This is a personal blog focused on computer software and hardware. Most projects are implementing software and hardware for a homelab. What is a homelab? I would say a homelab could be a single computer or dozens of computers connected in a network. You can also integrate with computers in the Cloud.
I use a mobile iOS app on my iPhone and Apple watch to record my workout sessions at the gym. I thought of this little project to encourage me to practice with some Python and SQL with data that I actually care about. This mobile app allows you to export data from previous workouts in a CSV file. You could import that file to a spreadsheet but I’m going to import it to a Postgresql database and run a few queries.
A new calendar year is already underway. My plans for the next year include projects related to what I am working on at my job. I will be reviewing my observability stack and taking a look at OpenTelemetry. I will also be testing some CI/CD tools. I think I will be overhauling my kubernetes environment again. I want something more simple but also maintain the goal of combining the resources of many low-power computers such as Raspberry Pi, Mac Mini, and small form factor desktop PCs.
Over the past year, I have undertaken several projects aimed at enhancing my homelab: I transitioned containerized applications to Kubernetes, ensuring scalability, reliability, and easier management of my self-hosted services. Or rather that was my goal. Here’s my previous post. I set up home assistant and started exporting data from it. This project has allowed me to collect more data about my house and visualize the data with dashboards. Additionally, I deployed systems to collect weather data from my house, enabling local monitoring and data analysis.
I picked up a mac mini with the m4 CPU, 24 GB shared memory, and 512 GB of storage. Even with solar power, especially in the winter, my lab is using too much power. My new goal is to use less power than my plant grow lights. Fortunately, I can measure all of that power usage now and store it in prometheus to query. I run two NAS systems 24/7 and one of them is off the shelf from Synology and it uses between 15-30 watt hours.
On Kubernetes, you can run a Prometheus server by installing a Helm chart. If you are looking for information about what to do with Prometheus, check out a previous post to get an overview. This chart is maintained by the community and is available to browse on GitHub. There are a lot of options that can be configured with a values YAML file. This chart can also optionally install some other software such as Grafana, a node metrics exporter, and the kube state metrics server.
updated: 2025-03-09 After running LLMs locally using Ollama and open-webui, I realized that the project has experimental support for image generation. If you are not familiar with those, check out a previous post to learn more and get started. I have seen image generation tools online but I never bothered to look into how to do it with a GPU. Fortunately I am late to the party and there are now a lot of tools available to make leveraging the underlying technology easier.