KeyholeSoftware.devโthe innovation arm of Keyhole Softwareโhas released a new open-source HTTP load testing command line utility implemented in Go. khsLoad is used to test the performance of APIs and websites through user simulation with features for creating data graphs useful for SLAs.
Kubernetes, or k8s, is an important container orchestration platform. In this blog, I’ll describe creating a workable Kubernetes cluster implemented on a stack of four Raspberry Pi boards. In the end, I’ll have provided an outline of how I created it and I’ll show how to replicate a stateless app across Kubernetes pods running on the nodes โ the Pi boards.
The steps described in this blog post allow for the adding of a Logic App on Azure to append rows to an Excel file. It took a lot of trial, and mostly error, to figure out how to describe what I wanted in the way that the Logic App would understand. Hopefully, the steps that I outlined in this blog post will save others the time it took me to come up with them.
Back in 2015 and 2016, I wrote two blogs that went step by step to develop a microservice/Netty architecture with fully working code called Whirlpool.
A lot has changed in the years since, so recently I decided to come back to the project, update it with the latest versions of Kafka and Netty, and add a React UI to it (rather than the vanilla JavaScript version it used before). In addition, I also added Windows Subsystem for Linux (WSL) scripts in addition to the Mac and Linux scripts that were there before and made all of the scripts more robust.
This blog will be about the work that went into all of those updates, plus a look at the new React UI. This provides an excellent view into what it takes to update an outdated microservices application implemented with Kafka (version .9 –>3.0) and Netty (4.1.3->5.0.0-alpha2), bringing all versions up to date and adding a React UI. By the end youโll be familiar with the latest versions of these frameworks, know some โgotchasโ to avoid, as well as understand how to integrate WebSockets into React.
Recently, while working for a large healthcare client in New York, I ran into an interesting problem that had slim literature on how to solve it.
Our application is primarily on-prem, but it does leverage Azure for a few functions that are easier to solve in a cloud-native environment. We wanted to be able to monitor those functions using the same Elastic Stack that we use to monitor our on-prem application.
I was tasked with building a bridge between where our functionality logs to in Azure (App Insights), and getting that securely back into our Elasticsearch instance that powers our Elastic Stack.
This blog post will detail the solution I landed on. I hope it will be useful to others that need to solve a similar problem!