Towards a World of Frictionless Change: The Role …...modern and unified stack, something that...
Transcript of Towards a World of Frictionless Change: The Role …...modern and unified stack, something that...
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W H I T E P A P E R
Towards a World of Frictionless Change: The Role
of Automation and AI in IT
Sections1. Change Is The New Normal ��������������������������������������������������������������������������������������������������������3
4. Future-proofing with abstraction �����������������������������������������������������������������������������������������������6
3. IT is still too artisanal ������������������������������������������������������������������������������������������������������������������7
3.1. Applying abstraction and automation to IT ���������������������������������������������������������������������8
3.2. Becoming more like a software company ������������������������������������������������������������������������9
4. Not just another wave ���������������������������������������������������������������������������������������������������������������12
5. Not all automation tools are alike ��������������������������������������������������������������������������������������������15
C O N T E N T S
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1. Change is the new normalIs it possible to prepare for events you can’t predict? Counterintuitive as it may sound, the answer is yes. And that
should be welcome news for enterprise IT leaders, who are so often on the receiving end of business demands and
technological developments they can neither foresee nor control. Change is the only constant in IT these days, and
it’s coming fast and furious. As much as CIOs might wish they could hit pause just long enough for their organizations
to catch their breath, there’s no letup in sight.
And while it may seem that the only reasonable response is to stick to the most urgent priorities and do a sort of
never-ending triage, there’s a better alternative – a way to smooth the road and make change relatively frictionless,
including both the changes you can see coming and the ones you have no inkling of. That’s what this paper is about.
85%of enterprise IT environments rely on a mix of manual processing, one-off scripts and other labor-intensive methods.
Information technology is racing ahead
with a Moore’s law-like inexorability and
compounding rate. That’s put enterprise IT
organizations in a vise: told to “modernize”
or “transform” by adopting the latest
technologies while still keeping a complicated
mix of older systems up and running. Even
if you’re in the enviable position of starting
from scratch and able to cherry-pick the
latest and greatest solutions, you can’t stay
greenfield forever. You’ll sooner or later have
legacy investments and heterogeneity to
contend with.
No wonder some commentators have called
the CIO’s job “the toughest in the C-suite.”
IT organizations can’t abandon the past, and
“embracing the future” is little more than a
slogan when we barely know what’s going
to happen next year, much less a decade
from now. So wouldn’t it be more realistic
to concentrate on the immediate challenge
of keeping the lights on and incrementally
upgrade whenever possible – in other words,
to focus on the knowable and near-term and
leave tomorrow for another day?
Actually, no. While it’s impossible to know
what’s next, it is possible get out of reactive
mode and get ahead of the game. And that
doesn’t mean simply focusing on practices
like DevOps or technologies like cloud
adoption and container stack selection.
Those are important advances, and they do
move the ball forward, but like all trends,
they’ll come and go. What we’re talking
about here is a more foundational approach
that puts you in a better position to take
advantage not only of current developments,
but any future innovations.
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The advent of the tidal wave of next generation technologies like Internet of Things, big data analytics, cloud services, etc. has provided an upsurge to many AI-driven solutions and employed the insights from the colossal volume of big data and information. This is helping businesses in ensuring that they are taking conversant decisions keeping all future possibilities in mind. A study conducted by Accenture Research and Frontier Economics stated that integrated AI into economic processes is directly proportional to potential for economic growth of a business.
Artificial Intelligence (AI) Adoption
Reasons businesses adopt Artificial Intelligence (AI) Saving time and money
Acquiring a Competitive Edge in the Global Market
Understandings of the Business niceties from Cutting-edge Analytic Solutions
Generating Business by Virtual Customer Support Arrangement
Ever-growing Collaborative Pedagogy on AI
Training
15%9%
5%
3%3% 1%
Side Note: Did you know?
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Think of it as a kind of institutional future-
proofing. It relies on two principles as old
as information technology itself. The first
principle is abstraction, which has been
defined as “inventing languages that let
us talk more nearly in a problem's own
terms and less in terms of the computer's
mechanisms or capabilities.”
That, in many ways, is the story of computing.
In the primordial days of the industry, using a
computer meant talking directly to the “bare
metal.” Programmers flipped switches or
configured wires, representing the raw ones
and zeroes of machine code. They specified
every tiny step the hardware had to perform,
right down to the precise register locations
and memory addresses.
It was painstaking, error-prone, highly
specialized and impossible to scale as the
speed and sophistication of the machines
grew.
Abstraction came to the rescue, freeing
programmers from the tedious details so
they could focus on the bigger picture. The
first stage of abstraction was assembly
language, which substituted words for
numerical machine codes. It was still deep in
the functional weeds, but easier for humans
to read and remember. Next came high-
level programming languages like COBOL
and Fortran, followed by even higher-level
languages like Ruby, Python, Perl and Visual
Basic.
Instead of directly talking to the hardware and
describing every elementary computational
step, programmers could specify the higher-
order tasks they wanted the computer to
accomplish – like rendering an image on
screen or indexing a file or creating a list.
There was no need to spell out the thousands
or millions of discrete operations that went
into performing those functions.
2. Future-proofing with abstraction & automationAbstraction came to the rescue, freeing programmers from the tedious details so they could focus on the bigger picture.
60%Automation is crucial for about 60% of organizations today.
Source: Tech Pro Research
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3. IT is still too artisanalIn fact, 85% of enterprise IT environments rely on a mix of manual processing, one-off scripts and other labor-intensive methods.
By buffering us against increasing complexity and flux, the abstraction-plus-
automation paradigm has helped make life livable in the information age. But
not all of the tech industry is tapping its full potential. Most IT departments, for
example, have at least one foot in an earlier era of manual methods. In fact, 85%
of enterprise IT environments rely on a mix of manual processing, one-off scripts
and other labor-intensive methods.
Many of those who do use automation are usually doing so in a piecemeal and
limited sense. They’re manually provisioning new servers with brittle scripts that
have evolved into a complex tangle of conditionals. They’re SSH-ing into machines
to directly update configurations. They’re mapping some UML-like application
model to a series of scripts that are supposed to configure the underlying
infrastructure for an application release.
That’s not the level of comprehensive and unified abstraction and automation
needed to manage increasingly intricate and fast-changing infrastructures. No
wonder IT shops are facing mounting backlogs, delays and costs, barely able to
keep older systems chugging along, much less satisfy the endless demand for new
services.
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3.1. Applying abstraction and automation to IT
Fortunately the same model that’s worked so well for computing can be applied to IT.
Just as programmers use abstract descriptions to specify what they want a computer
to do, sysadmins can do the same with diverse collections of IT resources, be they
applications, the services they use or the servers they run on. This practice is commonly
called managing your infrastructure as code or operating a software-defined data center.
If you have a sufficiently robust, standardized language for describing your infrastructure,
you can treat your entire infrastructure with the same degree of abstraction that
programmers benefit from. This includes everything from mainframes to load balancers
to cloud-based services, and from private data centers to public cloud environments.
Abstracting management across your infrastructure eliminates a huge amount of
complexity and multiplicity, making the work simpler, more uniform and easier to
understand, and facilitating better communication and collaboration.
Once you have a uniform description, you can apply automation. You just need software
that takes that high-level description and translates it into desired actions. Automation
dramatically simplifies and standardizes all sorts of IT processes, as these before/after
scenarios illustrate:
If you have a sufficiently robust, standardized language for describing your infrastructure, you can treat your entire infrastructure with the same degree of abstraction that programmers benefit from. This includes everything from mainframes to load balancers to cloud-based services, and from private data centers to public cloud environments.
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These benefits multiply when this approach is applied across the board, when all IT resources
are specified in a common language and wrapped in a comprehensive automation layer.
Companies that fully exploit the power of automation can deploy changes 200 times times
more frequently than the organizations that don't. And that means they have 200 times as
many opportunities to deliver better software to their users in the same amount of time.
3.2. Becoming more like a software company
In effect, you’ve turned your infrastructure into code. And that means you’re ready to take
advantage of the same efficiencies that make modern software development such a fast,
repeatable, and dependable process.
The payoffs include easier management of IT infrastructure, faster development and greater
resiliency in the face of change.
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The result of all this is that your IT operation becomes more like a leading-edge software company: able
to rapidly push out updates and new functionality to users, drive continual improvements and leverage the
sort of efficiencies that make companies like Google, Spotify and Amazon the envy of the industry.
One reason those companies are able to do the things they do is because they’re working with a relatively
modern and unified stack, something that enterprise IT departments, with their mixed arrays, could only
dream of in the past. Well, they don’t have to dream anymore because the combination of abstraction
and automation confers that uniformity, providing a common language and stable interface that hides the
underlying heterogeneity.
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Since you use a common language to describe what you want your apps, services and infrastructure to do, you can use the same language to help you adopt new software as well as maintain the old.
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4. Not just another waveSince you use a common language to describe what you want your apps, services and infrastructure to do, you can use the same language to help you adopt new software as well as maintain the old.
This isn’t the first solution aimed at managing complexity and change in IT. In fact, some of the most important IT trends today are partial stabs at the same problem. DevOps, for example, attempts to improve speed and predictability by
structuring and streamlining the often messy relationship between development and operations. Cloud computing outsources infrastructure maintenance and provides a clean, unified stack to work with. Containers simplify the provisioning and scaling of applications across processing resources.
These are all great, as far as they go. But each tackles only a piece of the problem. DevOps is just the latest in a long line of evolving cultural norms, and it won’t be the last. Cloud solutions only apply to your newer cloud-based applications, not your existing brownfield environments and legacy systems. 4 13
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The same goes for containers, which work best with newer, containerized microservices.
Taken alone, none of these solutions addresses the sheer breadth and diversity of real-world IT landscapes. But abstraction plus automation, applied broadly, does. It encompasses everything from aging mainframes to new cloud apps, providing a standard, simple, secure and scalable mechanism for delivering and operating all of the applications, services and infrastructure in your data center. Just as important, abstraction and automation are evergreen. It’s not just a temporary solution that will be swept aside by another wave in due time. Done right, it provides a platform for reliably delivering and integrating future technologies into your IT environment with minimal disruption.
Since you use a common language to describe what you want your apps, services and infrastructure to do, you can use the same language to help you adopt new software as well as maintain the old. So though the low-level technology is constantly evolving, you’re not constantly re-coding. And that goes not only for current technologies, but also for next-gen solutions yet to be imagined.
Just as important, abstraction and automation are evergreen. It’s not just a temporary solution that will be swept aside by another wave in due time. Done right, it provides a platform for reliably delivering and integrating future technologies into your IT environment with minimal disruption.
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5. Not all automation tools are alikeNote that when discussing these sweeping impacts, we’re talking about a particularly robust and comprehensive form of automation. While there are a variety of partial solutions that automate a limited set of tasks, the real payoffs come when you use a comprehensive approach. Look for a solution that provides the following:
• A common language that describes the desired state of all resources.
• Automation for the entire data center, from mainframes to containers, from physical to
virtual and from on-premises to cloud.
• Automation throughout the stack, including distributed apps, middleware and
infrastructure.
• Situational awareness, keeping you informed on the state of and changes to your
infrastructure.
• Change orchestration, providing detailed control and automation of ordered deployments
and change throttling, as well as real-time visibility as you push out changes to distributed
applications and global infrastructure.
• Inherent security and compliance with automatic policy enforcement, remediation and
reporting.
5.1. Constantly modernThe kind of tools we’re talking about aren’t pie in the sky. They aren’t aspirational. They’re
available now, and they’re already helping forward-thinking IT organizations realize the kinds
of results described above. Companies using best-of-breed automation solutions are far more
agile and adaptable, spending less time on firefighting and more time on innovation. They’re
able to deliver software 200 times more frequently, with 2,555 times faster lead times. They
spend 22% less time on unplanned work and rework, and 50% less time remediating security
issues.
Those are massive advantages, and the dividends accrue over time. A relatively modest
investment in automation today brings huge returns down the line. Not surprisingly,
companies who’ve gone all-in on automation are pulling away from their competitors at an
accelerating rate, and businesses still relying on older methods would do well to follow suit
while they can still close the gap.
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Companies using best-of-breed automation solutions are far more agile and adaptable, spending less time on firefighting and more time on innovation.
It’s the latest chapter of an old story. Automation has been transforming industries like manufacturing for centuries, upending the status quo and enabling whole new economies of scale. Now it’s IT’s turn for an industrial revolution, and there’s no going back.
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