about returning space to the file system, let’s first review how does it get allocated in the first place.

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A short post for now to answer a question that came up. In post two of this series I included graphs of performance data extracted from pButtons. I was asked off-line if there is a quicker way than cut/paste to extract metrics for mgstat etc from a pButtons .html file for easy charting in Excel.

See: - Part 2 - Looking at the metrics we collected

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After reading Stephen Wilson's article "Windows 7 performs shutdown too fast for Cache to close and so it gets forced down" I've recalled another solution that was based on Local Group Policy, which allows to control extra actions that should occur on computer startup or shutdown. How to add a computer shutdown script is well documented in MS Technet article.

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Article
· Nov 19, 2015 1m read
Disk and storage design considerations

There are many storage technologies available today from various vendors. The storage technology and configuration best for your application depends on the application access patterns and workloads.

The attached document discusses the various design considerations and recommendations for various technologies. This guide is to help you during discussions with your storage vendor to determine the appropriate storage technologies and products that will work best to meet the performance goals for your applications.

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InterSystems FAQ rubric

※Use this method if you want to compare databases that have been replicated using mirroring, shadowing, or some other mechanism.

You can use the DATACHECK utility to compare global variables. Please refer to the document below.
Overview of DataCheck [IRIS]

***

Routine comparisons use the system routine %RCMP or the Management Portal.

Below is how to use it in the Management Portal.

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** Revised Feb-12, 2018

While this article is about InterSystems IRIS, it also applies to Caché, Ensemble, and HealthShare distributions.

Introduction

Memory is managed in pages. The default page size is 4KB on Linux systems. Red Hat Enterprise Linux 6, SUSE Linux Enterprise Server 11, and Oracle Linux 6 introduced a method to provide an increased page size in 2MB or 1GB sizes depending on system configuration know as HugePages.

At first HugePages required to be assigned at boot time, and if not managed or calculated appropriately could result in wasted resources. As a result various Linux distributions introduced Transparent HugePages with the 2.6.38 kernel as enabled by default. This was meant as a means to automate creating, managing, and using HugePages. Prior kernel versions may have this feature as well however may not be marked as [always] and potentially set to [madvise].

Transparent Huge Pages (THP) is a Linux memory management system that reduces the overhead of Translation Lookaside Buffer (TLB) lookups on machines with large amounts of memory by using larger memory pages. However in current Linux releases THP can only map individual process heap and stack space.

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Article
· Jul 12, 2019 2m read
Basic Database Metrics example

This is a self contained class that can be run from the Intersystems Task Scheduler which records peak usage details for databases and licenses built up throughout the day and retaining 30 days history.

To schedule the task to run every hour:

d ##class(Metrics.Task).Schedule()

You can also specify your own start time, stop time, and run interval:

d ##class(Metrics.Task).Schedule(startTime, stopTime, intervalMins)

Metrics are stored in ^Metrics in the namespace that the class resides in/is run from.

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IMPORTANT NOTE InterSystems no longer provides a separate InterSystems Reports Server container. To run containerized InterSystems Reports Server, use Logi Reports Server container and your InterSystems Reports Server license. Documentation.

InterSystems Reports is powered by Logi Report (formerly named JReport), a product of Logi Analytics. InterSystems Reports is supported by InterSystems IRIS and InterSystems IRIS for Health. It provides a robust modern reporting solution that includes:

  • Embedded operational reporting which can be customized by both report developers and end users.
  • Pixel-perfect formatting that lets you develop highly specific form grids or other special layout elements for invoices, documents, and forms.
  • Banded layouts that provide structure for aggregated and detailed data.
  • Exact positioning of headers, footers, aggregations, detailed data, images, and sub-reports.
  • A variety of page report types.
  • Large-scale dynamic report scheduling and distribution including export to PDF, XLS, HTML, XML, and other file formats, printing, and archiving for regulatory compliance.

InterSystems Reports consists of:

  • A report designer, which provides Design and Preview Tabs that enable report developers to create and preview reports with live data.
  • A report server which provides end users browser-based access to run, schedule, filter, and modify reports.

From InterSystems documentation.

This article focuses on the Server part of InterSystems Reports and provides a guide on running Report Server in containers while persisting all the data.

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I wanted to write it as a comment to article of @Evgeny Shvarov . But it happens to be so long, so, decided to post it separately.

Image result for docker clean all images

I would like to add a bit of clarification about how docker uses disk space and how to clean it. I use macOS, so, everything below, is mostly for macOS, but docker commands suit any platform.

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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.

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Container Images

In this second post on containers fundamentals, we take a look at what container images are.

What is a container image?

A container image is merely a binary representation of a container.

A running container or simply a container is the runtime state of the related container image.

Please see the first post that explains what a container is.

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Article
· Jun 21, 2016 1m read
Simple Cache systemd Unit

Hello

I have noticed that Cache (2016.1 at the time of writing) doesn't come with a systemd startup script for RHEL7.

Here is a small example script I have built.

[Unit]
Description=Intersystems Cache

[Service]
Type=forking
ExecStart=/bin/bash -c '/usr/cachesys/cstart 2>&1 | logger -t cache_start'
ExecStop=/bin/bash -c '/usr/cachesys/cstop quietly 2>&1 | logger -t cache_stop'
RemainAfterExit=yes

[Install]
WantedBy=multi-user.target

The file should be placed as /usr/lib/systemd/system/cache.service

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Here you have an easy way to write and execute COS code from your unix scripts. This way one does not need to write routines or even open Studio or Atelier. It can be an option for simple and small actions for instance things like installation tasks or compiling.

See sample bash script (compile.sh) to compile classes:

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InterSystems FAQ rubric

If the journal file is too large to be searched or filtered using the Management Portal, you can refer to it using the following two methods.

① How to use the ^JRNDUMP utility
② How to reference it in a program

================================================== ==========

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InterSystems FAQ rubric

If the system does not stop for 24 hours, old journal files will be deleted at 0:30 according to the "Journal file deletion settings".

A possible cause of journal files remaining that are older than the "Journal file deletion settings" is that there are transactions that remain open.

In that case, you will be able to delete the journal file by searching for processes executing transactions and finalizing the transactions.

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I am often asked by customers, vendors or internal teams to explain CPU capacity planning for large production databases running on VMware vSphere.

In summary there are a few simple best practices to follow for sizing CPU for large production databases:

  • Plan for one vCPU per physical CPU core.
  • Consider NUMA and ideally size VMs to keep CPU and memory local to a NUMA node.
  • Right-size virtual machines. Add vCPUs only when needed.

Generally this leads to a couple of common questions:

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