We are Longevica (https://www.longevica.com/) Healthtech, a Boston-based healthy aging digital health startup. Longevica was born as a research company back in 2009; we pioneered the screening of chemicals, which would drastically extend the life span. With 1000 screened pharmaceuticals and 20 000 mice experiments, we have identified specific compounds that, if taken daily, could extend life by years. This discovery leads to two questions: how to measure the effect of aging progress in real-time and how to make this a lifelong habit. This led us to the digital health market to create a new company Longevica HealthTech.
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.
The common requirement in many applications is logging of data changes in a database - which data has changed, who changed them and when (audit logging). There are many articles about this question and there are different approaches on how to do that in Caché.
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.
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.
InterSystems IRIS 2020.1 brings a broad set of improved and new capabilities to help build important applications. In addition to the many significant performance improvements accrued through 2019.1 and 2020.1, we are introducing one of our biggest changes in recent SQL history: the Universal Query Cache. This article provides more context on its impact to SQL-based applications at a technical level.
The goal of this post is to discuss working with Websockets in a Caché environment. We are going to have a quick discussion of what websockets are and then talk through an example chat application implemented on top of Websockets.
We are ridiculously good at mastering data. The data is clean, multi-sourced, related and we only publish it with resulting levels of decay that guarantee the data is current. We chose the HL7 Reference Information Model (RIM) to land the data, and enable exchange of the data through Fast Healthcare Interoperability Resources (FHIR®).
This is a coding example working on Caché 2018.1.3 and IRIS 2020.2
It will not be kept in sync with new versions
It is also NOT serviced by InterSystems Support !
During my search for a snapshot of a persistent object, I met a feature that I would like tho share as it could be useful in some special situations. My trigger was to have a before- and an after-image during unit testing.
This short article was motivated by a problem of one of my customers. They use Ensemble to integrate many systems, some of them use just plain files.
So they naturally selected File Outbound Adapter to write into target file. Things were running smoothly for years, until recently, when the volume of data being written to the file reached large size of tens of megabytes. The operation took around half an hour to complete, causing timing problems where subsequent operations within the process had to wait, and third party system was not happy to wait so long.
For Data Synchronization inside Caché you have a range of ways to synchronize objects and tables. At DB level you can use Shadowing or Mirroring
This works excellent and if you need just a part of your data to be synchronized you may split your data into smaller pieces using Global mapping Or if you need bi-directional synchronization on Class/Table level you can use the Object Synchronization Feature
The limit of all these excellent features: They just work from Caché/IRIS to Caché/IRIS.
If you have to fill or change your class data other than by standard object filer or SQL filer you also have to get your indexes in line with your data. Rebuild Index might be time consuming exercise eventually blocking access at all.
I just detected ##class(%Library.Storage).%ValidateIndices()
Not really new, but in 2015.1.1 , 2016.2.1 there was not a single character of documentation to it. Now I see on latest
It was InterSystems hackathon time and our team, consisting of Artem Viznyuk and me had Arduino board (one) and various parts of it (in overabundance). And so like that our course of action was set - like all other Arduino beginners, we decided to build a weather station. But with data persistent storage in Caché and visualization in DeepSee!
I have been working on redesigning a Health Connect production which runs on a mirrored instance of Healthshare 2019. We were told to take advantage of containers. We got to work on IRIS 2020.1 and split the database part from the Interoperability part. We had the IRIS mirror running on EC2 instances and used containers to run IRIS interoperability application. Eventually we decided to run the data tier in containers as well.
This formation, accessible on my GitHub, will cover, in half a hour, how to read and write in csv and txt files, insert and get inside the IRIS database and a distant database using Postgres or how to use a FLASK API, all of that using the Interoperability framework using ONLY Python following the PEP8 convention.
As we all know, Caché is a great database that accomplishes lots of tasks within itself. However, what do you do when you need to access an external database? One way is to use the Caché SQL Gateway via JDBC. In this article, my goal is to answer the following questions to help you familiarize yourself with the technology and debug some common problems.
This article will describe and include an example of how to embed an external PDF file into an HL7 segment, specifically ADT_A01:2.3.1 OBX(). This can be useful when attempting to insert pictures or other external data into an HL7 message. In this example, the name of the PDF file to be embedded is provided in the incoming HL7 message in OBX(1):ObservationValue field.