I just saw Eric Dishman’s TED session on “Health care should be a team sport“. I love the idea of providing people with chronicle illness the means to be diagnosed and treated remotely and use big data to learn of a large group of patients with similar issues. Personally this would mean that when my sons have breathing problems we would not have to drag them in the middle of the night to a hospital where they are exposed to many viruses. Instead by measuring their oxygen level and listening to their longs a personalized remote diagnose could be made and some nebulizers or other things administered. At scale all equipment would probably cost less than £200 because Maplin already sells the nebulizer and oxygen level meter for a combined £110. Add another £90 at worst for a stethoscope that can be connected via bluetooth to a smartphone. Now via Hangout a doctor could remotely diagnose the results and even in the future a computer programme. All results of millions of patients would be collected in order to improve treatment. So no need for an expensive hospital in London with a receptionist, nurse and doctor dedicating 2 hours. By just avoiding one hospital night, the whole system would be enormously profitable. Additionally Ubuntu’s Juju can be used to set up all the big data and diagnostic software in minutes in any cloud or server on any place in the world. If other open source solutions are used then the total solution would be in reach for any developing country. There are probably more than one developer whose kids are asthmatic, and would happily contribute time. It sounds like an ideal Gates Foundation or Kickstarter project. If you think you can help please reach out to me because this is not work for me, this is personal engagement.
It is not often that one is responsible for cloud [and Big Data and IoT] strategy in a company of 600 people and you get told by the OpenStack foundation that your solution went from 55% market share to 64% while competitors like RedHat, HP, VMWare, etc. are spending hundreds [or more] of times more on marketing and engineering than you. Now I would love to claim responsibility for it but I would be lying. My mentors, Mark Shuttleworth and Simon Wardley, have laid the foundations years before I joined the company. But Ubuntu and Canonical, the company behind it, are the poster child example of why promoting chief financial officers into strategic roles in the last ten years was a terrible idea. Bean counters are about to inflict potentially irreparable damage onto iconic hardware and legacy software vendors. The reason is really easy: disruptive innovation. The innovator’s dilemma explained it years ago already. When some initial inferior technology comes along like Cloud Computing and OpenStack, then existing vendors will not get any demand from existing customers. Only when technology matures will customers start defecting en masse. But then already other companies have years of a head-start. Add to it that Ubuntu OpenStack is not only the most innovative solutions but also wants to be the most flexible [see our Autopilot, OIL, MAAS and Juju for more details] and the cheapest. So if you are on a quarter-based projected revenue track and you find out that your competitor is doing those three things extremely well, then it might be time to brush up those skills and experiences on your CV. Regarding the future, let me just tell you that the best is still to come :-)
If you thought Amazon’s Prime Instant Films is just an exception of Amazon trying to compete with its best customer then you are wrong. This is not an exception but a rule. Simon Wardley just explained why Amazon is fast following their best customers and why more companies should do it to, even in the physical world. The summary is:
If you don’t want to launch a 100 new services and assume failure on 90-95, then let others launch thousands and you commoditise the successful innovations.
So what does this mean?
It means that if you are a young startup that builds everything on AWS then they will just look at the traffic that goes through your servers. If all of a sudden they see that you are picking up more traffic then anybody else, then they will launch a competing solution shortly that commoditises your business. Since they have access to your solution they can actually look inside and see how it works and redesign a more optimised solution.
How to avoid your service to be commoditised by a fast follower?
First of all move faster than anybody else. Full automation is key. If you are faster to respond to customer’s needs then you will attract all customers in a winner takes it all market. Also follow lean startup and A/B testing. Do continuous experiments and only scale up engineering on a new feature after it was demonstrated to be successful with customers on a small scale test.
Second, don’t build for one cloud, build for multiple clouds. If you use cloud orchestration solutions that allow your solution to be moved from one cloud to another one then you are less likely to be trackable by one cloud provider. Treat the cloud providers like they are commodity and move your workloads where it makes more financial sense. Whatever you do, don’t get locked-in by some proprietary services because you will have a hard time moving out. Just ask Netflix how they feel about having their platform ran on top of their biggest competitor’s infrastructure without a chance of moving a way soon. Don’t want to be in their shoes? Use a cloud orchestration solution. Don’t know any open source? Check out Juju…
Third, assume you will have fast followers when you start so try to put barriers of entry in place. A good strategy would be to build a business on top of a network effect. Examples: Facebook has over 1 billion users. The more users the more synergies. Even if you would steal away all the code from Facebook and launch Headbook you would not be successful. Network effect businesses tend to be a winner takes it all markets as a consequence. The other counter intuitive strategy is to strategically open source parts of your solution. If you open source parts of your solution then there is nobody that can offer a “cheaper” solution then your freely available solution. So the incentive of building another solution to compete with a free solution is low. Additionally you will get contributions from others hence your team will be able to run faster than anybody else. Finally open source does not mean zero revenue. Netflix has open sourced their architecture. This means they lower their cost and higher their innovation speed but since you don’t have access to their content library and the multiple content they create themselves, it is extremely hard to compete with them. So open source those parts that help your strategy…
In 1999 you could easily spend $1M on having a company build a static web site. A few years later any student could make you a web site. HTML became a commodity. The same commodity effect needs to happen to Big Data.
The past: build your own petabyte solution
A few years back only the happy few extremely technically gifted companies were able to create solutions to store TBs and even PBs of data. Google started to write papers. Yahoo and Facebook started to release open source solutions. Shortly after Big Data became a buzz word and anybody that was somebody in the IT consultancy space was talking about Hadoop.
Now: open source solutions and lots of handholding
In 2014 it is possible to download Hadoop, Spark, Storm, etc. You can even find prepackaged solutions from Hortonworks, Cloudera, MapR, Pivotal, IBM, etc. But still Big Data projects are hard. You need very bright people or spend quite a lot to get anywhere. Many projects run over budget and under deliver.
Future: instant Big Data solutions
We are ready for the next step and convert Big Data in a commodity. Several startups are launching Big Data solutions as a service. Unfortunately for many SaaS providers, having a Big Data SaaS solution is not enough. Big Data means lots of data. Data that can hold sensitive information. Data that can grow with GBs a day. This is the reason why if any SaaS Big Data solution ought to be successful, it also needs an on-premise alternative.
We are also missing a portable Big Data logic container. The industry is raving about Docker. Several startups are working on making Docker containers the way to share your map-reduce logic. I predict that many more Big Data logic can be containerised and made portable. Any data scientist should be able to reuse Deep Belief or Random Forest algorithms by just reusing a container.
The other part of the puzzle that is still missing is data visualisation and manipulation tools. There are many Big Data key-value stores and map-reduce engines. However the data visualisation and reporting space is still wide open. The Apache Foundation does not [yet] provide a drag-and-drop tool to setup dashboards, generate reports, schedule notifications, run workflows, automate data imports, etc.
Industry specific reusable assets is another part that is missing. Nobody wants to go and reinvent eCommerce recommendation algorithms every time a new Big Data platform becomes available.
However all of this is coming at enormous speeds. As soon as all the pieces of the puzzle are coming together then cloud orchestration solutions like Juju, ServiceMesh, Brooklyn, etc. will allow enterprises to start consuming Big Data solutions as a commodity. Instant Big Data solutions are 6-36 months away depending on your requirements.
Have you ever counted the number of Linux devices at home or work that haven’t been updated since they came out of the factory? Your cable/fibre/ADSL modem, your WiFi point, television sets, NAS storage, routers/bridges, media centres, etc. Typically this class of devices hosts a proprietary hardware platform, an embedded proprietary Linux and a proprietary application. If you are lucky you are able to log into a web GUI often using the admin/admin credentials and upload a new firmware blob. This firmware blob is frequently hard to locate on hardware supplier’s websites. No wonder the NSA and others love to look into potential firmware bugs. They are the ideal source of undetected wiretapping.
The next IT revolution: micro-servers
The next IT revolution is about to happen however. Those proprietary hardware platforms will soon give room for commodity multi-core processors from ARM, Intel, etc. General purpose operating systems will replace legacy proprietary and embedded predecessors. Proprietary and static single purpose apps will be replaced by marketplaces and multiple apps running on one device. Security updates will be sent regularly. Devices and apps will be easy to manage remotely. The next revolution will be around managing millions of micro-servers and the apps on top of them. These micro-servers will behave like a mix of phone apps, Docker containers, and cloud servers. Managing them will be like managing a “local cloud” sometimes also called fog computing.
Micro-servers and IoT?
Are micro-servers some form of Internet of Things. Yes they can be but not all the time. If you have a smarthub that controls your home or office then it is pure IoT. However if you have a router, firewall, fibre modem, micro-antenna station, etc. then the micro-server will just be an improved version of its predecessor.
Why should you care about micro-servers?
If you are a mobile app developer then the micro-servers revolution will be your next battlefield. Local clouds need “Angry Bird”-like successes.
If you are a telecom or network developer then the next-generation of micro-servers will give you unseen potentials to combine traffic shaping with parental control with QoS with security with …
If you are a VC then micro-server solution providers is the type of startups you want to invest in.
If you are a hardware vendor then this is the type of devices or SoCs you want to build.
If you are a Big Data expert then imagine the new data tsunami these devices will generate.
If you are a machine learning expert then you might want to look at algorithms and models that are easy to execute on constraint devices once they have been trained on potentially thousands of cloud servers and petabytes of data.
If you are a Devop then your next challenge will be managing and operating millions of constraint servers.
If you are a cloud innovator then you are likely to want to look into SaaS and PaaS management solutions for micro-servers.
If you are a service provider then this is the type of solutions you want to have the capabilities to manage at scale and easily integrate with.
If you are a security expert then you should start to think about micro-firewalls, anti-micro-viruses, etc.
If you are a business manager then you should think about how new “mega micro-revenue” streams can be obtained or how disruptive “micro- innovations” can give you a competitive advantage.
If you are an analyst or consultant then you can start predicting the next IT revolution and the billions the market will be worth in 2020.
The next steps…
It is still early days but expect some major announcements around micro-servers in the next months…
At TADHack some months ago it was clear that SMS and phone calls are out and WebRTC is the new hot technology for developers. Via your browser you can talk to your salesman, doctor and coach. Your browser can be mobile. This means that video calls will be universal as soon as 4G is everywhere. Bad news for operators that will see data on their networks balloon without new revenues. Good news for users that will have a whole new world of communication opening up with voice, video, screen sharing, web apps, etc. all seamlessly integrated.
How can business be generated with WebRTC?
Per minute call billing is out. Unless of course you are talking to a highly paid consultant that charges you by the second or minute. One time payment like mobile apps are only viable if you can embed WebRTC technology in a mobile app, not if you need to support an ongoing business. This means that we need a new subscription model for WebRTC. We need a micro subscription model. Especially for services that will be used on a long term basis, e.g. conference facilities, next generation voice mails, etc. As always operators will be hesitant to cannibalise a juicy per minute business for a low margin 1-99 cents per months subscription service. So are there others that could bill micro-subscriptions? The obvious choice would be cloud providers. They can already do hourly micro billing on monthly cycles hence adding some recurring element would be straightforward. So my prediction is that WebRTC will see operator’s problems accelerate whereby cloud will no longer deliver you only IT solutions but also your communication services.
We all have “enjoyed” working with some software that was purchased because “You can’t get fired because you bought…”. This software is known for being the industry leader. Not because it is easy to use, easy to integrate, easy to scale, easy to do anything with,… It often is quite the opposite.
So why do people buy it? First of all it is easy to find experts. There are people out there that have been “enjoying” working with this solution for the last 10 years. It is relatively stable and reliable. There is a complete solution for it with hundreds or thousands of partner solutions. People have just given up on trying to convince their bosses on trying something different.
5 steps to disrupt the Dinosaur
Step 1: the basic use cases
The Pareto rule. What are the 80% of the use cases that only reflect 20% of the functionality.
Step 2: the easy & beautiful & horizontally scalable & multi-tenant clone
Make a solution that reflects 80% of these use cases but make it beautiful and incredibly easy to use. Use the latest horizontally scalable backends, e.g. Cassandra. Build multi-tenancy into the software from day 1.
Step 3: make it open source
Release the “improved clone” as an open source product.
Step 4: the plugin economy
Add a plugin mechanism that allows others to create plugins to fill in the 20% use case gap. Create a marketplace hence others can make money with their plugins. Make money by being the broker. Think App Store but ideally improve the model.
Step 5: the SaaS version
Create a SaaS version and attack the bottom part of the market. Focus on the enterprises that could never afford the original product. Slowly move upwards towards the top segment.
The expected result
You will make have a startup or a new business unit that will make money pretty quickly and will soon be the target of a big purchase offer from the Dinosaur or one of its competitors. You will spend a lot less sleepless nights trying to make money this way then via the creation of the next Angry Bird, Uber 0r Facebook clone.