Since March of 2020 I’ve been working on building out a homelab. Something about being inside a little more drove me to want to work with the computers at home. Normally that free time would be spent at community events or with presentations. Something had to fill the void and a homelab was it.
At first, the goal was simple; learn about different server technologies and edge computing by building a “data center” in a closet. The “data center” part of it is where most at home sysadmins fall into a bottomless pit of self-hosted technologies and I am no different. First it is a home media server, then a dashboard, then a database, then a data system, then a clustered set of systems, then there is suddenly a need for documentation for a lab you built yourself as it becomes too much to handle at once.
This will, hopefully, be the first of many posts about home labs that is written from personal and professional experience. Throughout the series there should be a showcase of how to use home labs for:
- Home Media
- Edge Computing
- Game Servers
- Development Servers
- Access and Control
- Dynamic Public Cloud Integration
- Redundancy and Disaster Recovery
- and… more
The first and foremost discussion to have is price control. Enterprise server contracts can start at seven figures. If this is what you are looking for, then this is not the blog you seek. What this blog will focus on is how to keep a relatively low budget. Lets see how far we can make the homelab budget go!
At this point, you may be wondering why the title is “Home Lab – a lie I tell myself”. When this journey started, this was a 1-2 tower server adventure. Over time this has exploded, both in scope and in price. At this point, the name “homelab” no longer describes the system I’ve built. Not just in size but also due to the fact that it is no longer at my home. Hopefully, this series can serve as both enablement and deterrent to an ever expanding homelab.
Some helpful resources I used when I got started:
Designing an Intelligent Edge in Microsoft Azure was just published on Pluralsight! Check it out. Here is a synopsis of what’s in it:
This course targets software developers that are looking to integrate AI solutions in edge scenarios ranging from an edge data center down to secure microcontrollers. This course will showcase how to design solutions using Microsoft Azure.
Cloud computing has moved more and more out of the cloud and onto the edge. In this course, Designing an Intelligent Edge in Microsoft Azure, you will learn foundational knowledge of edge computing, its intersection with AI, and how to utilize both with Microsoft Azure. First, you will learn the concepts of edge computing. Next, you will discover how to create an edge solution utilizing Azure Stack, Azure Data Box Edge, and Azure IoT Edge. Finally, you will explore how to utilize off the shelf AI and build your own for Azure IoT Edge. When you are finished with this course, you will have the skills and knowledge of AI on the edge needed to architect your next edge solution. Software required: Microsoft Azure, .NET
I look forward to speaking on AI on the Edge at DotNetSouth.Tech. This year is the conference’s first year so check it out.
AI on the Edge
The next evolution in cloud computing is a smarter application not in the cloud. As the cloud has continued to evolve, the applications that utilize it have had more and more capabilities of the cloud. This presentation will show how to push logic and machine learning from the cloud to an edge application. Afterward, creating edge applications which utilize the intelligence of the cloud should become effortless.
Coming soon I will be authoring a course for Pluralsight titled – “Identify Existing Products, Services and Technologies in Use For Microsoft Azure” . This course targets software developers who are looking to get started with Microsoft Azure services to build modern cloud-enabled solutions and want to further extend their knowledge of those services by learning how to use existing products, services, and technologies offered by Microsoft Azure.
Microsoft Azure is a host for almost any application, but determining how to use it within existing workflows is paramount for success. In this course, Identify Existing Products, Services and Technologies in Use, you will learn how to integrate existing workflows, technologies, and processes with Microsoft Azure.
We explore Microsoft Azure with the following technologies:
- Languages, Frameworks, and IDEs –
- IntelliJ IDEA
- Visual Studio Code
- .NET Core
- Microsoft Azure Products
- Azure App Services
- Azure Kubernetes
- Azure Functions
- Azure IoT Hub
Hopefully we can take a developer familiar with the languages, frameworks, and ides available and make have them up and running on Microsoft Azure after this short course.