Wednesday, December 20, 2017

Java Jigsaw Puzzles DevOps

Oh man that's a catchy blog title.

For the past couple o' weeks, my after-hours project has been trying out building webapps and batch jobs using the combo of Java 9, Spring Boot 2 milestone releases, Elasticsearch 6.1 and Docker Edge with Docker Compose. Just because I was in a WAF frame of mind I added modsecurity as a web application firewall in front of the app so I could learn a bit more about building WAF rules with Apache 2.

It was a fun lil' exercise, but in the end I found that all the cutting edge releases simply wouldn't play nicely with each other.

One painful exercise was trying to get Java 9 distributions to work within a Docker container just as it would within my desktop environment. Project Jigsaw is an oft-cited future feature of Java that build engineers have been asking for to end the myriad of JavaEE / Java ME / Java Desktop / Java Server distributions. It should help containerization by allowing svelte JRE installations to bootstrap within a minimal OS. However... this new way of distributing JREs with modular components creates yet another dependency management headache for builds. Once you begin writing manifest elements for Jigsaw + Java 9, every library and its mother now needs to be managed by your manifest as well. Its enough to drive you nuts.

Let's say you don't want to jump into building modular JARs yet and just build traditional JARs that don't use Jigsaw dependency management. Well... Ubuntu's OpenJRE 9 distribution doesn't automatically inject some Java 9 foundation libraries (such as javax.image), while Oracle's JDK does. If you use an Oracle JDK locally to develop things may appear just fine, but then you need to perform some command-line overrides for things to work on an OpenJRE 9 build. To make things more hairy, it seems that OpenJDK and Oracle have built implementations that might be runtime compatible but are NOT compatible from a build & deployment standpoint. Command-line arguments are vastly different, even though manifest formats are the same. That makes building standard build & deployment scripts a pain, as well as local testing. Distributing Oracle's JRE within a container is just to fraught for me to attempt - so I stick to distribution with OpenJDK instead.

I ended up burning too much time trying to get a consistent build between my streamlined Ubuntu-powered Docker container and my local MacOS development environment, so I punted back to Java 8. While Java 9 had some nice memory management features and some syntactic sugar, what I really needed was Lambda and Stream support. Java 8 was sufficient for this in both Oracle and OpenJDK-land.

The combo of Spring Boot 2 (milestone 7) and Elasticsearch 6.1.0 was another mix that simply didn't pan out. The Java libraries for Elasticsearch 6 had a few signature changes across the API which were entirely incompatible with Spring Data Elasticsearch, and the protocol between ES 5 and 6 did not appear to be compatible. I'm sure this will get patched up in short order within the Spring project, however until then I had to fall back to Elasticsearch 5.6.4. I wanted to stick with Spring Boot conventions as closely as possible, so I did not go native just for ES 6 support.

In the end... I do have a fully containerized solution using Spring Boot 2, Java 8, Elasticsearch 5.6.4, and modsecurity. Getting WAF protection, a single-node ES cluster, a web front-end and a indexing batch process running in the background all happens with:

export DOCUMENT_HOST_DIR=/mnt/documents && docker-compose up -d

...and that's it! Containers are also available at Docker Hub and require thankfully LITTLE dependency management.

Monday, May 15, 2017

Climate Change By The Dollar

One of my lil' neurosis is ensuring that I reduce my energy usage year over year. To make sure I'm following a downward trend, I've been trending the dollar cost for energy and water bills. Assuming that cost per unit does not go down year over year (which so far has been true), this should be a reflection of overall energy use.

Note that the large hills on the graph spurred on by heating bills (both water and central air) are shrinking each year. Air conditioning during the summer months is showing small increases. Over the past three years I have also replaced all light fixtures with LED lighting - which does help drop the constant spend month over month.

It is interesting that while both winters and summers are getting warmer, heating the house expends much more energy than cooling the house, providing an overall downward trend. Water use is also beginning to spike due to the lawn irrigation system, which is why I created the Sprinkler Switch project to only water when no rain has occurred recently or is forecast to occur that day.

This is an indirect measure of how our climate is changing, and only represents a four year sample size. The trends are still quite visible - and demonstrate how evolutions in home heating could significantly reduce energy consumption.

Saturday, February 04, 2017

Alarm Clock Hacking by Blocks

A little over two years ago I built an alarm clock intended for hacking by kids, using a web-based Python IDE. When I tested the lessons, I found that kids didn't like messing with Python and only learned enough to get things barely working. Yet, when it came to Scratch Jr or the desktop version of Scratch, they would spend hours at a time. I needed to find a more approachable way to code.

Recently I discovered Blockly, a product from Google for Education. With that framework you can code by blocks and use its transcoder to output JavaScript, Python, Lua, Dart or (ugh) PHP. The transcoder runs entirely client-side, and the output is human-readable - well indented and even commented.

Writing custom blocks turned out to be an easy thing, so I created blocks to modify the LED display, send audio out to a speaker, or react to button presses. Now you can use blocks to program the clock, while retaining all the functionality present in the older Python interface.

If I was going to redo the Hack Clock, this time I wanted to have a presentable site with full hardware and software lessons, for both Python and Blockly. I revamped the Hack Clock website, completed the Python lessons that I left incomplete last time, wrote new Blockly lessons for the new IDE, and completely re-did the hardware how-tos. Lesson writing took up the lion's share of time, since they all needed new images and better testing.

Another bit o' feedback I had received was that installing the Hack Clock software was too much of a pain. I tried to make this a bit easier this time by offering releases within a Debian pkg, although you still needed to use apt to install dependencies. Still, this cuts down installation from over an hour to about ten minutes... and most of those ten minutes is spent twiddling your thumbs while you want for packages to download and install.

The hardware needed tweaking as well. It turns out the Raspberry Pi headphone jack is just a PWM pin hack and it seemed that GStreamer sometimes just couldn't grok it. The headphone jack was never a complete solution either - it required a discrete amplifier to power speakers, and soldering wires onto a 1/8" jack is a GIGANTIC pain. To make the audio hardware easier to cope with, I moved away from the headphone jack to Adafruit's I2S decoder and amplifier. It provided better audio and cleaner installation without increasing my part count or price. It has proven out to be easier for everyone so far.

The old Hack Clock had another embarrassing flaw: it could only handle one button input and couldn't manage output at all. That drove me nuts and was probably the second biggest thing I wanted to fix. With the latest release the Hack Clock can handle as many buttons as you have GPIO pins, and you can also drive output pins as "switches" in code. The code-by-blocks IDE could deal with buttons and switches as simple function blocks - which meant reacting to user input became much easier to code.

Once things were ready, I installed the Hack Clock software in a mission-critical environment: kids' rooms. So far things have gone well; audio has been more reliable than with the headphone jack, and they have been able to tweak the software more easily than with Python. One bit I noticed this round however: kids don't like looking down to read something, then looking back to code it. The next generation Hack Clock should have an interactive demo to guide through the lessons so they never have to glance away from the IDE.

I'd love to hear what other people experience when they try to get the Hack Clock running as well. A hardware list is posted on Hackaday, and all the instructions are at Let me know what you think!