Recommended Readings

• Johannes Brodwall: This dependency injection madness must end! - it's very valuable to hear well-founded arguments against any popular belief and Dependency Injection is one of these. "I have started disliking the consequence of this strategy very much: All coupling in my system becomes implicit and harder to understand. I have instead reverted to using design patterns like the Singleton pattern, but with a slight twist."
• Computer Programmers Learn Tough Lesson in Sharing - WSJ.com - A balanced presentation of pair-programming including both benefits and issues. A key point: It is a skill that must be learned (to respect the other one, give her space, be aware of how your behavior is perceived by her, ...).
• Kent Beck: Functional TDD: A Clash of Cultures - TDD has been developed for object-oriented languages and applying it to a functional language with strong type brings interesting challenges. Also a good summary of the benefits of TDD: double checking of the logic (by the implementation and the, preferably quite different, test), solution decomposition (focus on part of the problem, once solve be sure it stays solved),  automatic checking of correctness, outside in design (API first, implementation after that). Plus the pleasant experience of the continuous cycle of tension (failing test) - relief (green).
• Paul Callaghan: Thinking Functionally with Haskell: Types? Tests? We Need a New Word - Powerful type systems eliminate possibility of defects thus venturing into the domain of testing - what can they offer and where the new border and symbiosis between types and tests will be?
• Tales from the Ops Side: Black Friday - an interesting and exciting view into the life of operations engineers one day when all went wrong. Key learnings: Many interdependant components are difficult to reason about; good monitoring and communication are crucial. The post refers to an interesting concept of Recovery-Oriented Computing, i.e. failures are inevitable and their prediction is nearly impossible thus we must focus on making the systems able to survive failures (e.g. vi damage containment, automatic fault detection, component-level restartability).
• Groovy: The road map for the popular JVM language - why was Groovy created (as Java companion focused on productivity), key changes in Groovy 2.0 (more suport for static typing, Java 7, modularity with speed as a side-effect) and in the future Groovy 3.0 (invokedynamic everywhere, more Groovy written in itself).
• Martin Fowler: Key Points from NoSQL Distilled - an overview of why NoSQL, data models, distribution models, consistency, map-reduce, polyglot persistence, criteries for choosing a database.
• You’re a Top Developer! - a surprising hypothesis that "90% of all developers never read a programming blog, never have any side projects to learn something new, and never spend any time or effort outside work hours to improve". However I haven't seen any data to back that up (the author only quotes  Peopleware) and the author doesn't propose any explanation for the fact. I'd really like to know if it is true and why it is so.

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This is a summary of the excellent JavaZone 2012 talk Going Native (vimeo) by Brian McCallister. Content: Using native libraries in Java and packaging them with Java apps, daemonization, trully executable JARs, powerful CLI, creating manpages, packaging natively as deb/rpm.

1. Using Native Libs in Java

Calling Native Libs

Calling native libraries such as C ones was hard and ugly with JNI but is very simple and nice with JNA (GPL) and JNR (Apache/LGPL)
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(Disclaimer: Based on personal experience and little research, the information might be incomplete.)

VisualVM is a great tool for monitoring JVM (5.0+) regarding memory usage, threads, GC, MBeans etc. Let's see how to use it over SSH to monitor (or even profile, using its sampler) a remote JVM either with JMX or without it.

This post is based on Sun JVM 1.6 running on Ubuntu 10 and VisualVM 1.3.3.


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Hadoop's NameNode and JobTracker expose interesting metrics and statistics over the JMX. Hive seems not to expose anything intersting but it still might be useful to monitor its JVM or do simpler profiling/sampling on it. Let's see how to enable JMX and how to access it securely, over SSH.


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The best code I have ever written is the code I never wrote. It works exactly as intended. There are no bugs, ever. It doesn't increase complexity of the application. Other people don't need to struggle to understand it. It gets never outdated.

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Republished from blog.iterate.no with the permission of my co-authors Stig Bergestad and Krzysztof Grodzicki.

Three of us, namely Stig, Krzysztof, and Jakub, have had the pleasure of spending a week with Kent Beck during Iterate Code Camp 2012, working together on a project and learning programming best practices. We would like to share the valuable lessons that we have learnt and that made us better programmers (or so we would like to think at least).


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I love testing. And I like productivity. There are many tools and libraries that make writing tests easier, more convenient, more fun. I would like to introduce here those that I found the most useful during the years, from selected advanced features of JUnit to assertion libraries, powerful behavior/fault injection, testing of database-related code, and finally to boosting your testing productivity hundredfold with Groovy.

This post accompanies my JavaZone 2012 lightning talk and goes more in depth and introduces additional tools and tips.


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Our code is often untestable because there is no easy way to "sense¹" the results in a good way and because the code depends on external data/functionality without making it possible to replace or modify these during a test (it's missing a seam², i.e. a place where the behavior of the code can be changed without modifying the code itself). In such cases the best thing to do is to fix the design to make the code testable instead of trying to write a brittle and slow integration test. Let's see an example of such code and how to fix it.


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Recommended Readings

• How To Fail With Agile:Twenty Tips to Help You Avoid Success - a great overview of ways people may make agile projects and initiatives fail - use them to either avoid the failure or to make it certain, according to your attitude towards agile
• vim-adventures.com: Learning Vim keys in an entertaining way by playing an on-line 2D game. A brilliant idea!
• The Search for a Better BIG Data Analytics Pipeline - how to use big data and analytics on it in a company. Big data = lot of data, simple processing; deep analysis = representative, small sample of data (no need for all), advanced techniques. Big data can provide input for analysis.

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The default PMD rules are little too strict for me (especially when starting on a legacy project) so I need to adjust them, usually by decreasing priority to warning. It's however quite difficult to find the rule responsible for an error message unless you know how to do it. The answer is the PMD Violations Overview view, which lists the rule names (such as "ConstructorCallsOverridableMethod", as opposed to the error message such as "Overridable method 'addSummaryPeriod' called during object construction").


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Real World Java EE Night Hacks - Dissecting the Business Tier, Adam Bien, 2011, ISBN 9780557078325.

I highly recommend this very thin and down-to-the-earth-practical book to everybody interested in back-end Java (a basic knowledge of servlets, Java ORM, and REST might be useful). The book evolves around a small but realistic project (X-Ray), which we follow from the inception through couple of iterations til the end. Bien shows us how lean Java EE can be, how to profit from the functionality that it offers, and how these pieces of functionality fit together to deliver something useful. He actually introduces a complete Java EE development environment including continuous integration (CI), code quality analysis, functional and stress testing.

Some of the things that I appreciate most in the book is that we can follow author's decision process with respect to implementation options (such as SOAP vs. REST vs. Hessian etc., a REST library vs. sockets, or when (not) to use asynchronous processing) and that we can see the evolution of the design from an initial  version that failed through cycles of growing and refactoring and eventually introducing new technologies and patterns (events, configuration over convention) to support new and increased requirements.
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I couldn't find any good, brief, practical introduction into Puppet that gives you basic working knowledge in minimal time, so here it is. You will learn how to do the elementary things with Puppet - install packages, copy files, start services, execute commands. I won't go into Puppet installation, nodes, etc. as this introduction focuses on the users of Vagrant, which comes with Puppet pre-installed and working in the serverless configuration.


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Too often companies and IT departments believe that they know what software they should create. However users often need and want something different than you believe, even if you're a domain expert yourself. My colleague and dear friend Ivar had exactly this experience when designing a meal planning tool for his girlfriend and himself. He knew everything perfectly - the previous tool they've used (a paper on the fridge), the problem domain, the users. Yet the first prototype tested did not at all match the ideas of what he thought was needed.


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We've recently changed our Zabbix 1.8.1 setup to include Zabbix Proxy, which broke all our active checks (f.ex. monitoring of log files). The solution seems to be having the proxy first, before the Zabbix Server, in the Zabbix Agent's config parameter Server, i.e. "Server=<proxy ip>,<server ip>".


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