InterSystems IRIS

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InterSystems IRIS Data Platform, Data Management, Analytics, Cloud Deployment, Interoperability

 

 

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Hi, Community!

Continuous Delivery is a 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. The approach helps reduce the cost, time, and risk of delivering changes by allowing for more incremental updates to applications in production.

Join us at 07:00 UTC, April 24th for a webinar with a live demo "Git flows and Continuous Delivery" by @Eduard Lebedyuk 

The language of the webinar is Russian.

Also, see the related articles on DC.

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Hi, Community!

Come join the meetup of M and InterSystems developers in Buchlov, Czech Republic 12th of April!

Developers and engineers meet to share experience, discuss problems and announce the solutions!

Come to discuss Intersystems IRIS Data Platform which would be announced on the meetup.

See the agenda below:

Last comment 12 days ago
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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.

Last comment 24 March 2018
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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.

Last comment 31 January 2018
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Modern businesses need new kinds of applications — ones that are smarter, faster, and can scale more quickly and cost-effectively to accommodate larger data sets, greater workloads, and more users.

With this in mind, we have unveiled InterSystems IRIS Data Platform™, a complete, unified solution that provides a comprehensive and consistent set of capabilities spanning data management, interoperability, transaction processing, and analytics. It redefines high performance for application developers, systems integrators, and end-user organizations who develop and deploy data-rich and mission-critical solutions.

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This article, and following two articles of the series, is intended as a user guide for developers or system administrators, who need to work with OAuth 2.0 framework (further referred to as OAUTH for simplicity) in their InterSystems product based applications.

Last comment 5 September 2017
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Created by Daniel Kutac, Sales Engineer, InterSystems

 

Part 3. Appendix

InterSystems IRIS OAUTH classes explained

In the previous part of our series we have learned about configuring InterSystems IRIS to act as an OAUTH client as well as authorization and authentication server (by means of OpenID Connect). In this final part of our series we are going to describe classes implementing InterSystems IRIS OAuth 2.0 framework. We will also discuss use cases for selected methods of API classes.

The API classes implementing OAuth 2.0 can be separated into three different groups according to their purpose. All classes are implemented in %SYS namespace. Some of them are public (via % package), some not and should not be called by developers directly.

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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.

Last comment 22 February 2017
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In this post I would like to talk about the syslog table.  I will cover what it is, how you look at it, what the entries really are, and why it may be important to you.  The syslog table can contain important diagnostic information.  If your system is having any problems, it is important to understand how to look at this table and what information is contained there.

Last comment 9 November 2016
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