Overview

We often run into connectivity problems with HealthShare (HS) deployments in Microsoft Azure that have multiple HealthShare components (instances or namespaces) installed on the same VM, especially when needing to communicate to other HS components while using the Azure Load Balancer (ILB) to provide mirror VIP functionality. Details on how and why a load balancer is used with database mirroring can be found this community article.

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Introduction

InterSystems has recently completed a performance and scalability benchmark of IRIS for Health 2020.1, focusing on HL7 version 2 interoperability. This article describes the observed throughput for various workloads, and also provides general configuration and sizing guidelines for systems where IRIS for Health is used as an interoperability engine for HL7v2 messaging.

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InterSystems and Intel recently conducted a series of benchmarks combining InterSystems IRIS with 2nd Generation Intel® Xeon® Scalable Processors, also known as “Cascade Lake”, and Intel® Optane™ DC Persistent Memory (DCPMM). The goals of these benchmarks are to demonstrate the performance and scalability capabilities of InterSystems IRIS with Intel’s latest server technologies in various workload settings and server configurations. Along with various benchmark results, three different use-cases of Intel DCPMM with InterSystems IRIS are provided in this report.

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The Amazon Web Services (AWS) Cloud provides a broad set of infrastructure services, such as compute resources, storage options, and networking that are delivered as a utility: on-demand, available in seconds, with pay-as-you-go pricing. New services can be provisioned quickly, without upfront capital expense. This allows enterprises, start-ups, small and medium-sized businesses, and customers in the public sector to access the building blocks they need to respond quickly to changing business requirements.

Updated: 10-Jan, 2023

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There are often questions surrounding the ideal Apache HTTPD Web Server configuration for HealthShare. The contents of this article will outline the initial recommended web server configuration for any HealthShare product.

As a starting point, Apache HTTPD version 2.4.x (64-bit) is recommended. Earlier versions such as 2.2.x are available, however version 2.2 is not recommended for performance and scalability of HealthShare.

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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.

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Continuing on with providing some examples of various storage technologies and their performance profiles, this time we looked at the growing trend of leveraging internal commodity-based server storage, specifically the new HPE Cloudline 3150 Gen10 AMD processor-based single socket servers with two 3.2TB Samsung PM1725a NVMe drives.

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Often InterSystems technology architect team is asked about recommended storage arrays or storage technologies. To provide this information to a wider audience as reference, a new series is started to provide some of the results we have encountered with various storage technologies. As a general recommendation, all-flash storage is highly recommended with all InterSystems products to provide the lowest latency and predictable IOPS capabilities.

The first in the series was the most recently tested Netapp AFF A300 storage array. This is middle-tier type storage array with several higher models above it. This specific A300 model is capable of supporting a minimal configuration of only a few drives to hundreds of drives per HA pair, and also capable of being clustered with multiple controller pairs for tens of PB's of disk capacity and hundreds of thousands of IOPS or higher.

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Database systems have very specific backup requirements that in enterprise deployments require forethought and planning. For database systems, the operational goal of a backup solution is to create a copy of the data in a state that is equivalent to when application is shut down gracefully. Application consistent backups meet these requirements and Caché provides a set of APIs that facilitate the integration with external solutions to achieve this level of backup consistency.

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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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++Update: August 2, 2018

This article provides a reference architecture as a sample for providing robust performing and highly available applications based on InterSystems Technologies that are applicable to Caché, Ensemble, HealthShare, TrakCare, and associated embedded technologies such as DeepSee, iKnow, Zen and Zen Mojo.

Azure has two different deployment models for creating and working with resources: Azure Classic and Azure Resource Manager. The information detailed in this article is based on the Azure Resource Manager model (ARM).

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Presenter: Mark Bolinsky
Task: Provide failover for distributed systems without using a VIP
Approach: Demonstrate using InterSystems’ database mirroring with external traffic managers such as F5 LTM/GTM

With distributed environments and even public cloud environments, the use of a VIP sometimes is not desirable or even possible given network topology or deployment. The session will demonstrate integrating database mirroring with external traffic managers such F5 LTM/GTM using API based triggers in InterSystems products to interface with the F5 appliances. This not only presents automated redirection for the local mirror members, but also provided automated client redirection to asynchronous DR mirror members.

Content related to this session, including slides, video and additional learning content can be found here.

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Presenter: Mark Bolinsky
Task: Decide whether a converged infrastructure is ideal for your enterprise applications
Approach: Discuss best practices and provide guidance on the right questions to ask

The traditional use of “SAN storage” is no longer the only choice for deploying enterprise application. Software defined data centers are making inroads into enterprise data centers, and there is good reason for it. There is the potential for significant infrastructure cost savings, architecture simplification, reduced administration costs, and depending on the configuration - even better performance. This session will discuss some best practices and outline decision guidance to help you ask the right questions when considering hyper-converged architectures.

Content related to this session, including slides, video and additional learning content can be found here.

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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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Article
· Feb 2, 2016 1m read
Cache' databases as UNIX sparse files

Some third party backup products may by default restore CACHE.DAT files as UNIX sparse files when there are trailing zeroes in the backup file.

The support for sparse files vary from UNIX distribution and file system types. Sparse files attempt to use file system space more efficiently when blocks allocated to the file are mostly empty similar to thin-provisioned storage. The file system transparently converts metadata representing empty blocks into "real" blocks filled with zero bytes at runtime. The application is suppose to be unaware of this conversion.

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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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The release of IBM POWER 8 processors with AIX 7.1 introduced up to 8 SMT threads per processor core (logical or physical). Which SMT level (1, 2, 4, or 8) to use can be confusing and varies based on multiple factors. This article is meant to help with a starting point for your specific application.

Firstly, if running on a version of 2014.x or older, it is advised to use SMT 4 or lower. SMT 8 with those older versions of Cache' has shown a decline in performance and scaling in benchmarking applications.

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Often times support and sales engineers are asked about recent benchmark results on various platforms and large scale configurations. These will be made available here in the Developer Community in the "Documentation" section, and as an example here's a link to a recent Intel E7 v2 series processor benchmark.

https://community.intersystems.com/documentation/data-scalability-intersystems-caché-and-intel-processors-0

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