Your Documents Under the Magnifying Glass

A few years ago I moved my household administrivia to a paperless system. Instead of stacking file folders deep with bills and statements, everything would be scanned & shredded. This greatly helped with storage space - but in a couple of years I ended up with a network drive filled with over 3,000 PDFs, images and documents. Bear in mind the majority of these are scanned documents - so the contents are images instead of machine-readable text. Everything was dumped into a single directory and files were named based on the timestamp of when they were scanned, taking hours to organize documents into folders and sub-folders.

Instead of burning hours sorting documents I started burning hours building a simple set of applications that would read document metadata, attempt to convert the images to text, group documents by common letterhead and then provide a simple search interface over all of it. Since optical character recognition is hit-and-miss, any full-text search should permit proximate indexing and searching to allow for fuzzy matches.

In the end I created two apps: DocMag and DocIndex. DocMag serves as the search front-end and allows users to perform full-text searches on scanned documents, label them with tags and automagically group other documents with the same letterhead or logo. The interface is pretty spartan and uses Spring Boot to build a straightforward integration into Elasticsearch. DocIndex is the batch process that crawls a filesystem and parses the documents using OCR, generates thumbnails, tags similar documents using computer vision-based template matching, and stores document metadata within Elasticsearch.

DocMag was created in Groovy using Spring Boot (Spring Web, Spring Data, etc). I did this mainly to understand how Spring Boot's conventions translated over to the Groovy world... it had been quite a while since I had worked with Grails. It turns out that Groovy, Spring Boot and Thymeleaf complemented each other quite well and make for fairly simple web development.

DocIndex was created with Spring Boot and Java 9 initially. I griped in an earlier post about my problems with Java 9's dependency management, so instead I fell back to the lambda expressions and work queue management within Java 8. This permits multithreaded parsing of discovered files, which then allows for vertically scaling document indexing by adding cores. Horizontal scaling should be possible by replacing the in-memory work queue with a proper shared message broker. There is a "reminder" issue I've already filed to migrate to a proper broker so this can be done sometime in the future.

Both DocMag and DocIndex are deployed as containers within DockerHub. This was especially necessary with DocIndex, as it relied heavily on native libraries for Tesseract OCR and OpenCV. OpenCV was the most contentious - each Linux distribution has a different version of OpenCV, and the version changes quite rapidly. Building containers for distribution allowed me to ensure users got the correct version of native libraries that worked well with their Java bindings.

Another nice feature of the containerized deployment model was composition - I was able to pair the correct revision of Elasticsearch, conditionally include Kibana, and provide a simple web application firewall by placing DocMag behind modsecurity and Apache. Network connections could be maintained between Elasticsearch, modsecurity, and DocMag without any of these interconnects leaking to the "outside" world, allowing me to do things such as only expose modsecurity to outside traffic and only permitting DocMag to receive requests through modsecurity. Elasticsearch could be hidden as well, only available on the internal network managed by Docker Compose.

Deployment can be relatively straightforward; since everything is deployed to Docker Hub as a container, one should just need to download the docker-compose.yml file and issue export DOCUMENT_HOST_DIR=/mnt/documents && docker-compose up -d. This should provision a single-node Elasticsearch instance, start DocMag behind modsecurity, and begin indexing with DocIndex.

If you are stuck digging through mountains of scanned documents, give DocMag a try. Ease of installation is one of its primary goals - so let me know if you find any issues getting it running!

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.

Telling a Tale for Ten Years

Exactly ten years ago I started this ridiculous blog as a way to collaborate with other game developers. At the time I thought I would dig deep and push out at least one title. This eventually led to the "Desktop Distractions" studio concept, and the nascent title Deskblocks. I also worked within the CrystalSpace engine as an entrant to the PlaneShift team. I just couldn't give these projects traction however, so I gave it up and moved on to tinkering.

Even though the driving force behind the blog had faded away, and even though no one else reads this blog (aside from the State of .NET Integration Frameworks post), I kept updating it. Writing - even if it exists only for your own edification - really does help with communication and critical thinking regardless of what you write about. Even though my day job has nothing to do with garage door openers, my posts on my garage door security system helped me organize the build in a way that informed the Hack Clock project. Back in 2006 I began investigating vector processing, and the resulting frameworks have helped me think about and design microservice architectures. Of course, there was plenty of venting as well with my favorite software companies being dissolved or SuSE Linux winning and failing and winning and failing again. All of this writing helped me when performing comparative analysis at work, or designing parallel architectures, or watching trends in software development.

It is hard to believe a decade has slipped by. It doesn't even seem real. I don't think I've evolved much since that one cram session in a crystal chair, but I'm glad to have my collected ramblings to reflect back on.

A Drift Into Failure

I'm still working towards catching up on my Christmas ready. I already wrote my missives on Thinking in Systems and A Pattern Language; next up is the DevOps favorite Drift into Failure.

The basic premise of Drift is that failures, even massive ones, don't (usually) happen because of a vast conspiracy or from the deeds of evil people. Massive failures occur from behavior that is considered completely normal, even accepted, as part of a daily routine. These routines give our perspectives tunnel vision and often don't allow us to see the underlying issue. Production goals, scarce resources and pressure on performance causes drift in these routines that slowly erode safe practices.

Fatal aircraft crashes and space shuttle disasters are often quoted in the book, however every operations or software engineer in IT has seen this play out a gazillion times before. The site goes down on a regular basis... and no one knows quite why. After digging and pushing new code and re-pushing bug fixes for many sleepless nights, one often finds out that the outage was due to a routine maintenance task gone awry. Maybe a query optimization cache was manually flushed within the production RDBMS, causing the entire cluster to freak out and create a bad query plan. It seemed perfectly sane at the time and even if every single person knew this was going to happen the day before, it likely wouldn't have been caught.

Drift points out how remediation and "root cause" reporting is often fruitless. The concept of high-reliability organizations was pushed in the 1980's as an entire school of thought, focused on errors and incidents as the basic units of failure. Dekker demonstrates that "the past is no good basis for sustaining a belief in future safety," and such a focus on root-cause analysis often does not prevent future incidents. The traditional "Swiss Cheese Model" for determining cause has attempted to see where all of the holes within established safety procedures line up, so as to create a long gap through which problems can drive themselves through. This type of reductionist thinking where atomic failures create linear consequences has turned out not to be predictive after all - instead we need to look at things through the lens of probability.

One of the best practices that anyone, including those supporting enterprise software, can encourage to avoid failure is to be skeptical during the quiet times and always invite in a wide range of viewpoints and opinions. Overconfidence can be your downfall, and dissent is always a healthy way to get new perspective. Dekker quotes Managing the Unexpected to point out that "success... breeds overconfidence in the adequacy of current practices and reduces the acceptance of opposing points of view." Those that were not technically qualified to make decisions often were the ones that made them, or outside pressures (event subtle ones) caused trade-offs in accepted practices. Redundancies that were supposed to make things highly available often make systems more complicated and, in turn, actually make them more likely to fail.

The best way to avoid a drift into failure is to invite outside opinion, even bring in disparate practice groups. Take minority opinions seriously. Don't distill everything to a slideshow. Be wary of adding redundancies and failsafes - often the most simple solution will be the most reliable. The recent re-invigoration in microservices is a great example of this - by simplifying the pieces of a complex system, we can allow each component to work in isolation and ignore the remainder of the system. This allows the system to grow, adapt and evolve without support systems usually provided for monolithic software stacks.

Drifting into failure occurs when an organization can't adapt to an increasingly complex environment. Never settle, always embrace diversity and keep exploring new ways to evolve. A great quote from Dekker is "if you stop exploring, however, and just keep exploiting [by only taking advantage of what you already know], you might miss out on something much better, and your system may become brittle, or less adaptive."

A Systems Language

A Pattern Language is an interesting book to pick up, and that's not just a joke about the size of the volume. Its web site betrays how old the book actually is; it was published in 1977 based on research that had been ongoing for several years. It's scope is pretty large and covers everything from the layout of an office building to the composition of an entire town. Much attention is focused on how to build communities within these spaces, and a lot of research provides evidence on optimal ways of building and tearing down boundaries.

Of particular interest to me were chapters concerning self-governing workshops and offices. The book stresses that no one enjoys their work if they are a cog in a machine. Instead, "work is a form of living, with its own intrinsic rewards; any way of organizing work which is at odds with this idea, which treats work instrumentally, as a means only to other ends, is inhuman." This is a fairly strongly worded assertion that means that employees must feel empowered in order to construct meaningful product.

Just as Thinking in Patterns postulated that groups should autonomously self-organize in order to realize their greatest efficiency, A Pattern Language encourages the formation of self-governing workshops and offices of 5 to 20 workers. A chapter is dedicated to the federation of these workgroups to produce complex artifacts - such as several independent workshops working in concert to build much larger things.

A Pattern Language also encourages keeping service departments small (less than 12 members) and ensuring that they can work without having to fight red tape. This applies to many shared services departments in both government as well as public sector organizations; departments and public services don't work if they are too large as the human qualities vanish. One must fight the urge to make an "idiot-proof system," since this can cause the system to devolve to the point that only idiots will run it.

The book is largely about physical space of course, so it has many recommendations on how offices should be connected. The authors specifically studied what isolated groups within a company, and even what we might consider small physical distances amounted to big interruptions in communication. If two parts of an office are too far apart, people will not move between them as often as they need to. If they are a floor apart, they sometimes will not speak at all.

Ultimately A Pattern Language has a lot of common sense to offer up about how to build a work community, backed by a fair amount of research that bucked many trends in the 70's. It had points that should not be glossed over even now, including:

You spend 8 hours at work - there is no reason it should be any less of a community

Workplaces must not be too scattered, nor too agglomerated, but clustered in groups of 15

Workplaces should be decentralized, not reliant on a central hub

Mix manual jobs, desk jobs, craft jobs, selling, etc. within a community

There should always be a common piece of land (or a courtyard) within the work community which ties offices together

The work community is interlaced with the larger community they operate within

Workspace efficiency and community engagement is definitely not a new practice, however we always tend to think it is. If we can remember the lessons learned thirty-seven years ago, we may be in a better place to make a better workplace today.

Thinking in Patterns

Cognitive Hazard by Arenamontanus

I've finally started to look at some recommended reading that has been on my wish list for going on two years now. Two of the books, Thinking in Systems and A Pattern Language, have particularly resonated with me since they spoke directly to the practice of software engineering without mentioning it once.

Donella Meadows has left behind quite a legacy, and has great observations on how people work within overarching systems. Systems are everywhere and are often composed of yet other systems - just as it is with how people manage their workload every day. In particular, Donella notes the traps that systems can cause which cause things to go completely awry. Let's see if we can identify any of these traps within the context of enterprise software development:

• Policy Resistance (think of "The War on Drugs," where two sides are trying to leverage the same system)
• Tragedy of the Commons (exhausting a shared resource)
• Drift to Low Performance (goals are eroded because negative feedback has more resonance than positive feedback)
• Escalation (one side is attempting to out-produce the other, without a balance in between the two sides)
• Competitive Exclusion (success to the successful)
• Shifting the Burden to the Intervenor (an addiction has removed a system's ability to shoulder its own burdens)
• Rule Beating (finding loopholes)
• Seeking the Wrong Goal

Any of those sound familiar in your current software engineering practice? No matter if this is exhibited between the business and the engineers, or PM's and engineers, or between engineers - these are universal pratfalls.

There are ways to influence systems and avoid the traps we often fall into. These leverage points within the system can allow you to alter behavior and encourage positive results. A tricky point remains that some of the leverage points that are easiest to alter have the smallest impact, and some of the largest impact leverage points are very difficult to manipulate. If we look at an Agile software scrum, you might identify least impactful to most these leverage points as:

1. Numbers, Constants and Parameters. It often feels like you're changing things because you have the most control over these knobs and dials... but all too often reactions are delayed and are cushioned by buffers within the system. Sure, you can change your sprint velocity or begin estimating bugs, but those are just different views on the same result.
2. Buffers, or the sizes of stabilizing stocks that act as reservoirs of results. A buffer may delay or even out the consequence of a change within the system. Changing buffers would be like changing from a two to a four week development sprint in Agile - you may give yourself more time to recover, but more than likely you're just delaying an inevitable fail.
3. Failing that, you might try to alter the real, physical parts of the system and how they interact. This can happen, but they are often difficult to change and result in a game of whack-a-mole. This is more fondly called "re-arranging the chairs on the Titanic," and often is exhibited by swapping out team members but keeping the system the same.
4. The next leverage point might be to try and change how quickly you respond to changes by reducing delays, which in turn alters how quickly the system changes. However, Donella does demonstrate that shorter reaction time can very easily result in greater volatility, and things can become so volatile that they crash. This is what Agile is meant to guard against by locking down a sprint and ensuring priorities aren't changed on a day-by-day basis.
5. In order to get a grasp on things one may also overlook the balancing feedback loops - or safety measures - that safeguard the system in times of emergency. The excuse is generally that "the worst is unlikely to happen," however this drastically reduces one's survival range. Adaptability is important, and if you take away the ability to adapt you can crash even harder.
6. Monitoring for reinforcing feedback loops is something that becomes crucially important. This tasks requires one to watch for runaway chain reactions, which can cause a meltdown if not kept in check. Here bad decisions and bad reactions begat even more bad decisions and bad reactions, causing a runaway system. Look for balance instead of infinite feedback loops; if you can keep pushing your tasks to the next sprint, you're only encouraging a runaway backlog of tasks.
7. Information flows can save a system. If information is in your face and always available, it influences even small decisions. Look at the Nest thermostat or smoke detector - here are devices whose primary purpose is to give you a nonstop flow of info wherever you are. The more info you have (such as how many hours heat was pumped into your house), the more you make small alterations to find balance. This is another part of the Agile process in the form of burndowns/burnups/velocity graphs. This info is meant to be viewed and reflected upon often.
8. Rules (incentives, punishments, constraints) often have to take place to enforce all the above points. In order to kill feedback loops, ensure emergency systems are maintained and information is shared some rules of the game have to be put into place.
9. Self-organization, which is an odd juxtaposition of the above rule about rules, is something that Donella prizes most about not only the human condition but systems in general. Usually if you let the component pieces of a system find their role, they will find a way to work with other components in harmony. This is the proof against micro-management; the more you manage, the more you can threaten a system's success. Let developers go free within the confines of the sprint, and don't hover over them (aside from a daily standup).
10. Find the right goals to change a system. If you focus on GDP, you will focus on gross domestic product at the exclusion of other things. Picking the right goal is tougher than it sounds - you need to know what you want first. However if you can clearly identify and communicate a measurable goal, you can have a huge amount of control over the system. Define what the business actually wants to see - and involve them in the decision making process.
11. Change your mindset. This is effectively what EVERY project management methodology attempts to do - make you think about the same problem in a different way. If it gives you a renewed perspective, this can be helpful. However...
12. ...ultimately you should transcend paradigms and realize no paradigms are true. This is what supposed "anti-patterns" are meant to exhibit, and it can be helpful to realize that Agile, just like Waterfall, will ultimately come and go. Just ship early, and ship often.

Just as we have "Gang of Four" or "Enterprise Integration" patterns, the above are system patterns that can help us decompose and deal with a system. Look for the common traps that always happen - and then evaluate your leverage points to counteract them.

Designing Head Patterns

When I saw Jason McDonald's design patterns quick reference guide I marked out. I forwarded the link to everyone I knew who heard of the Gang of Four and printed out a nice, one-page color version to keep. I almost freakin' framed it. I liked how succinct it is... it gives you the class diagrams so your brain is instantly sparked, and just enough description that you still have to think analytically about the pattern.

A few people asked me about the original Design Patterns book and a few others mentioned how much they liked Head First Design Patterns. I have to sadly admit - I originally wrote off the Head First series as just another "X for Dummies" clone, but now that I read the RMI section of their Java book and read the first 100 pages of their Design Patterns book I have to admit I judged... sigh... a book by its cover.

The RMI section was actually fairly straight forward and illustrative and even included an informative chapter that included Jini. The Design Patterns book has done a good job of explaining the Decorator pattern, something that I can't do with a pencil and paper in front of someone. Both books have been good references for me to pass along to other developers.

If only there was a pattern to remove outdated cliches two paragraphs ago.

DeckerEgo's Razor

I changed the title of this blog from "Tales of an Indy Game Developer" to "Tales of an Indie Developer." Right now my game development has stagnated and may go to zero. But I'm still hacking away on a number of open source projects... as well as hacking the various other constructs I have to live with in my day.

One of the things I'm supposed to do in my paid gigs is architect the infrastructure of entire enterprises. If the title sounds nebulous and nonsensical, it is. Basically I try to coordinate data center sprawl or hack away bits when it gets out of hand.

Through my days I've moved progressively from very myopic fields to extremely broad ones. I started out in LISP working on Chez Scheme, moving to C++ & Motorola 68k assembly, moving to 3D rendering pipelines, moving to enterprise applications, moving to Web applications, moving to corporate networking, moving to corporate infrastructure, moving to enterprise Web application development & infrastructure, now moving to enterprise infrastructure. The uncanny thing is that all of these different genres follows the same Tao of Programming, no matter if it's even really programming anymore.

I'm working on ConsultComm 4 now and it's ridiculously slow-going. I have ripped out every bit of old code and have completely redone things (again), this time trying to follow a more... organic... layout. I'm trying to avoid corner cases and develop things as main-stream to Java's intended architecture as possible. This includes more modern event handling (more akin to Servlet chains or AWT events), better thread management and hopefully a better UI with less "surprises" and non-intuitive user interface choices. This has meant a crapton of prototyping, a lot of refactoring and a lot of brute force hacking. But I'm hoping it will be worthwhile in the end; the goal is to make ConsultComm 4 the last major version.

I've also been spending a lot more time in the debugger. The new codebase is loaded with assert statements meant to catch errors as they happen and plan for unexpected consequences. By doing some deep introspection and catching mental assumptions I make while I code things are error'ing out a ton more, but I'm catching more bugs on the front-end. Also I'm able to catch a lot of one-off circumstances and fail over to more appropriate states.

The same thing applies if you're trying to build a nationwide enterprise-ready datacenter tho. Prototype out the wazoo. Go as mainline as possible - don't try to outsmart existing architecture standards. No surprises. Plain for failure and develop for the exceptions. Document your assertions and watch for when they fail. Introspect and watch all the traffic routing back and forth... catch errors before they become problems.

Ultimately both software and enterprise application infrastructure need to pass the same meta-tests in order to become a lasting solution. You should be able to slice away any piece of the structure and have it remain consistent with the layout of the whole. You wouldn't cut a loaf of wheat bread and somehow end up with a single slice of rye in the middle. However, I'd wager if you went into a typical corporate data center and picked out a random server... heck, even an entire rack... you'd likely find out that it is managed or designed differently than the remainder of the servers in the room. Likewise take an object or source file from a typical software application and you'll find code patterns that appear completely different than the rest of the codebase.

All servers should be managed the same. All racks of servers should be organized the same. All types of servers (DBMS, SAN, storage, application server, development servers, load balancers, firewalls) should be updated, backed up and access controlled in the same way. All objects in an application should follow the same pattern. Exceptions should be handled the same way across all methods. Events, error handling and user prompts should all look and feel the exact same. Refactor like mad if you have to... but if you re-design your pattern, you should re-implement your codebase/servers/data center.

The Tao of Programming said it best:

A program should be light and agile, its subroutines connected like a string of pearls. The spirit and intent of the program should be retained throughout. There should be neither too little or too much, neither needless loops nor useless variables, neither lack of structure nor overwhelming rigidity.

A program should follow the `Law of Least Astonishment'. What is this law? It is simply that the program should always respond to the user in the way that astonishes him least.

A program, no matter how complex, should act as a single unit. The program should be directed by the logic within rather than by outward appearances.

If the program fails in these requirements, it will be in a state of disorder and confusion. The only way to correct this is to rewrite the program.