In my previous post where I outlined challenges that I’ve encountered with Rancher. As part of the feedback to that I ended up having to rebuild one of my clusters. I took that time to try out RKE2 and K3s for my home lab. In this home lab, I use a custom CNI based on the official Bridge and DHCP IPAM CNIs (Read more) to enable my smart home software (HomeAssistant) to communicate with other devices on the same Layer 2 domain.
How to make your system robust against your worst nightmare–your future self
In this post, I talk about some strategies that I’ve learned to simplify class structures in Java services that load and persist data into data stores like DynamoDB or RDS at the same time making the codebase safer.
As always, my opinions are my own.
At Amazon, I ended up joining two teams that were suffering under the technical debt. Each time, I was asked to spend some time understanding why the products were unstable and users were encountering frequent bugs. In one system, responsible for managing critical metadata about products in the catalog, was experiencing problems where users were reporting that they’d randomly lose data.
Artwork by Sami Lee.
For the last 5+ years, I’ve been tracking my various aspects of my personal health using Samsung Health. It helps track weight, calories, heart rate, stress, and exercise and stores all of it in the app.
However, the app only gives some basic high level charts and insights. Luckily, it enables you to export your personal data into CSV files that you can then import into your tool of choice and perform any kind of analytics. In this post, I’m going to show how to export it all, then load it into Zeppelin and some sample Pandas queries that’ll enable you to start building more complex queries yourself.
This article is part of the Home Energy Monitoring series.
Ever wondered where the energy is going in your house and know exactly when and which circuit is consuming the most electricity? How much is your air conditioning unit costing you each month in kWh?
Home energy monitors are devices that you can use to monitor how much energy you’re using at any given point in time. You can use them to figure out how much each device or circuit you’re using overnight vs the day. If you have differing energy costs at the day vs night, you can use them to ensure devices run at lower cost time of day, you can use it to as part of a smart home automation to automatically notify you when your washing machine is done, or even identify when you need to upgrade a circuit because your server room is pulling too much.
In addition to my home lab K8s cluster, I have two dedicated servers that I run in the cloud running a separate Kubernetes cluster. This cluster runs my production servers, like this blog, Postfix, DNS, etc. I wanted to add a VPN between my home network and my prod k8s network for two reasons:
- All data should be encrypted between these networks. While I use HTTPS when possible, some traffic like DNS isn’t encrypted
- My servers outside the NAT should be able to access servers running behind my NAT. I run a Prometheus instance at home that I want my primary Prometheus instance to be able to scrape. Using a VPN can help bypass the NAT and firewall on my router so it can scrape. Additionally, I wanted to be able to access pods directly from my home as needed.
I came across a number of guides for basic Wireguard VPN tunnel configurations which were fine, but they didn’t describe how to solve some of the more advanced issues like BGP routing for MetalLB or how to encrypt traffic to the host itself.