Domain management for Office 365 (Small Business)

A few weeks ago, I wrote about configuring DNS for Exchange Online in Office 365. In that post, I mentioned that Microsoft is only supporting small business customers with domains that are delegated to (i.e. hosted on) Microsoft’s name servers – currently ns1.bdm.microsoftonline.com and ns2.bdm.microsoftonline.com.

I wasn’t entirely comfortable with this (for a start, the Office 365 DNS Manager is best described as “basic”), so I decided to see what happens if I went through the process, but never actually switched over the name server records… as it happens it seems to work quite well (albeit in an unsupported manner).

If you want to retain control of settings, all that’s involved is creating the same records with an external DNS provider.

For reference, on the markwilson.co.uk domain, these would be:

markwilson.co.uk. 3600 IN MX 0 markwilson-co-uk.mail.eo.outlook.com.
autodiscover 3600 IN CNAME autodiscover.outlook.com.
markwilson.co.uk. 3600 IN TXT “v=spf1 include:outlook.com ~all”
SRV _sip _tls 443 1 100 sipdir.online.lync.com. markwilson.co.uk 3600
SRV _sipfederationtls _tcp 5061 1 100 sipfed.online.lync.com. markwilson.co.uk 3600

Of course, if Microsoft changes the server names, you won’t be notified and that might affect your service but the settings seem to be the same as the ones provided to Enterprise customers as part of their domain management process.

Then, go through the normal process to add a domain to Office 365, but just click Next on the Edit Name Server Records page:

Ignore the step that advises changing DNS entries

At the time of writing, Office 365 is still in beta, so things could change (for example, the domain verification process has already switched from using CNAME records to using either TXT or MX records) but it might be worth a try…

[Update 20 June 2011: Microsoft has documented a workaround for domains that do not allow delegation (specifically for .NO and .DK but I see no reason why other domains should not be used in this way)]

Microsoft’s Windows Azure datacentres: some statistics

Last week I blogged about designing a private cloud infrastructure, based on the practices employed by the major cloud service providers.

Today I got a taste of the scale of some of those cloud operations, when Microsoft gave an online presentation on Windows Azure to their International Customer Advisory Board (ICAB) for Server and Cloud (of which I’m a participant).

Remember the shipping contains that I mentioned as units of scale in a modern datacentre? Here are a few stats about Microsoft’s Azure datacentres:

  • Each datacentre runs at around 95°F (or 35°C): that’s pretty warm but, even though there is air conditioning installed, it’s rarely used, as the containers are self-cooling (using a water system).
  • Containers are stacked in units that are two high and then connected to power, water and networks. (Now that’s some appliance!)

Microsoft's Azure appliances

  • Each container unit contains around 2500 servers and a whole datacentre has 360,000 servers.

Inside onr of the containers

  • The containers are normally dark – I described resource decay in my earlier post – that means that it’s rarely necessary to enter the datacentre.
  • In fact, the datacentres are so highly automated, that there are just 12 staff: 9 armed security guards and 3 administrators. (I’m guessing that’s working 3 shifts, so only 3 or 4 on duty at any one time.)
  • Humans are never alone – systems exist to ensure that people can only enter in pairs, and leave in pairs too.
  • So far, Microsoft has spent $2.5bn on its six Azure data centres, with more planned (and that doesn’t include the datacentres for its other operations).

Usage profiles for mobile devices

A few weeks ago, an agency presented some statistics to me about mobile apps.  Unfortunately, although I did ask for permission to use the statistics, I don’t have details of the source but I thought they were interesting to present on this blog, particularly in the light of Forrester CEO George Colony’s keynote comments on the “App Internet” at the Forrester IT Forum last month.

Mobile devices are changing the way we consume and engage digitally:

  • 66% [of mobile device owners] say they can’t live without their phone.
  • 64% [of mobile device owners] say mobiles and the Internet have made our life better.
  • 71% of smartphone owners have downloaded [at least one] app.
  • 28% [of Internet users] connect to the Internet via a mobile [device].
  • 20% of all Christmas online sales in 2010 were via a mobile [device].

What I found particularly interesting were two usage patterns that were presented to me for reading articles on smartphones and on tablets:

iPhone usage spikes

Smartphone users exhibited four spikes at:

  • 6am (early morning/breakfast).
  • 9am (start of work day).
  • 5-6pm (end of work day commute).
  • 8-10pm (couch/prime time, bed time).

Meanwhile, tablet devices are more likely to read at personal prime time – i.e. at the most relaxing time of the day:

iPad usage spikes

I’m not sure that I fit either of these profiles as I tend to use my tablet (my iPad) for my morning/evening commutes, and late at night (in bed) – in between I’m on a laptop, with occasional triaging of email (but not really reading articles) on a smartphone (an iPhone). Nevertheless, it’s interesting to see this marked difference in usage patterns for two classes of mobile device.

Designing a private cloud infrastructure

A couple of months ago, Facebook released a whole load of information about its servers and datacentres in a programme it calls the Open Compute Project. At around about the same time, I was sitting in a presentation at Microsoft, where I was introduced to some of the concepts behind their datacentres.  These are not small operations – Facebook’s platform currently serves around 600 million users and Microsoft’s various cloud properties account for a good chunk of the Internet, with the Windows Azure appliance concept under development for partners including Dell, HP, Fujitsu and eBay.

It’s been a few years since I was involved in any datacentre operations and it’s interesting to hear how times have changed. Whereas I knew about redundant uninterruptible power sources and rack-optimised servers, the model is now about containers of redundant servers and the unit of scale has shifted.  An appliance used to be a 1U (pizza box) server with a dedicated purpose but these days it’s a shipping container full of equipment!

There’s also been a shift from keeping the lights on at all costs, towards efficiency. Hardly surprising, given that the IT industry now accounts for around 3% of the world’s carbon emissions and we need to reduce the environmental impact.  Google’s datacentre design best practices are all concerned with efficiency: measuring power usage effectiveness; measuring managing airflow; running warmer datacentres; using “free” cooling; and optimising power distribution.

So how do Microsoft (and, presumably others like Amazon too) design their datacentres? And how can we learn from them when developing our own private cloud operations?

Some of the fundamental principles include:

  1. Perception of infinite capacity.
  2. Perception of continuous availability.
  3. Drive predictability.
  4. Taking a service provider approach to delivering infrastructure.
  5. Resilience over redundancy mindset.
  6. Minimising human involvement.
  7. Optimising resource usage.
  8. Incentivising the desired resource consumption behaviour.

In addition, the following concepts need to be adopted to support the fundamental principles:

  • Cost transparency.
  • Homogenisation of physical infrastructure (aggressive standardisation).
  • Pooling compute resource.
  • Fabric management.
  • Consumption-based pricing.
  • Virtualised infrastructure.
  • Service classification.
  • Holistic approach to availability.
  • Computer resource decay.
  • Elastic infrastructure.
  • Partitioning of shared services.

In short, provisioning the private cloud is about taking the same architectural patterns that Microsoft, Amazon, et al use for the public cloud and implementing them inside your own data centre(s). Thinking service, not server to develop an internal infrastructure as a service (IaaS) proposition.

I won’t expand on all of the concepts here (many are self-explanitory), but some of the key ones are:

  • Create a fabric with resource pools of compute, storage and network, aggregated into logical building blocks.
  • Introduced predictability by defining units of scale and planning activity based on predictable actions (e.g. certain rates of growth).
  • Design across fault domains – understand what tends to fail first (e.g. the power in a rack) and make sure that services span these fault domains.
  • Plan upgrade domains (think about how to upgrade services and move between versions so service levels can be maintained as new infrastructure is rolled out).
  • Consider resource decay – what happens when things break?  Think about component failure in terms of service delivery and design for that. In the same way that a hard disk has a number of spare sectors that are used when others are marked bad (and eventually too many fail, so the disk is replaced), take a unit of infrastructure and leave faulty components in place (but disabled) until a threshold is crossed, after which the unit is considered faulty and is replaced or refurbished.

A smaller company, with a small datacentre may still think in terms of server components – larger organisations may be dealing with shipping containers.  Regardless of the size of the operation, the key to success is thinking in terms of services, not servers; and designing public cloud principles into private cloud implementations.

Office 365 message filtering (and a horrible little bug that leaves email addresses exposed…)

One of my concerns with my recent switch from Google Apps Mail to Microsoft Office 365 was about spam email. You see, I get none.  Well, when I say I get none, I get plenty but it’s all trapped for me. With no effort on my part. Only a handful of missed spam messages in the last 2 or 3 years and almost as few false positives too.

I’ve had the same email address for about 12 years now (I think), and it’s been used all over the web. Some of my friends are more particular though – and, perhaps understandably, were annoyed when I accidentally emailed around 40 people with e-mail addresses visible in the To: field today. Except that I hadn’t intended to.

I think I’ve found a bug in Office 365’s Outlook Web App (at least, I hope it’s not closed as “by design”, assuming I find out how to file a bug report). If I send to a distribution group, it automatically expands the addresses and displays them to all recipients. That’s bad.

The annoying thing is that, previously, I had been BCCing the recipients. I have a feeling that at least one organisation was rejecting my mail because there was nothing in the To: field (although it didn’t like Google’s propensity to send mail from one domain “on behalf of” another address either), so I thought I’d use a list instead and the recipients would see the list name, rather than the actual email addresses. Thankfully it was only sent to my closest freinds and family (although that’s not really the point).

So, back to spam and Office 365 – does it live up to my previous experience with Google Apps Mail? Actually, yes I think it does. I’ve had to teach it a couple of safe senders and block a couple of others, but it really was just a handful and it’s settled down nicely.

All of Microsoft’s cloud-based e-mail services use Forefront Online Protection for Exchange. Enterprise administrators have some additional functionality (adapting SCL thresholds, etc.) but things seem to be working pretty well on my small business account too. Digging around in the various servers that the mail passes through sees hosts at bigfish.com and frontbridge.com – Frontbridge was an aquisition that has become part of Exchange Hosted Services (and it started out as Bigfish Communications) – so the technology is established, and another Microsoft property (Hotmail) is a pretty good test bed to find and filter the world’s spam.

Should we gamify the workplace?

Gamification is certainly one of this year’s buzzwords and the science of gamification (i.e. the use of game mechanics/dynamics to drive game-like engagement and actions in non-game environments) is a topic of great interest to me at the moment.

But how can we use gamification in the workplace? And should we even try?

Whilst it’s true that there is a moral hazard to avoid, the trick to successful gamification is making sure it doesn’t feel like the target is being played. Let’s take an example that well established in the workplace: flexitime. The motivation is for an employee to accrue enough additional work time to “earn” a day off; ability is controlled by the rules that govern the flexitime scheme; and the trigger is the point where sufficient “credit” is available to take some additional leave!

I have to admit that flexitime is not one of my benefits at Fujitsu but for those businesses that have such as scheme, it has benefits in terms of employee flexibility and morale. And there are other examples where we can re-engineer our business processes and introduce some elements of gamification.

Take, for example, the idea of a results-oriented work environment. What if, instead of being paid a salary, or an hourly rate, employees were given the opportunity to pick and choose their work and remunerated accordingly? Critics may see such an approach as a return to factory processes and piecework. Others may see an opportunity to free themselves from their 9 to 5 (or 8 to 6, or 6 to 8 work routine) and work in a more flexible manner. My background is as a solutions architect. What if projects were to be crowdsourced so that a pool or architects to pick tasks from a list of activities? Different values could be attributed depending on the difficulty or time sensitivity of the task, with all architects having to achieve a minimum number of credits (but the ability to earn more if they so desired). I’m sure there many human resources issues to overcome but I can see this being the “normal” way to work in future.

Problems come when the gamification feels controlling and is associated with “Big Brother”. We have to accept that one size does not fit all – and there is a risk that employees may feel disconnected, or that they are being patronised. Most people are smart and can work out how to “game” the system – so the game mechanics need to be honed to balance motivation and ability, and to trigger employees at the appropriate times.

If we gamify the workplace though, it seems there’s a risk of destroying some of the other elements of successful collaboration. The workplace is far more than just a literal place to work. There are social and environmental aspects to consider too. If we create an internal market of competing architects what’s the difference between that and a group of independant contractors working on a project? At what point do people stop working for a common purpose (the company’s mission) and start working for their own goals? People can’t be our most important asset when we don’t have any people any more!

It may be that gamification is not appropriate for mainstream activities but can be used for those on the periphery – those that are considered extra-curricular. For example, whilst I’d like everyone to want to contribute to our Open Innovation Community, the reality is that people can opt in or out. What if we were able to gamify the innovation process with a system of rewards?

This post doesn’t really provide any answers – it does pose some questions though. How would you feel about the gamification of your work environment? And would you consider there are significant advantages to be gained, or is the risk of disruption just too great?

[This post originally appeared on the Fujitsu UK and Ireland CTO Blog and was written with assistance from Ian Mitchell and Vin Hughes.]

Useful Links: May 2011

A list of items I’ve come across recently that I found potentially useful, interesting, or just plain funny:

The science of gamification (@mich8elwu at #digitalsurrey)

Gamification.

Gam-if-ic-a-tion.

Based on the number of analysts and “people who work in digital” I’ve seen commenting on the topics this year, “gamification” has to be the buzzword of 2011. So when I saw that Digital Surrey (#digitalsurrey) were running an event on “The Science of Gamification”, I was very interested to make the journey down to Farnham and see what it’s all about.

The speaker was Michael Wu (@mich8elwu) and I was pleased to see that the emphasis was very much on science, rather than the “marketing fluff” that is threatening to hijack the term.  Michael’s slides are embedded below but I’ll elaborate on some of his points in this post.

  • Starting off with the terminology, Michael talked about how people love to play games and hate to work – but by taking gameplay elements and applying them to work, education, or exercise, we can make them more rewarding.
  • Game mechanics are about a system of principles/mechanisms/rules that govern a system of reward with a predictable outcome.
  • The trouble is that people adapt, and game mechanics become less effective – so we look to game dynamics – the temporal evolution and patterns of both the game and the players that make a gamified activity more enjoyable.
  • These game dynamics are created by joining game mechanics (combining ands cascading).
  • Game theory is a branch of mathematics and is nothing to do with gamification!
  • The Fogg Behaviour Modellooks at those factors that influence human behaviour:
    • Motivation – what we want to do.
    • Ability – what we can do.
    • Trigger – what we’re told to do.
  • When all three of these converge, we have action – they key is to increase the motivation and ability, then trigger at an appropriate point. There are many trajectories to reach the trigger (some have motivation but need to develop ability – more often we have some ability but need to develop motivation – but there is always an activation threshold over which we must be driven before the trigger takes effect).
  • Abraham Maslow’s Hierarchy of Needs is an often-quoted piece of research and Michael Wu draws comparisons between Maslow’s deficiency needs (physical, safety, social/belonging and esteem) and game mechanics/dynamics. At the top of the hierarchy is self-actualisation, with many meta-motivators for people to act.
  • Dan Pink’s Drive discusses intrinsic motivators of autonomy, mastery and purpose leading to better performance and personal satisfaction.  The RSA video featuring Dan Pink talking about what motivates us wasn’t used in Michael Wu’s talk, but it’s worthy of inclusion here anyway:

  • In their research, John Watson and BF Skinner looked at how humans learn and are conditioned.  A point system can act as a motivator but the points themselves are not inherently rewarding – their proper use (a reward schedule) is critical.
  • Reward schedules include fixed interval; fixed interval and fixed ratio; variable interval; and variable ratio – each can be applied differently for different types of behaviour (i.e. driving activity towards a deadline; training; re-enforcing established behaviours; and maintaining behaviour).
  • Mihaly Csikszentmihalyi is famous for his theories on flow: an optimal state of intrinsic motivation where one forgets about their physical feelings (e.g. hunger), the passage of time, and ego; balancing skills with the complexity of a challenge.
  • People love control, hate boredom, are aroused by new challenges but get anxious if a task is too difficult (or too easy) and work is necessary to balance challenges with skills to achieve a state of flow. In reality, this is a tricky balance.
  • Having looked at motivation, Michael Wu spoke of the two perspectives of ability: the user perspective of ability (reality) and the task perspective of simplicity (perceptual).
  • To push a “user” beyond their activation threshold there is a hard way (increase ability by motivating them to train and practice) or an easy way (increase the task’s perceived simplicity or the user’s perceived ability).
  • Simplicity relies on resources and simple tasks cannot use resources that we don’t have.  Simplicity is a measure of access to three categories of resource at the time when a task is to be performed: effort (physical or mental); scarce resources (time, money, authority/permission, attention) and adaptability (capacity to break norms such as personal routines, social, behavioural or cultural norms).
  • Simplicity is dependant upon the access that individuals have to resources as well as time and context – i.e. resources can become inaccessible (e.g. if someone is busy doing something else). Resources are traded off to achieve simplicity (motivation and ability can also be traded).
  • A task is perceived to be simple if it can be completed it with fewer resources than we expect (i.e. we expect it to be harder) and some game mechanics are designed to simplify tasks.
  • Triggers are prompts that tell a user to carry out the target behaviour right now. The user must be aware of the trigger and understand what it means. Triggers are necessary because we may not be aware of our abilities, may be hesitant (questioning motivation) or may be distracted (engaged in another activity).
  • Different types of triggers may be used depending on behaviour. For example, a spark trigger is built in to the motivational mechanism; a facilitator highlights simplicity or progress; and signals are used as reminders when there is sufficient motivation and no requirement to simplify as task.
  • Triggers are all about timing, and Richard Bartle‘s personality types show which are the most effective triggers. Killers are highly competitive and need to be challenged; socialisers are triggered by seeing something that their friends are doing; achievers may be sparked by a status increase; and explorers are triggered by calls on their unique skills, without any time pressure. Examples of poorly timed triggers include pop-up adverts and spam email.
  • So gamification is about design to drive action: providing feedback (positive, or less effectively, negative); increasing true or perceived ability; and placing triggers in the behavioural trajectory of motivated players where they feel able to react.
  • If the desired behaviour is not performed, we need to check: are they triggered? Do they have the ability (is the action simple enough)? Are they motivated?
  • There is a moral hazard to avoid though – what happens if points (rather than desired behaviour) become the motivator and then the points/perks are withdrawn?  A case study of this is Gap’s attempt to gamify store check-ins on Facebook Places with a free jeans giveaway. Once the reward had gone, people stopped checking in.
  • More effective was a Fun Theory experiment to reduce road speeds by associating it with a lottery (in conjunction with Volkswagen). People driving below the speed limit were photographed and entered into a lottery to win money from those who were caught speeding (and fined).

  • Michael Wu warns that gamification shouldn’t be taken too literally though: in another example, a company tried incentivising sales executives to record leads with an iPad/iPhone golf game. They thought it would be fun, and therefore motivational but it actually reduced the ability to perform (playing a game to record a lead) and there was no true convergence of the three factors to influence behaviour.
  • In summary:
    • Gamification is about driving players above the activation threshold by motivating them (with positive feedback), increasing their ability (or perceived ability) and then applying the roper trigger at the right time.
    • The temporal convergence of motivation, ability and trigger is why gamification is able to manipulate human behaviour.
    • There are moral hazards to avoid (good games must adapt and evolve with players to bring them into a state of flow).

I really enjoyed my evening at Digital Surrey – I met some great people and Michael Wu’s talk was fascinating. And then, just to prove that this really is a hot topic, The Fantastic Tavern (#tftlondon) announced today that their next meeting will also be taking a look at gamification

Further reading/information

[Update 23:12 – added further links in the text]

 

Run Fatboy Run!

BUPA London 10,000
Was it just a co-incidence that the Simon Pegg film, “Run Fatboy Run” was shown on British TV this weekend? I think not! (great film by the way).

For those who’ve missed my last “Fit At 40” update – yesterday was the Bupa London 10,000 – and I lined up with several thousand other competitors (including my friend Eileen Brown) to run the course from St James’ Park to the City and back.  This was my first 10K and I’d been training with 5 mile (8km) runs at around 01:06:00, so I was hoping to come in at around 01:20:00 but, to be honest, a finish was what I was really after!

Not only was this my first 10K, but it was my first big race too – and, with the race starting in nine groups (with me in the ninth), the elite runners had completed the race before I was over the start line!

The first kilometre flashed by – I set off way too fast but I was in clear space towards the front of my group and wanted to stay out front so my supporters at the end of Horse Guards’ Parade could grab a decent picture. After that, I tried to settle down into a comfortable pace but my pre-race efforts to make sure I was sufficiently hydrated set me back a bit (and I wasn’t going to “do a Paula” [Radcliffe]).  I couldn’t see the toilets that were supposed to be at 3km so I kept going until I saw a McDonalds at just after 4km – and rushing off the course, down the stairs into the basement and back out again must have cost at least 3 minutes (I wasn’t the only one to do this either!).  Only then could I settle into my planned pace of 12 minutes run, 2 walk at around 12 minutes per mile (I’m not fast!) but the point is I did it!

I have to say that the whole event was incredibly well organised (by the same people who organise the London Marathon), the weather was kind to us, and even though the water station at 7km had run dry by the time I passed, some wonderful people were handing out cups of water just before, at around at about 6.5km (thank you guys).  Kudos too, to the guys who were clearing up the thousands of plastic bottles etc. on the course as well as to the marshalls that lined the whole route.

So, how did I do? Well, my (unoffocial) stats (from RunKeeper) show me at just over 1 hour 30 minutes and the official time was 01:30:04

Even though I’m a bit disappointed with my time, I’m absolutely stoked with the achievement. Not that long ago, I couldn’t run to the end of the street. Now it’s time to push on and lose some more weight, then run another 10K later this year (hopefully at closer to 01:20:00).

The challenge continues…

Rating images as part of a digital workflow

Earlier this week, I was at my local camera club meeting and fellow geek Haydn Langley was presenting on digital asset management (together with a few technical tips and tricks for photo editing).

One particular “lightbulb moment” was when Haydn put up an example of rating images (e.g. in Adobe Bridge or Lightroom). I’ve never been able to get my head around this because, over time, my idea of what makes a good image changes (as I, hopefully, get better at it). Now I think the key is to adopt a system that works and stick with it – any rating will be subjective but at least you’ll be consistent.

Haydn suggested rating images using a system similar to this (based on a system proposed by Mark Sabatella):

  • 1 star: images that are of no real quality (e.g. out of focus) and won’t be missed if deleted.
  • 2 stars: acceptable image but not one of the best. Nothing special, but could be kept as a record shot.
  • 3 stars: one of the better images of a subject. A “keeper”.
  • 4 stars: one of the best images: worth sharing with others (e.g. on Flickr), or printing large.
  • 5 stars: comparable to pros that we admire. Worthy of competition entry.

I might adapt this slightly, but it’s a good starting point.

He also suggested using colours to indicate where a particular image has reached in the workflow, for example:

  • Red: stage 1 – ingested (i.e. imported, renamed, etc.)
  • Yellow: stage 2 – global metadata assigned (copyright, etc.)
  • Green: stage 3 – survived initial cull
  • Blue: stage 4 – post-processed, survived final cull
  • Purple: stage 5- image-specific metadata assigned (keyword tags for subject/content/style, etc.)

As I’m approaching 10000 shots since I bought my D700 2 years ago, I’ve got some work to do to “sort everything out” but this system should help a lot.  I guess I should also think about renaming images on import rather than storing them as _DSCnnnn.NEF!