New post

#InterSystems IRIS

23

InterSystems IRIS is a Complete Data Platform
InterSystems IRIS gives you everything you need to capture, share, understand, and act upon your organization’s most valuable asset – your data.
As a complete platform, InterSystems IRIS eliminates the need to integrate multiple development technologies. Applications require less code, fewer system resources, and less maintenance.

Created by Daniel Kutac, Sales Engineer, InterSystems

Warning: if you get confused by URLs used: the original series used screens from machine called dk-gs2016. The new screenshots are taken from a different machine. You can safely treat url WIN-U9J96QBJSAG as if it was dk-gs2016.

Part 2. Authorization server, OpenID Connect server

9 12
3 5.6K

** 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.

6 9
5 5.5K

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:

15 10
2 5.2K

These days the vast majority of applications are deployed on public cloud services. There are multiple advantages, including the reduction in human and material resources needed, the ability to grow quickly and cheaply, greater availability, reliability, elastic scalability, and options to improve the protection of digital assets. One of the most favored options is the Google Cloud. It lets us deploy our applications using virtual machines (Compute Engine), Docker containers (Cloud Run), or Kubernetes (Kubernetes Engine). The first one does not use Docker.

5 0
3 4.9K

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.

5 4
1 4.8K

Your application is deployed and everything is running fine. Great, hi-five! Then out of the blue the phone starts to ring off the hook – it’s users complaining that the application is sometimes ‘slow’. But what does that mean? Sometimes? What tools do you have and what statistics should you be looking at to find and resolve this slowness? Is your system infrastructure up to the task of the user load? What infrastructure design questions should you have asked before you went into production? How can you capacity plan for new hardware with confidence and without over-spec'ing? How can you stop the phone ringing? How could you have stopped it ringing in the first place?

24 13
6 4.7K

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.

7 0
3 4.4K
Question
· Oct 12, 2019
How do you search with REST

The question is pretty much in title. I'm developing a REST API, it has a search endpoint with 10 optional parameters. How do I pass them and stay RESTFul?

To ease the question a bit let's agree that:

  • all parameters are AND parameters, user can't make combos, ORs, etc. User can only provide values
  • all values are integers so I don't have to think about URL limits
  • all values are atomic
  • all conditions are about equivalency

Some options I know of:

1. URL parameters.

0 9
0 4.2K

InterSystems supports use of the InterSystems IRIS Docker images it provides on Linux only. Rather than executing containers as native processes, as on Linux platforms, Docker for Windows creates a Linux VM running under Hyper-V, the Windows virtualizer, to host containers. These additional layers add complexity that prevents InterSystems from supporting Docker for Windows at this time.

12 12
6 4.2K

Introduction

In the first article in this series, we’ll take a look at the entity–attribute–value (EAV) model in relational databases to see how it’s used and what it’s good for. Then we'll compare the EAV model concepts to globals.

Open Exchange app
3 0
4 4.2K

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.

20 10
2 4.1K
Article
· Aug 14, 2019 9m read
Introducing InterSystems API Manager

As you might have heard, we just introduced the InterSystems API Manager (IAM); a new feature of the InterSystems IRIS Data Platform™, enabling you to monitor, control and govern traffic to and from web-based APIs within your IT infrastructure. In case you missed it, here is the link to the announcement.

In this article, I will show you how to set up IAM and highlight some of the many capabilities IAM allows you to leverage.

17 11
11 4.1K

I'm trying to convert a CSV inbound to an HL7 MFN^M16 outbound. I know I'm using book information as the CSV but I don't think that matters. Please let me know if that's incorrect.

My service is reading the file in just fine and when I don't have a DLT transformer the raw message passes through to outbound file folder just fine. However, when I include a basic DLT that simply copies a couple of fields over I get the "Ens.StreamContainer" error. Everything also seems to be good in the Record Mapper.

0 4
0 3.9K
Article
· Oct 7, 2016 4m read
Forwarding Requests in a REST Service

One useful feature of our REST framework is the ability for a dispatch class to identify request prefixes and forward them to another dispatch class. This approach of modularizing your URL map will improve code readability, enable you to easily maintain separate versions of an interface, and provide a means to protect API calls that only certain users will be allowed to access.

7 1
0 3.9K

Hi Community!

We're pleased to announce that that InterSystems IRIS Community Edition is available on the Docker Store! InterSystems IRIS Community Edition is the no-cost developer edition designed to lower the barriers to entry to get started with IRIS. Now that it is listed on the Docker Store, running an IRIS Community instance is as easy as -

10 14
2 3.8K
Article
· May 25, 2016 5m read
Random Read IO Storage Performance Tool

New Tool Available

Please see PerfTools IO Test Suite for a later version of the Random Read IO tool.

Purpose

This tool is used to generate random read Input/Output (IO) from within the database. The goal of this tool is to drive as many jobs as possible to achieve target IOPS and ensure acceptable disk response times are sustained. Results gathered from the IO tests will vary from configuration to configuration based on the IO sub-system. Before running these tests ensure corresponding operating system and storage level monitoring are configured to capture IO performance metrics for later analysis.

Open Exchange app
14 17
3 3.8K

In this article, we’ll build a highly available IRIS configuration using Kubernetes Deployments with distributed persistent storage instead of the “traditional” IRIS mirror pair. This deployment would be able to tolerate infrastructure-related failures, such as node, storage and Availability Zone failures. The described approach greatly reduces the complexity of the deployment at the expense of slightly extended RTO.

Open Exchange app
23 16
8 3.8K