In an earlier post, I made an error that incorrectly aggregated the energy data which resulted in hugely inflated aggregated energy usage. All the un-aggregated data was accurate, but the sums were wrong. Luckily I had all the raw data stored in InfluxDB and could rebuild it.
In this post, I walk through how to re-write the Home Assistant Long-term statistics database to fix this mistake.
My external cluster runs on 3 different dedicated servers (most from SoYouStart.com.) I have 3 machines since the Kubernetes control plane needs 3 or more to be able to have a quorum and be able to handle any one machine going down. If one machine goes down, then the other two maintain a majority and can agree on the state of the cluster.
I randomly encountered issues where the Kubernetes control plane of Rancher UI would crash and restart. While this cluster didn’t really matter, it still annoyed me and wanted to figure it out.
I narrowed it down to one single host and documented the steps I took to resolve this issue which seems to be have been caused by one machine using HDDs and all other hosts using SSDs.
Air—it’s invisible, I can’t see it, but I feel effects of it in so many ways, temperature, humidity, gas composition, but I lacked sensors to measure it. In this post, I walk through some different Air Quality sensors that I found and how I wired them up into a dashboard.
In the previous post in this series, I selected an energy monitoring system that is purely local based (no cloud), integrates into the breaker box, and showed how to connect it to the network and configure the size of each circuit. In this post, I’ll show how to connect the BrulTech GreenEye Energy Monitor to HomeAssistant and create some useful monitoring dashboards.
There were a few services that I ran that I wanted to be able to access from both inside my home network and outside my home network. If I was inside my home network, I wanted to route directly to the service, but if I was outside I needed to be able to route traffic through a proxy that would then route into my home lab. Additionally, I wanted to support SSL on all my services for security using cert-manager
Since my IPv4 addresses differ inside my network vs outside, I need to use split-horizon DNS to respond with the correct DNS query. Split-horizon DNS refers to the DNS on one horizon (inside the network) showing different results than outside the network.
JUnit is a popular testing library for Java applications and I extensively used it when working at Amazon for the numerous Java applications and services there. However, I came across a number of different anti-patterns and areas to improve the quality of the test code. This post introduces many of the different tricks and patterns that I’ve learned and shared with my coworkers, and now want to share
Another library to know and reference is Mockito, which I use extensively in JUnit test cases and will reference this too below.
These are all real things that I’ve seen developers do.
If you’ve got a service that provides clients with the ability to make changes to those entities, then you probably want an audit log that tracks who makes what changes.
I decided to write this post because I frequently saw teams at Amazon not thinking through these considerations. Some of the guidance does focus on AWS IAM, but a lot of it is practical for any type of audit log.
Google Guice is a dependency injection library for Java and I frequently used it on a number of Java services. Compared to Spring, I liked how simple and narrow focused on just dependency injection it was. However, I often times saw developers using it in incorrect or non-ideal patterns that increased boilerplate or were just wrong.
These are all recommendations that I’ve accumulated over several years at working at Amazon watching engineers and sometimes myself improperly leverage Google Guice.
DNS is the protocol that converts domain names like “technowizardry.net” into the IP address of the server that will respond like “188.8.131.52”. In DNS, domain names actually are supposed to end with a period. For example, the URL of this website is not “www.technowizardry.net”, but it’s actually “www.technowizardry.net.” Notice the period at the end.
Where does this come from? If you look at a DNS packet in a packet capture, you’ll see that each query looks something like this:
The queried domain starts right where I’ve highlighted in the above picture. Domain names are separated by each period. In this example, I have 3 separate domain parts: [“www”, “technowizardry”, “net”]. The byte sequence looks like: