arago AutoPilotEfficient and flexible through automated IT operations V 3.3

The arago AutoPilot

A business model that adjusts to our customers’ needs, “a step beyond ROI”

Market environment and market requirements

Today’s market requires perpetual motion and a groundbreaking

innovation. For that we offer• Complete flexibility of costs • Continuous improvement in service

Ever increasing number of applications & growing

dependence on IT availability

Growing complexity of applications as a result of

networking and distribution

Demand on quality with simultaneous cost

pressure

Time

Markets respond quickly to changes –IT is often lagging behind market developments!

Challenge: Flexible markets, inflexible budgetsB

usin

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Time

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What is lost?Work IT

Knowledge is stored in individual items that can be connected together as required to form a process.

The relevant process is therefore carried out automatically step by step.

What is knowledge-based automation?

The arago AutoPilot in four sentences

1. The arago AutoPilot is a knowledge-based system which automatically deals with system operations tasks.

2. AutoPilot carries out its assigned tasks by dynamically creating a “script” from a knowledge pool in order to solve a specific task.

3. AutoPilot helps companies meet compliance requirements through comprehensible, transparent IT operations.

4. AutoPilot facilitates affordable, flexible and individual IT service management with full documentation.

One step beyond ROI

The arago AutoPilot does not have any licence or maintenance costs.

The arago AutoPilot is only paid for work performed, i.e. the costs are adapted to the development of business.

The costs for the work performed are about half of the costs of manual labour.

Calculation example - basis

Jahr 0 Jahr 1 Jahr 2 Jahr 3 Jahr 40%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

18%24%

36%48%

Savings vs. cost of the AutoPilot

Series5EinsparungKosten AutopilotKosten ArbeitsumgebungAutomationsgrad

Co

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The costs are continually reduced by the transfer of know-how to the AutoPilot. The costs of the work environment are reduced with the work to be performed manually.

SavingsCost AutoPilotCost work environmentCost workAutomation degree

Year 0 Year 1 Year 2 Year 3 Year 4

The costs are adapted to your company!

The costs for tasks carried out automatically are determined by the actually incurred costs in your company for manual tasks.

If these KPIs exist in your company, the automatic handling of the tasks is priced at precisely 50% of previous expenses.

If these KPIs are not available, an independent benchmark will be used and expenses will be 70% of the benchmark.

Thus the AutoPilot always adds value and only costs when in action.

Are there preliminary investments?

Project work, consulting, introduction and training are on expense bases.

Time should be invested for employees to learn the knowledge transfer by ensuring constant improvement in automation.

Expenses are an integrated part of each and every project. But in contrast to other projects, upfront investments in licences or other ongoing maintenance are not necessary.

We live the win-win principle

Your motivation• The more you automate, the more you save. • The more knowledge you transfer to the AutoPilot, the more you automate.

Our motivation• The better our software works, the more we earn. • The more knowledge is available to the AutoPilot, the more is automated, the

more we earn.

Your risk• If the rate of automation is too low, you have wasted your manpower – We

work to avoid this using our introduction concept (pilot) that reviews targets reached at a very early stage.

Our risk• If the rate of automation is too low, we earn nothing at all. With that we

therefore bear almost all the financial risk of reaching our common goal.

The arago AutoPilot: Cost model

Gain share

Fee is payable only for tasks carried out automatically (tickets).

Fee is based on the costs for manual processing at the client and is 50% of this.

This means that the ROI is always 100%.

The ticket price is adjusted in line with the price for manual processing.

Payment is due only when AutoPilot does what it promises.

Licence

One licence is required per physical or virtual server that can be operated using AutoPilot.

The licence fee is divided into three categories (S,M,L) and is determined on the basis of the server size and the criticality of the processes run on that server.

We offer the licence model to provide access for companies with inflexible budget systems.

Enhanced quality with the AutoPilot – actually more important than cost reduction

Cost reduction

Single point of administration: tool complexity is reduced, thus less administrative cost

Routine tasks, standard tasks are carried out autonomously with low personnel effort

Automated reactive and proactive working results in low costs for IT operations

Optimum quality

Higher number of users per application / transaction system

Improved transparency and automated documentation of operations

Higher availability of the business-critical applications

Automation is the trigger for your positioning

Reduced operating costs with optimised service quality at the

same time

IT experts are deployed in a targeted manner for business

change

Archiving of knowledge protects against dependence and crisis

cases.

Effects of the arago AutoPilot in sample scenarios

Cost reduction potential in figures - initial situation

1,429 services of varying complexity are operated.

SLAs guarantee an availability of 99.98%.

All tasks (changes, major incidents, minor incidents, service requests, problems, capacity action, availability action) are recorded. All tasks have similar weighting in the example.

A total of 106,859 tasks were recorded in 2010.

Cost reduction in figures - real operation at arago.

Jan 10

Feb 10

Mar 10

Apr 10

May 10

Jun 10Jul 1

0

Aug 10

Sep 10

Oct 10

Nov 10

Dec 10

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

0%

10%

20%

30%

40%

50%

60%

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100%

Distribution of work at arago´s WebFarm operations

ManuellAutomatischAutomationsgrad

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arago’s automation procedure is well-established for 12 years. A degree of automation of 93% is achieved!

Manual

Automated

Automation degree

Jan 10 Feb 10 Mar 10 Apr 10 May 10 Jun 10 Jul 10 Aug 10 Sep 10 Oct 10 Nov 10 Dec 10

Cost reduction potential in figures -How is the degree of automation translated into FTEs?.

Under the assumption that the overhead in the team does not change, 112 FTEs would have to be employed to carry out everything without automation. With automation that 8 expert FTEs are sufficient.

ohne Automation 30% Automation 50% Automation 80% Automation arago (93% Automation)0

20

40

60

80

100

120112

78

45

22

8

FTEs experts

FTEs Experten

1429 Services106.859 Tasks p.a.

Without automation

30% automation

50% automation

80% automation

arago (93% automation)

Without Automation 30% Automation 50% Automation 80% Automation arago (93%

Additional benefit: significantly lower processing time

As the need for internal communication is vastly reduced (the AutoPilot can act without the need for coordination processes), only half of the implementation time otherwise required is needed.

Administration5%

Team communica-tion45%Customer commu-

nication15%

Technical anal-ysis25%

Troubleshooting10%

Time spent on troubleshooting

Introduction of the AutoPilot

Development of trust and

reduction in risks

1. It is provable that you can extract the solution for a specific task from a knowledge pool using an algorithm (inference engine).

2. The computing time of such algorithms is, however, practically infinite.

3. What’s special about the engine in the arago AutoPilot is that (similar to when cracking an encryption code) only a small part of this calculation needs to be carried out in order to reach the correct decision.

The functionality has been tested and has been certified by TÜV Rheinland (tested annually).

Trust in innovative technology

The standard introductory model

The pilot incorporates the installation, the “on-the-job” training of the client’s team and the implementation in the pilot implementation.

Continuous improvementTime to value

OperationRoll OutPilot

Why a pilot as initial training?

1. The pilot is carried out in a sub-area of your IT environment that currently entails a high level of outlay and appears to be suitable for a pilot test, as the relevant changes are measurable, for example. Objectives will be defined in advance and monitored at the end of the pilot phase.

2. The pilot takes place in your environment and is carried out by our experts in collaboration with your staff and lasts from 4 to 8 weeks.

3. The AutoPilot necessitates a change in work tasks, which can be best achieved in an existing and transparent environment.

4. Your own employees can motivate other colleagues substantially better during a roll-out than external staff can.

5. The toll on internal personnel is kept to a minimum.

Indications for selection of a pilot environment

Vertical

Suitable pilot environment

Generally an application consisting of various different components that currently poses operational challenges but is not business-critical.

In such an environment, as many teams as possible come into contact with AutoPilot.

Horizontal

Unsuitable pilot environment

E.g. a farm of 100 UNIX servers

In such an environment, AutoPilot and the relevant knowledge remain isolated, which does not allow for a knowledge-based approach.

............

The AutoPilot: Learning process

The AutoPilot: Learning phases

Automation already exists?

Why a new way is needed!

Every IT operator has automated something at some time or other

To automate a boring activity that has already been carried out 1,000 times,

a script is written:

And with time, scripts are extended by adding options (decisions) in order

to be able to cover more cases.

This type of automation has three limitations:1. Limited validity

Each script is made for a particular task. If appropriate preliminary conditions are met, the script carries out the task in full. Like on an assembly line!

As IT is constantly changing, the tasks and scripts must change as well.

This change entails large administrative and maintenance costs.

A collection of scripts soon becomes a central tool.

The function is guaranteed only with a precisely defined task.

Constant adjustments make scripts complex & administration more difficult

This type of automation has three limitations:2. Limited reuse of knowledge

In scripts, identical or similar sub-steps are frequently carried out in the solution

of different tasks.

Changes to existing scripts make the reuse of the same parts of a library more complicated and increase the administration complexity.

Necessary abstraction increases development costs.

Scrip

t 1Sc

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So as not to write exactly the same sub-steps more than once, they must be stored in a library. The reuse with similar sub-steps ensures additional complexity.

This type of automation has three limitations:3. Limited flexibility with networked knowledge

The simple scripts have long been written!

To achieve an improvement in operations, the knowledge of several experts / areas of competence must be combined.

This is the reason why you should never change a running system.

This is the reason why IT operations reacts to new requirements slowly and with great effort.

Firewall Net DB

When an expert wants to make changes in his area, he cannot do this without the other experts – because the scripts have to be adapted.

Summary:The three limitations of current automation

1. Limitation of applicabilityCurrent automation is like an assembly line. It necessitates that it has the right task on hand, which it then carries out by direct means to achieve the desired result. The attempt to soften this limitation results in complex procedures that are difficult to maintain.

2. Limitation of the reuse of knowledgeCurrent automation is comprised of firmly defined processes. Even if parts of the processes can be used more than once, they regularly appear in individual processes.

3. Limitation of flexibilityCurrent automation is created in collaboration between several experts. If changes are necessary, the same experts or at least the same competencies have to be called together. The more interlocked the knowledge and the more interlocked the automation per se, the more difficult a change becomes (“Never change a running system”).

What does the IT market offer as a means of bypassing these restrictions?

Work that is carried out entirely automatically• Automatic reaction for highly specialised application cases

e.g. cluster software, etc.• Automatic fulfilment for tasks that can be extremely standardised

e.g. data centre automation, automated provisioning, etc.

Tools used by the expert to make work easier• Automatic preparatory work for the manual implementation of the actual task

e.g. event correlation, event aggregation, root cause analysis, etc.• Automatic sequence, after individual decisions

e.g. automated remediation, etc.

Tools with which automation mechanisms are administered or work is delegated to unqualified personnel

• Administration tools for the administration of standardised processese.g. run book automation, etc.

• Administration tools for proposals / processes with manual worke.g. knowledge repositories

Despite an abundance of automation tools, the workload of experts is constantly increasing.Why?

Human experts achieve the better results

People carry out a great bandwidth of tasks• Unlike an assembly line, an expert reacts flexible to tasks. Where automation

is dependent on precisely standardised specifications, people can address similar tasks or tasks with other prerequisites.

People initially use the knowledge that is already available• An expert always works with the knowledge that he already has. Reuse of

experience is the basis for human activity.

People coordinate with one another in the event of questions or changed boundary parameters.• People react to changed environments either by using other experience or

by coordinating with other experts. The same applies if new questions arise during the work, e.g. due to a lack of initial information.

Human experts have limitations too I

Limited transparency• Tasks are often carried out under pressure. This inevitably results in a

lacking documentation. And the same expertise is required again to reconstruct the actions of an expert.

Limited availability • A person can only ever carry out one task absolutely simultaneously. The

number of experts is limited. Therefore the availability of appropriate expertise can never be guaranteed fully at compatible costs.

Human experts have limitations too II

Limited loyalty• A person can change employers. The great expert knowledge leaves with

him and thus not only the manpower but also the knowledge about implemented automation is gone.

Limited “desire” to carry out “machine jobs”• The greatest strength of people is their creativity and their urge to do

something new. This is not used when they are deployed as IT experts who constantly solve the same problems. This creates frustration and its consequences in the medium term.

A machine (not a tool) that works like a person is therefore required. But how does a person work?

Breakdown of human activity

Information basis

Information basis

Information basis

Task

Infoextraction Analysis

Infoextraction Decision

Inmplementation ControlVerification

Information basis

Task

Action

If a person works in a structured manner to deal with a task, he uses this or a similar process. In the process, he deploys his knowledge that he uses with different methods.

Example of human activityExample applicationKnowledge Knowledge app (method)

Knowledge

Acqu

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Actio

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Identify task

Analyse log file

Interpret logs

Plan extension

Check feasibility

Carry out extension

Check result

Conclude task

Example of human activity:knowledge, method, applicationKnowledge:• The pool of experience is the basis

Method:• The experience can be used in different ways

Anwendung:• A person generates a dynamic “script” in “real time”

1. Identifying task A conscientious person checks (e.g. by further enquiries or comparison) whether he has understood a task correctly and (e.g. through comparison of experience) whether he believes that he is capable of dealing with it.

2. Carrying out analysis (repeat if task not completed starts here) With any given task and the given information, a person carries out an analysis as to which knowledge or experience he has at his disposal to deal with the task. If more information is available, more experience can be used.

3. Making a decision Based on the insights gained in the analysis, the person makes a decision on which action he intends to carry out (which knowledge he wants or is able to use).

4. Carrying out an action Based on his decision, the person carries out the desired action. In the process, he adapts his standardised knowledge (his experience) to the specific environment (the context) in which work is currently being done.

5. Checking result (if task has not yet been fulfilled, back again to analysis) A conscientious person always checks the results of his actions. Did the action work? Did it provide the desired result? In this way, he also gains information about which other knowledge he could use.

6. Concluding task If the goal defined in the task is fulfilled, the person concludes the task. This usually includes the corresponding communication.

Summary: How do people work?

The tools for people

The IT expert must fulfil three requirements in order to support an IT environment:

He needs information on “WHAT NEEDS TO BE OPERATED?”He needs information on “WHAT THE STATUS OF THIS ENVIRONMENT IS”He must have the corresponding “EXPERT KNOWLEDGE”

ENVIRONMENT RESULTSPERSON

Expert

Knowledge

What needs to be

operated?

What is the status?

Actions

Documentation

He can then generate all required results (fulfilment of the tasks given to him in the form of changes, incidents, problems, …). These are then implemented as actions and documentation of these actions.

The arago AutoPilot

The “computer colleague”

The tools for the AutoPilot

He can then generate the required results (fulfilment of the tasks given to him in the form of changes, incidents, problems, …). These are then implemented as actions and documentation of these actions.

Just like the human expert, the AutoPilot also needs an appropriate working environment, which incorporates:

Access to the IT model (dependency map, MARS model) or “what needs to be operated?”Access to the monitoring or “What is the current status?”The knowledge imbedded in the autopilot.

ENVIRONMENT RESULTSAUTOPILOT

arago AutoPilot

Engine

Knowledge

IT model

Monitoring

Actions

Documentation

How does the AutoPilot work?

The AutoPilot does not carry out fixed scripts. The AutoPilot carries out necessary actions on a situational basis, step by step. For this purpose, the AutoPilot initially selects the method appropriate for the situation and then uses this method with the right piece of knowledge.The AutoPilot works like his human counterpart.

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Toolbox / Level 2 algorithms

Infoextraction

Analysis Decision Action

Knowledge / experience pool

Selects the appropriate method and the right piece of knowledge for a given situation

Decision engine / Level 1 algorithms

A E

MARS model & KI

The MARS model defines the environment that AutoPilot is to operate.

The definition of the MARS model does not have to be 100% accurate or complete – this means that environments that have undergone extensive changes can also be automated quickly and easily.

The MARS model is a structured illustration of the IT landscape from both a business and technical perspective.

The MARS model illustrates the interrelationships and dependencies of applications, resources, software and machines.

Business perspective Technical perspective

The MARS model

Technically speaking, a Web portal is an application that requires certain resources in order to operate.

In this case, these resources are:

– CMS: Content management system, provides Web content– Application server: Dynamic content (e.g. shop system)– Database: Stores the data required for the Web application– Load balancer: Distributes the load on the systems

In layman’s terms: An application is what users use for processing and resources are those IT blocks of which the users are also aware.

The MARS model, taking a Web portal as an example

The four levels of the MARS model

M = Machine

A = Application

R = Resource

S = Software

Bus

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These two levels illustrate the business-relevant and organisational parts of the company’s IT operations.

A = ApplicationR = Resource

The MARS model, taking a Web portal as an example: Business perspective

R

Web portal

DatabaseAppl.server CMS LB

A

Bus

ines

s pe

rspe

ctiv

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The MARS model, taking a Web portal as an example: Technical perspective

M

SMySQL Tomcat Apache FS

Win Linux Linux VM

The two lower levels, software and hardware, illustrate the technical side of the company’s IT operations.

Tech

nica

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spec

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S = SoftwareM = Machine

Several software nodes are grouped together into one resource when they are 100% technically dependent on one another.

MARS: Combination of business and technical perspectives

The MARS model, taking a Web portal as an example

With the MARS model, the IT landscape of a given company can bemapped from both a technical and business perspective.

Bus

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A

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Web portal

DatabaseAppl.server CMS LB

MySQL Tomcat Apache FS

Win Linux Linux VM

Environments are modelled differently by different people – but that’s ok!

New node types can be suggested in order to flexibly extend the MARS model. If enough users suggest a particular node type, it is adopted.

User-defined attributes can become standard attributes when enough users suggest these.

The MARS model is flexible

A node is transferred to AutoPilot as an XML structure.

XML can be generated from existing data or edited directly.

The attributes required are defined and validated using the MARS model.

All XML editors and frameworks (e.g. Eclipse) offer automatic validation.

If an attribute is missing for a node that has been created, this information is displayed to the node editor immediately.

If the validation process fails, the editor must subsequently maintain the missing or incorrect attributes.

The MARS model

The MARS model is a lean and simple model developed especially for automation purposes that is used to map IT landscapes.

The MARS model describes and categorises IT objects within a given system and illustrates the relationships between these.

IT objects are illustrated as nodes in a network plan and are linked together.

The nodes are described on the basis of attributes. These attributes consist of both mandatory fields and additional information fields.

A standard schema is delivered by arago and can be customised.

The MARS model thus meets the following requirement:minimal maintenance, maximum flexibility

The often unrealistic maintenance requirements of a conventional CMDB are minimised to a practical minimum.

MARS is a CMDB light version!

The MARS model: Summary

The MARS model provides AutoPilot with knowledge about the IT environment to be operated and its dependencies. “What needs to be operated?”

AutoPilot requires access for monitoring the IT environment. “What is the current status?”

Just like human colleagues, AutoPilot now also requires the expert knowledge that is to be applied. “How will the task be solved?”

AutoPilot receives this knowledge in the form of knowledge items (KI).

Expert knowledge in AutoPilot

A knowledge item (KI) is comparable to an “atomised” part of a script. Just one command/decision should be stored in any one KI.

AutoPilot selects from the knowledge pool the relevant KIs required to carry out a specific task. These perform activities such as:

– Acquire information – Make a decision about how to proceed– Perform actions to carry out the task

What is a knowledge item?

KI KI KI KI KI

Script

Maintaining knowledge items

“Atomise” a task

Can the knowledge be divided into smaller decision/execution

units?

Define WHERE it can be carried out

Define the circumstances under

which it can be applied

Define WHAT is to be decided/carried out

Describe which attributes have

changed in issue or nodes after execution

Define the RESULT

Yes

No

Define sub-tasks

The knowledge pool

How does knowledge get into the pool?

Today, it is common practice to obtain knowledge from online communities and forums.

In the planned AutoPilot community, clients who use the arago AutoPilot will be able to share knowledge items (KI).

Anyone who adds knowledge to the pool will also be able to take knowledge from the pool.

The prerequisite will be compliant with specific general rules governing the creation of KIs and a defined quality management.

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KI Wiki

arago

KI poolQM

Client n

Client 2Client 1

The vision: A knowledge community for IT operations

Do you have any questions?

arago Institut für komplexes Datenmanagement AGEschersheimer Landstr. 526 - 53260433 Frankfurt am MainTel: +49 (0) 69 405 680www.arago.dewww.automatisierungs-experten.de

Vorstand: Hans-Christian Boos, Martin FriedrichVorsitzender des Aufsichtsrats: Dr. Bernhard WaltherSitz: Kronberg im Taunus · HRB 5731 · Registergericht: Königstein i.TsUst.Idnr. DE 178572359 · Steuernummer 2603 003 228 43435

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