I needed to know programmatically if last ran failed or not.
After some exploring, here's the code:
ClassMethod isLastTestOk() As %Boolean
{
set in = ##class(%UnitTest.Result.TestInstance).%OpenId(^UnitTest.Result)
for i=1:1:in.TestSuites.Count() {
#dim suite As %UnitTest.Result.TestSuite
set suite = in.TestSuites.GetAt(i)
return:suite.Status=0 $$$NO
}
quit $$$YES
}
I am planning to implement Business Intelligence based on the data in my instances. What is the best way to set up my databases and environment to use DeepSee?
InterSystems Data Platform includes utilities and tools for system monitoring and alerting, however System Administrators new to solutions built on the InterSystems Data Platform (a.k.a Caché) need to know where to start and what to configure.
This guide shows the path to a minimum monitoring and alerting solution using references from online documentation and developer community posts to show you how to enable and configure the following;
Caché Monitor: Scans the console log and sends emails alerts.
System Monitor: Monitors system status and resources, generating notifications (alerts and warnings) based on fixed parameters and also tracks overall system health.
Health Monitor: Samples key system and user-defined metrics and compares them to user-configurable parameters and established normal values, generating notifications when samples exceed applicable or learned thresholds.
History Monitor: Maintains a historical database of performance and system usage metrics.
pButtons: Operating system and Caché metrics collection scheduled daily.
Remember this guide is a minimum configuration, the included tools are flexible and extensible so more functionality is available when needed. This guide skips through the documentation to get you up and going. You will need to dive deeper into the documentation to get the most out of the monitoring tools, in the meantime, think of this as a set of cheat sheets to get up and running.
In this series of articles, I'd like to present and discuss several possible approaches toward software development with InterSystems technologies and GitLab. I will cover such topics as:
Git 101
Git flow (development process)
GitLab installation
GitLab Workflow
Continuous Delivery
GitLab installation and configuration
GitLab CI/CD
In the previous article, we covered Git basics, why a high-level understanding of Git concepts is important for modern software development, and how Git can be used to develop software. Still, our focus was on the implementation part of software development, but this part presents:
GitLab Workflow - a complete software life cycle process - from idea to user feedback
Continuous Delivery - software engineering approach in which teams produce software in short cycles, ensuring that the software can be reliably released at any time. It aims at building, testing, and releasing software faster and more frequently.
I have a few cubes and numerous dashboards and I am ready to deploy them to our end users and administrators. How to configure DeepSee so that users don’t disrupt each other’s areas and are restricted from using functionalities specific to developers?
This is a quick tutorial how to install and use TFS in Atelier. It is based on my self experience and some tricks that I 've noted.
If you are used to using visual studio maybe you feel that is a bit slow and heavy, but you have the same TFS panel as you have in Visual Studio, so don't need any special "training" to use it
This is a posting about a particular feature of Caché which I find useful but is probably not well known or used. I am referring to the feature of Language Extensions.
This feature allows you to extend the commands, special variables and functions available in Caché Object Script with commands, special variables and functions of your own. This functionality also applies to other languages the Caché supports at the server, including Caché Basic and Multivalue Basic.
When working at the Caché command prompt I sometimes want to run an operating system command on the server host. By prefixing my command line with ! or $ I can do this with ease. The following examples are from 2017.1 on Windows, but the feature is available on all versions and platforms:
The goal of this “DeepSee Troubleshooting Guide” is to help you track down and fix problems in your DeepSee project.
If the problem can’t be fixed by following the guidelines, you will at least have enough information to submit a WRC issue with DeepSee Support and provide all the evidence to us, so we can continue the investigation together and resolve it faster!
Some people are lucky enough to have a totally separate environment to run production in.
-- Unknown
.
In this series of articles, I'd like to present and discuss several possible approaches toward software development with InterSystems technologies and GitLab. I will cover such topics as:
Git 101
Git flow (development process)
GitLab installation
GitLab WorkFlow
GitLab CI/CD
CI/CD with containers
This first part deals with the cornerstone of modern software development - Git version control system and various Git flows.
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.
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.
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.
In this article I would like to present the RESTForms project - generic REST API backend for modern web applications.
The idea behind the project is simple -after I wrote several REST APIs I realized that generally, REST API consists of two parts:
Work with persistent classes
Custom business logic
And, while you'll have to write your own custom business logic, RESTForms provides all things related to working with persistent classes right out of the box. Use cases
You already have a data model in Caché and you want to expose some (or all) of the information in a form of REST API
You are developing a new Caché application and you want to provide a REST API
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.
A request came from a customer to estimate how long it would take to encrypt a database with cvencrypt utility.
This question is a little bit like how long is a piece of string — it depends. But its an interesting question. The answer primarily depends on the performance of CPU and storage on the target platform the customer is using, so the answer is more about coming up with a simple methodology that can be used to benchmark the CPU and storage while running cvencrypt.
This post will guide you through the process of sizing shared memory requirements for database applications running on InterSystems data platforms. It will cover key aspects such as global and routine buffers, gmheap, and locksize, providing you with a comprehensive understanding. Additionally, it will offer performance tips for configuring servers and virtualizing IRIS applications. Please note that when I refer to IRIS, I include all the data platforms (Ensemble, HealthShare, iKnow, Caché, and IRIS).
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.
In this article I would like to tell you about macros in InterSystems Caché. A macro is a symbolic name that is replaced with a set of instructions during compilation. A macro can “unfold” in various instruction sets each time it is called, depending on the parameters passed to it and activated scenarios. This can be both static code and the result of ObjectScript execution. Let's take a look at how you can use them in your application.
If you've worked with iKnow domain definitions, you know they allow you to easily define multiple data locations iKnow needs to fetch its data from when building a domain. If you've worked with DeepSee cube definitions, you'll know how they tie your cube to a source table and allow you to not just build your cube, but also synchronize it, only updating the facts that actually changed since the last time you built or synced the cube. As iKnow also supports loading from non-table data sources like files, globals and RSS feeds, the same tight synchronization link doesn't come out of the box. In this article, we'll explore two approaches for modelling DeepSee-like synchronization from table data locations using callbacks and other features of the iKnow domain definition infrastructure.
NB. Please be advised that PKI is not intended to produce certificates for secure production systems. You should make alternate arrangements to create certificates for your productions. NB. PKI is deprecated as of IRIS 2024.1: documentation and announcement.
After a five-part series on sample iKnow applications (parts 1, 2, 3, 4, 5), let's turn to a new feature coming up in 2017.1: the iKnow REST APIs, allowing you to develop rich web and mobile applications. Where iKnow's core COS APIs already had 1:1 projections in SQL and SOAP, we're now making them available through a RESTful service as well, in which we're trying to offer more functionality and richer results with fewer buttons and less method calls. This article will take you through the API in detail, explaining the basic principles we used when defining them and exploring the most important ones to get started.
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.
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.
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.
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.
In this post I would like to talk about the syslog table. I will cover what it is, how you look at it, what the entries really are, and why it may be important to you. The syslog table can contain important diagnostic information. If your system is having any problems, it is important to understand how to look at this table and what information is contained there.
By update
