In my case, over my Christmas vacation, I checked into a Mom and Pop hotel, or rather a motel! It was about 24 rooms all in a row, occupying a single floor. Since they were on a budget, their Internet offering consisted of what appeared to be 5 or 6 Linksys routers set up every few rooms. You’d simply connect to the closest access point and have Internet.
But there was a problem: determining which access point was closest to me! The signal strength indicator on my computer showed several of them were 3/3 bars so that wasn’t much help. I tried connecting to the first one, but had virtually no Internet connectivity.
In the above example, I added in the TARGETS environment variable, and was sure to include 192.168.1.1, which was the IP for each router (they were all the same). Then I set Splunk “real-time mode” and periodically checked that tab as I was working. This is what I saw:
In a previous post, I wrote about using Splunk to monitor network health and connectivity. While building that project, I thought it would be nice if I could build a more generic application which could be used to perform ad hoc data analysis on pre-existing data without having to go through a complicated process each time I wanted to do some analytics.
So I built Splunk Lab! It is a Dockerized version of Splunk which, when started, will automatically ingest entire directories of logs. Furthermore, if started with the proper configuration, any dashboards or field extractions which are created will persist after the container is terminated, which means they can be used again in the future.
A typical use case for me has been to run this on my webserver to go through my logs on a particularly busy day and see what hosts or pages are generating the most traffic. I’ve also used this when a spambot starts hitting my website for invalid URLs.
This will download the container, start it up, and mount the appropriate directories. The containerized version of Splunk looks recursively for logs in /logs/, stores its data in /data/, and stores dashboards that are created in /app/. (Note that if you try to use “password” as your password, the container will refuse to start for safety reasons!)
First things first, let’s verify our data was loaded and do some field extractions!
I’ve been using Splunk professionally over the last several years, and I’ve become a big fan of using it for my data processing needs. Splunk is very very good about ingesting just about any kind of event data, optionally extracting fields at search time, and providing tools to graph that data, find trends, and see what is really happening on your platform. This is important when your platform consists of thousands of servers, as it does at my day job!
While Splunk can handle events in timestamp key=value key2=value2 format, it also has support for dozens of standardized formats such as syslog, Apache logs, etc. If your data is in a customized format, no problem! Splunk can extract that data at either index or search time! Finally, there’s the Search Processing Language, which is like SQL but for your event data. With SPL, you can run queries, generate graphs, and combine them all programatically.
So yeah, I’m a huge fan of Splunk. One thing I use it for out of the of office is to graph the health of my Internet connection. This is useful both for when I’m at home and when I am traveling–I just feed the output of ping into Splunk and then I can get graphs of packet loss and network latency.
Let’s just jump into an example screen–here’s what I saw when I was a friend’s place and I uploaded a video to YouTube:
Overall, I am pretty happy with the Twenty Seventeen theme that ships with WordPress, but one thing that really drives me crazy is that whatever cover image you upload takes up nearly 100% of the entire web browser when viewing on a desktop or laptop. I find it darn near infuriating, because I have to scroll down just to click on a menu link or see content. That ain’t right.
Way back in 2005, I converted my website (and its predecessor) over to Drupal. Drupal has served me well for the last 13 years, but due to the direction in which Drupal as a product has moved, I do not feel it is the right choice for me anymore.
So I instead checked out WordPress, and was rather happy with it. It does one thing (blogging) really really well, instead of trying to be the “kitchen sink” like Drupal. As of this writing, I’ve ported over just about all of the content I wanted to port over, and have since switched www.dmuth.org to point to this WordPress Install.
Along the way, I learned some thing about how to set up and configure WordPress, let me share them with you:
TL;DR If you are comfortable with Docker and Docker Compose, you can go straight to the GitHub repo and get started. For the everyone else, read on…
When I stood up this website, I wanted to do so in Docker, but I ran into an issue: the official WordPress Docker image runs Apache. Apache is a nice webserver for small amounts of traffic, but it does not scale well. As more concurrent connections come into a server running Apache, more copies of the httpd process are forked, which causes RAM usage to go up. Having RAM usage regularly go up and down is not ideal.
Fortunately, there is a better way. The Nginx webserver, combined with PHP running in FPM mode scales much better as the memory usage is more constant, which means that peak loads on the server won’t cause you to thrash the swapfile. Encryption would also be nice, so I wanted to have some SSL going as well.
I couldn’t find any existing solutions, so I built one! In this post, I’m going to walk through each piece of the puzzle.
I’m a big fan of Amazon S3 for storage, and I like it so much that I use Odrive to sync folders from my hard drive into S3 use S3 to store copies of all of my files from Dropbox as a form of backup. I only have about 20 GB of data that I truly care about, so that should be less than a dollar per month for hosting, right? Well…
Close to 250 GB billed for last month. How did that happen?
I’m a big fan of the Discord Musicbot, and run it on some Discord servers that I admin. Wanting to run it on a server, I first created an Ansible playbook and launched a server on Digital Ocean. But after a few months, I noticed that the server was sitting over 90% idle. Surely there had to be a better way.
So I next tried Docker, and created a Dockerized version of the Musicbot. I was quite happy with how much easier it was to spin up the bot, but still didn’t want to run it on a dedicated server on Digital Ocean. Aside from having unused capacity, if that machine were to go down, I’d have to do something manually.
I thought about running it in some sort of hosted Docker cluster, and came across Amazon’s container service. So this post is about creating your own cluster in ECS and hosting a Docker container in it. I found the process slightly confusing when I did it the first time, and wanted to share my experience here.