Jazoon 2013 Overview

25. October, 2013

Here is the list of blog posts about all the talks that I attended at Jazoon 2013:

Day 1

Day 2

Jazoon 2013 – Successful Collaboration in Agile Software Teams

25. October, 2013

Jazoon 2013 badgeIn his talk “Successful Collaboration in Agile Software Teams,” Martin Kropp lists the key factors for collaboration in agile software teams. (slides on slideshare)

For me the most important points were (slide 6):

“Agile collaboration is …

  • Face-to-face
  • Regular
  • Often
  • Informal
  • Openly
  • Under equals
  • Focused
  • Transparent
  • Respectful
  • Flexible

No is no “Agile by the Book.”

After that, he lists the usual pain points:

  • Hidden leaders
  • People sending assignments by email
  • Meetings without purpose and goals
  • Missing tools like chat, video conferencing
  • Physical vs. the digital whiteboard (slide 18)

Modern technologies like large touchscreens will make things better (slide 23).

A word about open-plan offices: They are the best tool to reduce productivity. See these articles to learn why:

Jazoon 2013 – The Economies of Scaling Software

25. October, 2013

Jazoon 2013 badgeIf you’re small, scalability is not an issue. If you’re big, you can plan for it. But what if you wake up one morning and you suddenly find you’ve become the next Google?

In his talk “The Economies of Scaling Software“, Abdelmonaim Remani talks about what scaling means, how you can plan for it (even if you don’t expect it to happen) and all the nasty details that stand between you and success (slides on slideshare).

Today, the ubiquity of the Internet has blurred the lines between consumers and enterprises. They start to ask the same questions which eventually all boil down to: “How can I find what I’m looking for in a universe of haystacks?”

One day, many of us will find themselves with the need to scale because the performance of the old solution has become unbearable and all low-hanging fruit (faster CPU, more RAM) have been picked.

To solve this, you can look at the CPU (slide 16-35) or you can start to build clusters (36-45).

Or your I/O might be the bottleneck (slides 46-60). You can solve this by looking at NoSQL databases and caching.

Is the network the problem? (slides 61-75) Start with asynchronous processing, batch jobs, content delivery networks (CDN), DNS sharding or use a different protocol to connect the various parts of your system.

But how do you know what part is the bottleneck? The answer here is monitoring. (slide 77)

Note that scaling often helps with disaster recovery, you still have to plan for it – if all nodes of your cluster are in the same room, it’s still a single point of failure (slide 79)

Software isn’t everything. Don’t forget your team (slide 82)

Jazoon 2013 – Open Safety For Drones

25. October, 2013

Jazoon 2013 badgeDrones – fully or partially autonomous aircraft – are the second most wide-spread form of private-owned robots today only challenged by room-cleaners. The current estimation is that there are 500’000 drones currently in use. Parrot AR alone sold about 250’000 units. In his talk “Open Safety For Drones,” Lorenz Meier asks important questions about safety, regulation and how this area will develop in the future.

When it comes to safety, then there are two areas: Safety when developing drones and safety when using them. People have started to demonstrate the usual stupidity by flying drones in crowded areas without regard to safety. Lorenz showed a video where an inexperienced controller flew a drone in Manhattan until it crashed into skyscraper and dropped into the streets below. In another example, someone flew a drone through a campus. I say “through” because he went below footbridges that connect the first floor of buildings, eventually passing a bus on the way. The “pilot” also failed to catch the drone after the stunt, crashing it into a hedge.

It will be interesting to see how legal bodies like the FAA respond to things like this.

Despite this, autonomous drones are already useful. A nice example is the new 3D model of the Matterhorn.

A more related issue is the other one: Building safe aircraft. Bugs in a drone can really ruin your day (or life). How can we make sure that hundreds of thousands of lines of code have an acceptable number of bugs?

The issues here are many:

  • If you want to fly an autonomous aircraft, you need to license it.
  • Regulation for drones are non-existing or immature. They might try to handle you like a normal aircraft manufacturer (think Boeing or Airbus). Can you even afford to apply for such a license?
  • You’re using an image recognition software. It uses a math library. In that library, a single line of code has changed. What is the impact on the safety of your drone? How do we bring safety and the need for faster iterations together?
  • Regulators might insist that you license the whole thing again.
  • To get real engineers on your project for a new drone, your API must be really simple. As every seasoned developer knows, nothing is harder than “simple.”

A word on the safety of military drones: Not a single one of them is allowed in civilian airspace. But it’s probably very expensive. Germany spent €562 million to certify the EuroHawk drone. The project was cancelled and the defense minister “referred to the project as being ‘a horror without end'”.

So how can we make a DIY drone ever safe?

There are some approaches:

  1. Involve as many people as possible in a project. Everyone will find something that can be improved.
  2. Allow commercial use of your project. Companies have completely different views on safety than hobbyists.
  3. Collect logs of your flights and share them. Share your project on github and make sure you include the hash of the changeset that was used to run the drone.
    Over time, you can use statistical data to locate even “once in a million years” bugs.

But there are good news, too. With a plane, you have X people on the aircraft and 0 on the ground (most crash in empty areas). With a drone, you have 0 people on the aircraft and X on the ground. But using the laws of physics, it’s pretty simple to estimate the maximum radius that a drone can still travel if it’s “brain” shuts down right now. That means we can test them pretty safely in a virtual cage. Also, since all the components are open, we can run extensive simulations before bringing the thing into the wild.

But the OSS approach also has drawbacks. With OSS, a unit test is easy to write, the test case is known and if something goes horribly wrong, we might experience data loss.

With unmanned systems, the worst case is loss of life. And where do you get your test cases from? How do you plan to test for a broken coil in an actuator? An overheated battery which results in unstable power? Wind gusts? Collisions with birds? Interference with other electrical systems?

Maybe it’s time to open a new field:

Open Safety – Build a safety track record in confined test areas in an open, community-driven process, and only let statistically proven safe systems out of the sandbox. SHARE validation results on the library and version level across systems.

Open Safety Manifesto

  1. Dropping is Free – Ground impact must only damage vehicle
  2. Anytime Shutdown – A separate shutdown unit is present to enforce a drop
  3. Built to Drop – Battery protected against impact, parachutes, etc.
  4. Every Flight is Logged
  5. Every Log is Reviewed – Can be done on Droneshare

State of the Art

Sites like Droneshare have collected so many flight hours for some drones to satisfy normal regulation rules.

Keep in mind that certification alone doesn’t make things safer, they just help to catch the most common errors. Simulations and test protocols improve the situation further. Lastly, lots of people mean that every part is tested in thousands of ways. Software developers know how quickly someone else finds problems with their work (one reason why pairing is so unpopular).

A big problem is YouTube since it teases out the “I more stupid” behavior in humans.

Military (Ab)Use

Another issue is the (ab-)use of this work in military drones used to kill. The scene is aware of this but they currently feel that the good (like cheap access to aerial photography, autonomous mesh networks built by drones in disaster areas) to outweigh the risk. A more visible discussion about OSS and hardware in military projects would be welcome. Some projects forbid military use (Gnutella). It’s worth noting that the US Navy has started to buy Linux based drones. Personally, I find things like the Samsung SGR-A1 military robot sentry (with 5.56 mm robotic machine gun and a grenade launcher) disturbing. Especially when it’s being advertised to be able to “identify and shoot a target automatically from over two miles (3.2 km) away.

Jazoon 2013 – User Storytelling: The Lost Art of User Stories

24. October, 2013

Jazoon 2013 badgeIn her talk “User Storytelling: The Lost Art of User Stories“, Ulrika Park (blog, slides on slideshare) made a case to become aware of the spreading practice of “snapshot user stories.” As an example compare “give warrant to use the bonus” (slide 14)  to slide 16:

Elisabeth sees in the MyStore newsletter that she this month has got 12€ in bonus and that she has a total of 16,7€ in bonus on her club card.
E’s husband Claes go to the store. He has a club card too. “You can probably pay with your card” says E.

Claes shops. When he will pays, no bonus is withdrawn from the sum at the cashier.
So he pays the whole sum and gets home. “Strange why can’t I pay with the bonus, how does this work”

E already has a registered user on mystore.se Sometimes she logs in to see her credit card balance.

E logs in and see the saldo “16,7€”. She clicks the balance and enters “events page”

There she sees that she’s bonus owner and that her co-bonuxcollector is Claes.

She gets information that she needs to sign warrant for him and choose the option to print a form.

She choose to print the form, checks Claes, signs the form and goes to the mailbox the day after.

2 weeks later she gets a letter from MyStore that confirms the warrant is verified. A week later Claes goes shopping. This time, the bonus is withdrawn from the total buy.

I think even without the highlighted parts, you can quickly see that the whole story is much richer than the “more efficient snapshots.” Moreover, it helped to expose some critical problems that no one noticed before:

  • Hidden expectations (user must already be registered)
  • This process takes four weeks! Do we really want that?
  • It helps more people. QA will be able to derive test cases from this. Developers will know much better what is expected from them. BAs will know which questions to ask.
  • It’s pretty easy to follow it, even if you’re not a software developer. Remember that these stories were meant as a means to communicate better with customer and managers?

A good story has these properties:

  • A hero
  • A platform
  • An enemy or challenge
  • Emotions (“how does this work?”)
  • Allies (cashier, web site)
  • A mission to accomplish

Everything is held together by a logical sequence of events.

Related articles:

Jazoon 2013 – Big Data beyond Hadoop – How to integrate ALL your Data

24. October, 2013

Jazoon 2013 badgeBig Data is being used everywhere. Kai Wähner mentioned a couple of examples in his talk “Big Data beyond Hadoop – How to integrate ALL your Data” (slides on slideshare):

Anyone else getting worried by these “success stories”? How do you feel as a mobile customer that your mobile company tries to prevent you from leaving? How about using Big Data to notice bad customer service and prevent making customers unhappy? How do Macy’s competitors feel about this “monitoring”?

Anyway …

One great point was “Silence the HiPPOs” (highest-paid person’s opinion). With the ability “to interpret unimaginable large data stream, the gut feeling is no longer justified!”

Why Big Data? 3 V’s: Volume, Velocity, Variety. But don’t forget the fourth: Value (slide 8)

Before you can start analysis, you need to get the data from somewhere. That usually means integration of a foreign system (reading the data), manipulation of the data (like string to int or date conversion, etc.) and filtering (duplicates, importance, …). See slide 9.

Beware that Big Data is no silver bullet. If you have a gigantic amount of data with poor quality, that will just give you huge problems.

When planning for a Big Data project, begin with a business opportunity (slide 22). Chose the right data (don’t just import everything because you might need it), combine different sources and use easy tooling (slide 26).

Be wary of ETL tools. The network will quickly become your bottleneck.

For the actual implementation, he suggested to look at Apache Camel (slide 34) as a pure integration framework and the talend Open Studio (slide 56) as an example of an integration suite.

Jazoon 2013 – True Git: The Great Migration

24. October, 2013

Jazoon 2013 badgeStefan Saasen told the tale how Atlassian migrated from SVN to Git in his talk “True Git: The Great Migration.” (slides on slideshare)

Atlassian has resources on their website if you want to know more about Git and how to implement your own workflow using it.

Key points from the talk:

  • Branching and merging are first class concepts in Git (unlike Subversion, where they were added as an afterthought)
  • Especially the merging support in Git is much, much better
  • You can use clever tools like bisect to zoom in on bugs
  • History rewriting allows to clean up mistakes
  • Adoption for Git is on the rise. In 2015, most companies and projects will have migrated to Git or another DVCS
  • Use a centralized repo for your enterprise – all the processes and tools will be much easier/happier
  • Make sure you have defined a clear workflow and your developers know about it


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