#Monitoring

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Monitoring is a process of controlling and management of performance and availability of software applications.

This article outlines the process of utilizing the renowned Jaeger solution for tracing InterSystems IRIS applications. Jaeger is an open-source product for tracking and identifying issues, especially in distributed and microservices environments. This tracing backend that emerged at Uber in 2015 was inspired by Google's Dapper and Twitter's OpenZipkin. It later joined the Cloud Native Computing Foundation (CNCF) as an incubating project in 2017, achieving graduated status in 2019. This guide will demonstrate how to operate the containerized Jaeger solution integrated with IRIS.

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Hello InterSystems Community,

I'm working with HealthShare, and need to create a user account for our development environment with specific access requirements. This user will need only to:

Review messaging and environments
See production and namespaces
NOT modify anything (read-only access)

After reviewing the documentation on user roles and rights management, I can see the default roles available in our system include:

Ensemble/Interoperability Roles:

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Hello, good morning, thank you so much for reading this question. ☺️🙂👍

We are developing a code to get information about our Production's items: services, processes and operations.

We know we can get various configurations of a given item: Category, Port, Enabled...

But we wonder how we could get the date time of the last mesage (most recent) received in an item.

To give a code snippet a small section of the code we have developed (and tested), it looks like:

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Introduction

Database performance has become a critical success factor in a modern application environment. Therefore identifying and optimizing the most resource-intensive SQL queries is essential for guaranteeing a smooth user experience and maintaining application stability.

This article will explore a quick approach to analyzing SQL query execution statistics on an InterSystems IRIS instance to identify areas for optimization within a macro-application.

Rather than focusing on real-time monitoring, we will set up a system that collects and analyzes statistics pre-calculated by IRIS once an hour. This approach, while not enabling instantaneous monitoring, offers an excellent compromise between the wealth of data available and the simplicity of implementation.

We will use Grafana for data visualization and analysis, InfluxDB for time series storage, and Telegraf for metrics collection. These tools, recognized for their power and flexibility, will allow us to obtain a clear and exploitable view.

More specifically, we will detail the configuration of Telegraf to retrieve statistics. We will also set up the integration with InfluxDB for data storage and analysis, and create customized dashboards in Grafana. This will help us quickly identify queries requiring special attention.

To facilitate the orchestration and deployment of these various components, we will employ Docker.

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Monitoring your IRIS deployment is crucial. With the deprecation of System Alert and Monitoring (SAM), a modern, scalable solution is necessary for real-time insights, early issue detection, and operational efficiency. This guide covers setting up Prometheus and Grafana in Kubernetes to monitor InterSystems IRIS effectively.

This guide assumes you already have an IRIS cluster deployed using the InterSystems Kubernetes Operator (IKO), which simplifies deployment, integration and mangement.

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