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#InterSystems Data Platform Blog

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This group consists of fairly long technical posts regarding InterSystems Technology features and experience.

Every post in this group is a story of a developer or engineer who wants to share his experience related to InterSystems Data Platform with you.

Every post in this group contains either snippets of code or even ready to use projects with sources on Github or with working demos of InterSystems Technology.

Every post is reviewed by InterSystems specialists through a special reviewing procedure.

Subscribe to the group and you'll get weekly posts with essentials of experience on developing, testing, deploying, maintaining solutions that utilize InterSystems Data Platform technology: multimodel DBMS Caché,  Platform for connected applications Ensemble, analytics technology DeepSee and unstructured data management technology  - iKnow.

Yes, you can contribute to this group. If you want to share your experience, promote interesting development tool or a framework to InterSystems Developer Community in the form of a long article reviewed by InterSystems engineers - please contact me.

Evgeny Shvarov,

InterSystems Community Manager

Released with no formal announcement in IRIS preview release 2019.4 is the /api/monitor service exposing IRIS metrics in Prometheus format. Big news for anyone wanting to use IRIS metrics as part of their monitoring and alerting solution. The API is a component of the new IRIS System Alerting and Monitoring (SAM) solution that will be released in an upcoming version of IRIS.

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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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Article
· Nov 14, 2016 14m read
Mastering the JDBC SQL Gateway

As we all know, Caché is a great database that accomplishes lots of tasks within itself. However, what do you do when you need to access an external database? One way is to use the Caché SQL Gateway via JDBC. In this article, my goal is to answer the following questions to help you familiarize yourself with the technology and debug some common problems.

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This post provides useful links and an overview of best practice configuration for low latency storage IO by creating LVM Physical Extent (PE) stripes for database disks on InterSystems Data Platforms; InterSystems IRIS, Caché, and Ensemble.

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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;

  1. Caché Monitor: Scans the console log and sends emails alerts.

  2. System Monitor: Monitors system status and resources, generating notifications (alerts and warnings) based on fixed parameters and also tracks overall system health.

  3. 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.

  4. History Monitor: Maintains a historical database of performance and system usage metrics.

  5. 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.

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A request came from a customer to estimate how long it would take to encrypt a database with cvencrypt utility.

This question is a little bit like how long is a piece of string — it depends. But its an interesting question. The answer primarily depends on the performance of CPU and storage on the target platform the customer is using, so the answer is more about coming up with a simple methodology that can be used to benchmark the CPU and storage while running cvencrypt.

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Hyper-Converged Infrastructure (HCI) solutions have been gaining traction for the last few years with the number of deployments now increasing rapidly. IT decision makers are considering HCI when scoping new deployments or hardware refreshes especially for applications already virtualised on VMware. Reasons for choosing HCI include; dealing with a single vendor, validated interoperability between all hardware and software components, high performance especially IO, simple scalability by addition of hosts, simplified deployment and simplified management.

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Article
· May 25, 2017 2m read
The Interns are Coming!

The Data Platforms department here at InterSystems is gearing up for this year's crop of interns, and I for one am very excited to meet them all next week!

We've got folks from top technical colleges with diverse specialties from hard core engineers to pure computer scientists to mathematicians to business professionals. They come from countries around the world like Vietnam, China, and Finland and they all come with impressive backgrounds. We're sure they will do very well this summer.

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This article contains the tutorial document for a Global Summit academy session on Text Categorization and provides a helpful starting point to learn about Text Categorization and how iKnow can help you to implement Text Categorization models. This document was originally prepared by Kerry Kirkham and Max Vershinin and should work based on the sample data provided in the SAMPLES namespace.

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Article
· May 20, 2016 12m read
Collations in Caché

Order is a necessity for everyone, but not everyone understands it in the same way
(Fausto Cercignani)

Disclaimer: This article uses Russian language and Cyrillic alphabet as examples, but is relevant for anyone who uses Caché in a non-English locale.
Please note that this article refers mostly to NLS collations, which are different than SQL collations. SQL collations (such as SQLUPPER, SQLSTRING, EXACT which means no collation, TRUNCATE, etc.) are actual functions that are explicitly applied to some values, and whose results are sometimes explicitly stored in the global subscripts. When stored in subscripts, these values would naturally follow the NLS collation in effect (“SQL and NLS Collations”).

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