automate i&o to answer digital disruption€¦ · automate i&o to answer digital disruption...

Automate I&O To Answer Digital Disruption Part 1 Of The Automation Manifesto Series

by Jean-Pierre Garbani, Amy DeMartine, Michele Pelino, Dave Bartoletti, Wolfgang Benkel, and William Martorelli with Eveline Oehrlich, Naveen Chhabra, and Megan DoerrAugust 6, 2015

FOr INFrAstruCturE & OPErAtIONs PrOFEssIONAls

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Key takeawaysProduction Volumes Mean That I&O Must Adopt AutomationI&O pros must make a fundamental change to their production models. they must think in terms of automation rather than continuing to use manual approaches.

Artificial Intelligence Improves I&O Automation Solutionsself-healing, self-adapting systems based on predictive and forecast behavior are now a reality. this makes complex artificial intelligence applications possible.

Automation Must Yield Business BenefitsAutomation optimizes and streamlines the production of business services. It makes them better, faster, and cheaper. But these are I&O benefits, not business ones. You must prove that a wonderful experience helps win, serve, and retain customers.

Why read this reportBefore commercial computing became the norm in enterprises, manufacturing companies implemented industrial process control solutions based on analog and then digital computers to automate processes performed by skilled trade workers. People could no longer perform repetitive tasks accurately and fast enough. today’s infrastructure and operations (I&O) organizations face an identical problem: Digital disruption is pushing the limits of what is humanly and financially manageable in data centers. today’s automation solutions answer the fundamental issues of scale, speed, costs, and repeatable accuracy that I&O organizations must resolve to stay competitive. this report is the first in a series on automation to inform I&O pros of the current market and how they can automate specific domains of technology management production to help win, serve, and retain customers.

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table Of Contents

Digital Disruption Drives I&O’s Need For Automation

Automation Combines Machine Speed With Human Knowledge

From Deterministic to Heuristic: the Future Of Automation

Automation Addresses Issues Such As Scale, Speed, And Cost

solutions use Different types Of Knowledge For Different tasks

Automation Can Help With Both low-level And Complex Processes

today’s solutions Can Automate Workloads, App releases, And Cloud

Avoid Automation Pitfalls

Sell The Broader Benefits Of Automation Tools To Your Business

recommendations

Don’t Hesitate — Automate!

Notes & resources

this report is the result of numerous briefings with software vendor companies, users, and potential clients of automation products and the experience of the Forrester I&O analyst team.

related research Documents

Five Data Center And It Infrastructure lessons From the Cloud Giants

the Forrester Wave™: Application release Automation, Q2 2015

systems Of Automation Will Enrich Customer Engagement

FOr INFrAstruCturE & OPErAtIONs PrOFEssIONAls

Automate I&O To Answer Digital DisruptionPart 1 Of The Automation Manifesto Series

by Jean-Pierre Garbani, Amy DeMartine, Michele Pelino, Dave Bartoletti, Wolfgang Benkel, and William Martorelliwith Eveline Oehrlich, Naveen Chhabra, and Megan Doerr

August 6, 2015

http://www.forrester.com/go?objectid=RES101601






http://www.forrester.com/go?objectid=BIO776









For InFrastructure & operatIons proFessIonals

Automate I&O To Answer Digital Disruption part 1 of the automation Manifesto series

august 6, 2015

© 2015 Forrester research, Inc. unauthorized copying or distributing is a violation of copyright law. [email protected] or +1 866-367-7378

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Digital Disruption Drives I&O’s Need For Automation

today’s digital disruption is resulting in smarter and smarter devices, an explosion of business services, and increased complexity for I&O professionals. to date, I&O has mainly responded by adopting virtualization, scripting some basic management tasks, paying lip service to cloud computing, and increasing headcount. However, efforts are preventing organizations from responding to productivity issues. to tackle the digital disruption challenge, I&O pros must make a fundamental change to their production model: use automation to increase speed, reliability, and predictability.

Automation Combines Machine speed With Human Knowledge

Machines are fast, accurate, and dumb. Humans are slow, erratic, and brilliant. In its simplest form, automation combines the speed of machines with the brilliance of humans, transforming a manual process into one that produces the same (or better) results without human intervention. What is a process? In generic terms, it is:

A series of actions using specific methods or procedures that leads to a particular result.

A workflow describes how information is routed and transformed to complete a process; it’s a predefined pattern of actions through which a product or information flows. In information systems workflows, a combination of applications and human resources perform each action.

For example, when an administrator applies a patch to a server, each action is well defined in terms of input, task, and expected result (see Figure 1). You can easily automate this process by:

› Using simple scripts. A script can perform each task or action by following guidelines such as “server name;” it then launches the required operations for each action until it completes the process.

› Building an automation software solution. A software solution can perform each action with specific software routines that you can assemble to form a completely automated process. You can then place routines in a catalog and reuse them to build other processes.

An action is the basic building block of an automation tool. Its architecture usually includes (see Figure 2):

› A trigger that launches the desired action. this trigger can be a manual intervention, a simple event such as a threshold being crossed, a complex event caused by an analysis of multiple events, or a calendar event such as a date or a time. It can also be the input from another action. For example, an Internet of things (Iot) device can identify triggers by analyzing inputs such as a person’s identity, status, and location from sensors and location-based technologies.1

› An analysis of the action. using the parameters passed in the message sent to the software routine, analysis will determine how the action is launched and the expected result.

› A software routine that executes each action. this routine is constantly monitored for completion and the result analyzed for success or failure by the action software. this analysis can, in turn, trigger further actions.



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figure 1 Example Of A simple Automated Process: Patching A server

STOPSTOPSTOP

Quit

Approvechange

Checkconnectivity

Stoptransactions

Declusterserver

Stopmonitoring

Installpatch

Create ticket

Create ticket

Create ticket Enablemonitoring

Reclusterserver

Reboot

figure 2 An Action Is the Basic Building Block Of Automation

Ana

lysi

s

Action

Human inputs(rules)

Trigger Result

Automation building block

Success

Failure

Monitor



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from Deterministic To Heuristic: The future Of Automation

We apply most forms of automation actions to tasks and processes, where the action software routine, the initial state, and the trigger inputs determine the results. While this is well suited to repetitive, pre-established tasks and processes that are time-consuming (and not terribly interesting), another branch of automation is moving toward using more sophisticated analytical algorithms based on AI (artificial intelligence): heuristic automation (see Figure 3). technology developments in terms of speed and capacity mean self-healing, self-adapting systems based on predicting behavior are now possible.

I&O pros will use heuristic automation applications for data analysis, pattern recognition, self-learning systems, and decision support, which can eventually lead to solutions such as self-healing systems. A heuristic solution based on artificial intelligence is difficult to implement but may require little maintenance, as it adapts itself to the environment. We see two broad categories of AI applications:

› Solutions using predefined and structured data samples. Most self-learning solutions fall into this category. the solution analyzes patterns in the data sample, sometimes against thresholds and parameters dynamically set from historical data, and “learns” what the corrective action should be; it can then automatically apply the corrective action each time it detects the pattern. this continuous enrichment of the knowledge base is the foundation of self-learning and self-healing automated solutions, which vastly improves the quality and speed of incident and problem management processes.

› Solutions applied to unstructured data. they continuously explore data that has no predefined meaning or structure to determine patterns using sophisticated algorithms. the patterns these solutions find help with decision-making and eventually lead to self-learning solutions, which is helpful when analyzing data from multiple, seemingly unrelated sensors. the Internet of things, which collects data from industrial machinery, consumer appliances, or environmental parameters such as pollution levels, is certainly fertile ground for automating complex processes. tech management could also use these solutions to automatically assign resources to workloads for application orchestration.



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figure 3 An Example Of A Heuristic Automation Building Block

Act

ion

sele

ctio

nan

alys

is

ActionEvent

Knowledge base

Pat

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Seeding mechanism

Automation Addresses Issues such As scale, speed, And Cost

Now is the perfect time to promote automation: Budgets are tight, technology and business service complexity is increasing by the day, technology components are growing exponentially, and qualified skills are scarce. Compounding these problems is the energy that I&O pros waste on housekeeping tasks. Automation can address issues where I&O organizations are:

› facing issues of scale and speed. systems of engagement require massive upgrades in computing, network, and storage to accommodate the onslaught of data collected from myriad user interactions. But with this increase in volume comes the need for an increase in speed: As application development groups are tasked with delivering continuous updates to business services, I&O must provide the delivery and production chain infrastructures to support them. this requires an enormous amount of provisioning, configuration, and verification work, which I&O cannot humanly provide in time.2

› Pressured by cost containment and productivity increases. As business processes become more and more automated due to the onslaught of business services, I&O needs to keep up with the availability and performance of applications and infrastructures. Automating parts of the incident and problem management processes as well as introducing a better decision support solution will increase I&O staff productivity.



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› Unable to resolve their skill shortages. I&O pros sometimes must perform multiple tasks that are way below their skill level. Automation is the perfect solution for simple, well-defined tasks, such as server provisioning; the commoditization and standardization of servers mean administrators add little value.

› responsible for improving process accuracy and repeatability. unlike humans, a machine will always perform the same way. Machines are impervious to fatigue, external inputs, emotions, and all the other distractions that make humans error-prone. Once you’ve successfully automated a process, a machine can perform it repeatedly with the same level of accuracy, while human errors are still a major cause of technology failures.

› Trying to cope with diversity and complexity. Data centers reflect the rapid evolution of technology: Many projects are built on platforms that are obsolete by the time they enter production. I&O pros manage these diverse technologies by using complex middleware and integration solutions. Automation can also help you manage this diversity by providing actions that are tailored to each platform under a unified user interface.

Solutions Use Different Types Of Knowledge for Different Tasks

Explicit knowledge is what you can effectively explain and write down in a document, while tacit knowledge is the result of many inputs that lead to decisions that are sometimes difficult to clarify logically; artistic skills are an example of tacit knowledge. I&O processes use explicit knowledge, tacit knowledge, or a mix of the two.3 Automation uses corresponding solutions; for example:

› Pure deterministic solutions use explicit knowledge. these solutions are typically triggered by a known event. For example, simple backups performed at specific times are usually pure deterministic functions.’

› rules and policies use a mix of explicit and tacit knowledge. For example, workload automation and its derivatives (such as release automation) use some tacit knowledge to create rules and policies that guide different actions. the rules and policies are based on the experience and know-how of I&O professionals to help them analyze events and select the right action.

› AI uses tacit knowledge for pattern recognition and self-learning. Heuristic automation is the embodiment of tacit knowledge. While there are few operational examples of this type of solution in today’s market, some will probably appear in 2015. the most interesting applications for I&O touch predictive analytics and forecasting, especially when used with orchestration and cloud infrastructures. systems of engagement will be the first to benefit from a better controlled customer-level performance.



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Automation can Help With Both Low-Level And complex Processes

today’s I&O organizations should:

› Use deterministic solutions based on explicit knowledge for low-level I&O processes. Deterministic solutions tend to be easy to implement but may require constant maintenance, as they are tightly coupled to specific infrastructures that evolve with time. these processes consume server, network, and database administrator resources. Most are repetitive and follow a well-defined and documented workflow but require manual intervention to feed the right information to the right tool. scripting has helped automate some of these manual tasks, but maintaining and updating scripts can be a daunting task, especially when it involves other people’s scripts. A graphical interface could easily describe low-level processes, such as patching a server or feeding files into a data warehouse — and make maintenance and adaptation easier. It can also monitor the accuracy of execution — unlike scripting, which doesn’t provide execution reports. low-level process automation can dramatically improve the ratio of administrators to servers or databases. Process automation thus brings both a technical advantage — it’s much easier than scripting — and an economic advantage — it saves time and improves accuracy.

› Use mixed solutions for more complex processes. Incident and problem management process relies on the operations center being able to quickly identify the criticality and root cause of the problem — and either implement a known correction or escalate it to the right level 2 person. You can use process automation at that level to automate launching tests and collecting information from multiple sources. Pushed a step further, it can transfer the right information to the right person in level 2 support and launch the forensic tool that this person needs to diagnose the problem. today’s public cloud platforms operate this way. there’s no way to manage an on-demand, self-service cloud platform that delivers resources in minutes using a collection of people running scripts, whether it’s public, private, or combination of the two. Cloud delivery depends on a standardized set of self-provisioning, self-scaling, and self-healing components.4 Model- and policy-driven automations are abstracted from the underlying infrastructure yet are not completely self-sufficient (see Figure 4).



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Today’s Solutions can Automate Workloads, App releases, And cloud

I&O can benefit from automation solutions that manage batch computing, automate application release, orchestrate and manage virtual infrastructure components, provision new components, manage the configuration of and changes to the data center infrastructure, and distribute patches and new software versions. these are generally deterministic and mixed automation products. today’s off-the-shelf solutions can help you with:

› Workload automation. the information that magically appears on our smart devices depends on our ability to organize, sort, normalize, process, and transport masses of raw data. this is the product of workload automation: a software solution that is able to schedule, launch, and control the sequence of operations that mostly consolidate and update data sources. Workload automation, the latest evolution of job scheduling, is able to track down the execution status of thousands of job steps, control resources, and backups, and react to external and machine events with calls to other automation solutions such as server and virtual machine provisioning.

› Incident, problem, and change management. today’s quality of service is dependent on resource provisioning, configuration accuracy, alignment of development and production environments, and the quality of the code put into production. remediation is a sequence of operations that can be described in a workflow but requires strong analytics to be fully automated. We are now seeing credible efforts to create heuristic algorithms which, coupled with self-learning capabilities, expand to real preventive analysis and eventually to forecast analysis. this will link incident and problem automation to provisioning and orchestration.

figure 4 the relationship Between Knowledge And Automation

Automationsolution type

Knowledgerequired

Implementationeffort

Deterministic Explicit Easy

Mixed Explicit with tacitknowledgerepresented by rulesand policies

Function ofimplementationscale

Heuristic Tacit High: requirestraining andseeding of solution

Skill levelrequired

Applicationexample

High

Medium

Low

Maintenancelevel

Low

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Specialist

Patchdistribution

Workloadautomation

Self-learningand self-healingincident process



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› Application release automation (ArA). Application developers are using Agile practices to speed the development of apps, resulting in faster, smaller releases that require application release automation. this means that you can implement a well-defined process in a new environment in the public cloud, install and configure any middleware software, and install and configure an entire application or any changed part of the application. ArA tools also offer release pipeline views, giving release managers visibility into which environment a specific version of the release is in.5

› Orchestration and virtualization management automation. these automation solutions ensure the optimum performance and resource utilization of applications running in virtual machines by reallocating resources on demand and generally avoiding potential conflicts at the physical layer of platforms. today there’s mostly a mix of deterministic and basic heuristic solutions using a definite set of variables and rules and policies, but they should evolve into complete heuristic-based solutions, as the problem of resource usage forecasting requires more than a limited set of machine-oriented parameters.

› configuration automation. One of the more mature automation solution areas is infrastructure and application configuration. Over the last 10 years, infrastructure-as-code (IaC) solutions have brought model-driven automation to configuration processes. standardized models representing desired states are placed under version control, stored in repositories, and called programmatically. scripts are simple documents, but a Puppet manifest or a Chef recipe is more like code, and managing them like code saves time and reduces errors and yields immediate benefits in consistency, roll-back, and auditability.6

› cloud automation. Building on configuration automation and integration with ArA tools, cloud management and automation solutions orchestrate the selection, configuration, provisioning, scaling, protection, and governance of infrastructure and application components running in public, private, or hybrid cloud environments. they extend ArA tools beyond the release phase of the software development life cycle to automate life-cycle processes (start, stop, scale, reconfigure, monitor, etc.) for cloud apps and infrastructure. these emerging solutions, available from a wide range of vendors, generally include a self-service request portal, methods for building standardized services across multiple clouds, and a policy-driven governance engine to automate a wide range of life-cycle operations.7

› IoT software platform automation. Automating, connecting, and controlling physical systems with software involves complex, task-, or industry-specific technologies. Iot software platforms simplify the process of developing, connecting, controlling, and capturing insight from connected products and assets. these Iot platforms include functions such as connecting to the fragmented array of wireless and wireline networks, interfacing with analytic solutions, and incorporating device monitoring tools. In addition, platforms help standardize the application development processes, which will ultimately result in lower prices and faster time-to-market for automated Iot solutions.8



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Avoid Automation Pitfalls

Automation is a matter of economics. If a data center has 10 servers, it doesn’t make a lot of sense to invest great chunks of budget into automating their administration. In a data center with 100 servers, automating is debatable: hiring a second administrator may prove to be more economical. At the 1,000-server mark, it’s no longer a question: You have to automate patching, updating, and configuring tasks. these are the two basic tenets of automation: the job at hand has to be an automation candidate (e.g., boring) and it has to make financial sense and eventually benefit the business. to avoid common automation pitfalls, you must:

› Have a strategy. Automating each new thing with the tool it comes with or by tweaking something you’ve already got is going to mire you in yet more complexity. Without an automation strategy and automation architecture, you end up with just a bunch of scripts only a few gurus know how to operate and maintain.

› Avoid automating for the sake of automating. Analyze the expected value versus the cost of implementation and maintenance of the automation solutions for the problems you’re trying to solve. Identify simple metrics to measure automation’s value, such as time-to-delivery, frequency of software releases, and time-to-remediation.

› carefully select an automation solution. Many products on the market today are very specialized solutions: they only do one thing well. In selecting a solution, you must understand the vendor’s long-term strategy and whether it’s actually considering a deep and broad engagement in automation or just pushing a one-off solution that’s a stepping stone for its product portfolio. Make sure your automation solution strongly encourages abstraction, reuse, and third-party extensions. You don’t need another tool to configure a new version of linux; you need a platform that helps you configure operating systems.

› Avoid simple scripting at all costs. scripting alone is not enough automation. scripting is a way to quickly execute a very specific (usually imperative) operation, and the script should not survive that execution. A collection of scripts is not an adequate automation platform because: 1) scripts can be opaque and difficult to maintain (as they are very explicit in nature, they are brittle and break easily); 2) they require specialized knowledge to create and understand; and 3) their execution is not well controlled (and therefore they can cause a lot of damage).



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sell the Broader Benefits Of Automation tools to Your Business

A major obstacle to the adoption of automation has always been the difficulty of showing direct business benefits. Automation provides a better way for I&O pros to manage systems of record and systems of engagement, but this just streamlines and optimizes the production of business services: the services may be more reliable and cheaper, but from a pure business productivity standpoint, they are not better. By optimizing its traditional services of application deployment, infrastructure sourcing, and service management, I&O is just meeting business expectations, not improving the business itself.

the business’ perception of technology capabilities has evolved with usage. Fifty years ago, technology was mostly unknown outside of a restricted circle of specialists. today, technology is so common as to be seemingly understood by every smartphone user. the danger in this is that the business no longer perceives the complexity of assembling and delivering business services as a justifiable obstacle to providing sophisticated business services. thus, I&O pros should show the business:

› The economic benefits of automation. these benefits will come from keeping the business competitive by providing a better (more scalable) and faster (application and infrastructure delivery and sourcing) service, which will in turn improve customer experience. Also stress that you can transfer budgets from the maintenance and support of existing services to innovation and creation of new services, which will enhance the business’ image.

› The way automation will fit within the overall technology strategy. Hopefully, I&O and CIO organizations have devised a strategy based on new technologies for systems of record and systems of engagement. You must present automation to the business as a solution that fits into today’s organization and supports tomorrow’s technology management evolution.

› The impact automation will have on governance, personnel, and overall skills. You must examine how automation will affect the different areas of technology management. For example, how will it affect I&O personnel and training requirements?9 What will your admins do once their tasks have been automated? You must have an answer for that or you’re dead in the water. No one wants to assemble the robot that takes her job.

› When it will see the benefits of automation. Patience is not one of today’s virtues. In technology management, the long term is sometimes measured in months, not years. thus your automation project proposal should set expectations that are in line with the pace of digital disruption and show how it converges with other major projects in technology or business services.



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recommendations

Don’t Hesitate — Automate!

Most I&O leaders are close to breaking: they are throwing people at the problem by increasing their tech management staff in step with their increase in business services. this may provide some respite, but budgets and human resources are subject to the law of diminishing returns, and this strategy will simply delay the inevitable. the growth in complexity requires that I&O organizations close their management gap and put in place solutions that will make it possible to filter the complexity so that it becomes controllable and manageable. When considering automation:

› Don’t believe that you’re special. too often, organizational resistance stymies automation efforts: “Our systems and processes are just too specialized and complex to be automated!” that excuse is quickly losing merit. As more and more cloud services are able to augment or replace even the most complex data center software and technology, it’s no longer a valid excuse to claim something is just too complicated to be automated. Yes, your current email backup processes can be automated . . . and should have been long ago.

› Don’t do it alone and don’t reinvent what’s already available. A vibrant and active community of open source vendors and a wide range of open source automation tools exists today. Cloud platform leaders increasingly share the tools they build to run their own large elastic infrastructures. And many automation platform vendors already support open source and other community extensions to their solutions. leverage what exists and extend it to your needs wherever you can — don’t invent from scratch.

› Don’t take any claim at face value. We have made enormous progress in AI and in the concept of heuristic automation. But it is difficult to believe that the monster applications that have been built over the decades can be tamed with simple parameters, rules, and policies. We are now developing computing infrastructures that provide just enough horsepower to propel automation in the early stages of heuristic solutions, but apply the “caveat emptor” rule to any pie-in-the-sky claim.

› Don’t be shy: Partner with specialists if needed. Many specialists, automation vendors, consulting groups, and service providers are developing automation solutions and services. they can help you not only implement products but also acquire the skills needed to see the larger picture.



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Endnotes1 For more details on the Internet of things and trigger events, see the “Inquiry spotlight: Five Ways to Energize Your

Business With the Internet Of things” Forrester report.

2 For more information on how the requirement for delivery speed and quality is affecting I&O professionals today, please see the “What Makes Modern service Delivery Modern?” Forrester report.

3 source: “the Different types of Knowledge,” Knowledge Management tools (http://www.knowledge-management-tools.net/different-types-of-knowledge.html).

4 For more information, see the “Five Data Center And It Infrastructure lessons From the Cloud Giants” Forrester report.

5 For more information on release pipeline views available through ArA tools, please see the “Market Overview: Application release Automation tools” Forrester report.

For a product comparison between these ArA products, please see the “the Forrester Wave™: Application release Automation, Q2 2015” Forrester report.

For an outlook on the adoption rate of ArA tools, please see the “Brief: Application release Automation Market Forecast” Forrester report.

6 For a description of IaC tools, see the “Gear up For Modern service Delivery” Forrester report.

7 For an overview of the key capabilities to look for in a cloud management solution, see the “Cloud Management In A Hybrid Cloud World” Forrester report.

http://forr.com/1einFan

http://www.forrester.com/Analyst-Advisory/-/E-MPL172
















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8 For insight into how Iot software platforms are simplifying the process of developing and deploying smart, connected products and retrofitting existing equipment, see the “Internet-Of-things software Platforms simplify transformation Of Business Operations” Forrester report.

9 source: Nicholas Carr, The Glass Cage: Automation And Us, W.W. Norton & Company, 2014.



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