System Monitor is a flexible and highly configurable tool supplied with Caché (Ensemble, HealthShare), which collects the essential metrics of the operating system and Caché itself. System Monitor also notifies administrators about issues with Caché and the operating system, when one or several parameters reach the admin-defined thresholds.

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This post will show you an approach to size shared memory requirements for database applications running on InterSystems data platforms including global and routine buffers, gmheap, and locksize as well as some performance tips you should consider when configuring servers and when virtualizing Caché applications. As ever when I talk about Caché I mean all the data platform (Ensemble, HealthShare, iKnow and Caché).


A list of other posts in this series is here

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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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In this post, I am going to detail how to set up a mirror using SSL, including generating the certificates and keys via the Public Key Infrastructure built in to Caché. The goal of this is to take you from new installations to a working mirror with SSL, including a primary, backup, and DR async member, along with a mirrored database. I will not go into security recommendations or restricting access to the files. This is meant to just simply get a mirror up and running.

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Ansible helped me solve the problem of quickly deploying Caché and application components for Data Platforms benchmarks. You can use the same tools and methodology for standing up your test labs, training systems, development or other environments. If you deploy applications at customer sites you could automate much of the deployment and ensure that system, Caché and your application are configured to your applications best practice standards.

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Article
· Dec 15, 2016 1m read
Version history for the production class

Last week I was onsite with a new customer of ours, implementing Deltanji to give them control of their development and deployment cycle. One particularly satisfying part of the visit was seeing their pleasure at how their production class now records its changes over time, allowing them to quickly diff the versions and see what configuration items have been added or what settings altered. ​

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One of the great availability and scaling features of Caché is Enterprise Cache Protocol (ECP). With consideration during application development distributed processing using ECP allows a scale out architecture for Caché applications. Application processing can scale to very high rates from a single application server to the processing power of up to 255 application servers with no application changes.

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Enterprises need to grow and manage their global computing infrastructures rapidly and efficiently while simultaneously optimizing and managing capital costs and expenses. Amazon Web Services (AWS) and Elastic Compute Cloud (EC2) computing and storage services meet the needs of the most demanding Caché based application by providing
 a highly robust global computing infrastructure.

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Importance and Collection of Exact Version Information ($zv / $zversion)
The explanation of:
- why collecting $zv is important (The WHY),
- what the components of $zv mean (The WHAT),
- and how to collect $zv (The HOW).
(The Ultimate $zv Guide to the ISC Galaxy in large, friendly letters)
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Index

This is a list of all the posts in the Data Platforms’ capacity planning and performance series in order. Also a general list of my other posts. I will update as new posts in the series are added.


You will notice that I wrote some posts before IRIS was released and refer to Caché. I will revisit the posts over time, but in the meantime, Generally, the advice for configuration is the same for Caché and IRIS. Some command names may have changed; the most obvious example is that anywhere you see the ^pButtons command, you can replace it with ^SystemPerformance.


While some posts are updated to preserve links, others will be marked as strikethrough to indicate that the post is legacy. Generally, I will say, "See: some other post" if it is appropriate.


Capacity Planning and Performance Series

Generally, posts build on previous ones, but you can also just dive into subjects that look interesting.


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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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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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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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When running the built in Ensemble Purge task (Ens.Util.Tasks.Purge) there are three parameters DaysToKeep, BodiesToo, and KeepIntegrity. This article focuses on the KeepIntegrity boolean parameter, but more information about running this task can be found here:

http://docs.intersystems.com/latest/csp/docbook/DocBook.UI.Page.cls?KEY=...

KeepIntegrity determines which Ensemble Messages are marked for deletion within the time specified by DaysToKeep.

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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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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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The goal of this writing was to illustrate how to restore backup before the patch would be applied. The alert notes that:

The risk can be avoided by applying journals from the beginning of the journal file that was switched to at the start of the backup, rather than accepting the default of starting from the journal marker position.

Having non-patched Caché 2015.1.4, I ran sample database backup and restore just to get where I should answer "No". Collecting journal info from the backup log:

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This text is a continuation of my article where I explained the structure a Caché database. In this article, I described the types of blocks, connections between them and their relation to globals. The article was purely theoretical. I made a project that helps visualize the block tree - and this article will explain how it works in great detail.

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Article
· Sep 20, 2016 4m read
Diagnosing Framing Errors

Framing refers to the characters that mark the start and end of an HL7 message (or other types of framed messages). Most HL7 services and operations have a Framing setting that allows the user to define this framing. The most common choices are available as defaults, but with the AsciiMM/NN setting, components can be configured to recognize any framing characters.

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