On platforms 1

On Platforms (part 1)

A serendipitous two days: firstly the Google Cloud Next 17exhibition at Excel, and next a workshop at LSE on digital platforms.

The Google event was lavish: the middle manager as rock star. (We got as high as a Senior Vice President). Free food, some comfortable chairs, sinister photographers lurking in the shadows to film the 4,600 delegates learning. Lots of slogans.

I came out of it feeling that:
1. Google’s aim is to get every business running all its IT on their cloud. This has many advantages: IT becomes OPEX rather than CAPEX, and you can expand or change your setup quickly and easily. Google engineers look after your servers and your security.
2. To this end they have huge infrastructure (they claim to be the only software company to build its own undersea cable).
3. They also have a complex set of architectures based around the open-source Kubernetes platform, which supplies ‘containers’ into which you fit your own IT package. It seems to be rather like OO is to small-scale prgoramming: a black box with consistent, standardised input and output flanges, if I may mix my metaphors.
4. On top of this they have all sorts of software offerings, allowing you to set up your own company IT based around the ‘G Suite’, together with all sorts of data analysis and machine learning packages.

Some quite impressive stuff: for example, companies are finding the are now getting too much personal information which they don’t want to store. So if a client accidentally tells you his credit card number, they have an algorithm that will detect this and **** it out in your records. Also they offer machine learning packages and heaven knows what else. So even a small company can have an intelligent chatbot on its website.

There’s a whole ecosystem of ‘partners’ who provide various services to end-users. Ranging from Accenture and Intel to people I had never heard of like
Pythian (‘ help companies adopt and manage disruptive technologies to better compete’).
Netpremacy: “choosing Netpremacy isn’t just about choosing the right product for your needs, but choosing teams of expertly trained, Google Accredited, engineers to ensure that what ever service you require, will be delivered on time and within budget with unparalleled training and support”
Datatonic: “We craft analytical applications. Our team of data experts can help drive your business through the power of data.”
Virtru: “your data privacy force field, wrapping and protecting emails and files wherever they’re shared.”
Lookers:”It’s time everyone has access to fresh, reliable data. Drill deeper. Ask more. Share easier. ”
Equinix: “Innovate at the Edge with Equinix. See how next generation architectures drive competitive advantage at the digital edge – transforming your ability to connect all your people, locations, clouds and data.”
Ancoris: “We accelerate your digital transformation with web and mobile solutions built securely with Google Cloud”

Google’s business offerings do not pry like their personal offerings do. The G Suite FAQ says: “Unlike Google’s consumer offerings, which may show ads, we do not collect, scan or use your G Suite data for advertising purposes and do not display ads in G Suite, Education, or Government core services. We use your data to provide the G Suite services, and for system support, such as spam filtering, virus detection, spell-checking, capacity planning, traffic routing, and the ability to search for emails and files within an individual account.Put simply, the data that companies, schools and government agencies put into our G Suite services does not belong to Google. Whether it’s corporate intellectual property, personal information or a homework assignment, Google does not own that data and Google does not sell that data to third parties. ”

Indeed one of their many announcements was that they now have an agreement under which SAP will act as a ‘data trustee’ for Google’s European customer data. (The EU General Data Protection Regulation has many companies quite scared.)

I came out feeling overwhelmed by the complexity of all this. Wikipedia lists 256 cloud providers, but this is a segmented field. There are several service models:
– EaaS or XaaS or aaS: everything as a service
– I(nfrastructure)aaS: ‘online services that abstract the user from the details of infrastructure like physical computing resources, location, data partitioning, scaling, security, backup etc’
– P(latform)aaS: ‘offer a development environment to application developers. The provider typically develops toolkit and standards for development and channels for distribution and payment. In the PaaS models, cloud providers deliver a computing platform, typically including operating system, programming-language execution environment, database, and web server. Application developers can develop and run their software solutions on a cloud platform without the cost and complexity of buying and managing the underlying hardware and software layers’
– S(oftware)aaS: ‘ users gain access to application software and databases. Cloud providers manage the infrastructure and platforms that run the applications. SaaS is sometimes referred to as “on-demand software” ‘
– M(obile)B(ackend)aaS: ‘ web app and mobile app developers are provided with a way to link their applications to cloud storage and cloud computing services with application programming interfaces (APIs) exposed to their applications ‘

The Google Cloud seems to cover most of this and is expanding rapidly with many new offerings since it began in 2008. Its main rivals seem to be
Amazon Web services: “Amazon Web Services (AWS) is a subsidiary of Amazon.com[3] that offers on-demand cloud computing platforms. These services operate from 16 geographical regions across the world.[4] They include Amazon Elastic Compute Cloud, also known as “EC2”, and Amazon Simple Storage Service, also known as “S3″. As of 2016 AWS has more than 70 services, spanning a wide range, including compute, storage, networking, database, analytics, application services, deployment, management, mobile, developer tools and tools for the Internet of things. ”
Microsoft Azure: ” a cloud computing service created by Microsoft for building, deploying, and managing applications and services through a global network of Microsoft-managed data centers. It provides software as a service, platform as a service and infrastructure as a service and supports many different programming languages, tools and frameworks, including both Microsoft-specific and third-party software and systems.”

All these seem to offer IaaS, PaaS, storage, and all the other bells and whistles.

I found myself asking what the implications are, for example, if just about every business in the world works on a platform provided by one of these three.

Ignoring the obvious (Google might go bankrupt, Amazon might turn rogue and decide to bring down capitalism at a stroke, Microsoft might just finally lose the plot and announce that its technology no longer works) I find myself asking whether:
– enforced standardisation of the ‘containers’ will affect business
– increasing virtualisation will have any effect?
– competition to develop new services will lead to too much complexity?

As examples:
– when I set up my first web-based business, I rented space on a server run by a company based in West London. To their amusement, I went up to see them and asked to see ‘my server’. (Nobody else ever had, and I’m not sure why I did. One rack mount looks pretty much like another.) But with the cloud, all servers are virtual. All that existsd is an ‘image’, a template or set of instructions, using which your server can be ‘spun up’: that is, a software package can be set going on any available physical server in the Google/ Amazon/ Microsoft network, and for as long as it takes, that is ‘your’ server. Somewhere there is a huge store of ‘images’, waiting for an HTTP request to summon them to life.
– new services are great but there are too many companies competing to produce them, and businesses are quite likely to be talked into buying things they don’t need. Web site chatbots are (in my view) a good example. The AI and NLP involved is ferocious, and they save the coss of having someone to answer the phone. But they are not a major development in the way that the first database, the first spreadsheet, or even the first telegraph cable were. There’s a lot of rhetoric about ‘tools’ for cooperation and communication, but how necessary is an interactive whiteboard, for example?

Somewhat bemused by all this I went the next day to LSE…

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