So, You Should Dump IPsec, Right?

Wrong. Probably.

So, Since I just posted the other day about dumping my pile of Python scripts and IPsec VPNs and moving to Tailscale for my personal use case, several folks have sparked conversations with me about the topic.

In my case, it made complete sense to do something else. I was using a solution that was the essentially held together with bubblegum, duct tape, and baling wire. It was fragile, it kept breaking, and let’s be real – I was bending the solution into a shape it wasn’t designed to be used in – which is why it kept breaking in the first place.

You see, IPsec tunnels are intended to work when you’ve got stable, fixed endpoints. Over time, things have been done so that endpoints can become dynamic. But typically just one endpoint. Suddenly, with two dynamic endpoints, results become… Unpredictable. I think that’s a kind way of putting it even. That right there, explains my repeated breakage problems.

So, if you’re still using traditional firewall & VPN in a more traditional use case, then yes, keep doing things more traditionally – keep on using IPsec VPNs. It’s quite honestly the best tool in the bag for what you’re hoping to accomplish in terms of securing data that’s in motion, provided you’re able to meet the bars of entry in terms of hardware support as well as supported feature set.

So, get rid of your firewalls? Not a chance. Get rid of my SRX firewalls and EX switches? No way, no how. You can have my Junos stuff when you pry it from my cold, dead hands. Heck, I make my living with Junos. But just like the whole story of the guy who only has a hammer and thinks everything is a nail, sometimes you’ve just got to use a different tool to do the job right.

But taking the time to think about how to break up with complexity and technical debt? Yeah, that’s totally worth your time. Sometimes that means saying goodbye to old friends, even when you forced them into places where they didn’t quite fit.

So, in the end the whole square-peg-round-hole thing? Stop doing that.

Ditching Technical Debt. Embracing Simplicity.

I work in networking. I’ve been doing that for a long time now. Along that journey, I’ve also had occasional detours into worlds like generic IT and data security as well. I also do volunteer work at a nonprofit. Plus, like many of you who work in tech, there’s stuff that lives at the home(s) of relatives that you maintain because you’re that sort of person.

Sometimes, you do it cheap, sometimes you do it right, and sometimes you do it somewhere in-between. Like where you’ve got DHCP-assigned WAN interfaces everywhere because everywhere has home-user type Internet services, or less-expensive business-class occasionally. Anyhow, you can’t always count on having the same IP in the same place twice. BUT, you want things to be secured, and you don’t just want wide-open port forwards with plain old Dynamic DNS.

How things used to work, in the IPsec days…

You’ve got some Juniper SRX firewalls you’ve bought for lab work & study previously, you want to make use of them with IPsec VPNs, but to do it right, you really need static IPs. So, what do you do? You fake it. You just pretend you’ve got static IPs on the tunnel endpoints and configure it up. The tunnels come up, you post up your BGP sessions between your st0.0 IFLs, announce some routes, put some reasonable security policies in place. Yes, I did have security policies in there. I was born at night, but it wasn’t last night, guys. But how did I keep it working with IPs changing all the time?

Here’s how I was solving that problem up until fairly recently. I’ve been hacking away at my DNS-o-Matic and DNS Made Easy updaters for a while now. The DME updater was much better, IMHO, as it directly updated a single, private zone that only I ever cared about rather than rely on someone else to sit in the middle and do the updates for me. Plus, I wrote the whole thing from the ground up using DME’s API docs, so I knew exactly how it worked, inside & out. No excuses for it doing anything I didn’t understand, and honestly, I’m really happy with how well it’s been working. It’s been a great opportunity to get better at Python, in particular doing things in a more “Pythonic” way, rather than trying to “just get it done”, or worse, trying to make it work the way I used to do things in Perl or PHP years ago. Is it iconic? Not even close, but it does works pretty darn well.

So, with these containers all ran on Intel NUCs under Ubuntu Linux at each site. There were 1 more container on each of these NUCs as part of this operation. I had a set of Telegram Bots that talked to each other as part of this network to inform each other of site IP changes. So, if HOME changed its IP, the bot at HOME sent a message to the group that included the bots for NONPROFIT and INLAWS. Those bots saw note that the IP had changed and they should go find out the new IP of HOME, so they can update their tunnel endpoints. This in turn fired off a function that used the Junos PyEZ API module to update the IPsec tunnel endpoint IPs.

Did it all work? Yes, believe it or not, this actually all worked. Was it pretty fragile and not for the faint of heart? Oh yeah, for sure. Would I recommend doing it? Not a chance. So much so that I’m not even going to share the code, apart from the DDNS updaters. The other stuff is definitely hackjob territory. So, since it was so fragile and had the tendency to break, what did I do? Well, the first few times, I drove and fixed. Which frankly, sucked. After that, I installed an OpenVPN container at each of the locations. Later, I replaced those with linuxserver/wireguard containers. But, after it all broke like twice in about a month, I’d just about had enough. I cried Uncle and decided I was going to look for some other way to do this.

And that’s when my old pal Bhupen mentioned Tailscale to me. I was already into Wireguard. So making it easier, faster, and more useful were all on my short list. Drop the tailscale client on the NUC, get it logged in announcing the local subnet into the tailnet (their name for the VPN instance), making it a “subnet router”, approve the route announcement in the portal and it’s going. I’ve got control over key expiry too. Security policy (naturally) moved from the SRX down to the tailscale gateways, but their ACL language wasn’t too difficult to wrangle. It’s all JSON, so it’s reasonably straightforward.

The new Tailscale VPNs
The new Tailscale VPNs

So, with all the scripts gone and the IPsec stripped away, what’s it all look like? Well, we also added 1 more site into the mix as well – the in-laws vacation place. They bought a place and I stuck a Raspberry Pi up there for future IOT use. Not entirely sure about the “what” yet, but they just updated the HVAC, and it’s all smart stuff, so I expect there will be instrumentation. Maybe something that spits out time series info to Influxdb or somesuch. Who knows? Or Perhaps HomeKit/Homebridge stuff. Time will tell.

In the time since I made the diagrams and wrote this up, things have also changed slightly on the homefront.. I’ve deployed a 2nd subnet router at Home. In the Tailscale docs, they say all over the place not to deploy two subnet routers with the same IP space, and generally speaking, it’s with good reason – traffic destined for those prefixes announced by those routers will be round-robin’d back and forth between them. In my case, since they’re on the same physical subnet, this is essentially ECMP routing, so no big deal. I haven’t validated if they’re really getting the hashing correct, but haven’t really noticed any ill effects yet, so I haven’t shut off the 2nd subnet router yet.

So, by dropping all the BGP sessions, IPsec tunnels, Python scripts, Telegram bots, and Docker containers, things have become much simpler, and much more stable. I’m really happy with Tailscale. So much so that I ended up subscribing at the Personal Pro tier. Great bunch of folks – can’t help but recommend them.

UPDATE: This ended up sparking a bunch of sidebar conversations. Go read what I had to say as a followup

Data Visualization and You…

Sometimes there’s data. You’ve got a bunch of it, you need to work out how to represent it in a way that not only makes sense to you, but is also appealing in some fashion. I’m going to talk about a couple of different use cases in this post, each with their own unique data presentations. First, the sensors.

I’ve got a couple of SwitchBot Meter Plus sensors around the house. One is in my office, and the other is in the garage. There isn’t much to them, small little things, battery powered. Pretty much it’s a little monochromatic LCD screen with a temp/humidity sensor and a bluetooth radio. That won’t do, on its own, of course. So, I added SwitchBot’s Hub Mini to the party. It’s a little bridge device that plugs into the house’s AC mains, and has both BT and WiFi radios inside. While I haven’t cracked it open, the device shows up with a MAC address that suggests it’s little more than an ESP32 or ESP8266 microcontroller inside. With the hub in place, connecting the sensors to the SwitchBot cloud, a really important thing happens – the sensors become accessible via SwitchBot’s REST API. So, I’m using some custom-written Python code that runs under Docker to read the sensors. Turns out it was all surprisingly easy to put the pieces together. It was also a pre-cursor to another project I went on to do, where I helped a friend using a similar sensor to control a smart plug to operate a space heater.

So, what does one do with a sensor like this? You read it, naturally. You keep reading it. Over and over at some sort of fixed interval. In my case, I’m reading it every 5 minutes, or 300 seconds, and storing the data in a database. This type of data isn’t particularly well-suited to living in a SQL database like MariaDB, Postgres, etc. This is a job for a time-series database. So, I called on InfluxDB here. It’s relatively small, lightweight, and very well understood. The Python modules for it are pretty mature and easy to work with even, so it was easy to implement as well. Total win. So, read sensor (convert C to F, since I’m a Fahrenheit kind of guy), store in database, sleep(300), do it again. Lather, rinse, repeat. Just keep on doing that for roughly the next, forever. Or until you run out of space or crash. That’s the code right there, in a nutshell.

Sensors Data Visualization
Sensors Data Visualization

So, what are we visualizing? At the right, you can actually see what I’m graphing. The InfluxData team were nice enough to include some visualization tools right there in the box with InfluxDB, so I’m happy to take advantage of them. Many folks would prefer to use something a bit more flashy and customizable like Grafana, and that’s totally cool. I’ve done it too, even with this same dataset, and the data looks just as good. Heck, probably even looks better, but for me, it was just one more container to have to maintain with little extra value returned. The visualization tools baked into InfluxDB are good enough for what I’m after.

LibreNMS WAN Metrics
LibreNMS WAN Metrics

Next up? Keeping an eye on what’s up with my WAN router’s Internet-facing link. Here at the homestead, I’m running LibreNMS to keep an eye on things. Nothing nearly as custom here. It’s more off the shelf stuff here. It all runs (again) in Docker containers, and as you’d likely expect, uses SNMP to do the bulk of its monitoring duties. at the right, you can see some sample graphs I’ve got stuck to the dashboard page that give a last 6-hours view of the WAN-facing interface of my Internet router, a Juniper SRX300. You see the traffic report as well as the session table size. Within LibreNMS, I’ve got all sorts of data represented, even graphs of how much toner is left in the printer and the temperature of the forwarding ASIC in the switch upstairs in the TV cabinet. All have their own representations, each unique to the characteristics of the data.

Bottom line? Any time you’re dealing with data visualization, there is no one-size-fits-all. Spend the time with the data to figure out what makes the most sense for you and then make it so!

A Journey To A Smarter Dryer

This one was much more difficult. A lot more difficult.

If you recall from my post about the washer, I was able to pull off some fairly useful stuff without a ton of effort. Read a smart plug’s API to see how much power the washer is using to figure out when it turned on, then wait for it to turn off again, then let the fam know that the washer finished, and go take action so that the laundry doesn’t sit around for days, get funky and need to get re-washed. This was of course pretty easy simply because we were able to rely on the fact that the 120V motor in the washer draws well under 15A, the top end of the smart plugs I’m using, the Etekcity ESW15.

Sadly, when we moved into our house, we had an electric dryer. We’ve got natural gas in the house. Heck, in the same room even for the furnace and water heater even. But, back when the last washer sprang a leak and we needed a new washer in a hurry, and unfortunately at the time it was going to be months to get the matching gas dryer back in stock, so we just punted and stuck with the electric model. Sadly, this means for us this means we can’t take the same approach we did with the washer, since nobody makes a smart plug that works on 240V AC 30A circuits.

Unwilling to settle for relying on setting timers with Alexa, having to remind the kids to set timers, or just plain forgetting to do it, I started Googling about, looking for ways to go about monitoring the dryer. Monitoring energy use is the natural fit. When the dryer is in use, it’s consuming loads of energy, and when the clothes are dry, the energy use falls right off. This really shouldn’t be that hard to figure out, right? Right? Sadly, it was.

My next move was to play around with a split core current transformer clamp, and build a circuit with a burden resistor, reading the thing with a microcontroller. I read about the whole process in a handful of places online and it didn’t seem to ridiculous to build the circuit, so I sourced the parts. I got a little breadboard, some jumper wires, the resistors, capacitors, and the CT sensor clamp, and a sacrificial extension cord, which I’d use for my proof of concept test. You see, the CT clamp goes around a single conductor, not the whole cable assembly, so I needed to modify the cable slightly. Relax, the real cable was one of those “flat, side-by-side” types, so it would only mean peeling them apart, not really cutting anything. Sadly, I never made it to that phase. During my POC phase, I was able to get readings back from the sensor, but they never made sense. I was using an ESP32 microcontroller with MicroPython, so maybe that’s related. Or maybe I had a bum CT clamp. Or something else was wrong. We’ll never know, since I gave up after several evenings of bashing my head against the desk.

Failing at the “point” solution of energy monitoring, I moved on to looking at whole-house power monitoring. Hey, if we can’t kill this fly with a newspaper, let’s try a missile, right? Sense landed at the top of the pile. It had the API I was after, though they sort of keep that on the DL. Not in love with that, since those sometimes disappear. If I’m going to drop a couple of hundred bucks on something to use the API for something, it better not just disappear on a whim someday. Plus, our panel is in my home office, recessed in the wall, and there’s not exactly a clean way to get the Sense WiFi antenna back out without it looking really weird. I could make it clean, but then there’d just be a random RP-SMA antenna sticking out of my wall. Interesting decor choice. Sure to be a selling point when we sell the house some day.

Which brings me to the vibration sensor. I was reading one day, still searching, and I came across Shmoopty, and my problems were (half) solved. Sure, I had a Pi Zero W already laying around and I could have just built exactly what he had done, but what’s the fun in that? Remember, I’m already invested. It’s overkill time. So, I ordered up a couple of those 801s vibration sensors and got to work. You know, it was surprisingly hard to get one that met my needs at the time. Why? Most of the 801s units out there are analog-only. Since I’m using a Raspberry Pi, I wanted a digital output, so I didn’t need to mess around with the need for extra ADC (Analog to Digital Conversion) circuitry, just to read a simple sensor. So, I had to order from AliExpress and wait the long wait for shipping from China.

After my sensors finally turned up, I worked out the arrangement of my project boxes and so forth in the laundry room. I landed on a wall-mounted box for the Pi with a 1m pair of wires connected to the sensor, with the sensor inside another small box, which is stuck to the top of the dryer using a little strip of 3M VHB tape. Shmoopty’s Python made it easy to figure out how to read the sensor, so I was happy to be able to draw my inspiration from that. His approach is to keep it small, run on a Pi Zero W, even make it renter-friendly, while mine is more of a “go big” approach – building a Docker container to run it inside of.

Well, at the end of it all, it shares a lot of common philosophy with the plugmon tool, in that it loops infinitely, looking for start and stop conditions. Instead of watching power consumption, it’s watching for the dryer to start vibrating a lot. When that starts an appreciable amount of time, the dryer is declared to be “on”. Once it transitions back to “off”, it fires an event that causes a Telegram message to get sent to the family group chat, again, much like when the washer finishes!

Well, if you’ve made it this far, you’re ready to go check it out. So, get going and get reading. Smarten up that laundry room, report back what you did, and how you did it!

The Robots are Speaking…

So many applications and processes involve notifications. As we begin to automate processes, it becomes increasingly important to know if tasks we’ve initiated succeeded or not. That’s where automated notifications come into play. In my case, often times, these take the form of chatbots that send messages to let me know that something happened, or that a process either succeeded or failed.

I’ve settled on Telegram as my platform of choice for this. What’s attractive about Telegram? It’s available for a wide variety of platforms – iOS/iPadOS, Android, macOS, Linux, Windows, there’s even a web client.

So, how does one create a bot? You have a conversation with the BotFather. BotFather is a Telegram bot that creates bots (how meta, right?) for you. The bot walks you through the whole process. When the process is complete, you’re given a token – this is a secret value that serves as the “keys” to the bot. Once you’re done this process, you’re almost ready to start using the bot in your automations. Next, you start having a chat with the bot, just like you would with another human. Send the /start command to the bot to start it up. Once you’ve done that, you want to figure out the chat_id for that chat. This is pretty straight forward to do, fortunately.

To get the chat_id value for a private chat with your bot, you visit this URL:

https://api.telegram.org/bot[your-bot-token]/getUpdates

Want to use the bot to notify multiple people? Create a Group Chat and add the bot to it. Send a message to the group and reload that URL up above. Check the updates for the Group Chat messages, and look for the chat_id for the Group Chat in there. How can you tell the difference between a regular chat with the bot vs a Group Chat that the bot belongs to? Easy. All chat_id values are 32-bit integers, but Group Chats ID values are negative, while individual chats are positive. Easy, right?

Ok, so you’ve got the Token, and a chat_id value. It’s time to put those bits to work. Here’s an example, in Python, using the python-telegram-bot module, which you can install using pip install python-telegram-bot.

#!/usr/bin/env python3

import telegram

myToken = '123456789:ABC-123456-foobarbaz9876543210'
chatID = -123456789

bot = telegram.Bot(token=myToken)
bot.sendMessage(chat_id=chatID, text="Hello World!")

This is just one of many ways possible to send notifications. Find the one that works best for you and your workflows and go with it! If you want to take a shot at using Telegram, give their docs a read before you start.

Juniper Switch Port Bounce

How many times do you want to bounce a switchport? Ok, it’s not every 5 minutes, I’ll grant you that. But when you need to, you need to. There’s a handful of strategies we can employ to do this.

Firstly, wild-west style. Just walk right up, yank the cable out, count to 10, and shove it back in. Did it work? Did I grab the right cable? Shoot, I hope so. Wait, Juniper starts counting at zero and Cisco starts counting at 1. Oh crap. I pulled the wrong cable. Let’s go back and do it again. Once more, with feeling, and the right cable this time.

Or, we could take the vastly more measured approach of writing up a full MOP, taking it to the Change Control team, getting it approved, scheduling a change window, coordinating with testing teams, double-checking that we’ve got the right cable, then pull it out, count to 10, plug it back in, have the testers verify that everything works correctly, close out the change window, and then go to bed. But that seems slightly excessive, especially if we really need to bounce that port right now, since the thing on the other end’s not responding and we’re troubleshooting because there’s no connectivity.

What if we take the middle-ground? What if we automated the process a bit to lower the risk of some of the human error factors? If we know what port we want to bounce, we can make that happen in a measured, programmatic way through the Junos Python API, which of course, uses NETCONF under the hood.

Enter the Python script I wrote last night. It’s written (naturally) in Python 3, since Python 2 is now EOL, as of a couple of years ago. Seriously gang, if you’re still writing in Python 2, stop. Anyhow, I’m on the road for a couple of days for work, and after a drive last night, and some time stuck in traffic, and some dinner with a work contact, I was just relaxing, and I wrote this.

Yeah, I know, weird way to relax, right? Ok, I had been pondering this the other day, and just sort of threw the idea in the background for processing at a low priority. You know how that goes. Wrote a bit of code, cranked up the VPN back to home, experimented with bouncing the link connected to a Raspberry Pi on the network at home a few times and here we are.

Feed the script a hostname/IP for the switch, (optionally) a username – if you don’t, it will default to whatever your environment resolves for $USER, (optionally) a password – if you don’t, it will expect to be trying to authenticate using SSH keys, and the port you’re looking to shut and turn back up. Using the Junos Python API, the script connects, does an exclusive config lock, disables the port, commits the config, rolls back, commits again, and finally unlocks the config.

At any rate, here it is, in all its splendor… I also copied and pasted most of the same code and at the same time wrote a “PoE Sledgehammer“. It disables PoE on the switch, then rolls back the change. Useful if you need to do something like simultaneously reboot every phone and/or WLAN AP connected to the switch at the same time. As the name implies, it’s kind of a blunt instrument. Use it with caution…

Smartening Up the Washer

I solved this problem once a couple of years ago using a Wemo smart plug, IFTTT and WhatsApp. Well, fast forward a couple of years, and everything broke. Wemo went and totally broke their IFTTT integration, IFTTT completely changed their model pricing model, and Facebook really changed how they were handling how involved they were (and what level of privacy they were giving to) with WhatsApp. So, given how broken things were, I had to go back to the drawing board.

After a conversation with a guy from work that does a bunch of projects like these, I settled on one of the Etekcity smart plugs from Amazon that uses the VeSync app. These days, these seem harder to come by. If I was going to do this over again, I’d probably do it with a Kasa smart plug and use their local API. Anyhow, the VeSync app also has an unofficial, but pretty well-defined, and stable HTTP API that works really well.

So we’re going to leave IFTTT out of the party this time around, just read directly from the plug’s API, figure out how much power is being used to determine whether or not the washer is running, and once we know the washer has stopped, we alert the family by way of a group text. While in the past this was a group text via WhatsApp, now it’s a message to a Telegram group using a bot. I’ve got no great affinity for Telegram beyond the fact that it’s easy enough to setup the bots and get everyone setup on it.

The bottom line? All of this together enables a pure-Python solution that runs under current Python 3 releases, plays super nicely inside a Docker container, which is how I choose to run it. In essence, the code is pretty simple – turn on the plug, start up an infinite loop where you keep reading power levels. After you change to “ON” state, wait for power to drop below a line, to go back to “OFF” state, at which time you throw out a Telegram message to notify the family that the load in the washer finished up and it’s time to go downstairs and move the wash to the dryer.

This has really been super effective at reminding us to stay on top of the laundry. The number of times that we forget loads in the wash and end up needing to re-wash because stuff got forgotten and ended up getting funky smelling has been slashed down to nothing. Great stuff!

Grab the code, or deploy a container today!