Multi Cloud Governance

02Oct18

This is one of those posts that started life on an email thread. It comes from a discussion on the topic of multi cloud governance for large enterprises.

Why cloud?

The answer is not ‘cloud is cheaper’, because it just isn’t. We know from Amazon’s financials that it’s gushing money because cloud is a high margin and very profitable business. Any halfway competent large enterprise can run its own data centres cheaper, and the mainframe and midrange legacy isn’t going anywhere so neither are those data centres.

The answer is ‘cloud is faster’. Cloud enables quicker delivery of value in response to changing user needs. ‘Digital’ is built out of continuous delivery (CD) pipelines, and CD pipelines need cloud at the end of them, because you can’t do continuous delivery without API enabled on demand infrastructure (which is lots of words for ‘a cloud’).

What kind of cloud?

Having focused our attention on the right category – applications that deliver outcomes more quickly by constructing CD pipelines – we finally come to the vexed question of what type of services do they want to consume? Is it IaaS, CaaS, FaaS (or some combination)?

Safety First

The crucial outcome is safety[1]. The app developers need to be able to consume services without crossing lines with respect to security and compliance.

Safety costs money (but far less than unsafe practices) so we end up at a cost/benefit trade off. For every class of services that consumed how much does it cost to make them safe, and what benefit is accrued (in speed to market and revenue achieved from that)? This doesn’t just apply to which cloud will be used (AWS vs Azure vs Google); it also applies at a finer grained level to which services are consumed within those clouds.

Control vs Productivity

Most large enterprises are looking down the wrong end of the telescope. They’re thinking about control before productivity rather than productivity before control; and that pattern is borne from the traditional enterprise mindset of standardisation to reduce complexity and cost.

Many enterprises feel like they have these options:

  1. Make the complexity appear to go away by putting a unifying broker layer between the cloud and its consumer.
  2. Accept that there will be multiple data centres and cloud providers and use some sort of common technology (e.g. containers) to enable common approaches to application development and deployment.
  3. Some combination of (1) and (2) where elements of the infrastructure and operations are treated in a common way (e.g. billing, operational data, software delivery).

None of them are good, because all of them presuppose that we make an activity safe before we even know what the activity is. It’s a great way of spending time and treasure on something that never delivers any practical value[2].

Getting to the cost/benefit trade off

This means actually knowing the cost, and actually being able to figure out the benefit. A managed cloud service with safety built in (like you get from a services company rather than the raw cloud underneath it) will show a sticker price for cost – so we’re half way there. The other half naturally extends into the enterprise’s own investment appraisal processes (and there’s room for services companies to be facilitators for the extra work needed there).

In the end it doesn’t matter whether they use one cloud or five. Whether they use containers, functions or VMs. It only matters that engineers are safe, and the overhead of achieving that safety is part of the broader business case for the functionality.

The final issue is the classic ‘buy the restaurant to eat the first meal’ problem that so often comes up with large enterprises, where any given app can’t make the business case stand up on its own. That takes us to a portfolio management exercise where the investment in safety for a category of apps with common needs gets justified by the expected benefits of all those apps (and the apps that might follow them). So there’s a need for some degree of aggregation. What happens next is essentially paving the cow paths – early success becomes the path of least resistance for things that follow (so that they don’t have to make fresh cases for their own new safety demands).

What this brings us to is the ability to say to application developers ‘you can have anything you want provided that you can afford the safety’, ‘you may club together to pay for safety’. That leads to an initial cohort of apps that make something happen within the confines of a given set of safety systems. It’s easy to follow them, because the safety investment has already been paid down. Apps can choose not to follow, but that choice comes with the consequence that they need to stand up their own safety and pay the premium.

They key point is ‘they come and we build it’ rather than ‘build it and they shall come’.

Notes

[1] I’ve written about safety (first) before.
[2] For more on why brokers are considered an anitpattern take a look at Barclays’ Infrastructure CTO Keiran Broadfoot in his 2017 re:Invent presentation.



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