Things n' Stuff Thoughts about the universe in general

That I’ve seen in a while anyway. If you go to Stack Overflow today, you’d find a helpful rubber duck in the corner that will help you solve all of your (code) problems:

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With version 8, Java finally jumped on the asynchronous programming bandwagon with its own Promise-Oriented programming model, implemented by the CompletableFuture class and a set of interfaces and implementations it uses. The model is generally useful and not as horribly complicated as we sometimes get in the Java foundation class library¹, and it lends itself to fluent programming much better than the comparable model from fluent API proponent Vert.x project.

The Problem

One thing that most asynchronous computing models suffer from – and Java’s CompletableFuture is no exception – is the loss of typed exception handling. While CompletableFuture.exceptionally() is a good model that does not introduce a lot of boilerplate², you do lose the ability of the try..catch..finally syntax to effortlessly ignore exceptions you are not ready to handle and just letting them propagate up the stack. (more…)

1. especially for things that claim to be “enterprise versions”, aughh [↩]
2. again, compare to Vert.x AsyncResult handlers. Other APIs, such as RX also do a good job in reducing boilerplate around error handling [↩]

In case you’re looking to host a Polymer application, S3 is a great and cheap option. The main problem is with no rewrite rules, you must use hash tag routing.

But with a simple configuration hack and a Cloudfront distribution you can use proper URLs for your S3 hosted polymer application – as detailed by Keita Kobayashi in his blog.

Ever needed to create a “secure” password to register to a web site¹ and you couldn’t be bothered to invent a secure password? Just paste this command line to your terminal:

ruby -e 'puts [*"a".."z",*"A".."Z",*"0".."9",
  "!@#$%^&*()_+[]/-=.,".split("")
  ].shuffle[0..(ARGV.shift.to_i)].join' 16

The last argument is the number of characters to put into the password.

1. that probably annoyingly require “at least 1 upper case letter, 1 lower case letter, 1 number and 1 special character” [↩]

Maybe you are a consultant and juggle multiple clients with Amazon Web Services deployments, maybe you just have accounts for all the start-ups you ever worked for, or maybe you just like to use 17 different AWS accounts for the free-tier usage, but eventually your ~/.aws/credentials file looks like an MS-Windows INI file.

At this point, running the AWS CLI is kind of annoying – you need to remember the correct --profile flag to set for each scenario, and bash will not complete these for you…

Bash aliases to the rescue!

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In the past, I’ve discussed using SSH to circumvent restricted networks with censoring transparent proxies, but that relied on the restricted network allowing free SSH access on port 22 (what we call in the industry – the single network requirement for getting work done).

Unfortunately, there are restricted networks that don’t even allow that – all you get is the transparent censoring HTTP proxy (which has recently became the case with the free Wi-Fi on the Israeil Railways trains).

But fortunately for us, there is still one protocol which they can’t block, they can’t proxy and they can’t man-in-the-middle  – or else they’d break the internet even for people who only read news, search google and watch YouTube – that is HTTPS.

In this article I’ll cover running SSH-over-HTTPS using ProxyTunnel and Apache. The main consideration is that the target web server is also running some other websites that we can’t interrupt. The main content is based on this article by Mark S. Kolich, but since it only covers using plain HTTP and in addition to some simple changes in the example configurations I also wanted to cover getting an SSL certificate, here’s my version of the tutorial:

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When creating web applications, we often need to have some parts of the application configuration for the deployment environment – usually web service API endpoints have different URLs in different environments, such as using a production web service in production and a locally hosted web service during development.

Such a feature is implemented in many web frameworks and building tools for web applications, such as Gulp or Grunt. Unfortunately, when building applications using Google’s Polymer SDK, there are no such features available – reviewing the Polymer documentation one, there isn’t even any mention of how one handles such mundane tasks as configuring API URLs, except hard-coding them¹.

Developers have tried to solve this problem in different ways, from adding “environments” feature for Polymer’s internal build tool; abusing “behavior modules”; or using “app globals” custom element with complex code to share application-level state. None of these features work well or elegantly (except maybe the environments feature, if it ever gets implemented).

Here is the solution I came up with – with many thanks to Daniel Tse that described part of the implementation in this article – just using the core Polymer elements iron-ajax and iron-meta and without any custom code. Its not the most elegant thing that can be done, but it is relatively simple and works well. Its main down-side is that the application configuration is not embedded in the application during build time but loaded from an external file when the application loads – this may even be a required feature in some scenarios but its not the generally accepted practice.

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1. all iron-ajax examples, as an obvious example, use hard-coded URLs [↩]

This is an open letter to Chris Fisher from Jupiter Broadcasting (and friends) regarding the recent tirade against Google “winning” the court battle against Oracle for the use of the Java APIs.

A short summary for the uninitiated:

After Oracle bought Sun including their Java implementation, they sued Google who implemented (some of) the Java APIs for use in the Android operating system, for copyright infringement in some source code, copyright infringement on the API definitions themselves and a couple of software patents they held about how to implement some Java behavior. Round one: Some source code was ruled infringing, APIs were found non-copyrightable  and patents were found not-infringing. Round two: A federal court (that normally rules on patent issues) held the ruling of copying (for Oracle) and patents (for Google) but ruled APIs copyrightable and Google infringing on that. Third round: a jury found that Google’s use of the Java APIs was fair-use and no damages should be awarded.

After the last jury decision, there was a lot of back and forth on the internet, notably one Ars Technica article (“op-ed”), by an Oracle lawyer claimed that the result boils down to nullifying any and all open source licenses:

if you offer your software on an open and free basis, any use is fair use.

Then we come to Chris Fisher – as the host of his Linux Action Show podcast, he has spoke out against Google many times in the past, but this tirade in the discussion of the Oracle vs. Google action in the most recent Linux Action Show #419, really demonstrates well the extents of his Googlephobia (LAS #419, 0:46:42):

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One type of task that I often find myself implementing as a bash script, is to periodically generate some data and display or operate on it – maybe through a cron job, watch or simply a loop. Sometimes part of the process is an expensive computation (could be network based, IO intensive or simply subject to throttling by another entity). The way to deal with issues like that in modern programming languages is a caching technique known as “memoization” (based on the word “memorandum”) in the results of an expensive call is retained in memory after the first time, and returned for future calls instead of running the expensive calculation. We also need to clear the cache every once in a while, but that’s another issue.

So, how to implement in bash?

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Cloud-init is a Linux technology that allows easy setup and automation of virtual machines. The concept is very simple – the VM infrastructure provides some way of setting some custom data for each virtual machine (many providers call this “user data”), and when the operating system starts the cloud-init service reads that configuration, loads a bunch of modules to handle various parts and let them configure the system. As a user it is very convenient – you write a setup scenario using the variety of tools offered by cloud-init, you can store the scenario in a source control to allow to develop the scenario further, then just launch a bunch of machines with the specified scenario and watch them configure themselves.

The situation is much worse on the MS-Windows side of the fence: want to have an MS-Windows server configured and ready to go? Start a virtual machine, connect to is using RDP and Next, Next, Finish until your fingers are sore. Need to deploy a new version? either retrofit an existing image (again, manually) and risk deployment side effects, or do the whole process again from scratch.

Here’s a script to try to help a bit with the problem – at least on Amazon Web Services: a poor man’s cloud-init-like for MS-Windows server automation.

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