As soon as you make the leap from developer to manager one of the most immediate changes you notice, apart from the crushing uncertainty of not knowing what it is you’re supposed to be doing, is that your calendar will fill up quicker than you can say “let’s schedule 30 minutes to discuss that”.

Clockwise is a new tool that has proliferated around the managers at work which claims to solve your meeting woes by taking over the scheduling and booking rooms for you. It’s like having your own PA, only without, you know, actually being important enough to justify one.

Technically Clockwise is a browser plugin which integrates with Google Calendar. Every day at 4pm it looks at meetings occurring over the next week and rearranges them to resolve conflicts, and to try and create blocks of “focus time”. Focus time is a chunk of meeting-free time, two hours or longer, in which you can get stuck into work, rather than having a series of 30-minute gaps where it’s hard to achieve anything.


Glow Bright

When my electricity provider, nPower, upgraded me to a smart meter I was excited about getting access to more data about my electricity and gas usage. Unfortunately, it turned out that the extra data provided by the connected meters was only available to the power supplier, and not to me as a consumer. They provided a little device with a screen (known as an IHD, or in-home device) which displayed the current and daily/weekly/monthly usage, but little else. No mobile app, no ability to dig into your historical usage, and definitely no API access.

While I was disappointed and frustrated about not having access to what I consider be my data, I left it as I had more important things to worry about (i.e. kids). With my recent project to look at collecting more data from my house, I wanted to revisit this, and collect the data.

There are two meter standards in the UK, SMETS1 and SMETS2. SMETS1 is the older standard, which is no longer being rolled out. SMETS2 is the current standard, which operates quite differently to SMETS1. The main benefit being that if you switch provider your smart meter will continue to work, something that wasn’t true with the earlier standard. If you’re unlucky enough to have a SMETS1 meter you can ask for it to be upgraded. Fortunately, I had a SMETS2 meter.

The way these meters work is that both the electricity and gas meters broadcast their readings locally over a ZigBee network. This is picked up by your IHD, and displayed live. The electricity meter also listens to the gas readings and every so often uploads them over a mobile phone connection to a central data broker. This is then forwarded on your supplier. has much more detail on this process.

The key point is that your data can not only be forwarded on to your supplier, but you can grant access to other companies too. Enter Glow who act as what is known as DCC Other User and use smart meter data to help companies do research and development. They also provide more tools for consumers to use their data.

After installing the app you need to go through a security verification process. This involves uploading details of your electricity meter and address (by taking photos of your bill), a photo of some photo id, and a selfie video of yourself saying “I’m My Name, and I accept the terms and conditions”. After that, your details are sent away for a manual verification process, which in my case took two days. I also received an email asking whether I was planning to buy their display. When I said yes they said they wouldn’t process my application until it arrived. This was a bit frustrating as it meant I couldn’t use the app in the meantime. Once the device arrived the application was processed quickly.


Bad Words In A URL

Today I wanted to share one of the more interesting debugging experiences that I’ve had. This happened quite a few years ago when I was involved in migrating a set of websites over to use a single login. The idea was that as soon as you landed on a site and your session wasn’t logged in, you would be bounced over to an authentication site, which would bounce you back again. The two sites communicated via a backchannel, and if you were logged in on the authentication site the main site would log you in too. If not then you’d browse as a logged-out user, and when you logged in you were bounced over to the authentication site with your credentials passed via a backchannel. If successful then you were logged in on both sites, otherwise an error was displayed.

The backchannel communication was all encrypted with preshared keys, and when the user was bounced to the authentication site they were also given an encrypted token to ensure that a bad actor couldn’t attempt to hijack another user’s session. The exact details of the token aren’t important, but they included the user’s session-id, details of the site they landed on, and the time they were bounced (to prevent against replay attacks).

Everything was working great in testing, and we gradually rolled the change out to more and more users. Eventually, we started getting reports of a small number of users not being able to log in. We were able to determine that they landed on the main site ok, and were bounced to the authentication site, but never arrived there.


Router Stats To Prometheus

I’ve previously written about my plan to collect much more data about my house. In the current work-from-home environment the quality of our internet connection is paramount, and I wanted to be able to monitor it and potentially be alerted to any degradation before it becomes an issue.

Although I’ve replaced my wifi with a UniFi based system, I still use the router that was supplied by my ISP - which is a ZyXEL VMG1312-B10D. Like most networking equipment the ZyXel supports SNMP which is a technology for reading and writing stats and configuration from equipment, and aggregating them together. On paper it sounds great, but unfortunately SNMP is a nightmare to work with, and you need a mapping file for each device, which doesn’t exist for this model. After looking into creating this mapping, and integrating my preferred technology slack of Grafana and Prometheus, I decided to change tack and extract the data myself.

Fortunately the router UI contains some plain text data which looks easy to scrape. So, filled with confidence that this would be an easier approach that learning SNMP I spun up a GitHub project and got to work cranking out some code.


House Measurements

For a long time now I’ve tracked the weather outside my house with my weather station. I also have smart electric and gas meters which display my usage on a little screen in my kitchen, but I didn’t try to do anything useful with that data. Recently I brought an electric car and given that it’s essentially a giant iPad on wheels it inspired me to look into what data I could collect from it, and from elsewhere in my house.

Towards the end of last year, I upgraded my Synology NAS to a newer model which has an Intel, rather than MIPS processor, partly because it was old and I was worried about it dying, but mostly so I could run Docker containers on it. I’ve been running both a Ubiquiti UniFi Controller and PiHole since then, but I knew as part of this project I’d want to run many more containers so I took the opportunity to tidy up the setup.

Docker Compose is a tool that sits above the normal docker command and it lets you run multiple docker containers while simplifying the management of images and the options you need to set for the container to work correctly. You can find my docker-compose.yml file here.