Seven technology trends to watch 2017-2020

Just over a week ago, risual held its bi-annual summit at the risual HQ in Stafford – the whole company back in the office for a day of learning with a new format: a mini-conference called risual:NXT.

I was given the task of running the technical track – with 6 speakers presenting on a variety of topics covering all of our technical practices: Cloud Infrastructure; Dynamics; Data Platform; Unified Intelligent Communications and Messaging; Business Productivity; and DevOps – but I was also privileged to be asked to present a keynote session on technology trends. Unfortunately, my 35-40 minutes of content had to be squeezed into 22 minutes… so this blog post summarises some of the points I wanted to get across but really didn’t have the time.

1. The cloud was the future once

For all but a very small number of organisations, not using the cloud means falling behind. Customers may argue that they can’t use cloud service because of regulatory or other reasons but that’s rarely the case – even the UK Police have recently been given the green light (the blue light?) to store information in Microsoft’s UK data centres.

Don’t get me wrong – hybrid cloud is more than tactical. It will remain part of the landscape for a while to come… that’s why Microsoft now has Azure Stack to provide a means for customers to run a true private cloud that looks and works like Azure in their own datacentres.

Thankfully, there are fewer and fewer CIOs who don’t see the cloud forming part of their landscape – even if it’s just commodity services like email in Office 365. But we need to think beyond lifting and shifting virtual machines to IaaS and running email in Office 365.

Organisations need to transform their cloud operations because that’s where the benefits are – embrace the productivity tools in Office 365 (no longer just cloud versions of Exchange/Lync/SharePoint but a full collaboration stack) and look to build new solutions around advanced workloads in Azure. Microsoft is way ahead in the PaaS space – machine learning (ML), advanced analytics, the Internet of Things (IoT) – there are so many scenarios for exploiting cloud services that simply wouldn’t be possible on-premises without massive investment.

And for those who still think they can compete with the scale that Microsoft (Amazon and Google) operate at, this video might provide some food for thought…

(and for a similar video from a security perspective…)

2. Data: the fuel of the future

I hate referring to data as “the new oil”. Oil is a finite resource. Data is anything but finite! It is a fuel though…

Data is what provides an economic advantage – there are businesses without data and those with. Data is the business currency of the future. Think about it: Facebook and Google are entirely based on data that’s freely given up by users (remember, if you’re not paying for a service – you are the service). Amazon wouldn’t be where it is without data.

So, thinking about what we do with that data: the 1st wave of the Internet was about connecting computers, 2nd was about people, the 3rd is devices.

Despite what you might read, IoT is not about connected kettles/fridges. It’s not even really about home automation with smart lightbulbs, thermostats and door locks. It’s about gathering information from billions of sensors out there. Then, we take that data and use it to make intelligent decisions and apply them in the real world. Artificial intelligence and machine learning feed on data – they are ying and yang to each other. We use data to train algorithms, then we use the algorithms to process more data.

The Microsoft Data Platform is about analytics and data driving a new wave of insights and opening up possibilities for new ways of working.

James Watt’s 18th Century steam engine led to an industrial revolution. The intelligent cloud is today’s version – moving us to the intelligence revolution.

3 Blockchain

Bitcoin is just one implementation of something known as the Blockchain. In this case as a digital currency.

But Blockchain is not just for monetary transactions – it’s more than that. It can be used for anything transactional. Blockchain is about a distributed ledger. Effectively, it allows parties to trust one another without knowing each other. The ledger is a record of every transaction, signed and tamper-proof.

The magic about Blockchain is that as the chain gets longer so does the entropy and the encryption level – effectively, the more the chain is used, the more secure it gets. That means infinite integrity.

(Read more in Jamie Skella’s “A blockchain explaination your parents could understand”.)

Blockchain is seen as strategic by Microsoft and by the UK government and it’s early days but we will see where people want to talk about integrity and data resilience with integrity. Databases – anything transactional – can be signed with blockchain.

A group of livestock farmers in Arkansas is using blockchain technology so customers can tell where their dinner comes from. They are applying blockchain technology to trace products from ‘farm to fork’ aiming to provide consumers with information about the origin and quality of the meat they buy.

Blockchain is finding new applications in the enterprise and Microsoft has announced the CoCo Framework to improve performance, confidentiality and governance characteristics of enterprise blockchain networks (read more in Simon Bisson’s article for InfoWorld). There’s also Blockchain as a service (in Azure) – and you can find more about Microsoft’s plans by reading up on “Project Bletchley”.

(BTW, Bletchley is a town in Buckinghamshire that’s now absorbed into Milton Keynes. Bletchley Park was the primary location of the UK Government’s wartime code-cracking efforts that are said to have shortened WW2 by around 2 years. Not a bad name for a cryptographic technology, hey?)

4 Into the third dimension

So we’ve had the ability to “print” in 3 dimensions for a while but now 3D is going further.Now we’re taking physical worlds into the virtual world and augmenting with information.

Microsoft doesn’t like the term augmented reality (because it’s being used for silly faces on photos) and they have coined the term mixed reality to describe taking untethered computing devices and creating a seamless overlap between physical and virtual worlds.

To make use of this we need to be able to scan and render 3D images, then move them into a virtual world. 3D is built into next Windows 10 release (the Fall Creators update, due on 17 October 2017). This will bring Paint 3D, a 3D Gallery, View 3D for our phones – so we can scan any object and import to a virtual world. With the adoption rates of new Windows 10 releases then that puts 3D on a market of millions of PCs.

This Christmas will see lots of consumer headsets in the market. Mixed reality will really take off after that. Microsoft is way ahead in the plumbing – all whilst we didn’t notice. They held their Hololens product back to be big in business (so that it wasn’t a solution without a problem). Now it can be applied to field worker scenarios, visualising things before they are built.

To give an example, recently, I had a builder quote for a loft extension at home. He described how the stairs will work and sketched a room layout – but what if I could have visualised it in a headset? Then imagine picking the paint, sofas, furniture, wallpaper, etc.

The video below shows how Ford and Microsoft have worked together to use mixed reality to shorten and improve product development:

5 The new dawn of artificial intelligence

All of the legends of AI are set by sci-fi (Metropolis, 2001 AD, Terminator). But AI is not about killing us all! Humans vs. machines? Deep Blue beating people at Chess, Jeopardy, then Google taking on Go. Heading into the economy and displacing jobs. Automation of business process/economic activity. Mass unemployment?

Let’s take a more optimistic view! It’s not about sentient/thinking machines or giving human rights to machines. That stuff is interesting but we don’t know where consciousness comes from!

AI is a toolbox of high-value tools and techniques. We can apply these to problems and appreciate the fundamental shift from programming machines to machines that learn.

Ai is not about programming logical steps – we can’t do that when we’re recognising images, speech, etc. Instead, our inspiration is biology, neural networks, etc. – using maths to train complex layers of neural networks led to deep learning.

Image recognition was “magic” a few years ago but now it’s part of everyday life. Nvidia’s shares are growing massively due to GPU requirements for deep learning and autonomous vehicles. And Microsoft is democratising AI (in its own applications – with an intelligent cloud, intelligent agents and bots).

NVIDIA Corporation stock price growth fuelled by demand for GPUs

So, about those bots…

A bot is a web app and a conversational user interface. We use them because natural language processing (NLP) and AI are here today. And because messaging apps rule the world. With bots, we can use Human language as a new user interface; bots are the new apps – our digital assistants.

We can employ bots in several scenarios today – including customer service and productivity – and this video is just one example, with Microsoft Cortana built into a consumer product:

The device is similar to Amazon’s popular Echo smart speaker and a skills kit is used to teach Cortana about an app; Ask “skillname to do something”. The beauty of Cortana is that it’s cross-platform so the skill can show up wherever Cortana does. More recently, Amazon and Microsoft have announced Cortana-Alexa integration (meanwhile Siri continues to frustrate…)

AI is about augmentation, not replacement. It’s true that bots may replace humans for many jobs – but new jobs will emerge. And it’s already here. It’s mainstream. We use recommendations for playlists, music, etc. We’re recognising people, emotions, etc. in images. We already use AI every day…

6 From silicon to cells

Every cell has a “programme” – DNA. And researchers have found that they can write code in DNA and control proteins/chemical processes. They can compile code to DNA and execute, creating molecular circuits. Literally programming biology.

This is absolutely amazing. Back when I was an MVP, I got the chance to see Microsoft Research talk about this in Cambridge. It blew my mind. That was in 2010. Now it’s getting closer to reality and Microsoft and the University of Washington have successfully used DNA for storage:

The benefits of DNA are that it’s very dense and it lasts for thousands of years so can always be read. And we’re just storing 0s and 1s – that’s much simpler than what DNA stores in nature.

7 Quantum computing

With massive data storage… the next step is faster computing – that’s where Quantum computing comes in.

I’m a geek and this one is tough to understand… so here’s another video:

Quantum computing is starting to gain momentum. Dominated by maths (quantum mechanics), it requires thinking in equations, not translating into physical things in your head. It has concepts like superposition (multiple states at the same time) and entanglement. Instead of gates being turned on/off it’s about controlling particles with nanotechnology.

A classical 2 bit on-off takes 2 clock cycles. One quantum bit (a Qubit) has multiple states at the same time. It can be used to solve difficult problems (the RSA 2048 challenge problem would take a billion years on a supercomputer but just 100 seconds on a 250-bit quantum computer). This can be applied to encryption and security, health and pharma, energy, biotech, environment, materials and engineering, AI and ML.

There’s a race for quantum computing hardware taking place and China sees this as a massively strategic direction. Meanwhile, the UK is already an academic centre of excellence – now looking to bring quantum computing to market. We’ll have usable devices in 2-3 years (where “usable” means that they won’t be cracking encryption, but will have initial applications in chemistry and biology).

Microsoft Research is leading a consortium called Station Q and, later this year, Microsoft will release a new quantum computing programming language, along with a quantum computing simulator. With these, developers will be able to both develop and debug quantum programs implementing quantum algorithms.

Predicting the future?

Amazon, Google and Microsoft each invest over $12bn p.a. on R&D. As demonstrated in the video above, their datacentres are not something that many organisations can afford to build but they will drive down the cost of computing. That drives down the cost for the rest of us to rent cloud services, which means more data, more AI – and the cycle continues.

I’ve shared 7 “technology bets” (and there are others, like the use of Graphene) that I haven’t covered – my list is very much influenced by my work with Microsoft technologies and services. We can’t always predict the future but all of these are real… the only bet is how big they are. Some are mainstream, some are up and coming – and some will literally change the world.

Credit: Thanks to Rob Fraser at Microsoft for the initial inspiration – and to Alun Rogers (@AlunRogers) for helping place some of these themes into context.

Adopting cloud services means being ready for constant change

There’s a news story today about how Microsoft may be repositioning some (or all) of Skype for Business as Microsoft Teams (the collaborative group-based chat service built on various Office 365 services but Skype for Business in particular).

The details of that story are kind of irrelevant to this post; it’s the reaction I got on Twitter that I felt the need to comment on (when I hit 5 tweeted replies I thought a blog post might be more appropriate).

Change is part of consuming cloud services. There’s a service agreement and a subscription/licensing agreement – customers consume the service as the provider defines it. The service provider will generally give notice of change but you normally have to accept it (or leave). There is no option to stay on legacy versions of software for months or years at a time because you’re not ready to update your ways of working or other connected systems.

That is a big shift and many IT departments have not adjusted their thinking to adopt this new way of working.

I’ve seen many organisations moving to cloud services (mostly Office 365 and Azure) and stick with their current approach. They do things like try to map drive letters to OneDrive because that’s what users are used to, instead of showing them new (and often better) ways of working. They try to use old versions of Office with the latest services and wonder why the user experience is degraded. They think about the on-premises workloads (Exchange, Lync/Skype for Business, SharePoint) instead of the potential provided by the whole productivity platform that they have bought licences to use. They try to turn parts of the service off or hide them from users.

My former colleague Steve Harwood (@SteeveeH) did some work with one of risual’s customers to define a governance structure for Office 365. It’s great work – and maybe I’ll blog about it separately – but the point is that organisations need to think differently for the cloud.

Buying services from Microsoft, Amazon, Google, Salesforce, et al is not like buying them from the managed services provider that does its best to maintain a steady state and avoid change at all costs (or often at great cost!). Moving to the cloud means constant change. You may not have servers to keep up to date once your apps are sold on an “evergreen” subscription basis but you will need to keep client software up to date – not just traditional installed apps but mobile apps and browsers too. And when the service gains a new feature, it’s there for adoption. You may have the ability to hide it but that’s just a sticking plaster solution.

Often the cry is “but we need to train the users”. Do you really? Many of today’s business end users have grown up with technology. They are familiar with using services at home far more advanced than those provided by many workplaces. Intuitive user interfaces can go a long way and there’s no need to provide formal training for many IT changes. Instead, keep abreast of the advertised changes from your service provider (for example the Message Center in Office 365) and decide what the impact is of each new feature. Very few will need a full training package! Some well-written communications, combined with self-help forums and updated FAQs at the Service Desk will often be enough but there’s also the opportunity to offer access to Massive Open Online Courses (MOOCs) where training needs are more extensive.

There are, of course, examples of where service providers have rolled out new features with inadequate testing, or with too little notice but these are edge cases and generally there’s time to react. The problem comes when organisations stick their proverbial heads in the sand and try to ignore the inevitable change.

Serverless and the death of DevOps

A couple of weeks back, I took a trip to London after work to attend the latest CloudCamp meet-up. It’s been a while since I last went to CloudCamp but I was intrigued by the title of the event: “Serverless and the death of DevOps?”. The death of DevOps? Surely not. Most organisations I’m working with are only just getting their heads around what DevOps is. Some are still confusing a cultural change with some tools (hey, we’ll adopt some new tools and rebrand our AppDev function as DevOps). If anything, DevOps is at the top of the hype curve; it can’t possibly be dead!

Well, 5 minutes into the event and, after Simon Wardley (@SWardley)’s introduction, I could see where he was coming from. Mix the following up with some “Wardley Mapping” and you can see that what’s being discussed is not really the death of DevOps (as a concept where development and operations teams work in a more integrated fashion) but it may well be a new cloud computing paradigm, in the form of “serverless” computing (AWS Lambda, Azure Functions, etc.):

  • Back in the beginning of computing, systems were hard-wired (e.g. Colossus).
  • Then, they evolved and we had custom-built computing (e.g. Leo) with the concept of applications and an operating system.
  • This evolved and new products (like the IBM 650) were born with novel architectural practices, based around the concept of compute as a product.
  • These systems had a high mean time to recover (MTTR) so the architecture of the day was designed around N+1, DR tests, scaling up.
  • Evolution continued and novel architectural practices became emerging, then good. Computing became more resilient.
  • Next came frameworks. We had applications and an emerging coding practice based around these frameworks, running on an operating system using good architectural practice, all built around the concept of compute as a product (a server).
  • All was happy.
  • Then along came the cloud. Compute was no longer a product but a utility. It brought new benefits of efficiency, pooling resources, agility. Computing had new sources of worth.
  • And organisations said “make my legacy cloudy” [actually, this is as far as many have got to…].
  • Some people asked “but shouldn’t architecture evolve too?” And, after the initial cries of “burn him, heretic”, a new novel architectural practice emerged, built around a low MTTR. It took seconds to get a new virtual machine, distributed systems were designed for failure, indeed chaos monkeys were introduced to the environment to introduce failure and ensure resilience. We introduced co-evolution (which has been practiced in other fields throughout history) and we called it DevOps.
  • This evolved until it became good architectural practice for the utility world and the old practices for a product world became legacy.
  • The legacy world was held back by inertia but the cloud was about user needs, measurement, automation, collaboration and fast feedback.
  • Then a new tribe began to rise up. Using commodity operating systems and functions as a framework. This framework is becoming a utility. And it will move from emerging to good practice, then best practice and “serverless” will be the future.
  • The old world will become legacy. Even the wonderful world of “DevOps”.
  • But, for now, if we say that “DevOps” is legacy, the response will be “burn him, heretic”.

So that’s the rise of serverless and the “death of DevOps”.

[Simon Wardley does a much better job of this… hopefully, there’s a video out there of him explaining the above somewhere…]

Do we need another as-a-service to describe functions?

Last week saw quarterly earnings reports for major cloud vendors and this tweet caught my eye:

You see, despite Azure growing by 93%, this suggests that Amazon has the cloud market sewn up. Except I’m not sure they do…

I think it would be interesting to see this separated into infrastructure-, platform- and software-as-a-service (IaaS/PaaS/SaaS). I suggest that would present three very different stories. And I’d expect that Amazon would only really be way out front for IaaS.

My friend and former colleague, Garry Martin (@GarryMartin) questioned the relevance of those “legacy” distinctions but I think they still have value today.

In the early days of what we now recognise as cloud computing, every vendor was applying their own brand of cloud-washing. It still happens today, with vendors claiming to offer IaaS when really they have a hosted service and a traditional delivery model.

Back in 2011, the US National Institute of Standards and Technology (NIST) defined cloud computing, including the service models of IaaS, PaaS and SaaS. Those service models, along with the (also abused) deployment models (public cloud, private cloud, etc.) have served us well but are they really legacy?

I don’t think they are. Six years is a long time in IT, let alone the cloud but I think IaaS, PaaS and SaaS are as relevant today as they were when NIST wrote their definition.

When asked how “serverless” technologies like AWS Lambda, Azure Functions or Google Cloud Functions fit in, I say they’re just PaaS. Done right.

Some people want to add another service model/definition for Function-as-a-Service (FaaS). But why? What value does it add? Functions are just PaaS but we’ve finally evolved to a place where we are moving past the point of caring about what the code runs on and letting the cloud manage that for us. That’s what PaaS has supposed to have been doing for years (after all, should I really need to define a number of instances to run my web application – that all sounds a bit like virtual machines to me…)

To my mind, “serverless” is just the ultimate platform as a service and we really don’t need another service model to describe it.

To quote a haiku from Onsi Fakhouri (@onsijoe):

“Here is my code
Run it in the cloud for me
I don’t care how”

Or, as Simon Wardley (@swardley) “fixed” this Cloud Foundry diagram:

Designing for failure does not necessarily mean multi-cloud

Earlier this week, Amazon Web Services’ S3 storage service suffered an outage that affected many websites (including popular sites to check if a website is down for everyone or just you!).

Unsurprisingly, this led to a lot of discussion about designing for failure – or not, it would seem in many cases, including the architecture behind Amazon’s own status pages:

The Amazon and Azure models are slightly different but in the past we’ve seen outages to the Azure identity system (for example) impact on other Microsoft services (Office 365). When that happened, Microsoft’s Office 365 status page didn’t update because of a caching/CDN issue. It seems Amazon didn’t learn from Microsoft’s mistakes!

Randy Bias (@RandyBias) is a former Director at OpenStack and a respected expert on many cloud concepts. Randy and I exchanged many tweets on the topic of the AWS outage but, after multiple replies, I thought a blog post might be more appropriate. You see, I hold the view that not all systems need to be highly available. Sometimes, failure is OK. It all comes down to requirements:

And, as my colleague Tim Siddle highlighted:

I agree. 100%.

So, what does that architecture look like? Well, it will vary according to the provider:

So, if we want to make sure our application can survive a region failure, there are ways to design around this. Just be ready for the solution we sold to the business based on using commodity cloud services to start to look rather expensive. Whereas on-premises we typically have two datacentres with resilient connections, then we’ll want to do the same in the cloud. But, just as not all systems are in all datacentres on-premises, that might also be the case in the cloud. If it’s a service for which some downtime can be tolerated, then we might not need to worry about a multi-region architecture. In cases where we’re not at all concerned about downtime we might not even use an availability set

Other times – i.e. if the application is a web service for which an outage would cause reputational or financial damage – we may have a requirement for higher availability.  That’s where so many of the services impacted by Tuesday’s AWS outage went wrong:

Of course, we might spread resources around regions for other reasons too – like placing them closer to users – but that comes back to my point about requirements. If there’s a requirement for fast, low-latency access then we need to design in the dedicated links (e.g. AWS Direct Connect or Azure ExpressRoute) and we’ll probably have more than one of them too, each terminating in a different region, with load balancers and all sorts of other considerations.

Because a cloud provider could be one of those single points of failure, many people are advocating multi-cloud architectures. But, if you think multi-region is expensive, get ready for some seriously complex architecture and associated costs in a multi-cloud environment. Just as in the on-premises world, many enterprises use a single managed services provider (albeit with multiple datacentres), in the cloud many of us will continue to use a single cloud provider.  Designing for failure does not necessarily mean multi-cloud.

Of course, a single-cloud solution has its risks. Randy is absolutely spot on in his reply below:

It could be argued that one man’s “lock-in” is another’s “making the most of our existing technology investments”. If I have a Microsoft Enterprise Agreement, I want to make sure that I use the software and services that I’m paying for. And running a parallel infrastructure on another cloud is probably not doing that. Not unless I can justify to the CFO why I’m running redundant systems just in case one goes down for a few hours.

That doesn’t mean we can avoid designing with the future in mind. We must always have an exit strategy and, where possible, think about designing systems with a level of abstraction to make them cloud-agnostic.

Ultimately though it all comes back to requirements – and the ability to pay. We might like an Aston Martin but if the budget is more BMW then we’ll need to make some compromises – with an associated risk, signed off by senior management, of course.

[Updated 2 March 2017 16:15 to include the Mark Twomey tweet that I missed out in the original edit]

IT transformation: why timing is crucial

In my work, I regularly find myself discussing transformation with customers who are thinking of moving some or all of their IT services to “the cloud”.  Previously, I’ve talked about a project where a phased approach was taken because of a hard deadline that was driving the whole programme:

  1. Lift and shift to infrastructure-as-a-service (IaaS) and software-as-a-service (SaaS).
  2. Look for service enhancements (transform) – for example re-architect using platform-as-a-service (PaaS).
  3. Iterate/align with sector-wide strategy for the vertical market.

The trouble with this approach is that, once phase 1 is over, the impetus to execute on later phases is less apparent. Organisations change, people move on, priorities shift. And that’s one reason why I now firmly believe that transformation has to happen throughout the project, in parallel with any migration to the cloud – not at the end.

My colleague Colin Hughes (@colinp_hughes) represented this in diagrammatical form in a recent presentation (unfortunately I can’t reproduce it on my personal blog) but it was interesting to listen to episode 6 of Matt Ballantine and Chris Weston’s WB-40 podcast when they were discussing a very similar topic.

In the podcast, Matt and Chris reinforced my view that just moving to the cloud is unlikely to save costs (independently of course – they’re probably not at all bothered about whether I agree or not!). Even if on the surface it appears that there are some savings, the costs may just have been moved elsewhere. Of course, there may be other advantages – like a better service, improved resilience, or other benefits (like reduced technical debt) – but just moving to IaaS is unlikely to be significantly less expensive.

Sure, we can move commodity services (email, etc.) to services like Office 365 but there’s limited advantage to be gained from just moving file servers, web servers, application servers, database servers, etc. from one datacentre to another (virtual) datacentre!

Instead, take the time to think about what applications need; how they could work differently; what would be the impact of using platform services; making use of a microservices-based approach*; could you even go further and re-architect to use so-called “serverless” computing* (e.g. Azure Functions or AWS Lambda)

But perhaps the most important point: digital transformation is not just about the IT – we need to re-design the business processes too if we’re really going to make a difference!

 

* I plan to explore these concepts in more detail in future blog posts.

Not all software consumed remotely is a cloud service

Helping a customer to move away from physical datacentres and into the cloud has been an exciting project to work on but my scope was purely the Microsoft workstream: migrating to Office 365 and a virtual datacentre in Azure. There’s much more to be done to move towards the consumption of software as a service (SaaS) in a disaggregated model – and many more providers to consider.

What’s become evident to me in recent weeks is that lots of software is still consumed in a traditional manner but as a hosted service. Take for example a financial services organisation who was ready to allow my customer access to their “private cloud” over a VPN from the virtual datacentre in Azure but then we hit a road block for routing the traffic. The Azure virtual datacentre is an extension of the customer’s network – using private IP addresses – but the service provider wanted to work with public IPs, which led to some extra routers being reployed (and some NATting of addresses somewhere along the way). Then along came another provider – with human resources applications accessed over unsecure HTTP (!). Not surprisingly, access across the Internet was not allowed and again we were relying on site-to-site VPNs to create a tunnel but the private IPs on our side were something the provider couldn’t cope with. More network wizardry was required.

I’m sure there’s a more elegant way to deal with this but my point is this: not all software consumed remotely is a cloud service. It may be licenced per user on a subscription model but if I can’t easily connect to the service from a client application (which will often be a browser) then it’s not really SaaS. And don’t get me started on the abuse of the term “private cloud”.

There’s a diagram I often use when talking to customers about different types of cloud deployments. it’s been around for years (and it’s not mine) but it’s based on the old NIST definitions.

Cloud computing delivery models

One customer highlighted to me recently that there are probably some extra columns between on-premises and IaaS for hosted and co-lo services but neither of these are “cloud”. They are old IT – and not really much more than a different sort of “on-premises”.

Critically, the NIST description of SaaS reads:

“The capability provided to the consumer is to use the provider’s applications running on a cloud infrastructure. The applications are accessible from various client devices through either a thin client interface, such as a web browser (e.g., web-based email), or a program interface. The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited userspecific application configuration settings.”

The sooner that hosted services are offered in a multi-tenant model that facilitates consumption on demand and broad network access the better. Until then, we’ll be stuck in a world of site-to-site VPNs and NATted IP addresses…

Short takes: Amazon Web Services 101, Adobe Marketing Cloud and Milton Keynes Geek Night (#MKGN)

What a crazy week. On top of a busy work schedule, I’ve also found myself at some tech events that really deserve a full write-up but, for now, will have to make do with a summary…

Amazon Web Services 101

One of the events I attended this week was a “lunch and learn” session to give an introduction/overview of Amazon Web Services – kind of like a breakfast briefing, but at a more sociable hour of the day!

I already blogged about Amazon’s reference architecture for utility computing but I wanted to mention Ryan Shuttleworth’s (@RyanAWS) explaination of how Amazon Web Services (AWS) came about.

Contrary to popular belief, AWS didn’t grow out of spare capacity in the retail business but in building a service-oriented infrastructure for a scalable development environment to initially provide development services to internal teams and then to expose the amazon catalogue as a web service. Over time, Amazon found that developers were hungry for more and they moved towards the AWS mission to:

“Enable business and developers to use web services* to build scalable, sophisticated applications”

*What people now call “the cloud”

In fact, far from being the catalyst for AWS, Amazon’s retail business is just another AWS customer.

Adobe Marketing Cloud

Most people will be familiar with Adobe for their design and print products, whether that’s Photoshop, Lightroom, or a humble PDF reader.  I was invited to attend an event earlier this week to hear about the Adobe Marketing Cloud, which aims to become for marketers what the Creative Suite has for design professionals.  Whilst the use of “cloud” grates with me as a blatant abuse of a buzzword (if I’m generous, I suppose it is a SaaS suite of products…), Adobe has been acquiring companies (I think I heard $3bn mentioned as the total cost) and integrating technology to create a set of analytics, social, advertising, targeting and web experience management solutions and a real-time dashboard.

Milton Keynes Geek Night

MK Geek Night #mkgn

The third event I attended this week was the quarterly Milton Keynes Geek Night (this was the third one) – and this did not disappoint – it was well up to the standard I’ve come to expect from David Hughes (@DavidHughes) and Richard Wiggins (@RichardWiggins).

The evening kicked off with Dave Addey (@DaveAddey) of UK Train Times app fame, talking about what makes a good mobile app. Starting out from a 2010 Sunday Times article about the app gold rush, Dave explained why few people become smartphone app millionaires, but how to see if your idea is:

  • Is your mobile app idea really a good idea? (i.e. is it universal, is it international, and does it have lasting appeal – or, put bluntly, will you sell enough copies to make it worthwhile?)
  • Is it suitable to become a mobile app? (will it fill “dead time”, does it know where you go and use that to add value, is it “always there”, does it have ongoing use)
  • And how should you make it? (cross platform framework, native app, HTML, or hybrid?)

Dave’s talk warrants a blog post of it’s own – and hopefully I’ll return to the subject one day – but, for now, that’s the highlights.

Next up were the 5 minute talks, with Matt Clements (@MattClementsUK) talking about empowering business with APIs to:

  1. Increase sales by driving traffic.
  2. Improve your brand awareness by working with others.
  3. Increase innovation, by allowing others to interface with your platform.
  4. Create partnerships, with symbiotic relationships to develop complimentary products.
  5. Create satisfied customers – by focusing on the part you’re good at, and let others build on it with their expertise.

Then Adam Onishi (@OnishiWeb) gave a personal, and honest, talk about burnout, it’s effects, recognising the problem, and learning to deal with it.

And Jo Lankester (@JoSnow) talked about real-world responsive design and the lessons she has learned:

  1. Improve the process – collaborate from the outset.
  2. Don’t forget who you’re designing for – consider the users, in which context they will use a feature, and how they will use it.
  3. Learn to let go – not everything can be perfect.

Then, there were the usual one-minute slots from sponsors and others with a quick message, before the second keynote – from Aral Balkan (@Aral), talking about the high cost of free.

In an entertaining talk, loaded with sarcasm, profanity (used to good effect) but, most of all, intelligent insight, Aral explained the various business models we follow in the world of consumer technology:

  • Free – with consequential loss of privacy.
  • Paid – with consequential loss of audience (i.e. niche) and user experience.
  • Open – with consequential loss of good user experience, and a propensity to allow OEMs and operators to mess things up.

This was another talk that warrants a blog post of its own (although I’m told the session audio was recorded – so hopefully I’ll be able to put up a link soon) but Aral moved on to talk about a real alternative with mainstream consumer appeal that happens to be open. To achieve this, Aral says we need a revolution in open source culture in that open source and great user experience do not have to be mutually exclusive. We must bring design thinking to open source. Design-led open source.  Without this, Aral says, we don’t have an alternative to Twitter, Facebook, whatever-the-next-big-platform-is doing what they want to with our data. And that alternative needs to be open. Because if it’s just free, the cost is too high.

The next MK Geek Night will be on 21 March, and the date is already in my diary (just waiting for the Eventbrite notice!)

Photo credit: David Hughes, on Flickr. Used with permission.

[Amazon’s] Reference architecture for utility computing

Earlier this week, I attended an Amazon Web Services (AWS) 101 briefing, delivered by Amazon UK’s Ryan Shuttleworth (@RyanAWS).  Although I’ve been watching the “Journey into the AWS cloud” series of webcasts too, it was a really worthwhile session and, when the videos are released to the web, well worth watching for an introduction to the AWS cloud.

One thing I particularly appreciate about Ryan’s presentations is that he approaches things from an architectural view. It’s a refreshing change from the evangelists I’ve met at other companies who generally market software by talking about features (maybe even with some design considerations/best practice or coding snippets) but rarely seem to mention reference architectures or architectural patterns.

During his presentation, Ryan presented a reference architecture for utility computing and, even though this version relates to AWS services, it’s a pretty good model for re-use (in fact, the beauty of such a  reference architecture is that the contents of each box could be swapped out for other components, without affecting the overall approach – maybe I should revisit this post and slot in the Windows Azure components!).

So, what’s in each of these boxes?

  • AWS global infrastructure: consists of regions to collate facilities, with availability zones that are physically separated, and edge locations (e.g. for content distribution).
  • Networking: Amazon provides Direct Connect (dedicated connection to AWS cloud) to integrate with existing assets over VPN Connections and Virtual Private Clouds (your own slice of networking inside EC2), together with Route 53 (a highly available and scalable global DNS service).
  • Compute: Amazon’s Elastic Compute Cloud (EC2) allows for the creation of instances (Linux or Windows) to use as you like, based on a range of instance types, with different pricing – to scale up and down, even auto-scalingElastic Load Balancing  allows the distribution of EC2 workloads across instances in multiple availability zones.
  • Storage: Simple Storage Service (S3) is the main storage service (Dropbox, Spotify and others runs in this) – designed for write once read many applications.  Elastic Block Store (EBS) can be used to provide persistent storage behind an EC2 instance (e.g. boot volume) and supports snapshotting, replicated within an availability zone (so no need to RAID). There’s also Glacier for long term archival of data, AWS Import/Export for bulk uploads/downloads to/from AWS and the AWS Storage Gateway to connect on-premises and cloud-based storage.
  • Databases: Amazon’s Relational Database Service (RDS) provides database as a service capabilities (MySQL, Oracle, or Microsoft SQL Server). There’s also DynamoDB – a provisioned throughput NoSQL database for fast, predictable performance (fully distributed and fault tolerant) and SimpleDB for smaller NoSQL datasets.
  • Application services: Simple Queue Service (SQS) for reliable, scalable, messages queuing for application decoupling); Simple Workflow Service (SWF) to coordinate processing steps across applications and to integrate AWS and non-AWS resources, to manage distributed states in complex systems; CloudSearch – an elastic search engine based on Amazon’s A9 technology to provide auto-scaling and a sophisticated feature set (equivalent to SOLR); CloudFront for a worldwide content delivery network (CDN), to easily distribute content to end users with a single DNS CNAME.
  • Deployment and admin: Elastic Beanstalk allows one click deployment from Eclipse, Visual Studio and Git  for rapid deployment of applications with all AWS resources auto-created; CloudFormation is a scripting framework for AWS resource creation that automates stack creation in a repeatable way. There’s also Identity and Access Management (IAM), software development kits, Simple Email Service (SES), Simple Notification Service (SNS), ElastiCache, Elastic MapReduce, and  the CloudWatch monitoring framework.

I suppose if I were to re-draw Ryan’s reference architecture, I’d include support (AWS Support) as well some payment/billing services (after all, this doesn’t come for free) and the AWS Marketplace to find and start using software applications on the AWS cloud.

One more point: security and compliance (security and service management are not shown as they are effectively layers that run through all of the components in the architecture) – if you implement this model in the cloud, who is responsible? Well, if you contract with Amazon, they are responsible for the AWS global infrastructure and foundation services (compute, storage, database, networking). Everything on top of that (the customisable parts) are up to the customer to secure.  Other providers may take a different approach.

What-as-a-service?

I’ve written previously about the “cloud stack” of -as-a-service models but I recently saw Microsoft’s Steve Plank (@plankytronixx) give a great description of the differences between on-premise,  infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS).

Of course, this is a Microsoft view of the cloud computing landscape and I’ve had other discussions recently where people have argued the boundaries for IaaS or PaaS and confused things further by adding traditional web hosting services into the mix*.  Even so, I think the Microsoft description is a good starting point and it lines up well with the major cloud services offerings from competitors like Amazon and Google.

Not everyone will be familiar with this so I thought it was worth repeating Steve’s description here:

In an on-premise deployment, the owning organisation is responsible for (and has control over) the entire technology stack.

With infrastructure as a service, the cloud service provider manages the infrastructure elements: network, storage, servers and virtualisation. The consumer of the IaaS service will typically have some control over the configuration (e.g. creation of virtual networks, creating virtual machines and storage) but they are all managed by the cloud service provider.  The consumer does, however, still need to manage everything from the operating system upwards, including applying patches and other software updates.

Platform as a service includes the infrastructure elements, plus operating system, middleware and runtime elements. Consumers provide an application, configuration and data and the cloud service provider will run it, managing all of the IT operations including the creation and removal of resources. The consumer can determine when to scale the application up or out but is not concerned with how those instances are operated.

Software as a service provides a “full-stack” service, delivering application capabilities to the consumer, who only has to be concerned about their data.

Of course, each approach has its advantages and disadvantages:

  • IaaS allows for rapid migrations, as long as the infrastructure being moved to the cloud doesn’t rely on other components that surround it on-premise (even then, there may be opportunities to provide virtual networks and extend the on-premise infrastructure to the cloud). The downside is that many of the management issues persist as a large part of the stack is still managed by the consumer.
  • PaaS allows developers to concentrate on writing and packaging applications, creating a service model and leaving the underlying components to the cloud services provider. The main disadvantage is that the applications are written for a particular platform, so moving an application “between clouds” may require code modification.
  • SaaS can be advantageous because it allows for on-demand subscription-based application use; however consumers need to be sure that their data is not “locked in” and can be migrated to another service if required later.

Some organisations go further – for example, in the White Book of Cloud Adoption, Fujitsu wrote about Data as a Service (DaaS) and Business Process as a Service (BPaaS) – but IaaS, PaaS and SaaS are the commonly used models.  There are also many other considerations around data residency and other issues but they are outside the scope of this post. Hopefully though, it does go some way towards describing clear distinctions between the various -as-a-service models.

* Incidentally, I’d argue that traditional web hosting is not really a cloud service as the application delivery model is only part of the picture. If a web app is just running on a remote server it’s not really conforming with the broadly accepted NIST definition of cloud computing characteristics. There is a fine line though – and many hosting providers only need to make a few changes to their business model to start offering cloud services. I guess that would be an interesting discussion with the likes of Rackspace…