Article
· Apr 26, 2021 3m read
SSH for IRIS container

Why SSH ?

If you do not have direct access to the server that runs your IRIS Docker container
you still may require access to the container outside "iris session" or "WebTerminal".
With an SSH terminal (PuTTY, KiTTY,.. ) you get access inside Docker, and then, depending
on your needs you run "iris session iris" or display/manipulate files directly.

Note:
This is not meant to be the default access for the average application user
but the emergency backdoor for System Management, Support, and Development.

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Hi, this post was initially written for Caché. In June 2023, I finally updated it for IRIS. If you are revisiting the post since then, the only real change is substituting Caché for IRIS! I also updated the links for IRIS documentation and fixed a few typos and grammatical errors. Enjoy :)

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Article
· Jan 31, 2018 3m read
Container - What is a Container?

Containers

With the launch of InterSystems IRIS Data Platform, we provide our product even in a Docker container. But what is a container?

The fundamental container definition is that of a sandbox for a process.

Containers are software-defined packages that have some similarities to virtual machines (VM) like for example they can be executed.

Containers provide isolation without a full OS emulation. Containers are therefore much lighter than a VM.

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Article
· Feb 13, 2017 14m read
Creating custom SNMP OIDs

This post is dedicated to the task of monitoring a Caché instance using SNMP. Some users of Caché are probably doing it already in some way or another. Monitoring via SNMP has been supported by the standard Caché package for a long time now, but not all the necessary parameters are available “out of the box”. For example, it would be nice to monitor the number of CSP sessions, get detailed information about the use of the license, particular KPI’s of the system being used and such. After reading this article, you will know how to add your parameters to Caché monitoring using SNMP.

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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?

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++ Update: August 1, 2018

The use of the InterSystems Virtual IP (VIP) address built-in to Caché database mirroring has certain limitations. In particular, it can only be used when mirror members reside the same network subnet. When multiple data centers are used, network subnets are not often “stretched” beyond the physical data center due to added network complexity (more detailed discussion here). For similar reasons, Virtual IP is often not usable when the database is hosted in the cloud.

Network traffic management appliances such as load balancers (physical or virtual) can be used to achieve the same level of transparency, presenting a single address to the client applications or devices. The network traffic manager automatically redirects clients to the current mirror primary’s real IP address. The automation is intended to meet the needs of both HA failover and DR promotion following a disaster.

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This time I want to talk about something not specific to InterSystems IRIS, but that I think is important if you want to work with Docker and your server at work is a PC or laptop with Windows 10 Pro or Enterprise.

As you likely know, containers technology comes basically from Linux world and, nowadays, is on Linux hosts were it shows maximum potential. Those who use Windows on a normal basis see that both, Microsoft and Docker, have done important efforts during these last years that allow us to run containers based on Linux images on our Windows system in a really easy way... but it's something not supported for production systems and, this is the big problem, is not reliable if we want to keep persistent data outside of containers, in the host system,... mostly due to the big differences between Windows and Linux file systems. In the end, Docker for Windows itself uses a small linux virtual machine (MobiLinux) to run the containers... it does it transparently for the windows user... and it works perfectly well if, as I said, you don't require that your databases survive longer than the container...

Well,...let's get to the point,... the point is that many times, to avoid issues and simplify, we need a full Linux system and, if our server is based on Windows, the only way of having it is through a virtual machine. At least till WSL2 in Windows is released, but that will be another story and sure it'll take a bit of time to become robust enough.

In this article, I'll tell you, step by step, how to install an environment where you'll be able to work, if you need it, with Docker containers on an Ubuntu system in your Windows server. Let's go...

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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 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
· 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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Suppose you have developed your own app with InterSystems technologies stack and now want to perform multiple deployments on the customers' side. During the development process you've composed a detailed installation guide for your application, because you need to not only import classes, but also fine-tune the environment according to your needs.
To address this specific task, InterSystems has created a special tool called %Installer. Read on to find out how to use it.

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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
· 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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While the integrity of Caché and InterSystems IRIS databases is completely protected from the consequences of system failure, physical storage devices do fail in ways that corrupt the data they store. For that reason, many sites choose to run regular database integrity checks, particularly in coordination with backups to validate that a given backup could be relied upon in a disaster.

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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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One of the topics that comes up often when managing Ensemble productions is disk space:

The database (the CACHE.DAT file) grows in a rate that was unexpected; or the Journal files build up at a fast pace; or the database grows continuously though the system has a scheduled purge of the Ensemble runtime data.

It would have been better if these kind of phenomena would have been observed and accounted for yet at the development and testing stage rather than on a live system.

For this purpose I created a basic framework that could aid in this task.

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Pouring The Coffee: Creating and scheduling a task

Don't you wish a fresh, hot cup of coffee could be waiting for you right when you get into the office? Let's automate that!

Cache and IRIS come with a built-in Task Manager, which should have a familiar feel to those used to using the Windows task scheduler or using cron on Linux. Your user account will need access to the %Admin_Task resource to use it, and you can access it in the management portal under System Operation -> Task Manager. When first installed, there are roughly 20 types of task that you can schedule.

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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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