How Blended Analytics Can Transform IT Efficiency and Value

How Blended Analytics Can

Transform IT Efficiency and Value

March 8, 2016

Dennis Drogseth

VP of Research

EMA

http://www.enterprisemanagement.com

@dndrogseth

Sasha Gilenson

Founder & CEO

Evolven Software

http://www.evolven.com

@sgilenson

http://www.enterprisemanagement.com/

https://twitter.com/dndrogseth

http://www.evolven.com/

https://twitter.com/sgilenson

Featured Speakers

Dennis Drogseth, VP of Research, EMA

Dennis brings over 30 years of experience in various aspects of

marketing and business planning for service management

solutions. He supports EMA through leadership in Business Service

Management (BSM), CMDB Systems, automation systems and

service-centric financial optimization.

Sasha Gilenson, Founder and CEO, Evolven Software

Sasha is a recognized IT Operation Analytics (ITOA) thought

leader. Prior to founding Evolven, Sasha was Mercury's (now HP)

top "guru" in quality processes and IT practices, has advised

numerous Fortune 500 companies on technology and process

optimization.

Slide 2 © 2015 Enterprise Management Associates, Inc.

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How Blended Analytics Can

Transform IT Efficiency and Value

March 8, 2016

Dennis Drogseth

VP of Research

EMA

http://www.enterprisemanagement.com

@dndrogseth


https://twitter.com/dndrogseth

Agenda

• IT’s struggle to change

• What is blended (or tiered) analytics, and how can it come to the

rescue?

• How is blended analytics different from tradiational big data?

• How does it work with monitoring and other toolset investments?

• How does it bring service modeling and analytics together?

• Why change and performance management belong together

• Impacts of Blended Analytics– in one particular deployment

• Summary/ Conclustion


IT’s Struggle to Change


How and Why IT Needs to Change to Become More

Effective and Valued?

• Reactive versus proactive

• Still fragmented in technical and political silos

• Toolset fragmentation

• A failure of communication

• Narrowly defined technical priorities versus business priorities

• A changing consumer population

• More dynamic business requirements

• And yet IT services are more potentially relevant and transformative

than ever!


Stress Factors/Catalysts:

Where IT Organizations Have to Change

• Cloud A – IT as a “broker of services”

• Cloud B – IT as its own extended enterprise with new dimensions

for resource optimization

• Agile – IT ups the speed in business responsiveness

• “The Consumerization of IT”

• A new, more savvy, IT service consumer

• The acronymic wall isolating “back-office IT” must crumble

• IT as a “Retail Organization”

• IT as a true business partner


An

integrated

team combining

IT service

management and

operations:

The “New War Room” Goes Beyond Silos

• Versatile dialog between ITSM and operations

insights

• Upward visibility to the IT executive suite and

business stakeholders when relevant

• Integrated operations: workflows +

analytics+ user experience

• Integrated DevOps: workflows +

feedback loops+ service modeling

• Attention to change management

and service impact: analytics,

automation, CMDB/CMS/ADDM

• Optimizing the cloud opportunity


What is Blended Analytics?


What is Blended Analytics—and How is it Part of the

Solution?

• Blended analytics is optimized for real-time

and sometimes predictive requirements.

But also includes advanced historical

trending capabilities.

• It differs from classic warehousing in its

focus on near-real-time data, discovery

and data collection, service modeling and

distinctive use of trusted sources.

• Blended analytics can scale well because

of its “tiered” or “blended” capabilities to

leverage other analytic resources as input.

• Blended analytics is uniquely suited to

combining change management with

performance, security, capacity

optimization and improved IT efficiencies.


Blended Analytics and Advanced IT Analytics

• Blended Analytics is at the heart of EMA’s look at the industry’s

broader Advanced IT Analytics (AIA) marketplace.

• Blended Analytics’ tiered approach to data collection makes it

versatile, adatable multiple types of data sources to optimze

existing investments.

• Blended Analytics’ solid capabilities in assimilating service

interdependencies for “context” also puts it in the forefront of AIA.

• Other AIA adoptions include:

• Data lake approaches focused on searching data (homegrown, or third-

party, or mixed)

• More limited tools in terms of data collection with predictive insights

• Event-only solutions with broad/eclectic foundations

• Time-series-only optimized solutions


Top 7 Analytics Technical Triage and Diagnostic Priorities

1. Cross-domain problem isolation across the application

infrastructure

2. Security-related issues (SIEM)

3. Isolate infrastructure issues within the network

4. Triage across virtualized systems

5. Triage across application tiers/and or middleware

6. Isolate problems in provisioning applications

7. Isolate infrastructure issues internal to systems


Blended Analytics versus Classic Big Data

• Speed in data collection – versus classic ETL

• Speed in analysis – real time or near

• Context = increased relevance in sourcing

• Context = interdependencies in discovery

• Flexibility = federated trusted sources versus one single melting

pot – “tiered” or “blended” analytics

• Custom turnaround from “months to days,” “hours to minutes”


What Should You Be Looking for in

an Advanced Analytics Solution?

• Service-centric or cross-domain analytics versus siloed analytics

• Assimilative power for both “symptoms” and “context”

• Breadth of constituency (stakeholder) support

• Realized versus just potential value

• Virtualization and cloud (resource) and (environment)

• Quick time to value

• Minimal administrative overhead

• Advanced analytics transcends classic monitoring and classic

configuration or change management


Three Role Perspectives on Analytic Priorities

• Application management:

Prioritizes application optimization, problem isolation in systems, business

events and time series data, app performance, event management and

operational dashboard integrations, ADDM for performance

• Change and configuration management:

Prioritizes configuration and change management effectiveness, isolating

problems in provisioning applications, if/then change impact, capacity

planning, CMDB/CMS /ADDM linkages, are ‘extremely successful’

• Software development:

Prioritizes systems availability and performance, if/then change impact, log

files, integrations with dev/ops tools, ADDM for performance


7 Top Analytics Achieved Benefits

1. Faster time to resolve problems and incident prevention

2. Better optimization of IT assets overall

3. Gain real-time insights and historical trends on IT services

4. Better correlation between change and performance

5. More efficient use of infrastructure capacity

6. Faster identification of security threats

7. Less overhead in writing and maintaining rules and thresholds


Advanced Analytics and DevOps


What are your org's Dev/Ops priorities for advanced analytics?

Sample Size = 163, Valid Cases = 163

Why Change and Performance

Management Have Become

Inseparable


Role (skills)-related Analytics Priorities:

Change and Configuration Management

• Prioritizes configuration and change

management effectiveness,

• Isolating problems in provisioning

applications,

• If/then change impact

• Capacity planning,

• CMDB/CMS /ADDM linkages, are

“extremely successful”


Change and

configuration

management:

Capturing Interdependencies and Blended

Analytics


What interdependencies does your organization view as

critical for its advanced analytics investments?

Sample Size = 252, Valid Cases = 252

Service Modeling and Blended Analytics

• Top priorities for linking service modeling to advanced analytics are:

• Service modeling topology included within the analytics solution

• Application Discovery and Dependency Mapping for performance

• Application Discovery and Dependency Mapping for change

• Federated Configuration Management System

• Service Modeling Dashboard for Business Impact

• Only 3% had no intention to link analytics with service modeling


Impacts of Blended Analytics in One

Particular Deployment


Context and Challenge

• Context and Challenge: A large financial services organization

• Spans 14 countries

• 9,000 staff

• Owner—product owner for IT service management and the

configuration management system (CMS)

• Target---performance and DevOps

• History

• Began with ITIL incident, problem, change and configuration

management. Supported help desk

• Moved away from portions of ITIL v3 framework for a more agile and

automated approach (continuous development/continuous integration)

or CD/CI


Directions in Blended Analytics

• “We started automating event management—targeting user

interfaces for critical business applications (e.g. Internet banking).”

• “Using blended analytics we are bringing automation and analytics

much more closely into the CMS fabric with a distributed

framework.”

• “We leverage blended analytics to keep a more dynamic record and

facilitate automation that’s critical for performance and change

management and our DevOps initiative.”

• “Now we have an analytically rich capability that complements our

need for currency in understanding actual changes and how they

impact application performance.”


Current Victories

• “With the advent of a more automated and anlaytically aware

environment, we have been able to reduce our core CMDB

administration considerably.”

• “It used to take 11 weeks to provision a VM, and now it takes

eight minutes.”

• “We also have a much cleaner set of change verification

histories—we’re not dealing with unknowns.”

• “This has helped DevOps and development see the impacts of

what they plan for their manifests to go into production.”

• “Taking this approach, we have seen double-digit percentile cost-

efficiency improvements over a one to two year period of time,

while our time-to-market has drastically decreased.”


Conclusion: Summary and

Predictions


Summary

• IT organizations have to move to support more dynamic, cross-

domain requirements given the pressures of cloud, agile and digital

transformation.

• Blended analytics can come to the rescue by optimziing existing

monitoring, configuration and other management investments while

showing quick tim to value.

• Change management, service modeling, and blended go hand-in-

hand and the combination in EMA research often separates

winners from losers.

• In one example, EMA dialog showed dramatic values in reducing

administrative overhead, acclereated provisioning, support for

DevOps/agile, and double-digit cost-efficiency improvements.


Predictions for Advanced Analytics

• A growing number of vendors will create analytic offerings with

differing architectures and distinctive value-feature focus.

• There will be a greater interest in service modeling integrations with

analytic investments—including ADDM, and CMDB/CMS.

• Blended analytics in particular will increasingly become a stimulus

for process awareness and cross-domain process training.

• Blended analytics will also promote more meaningfully integrated

cross-domain relationships, including operations-to-service desk,

development-to-IT, security-to-operations-and-development, and

IT-to-business.


Sasha Gilenson

Founder & CEO

Blended

AnalyticsTransforming IT Efficiency and Value

31 | Evolven Proprietary & Confidential

EVOLVEN – AN ITOA LEADER

TRUSTED BY LEADERS STRONG ANALYST SUPPORT

Transforms IT Efficiency

and ValueDennis Drogseth

VP Research

Will Cappelli, Research VP

Ronni Colville, VP Dist. Analyst

The only vendor to marry IT

Operations Analytics to CCM.

INDUSTRY RECOGNITION


What Changed?

Knowledge

Base

Risk

Dimensions

Anomaly

Detection

Machine

Learning

Root-cause

Risk Prediction

Symptoms

Changes

IT Context

All

Relevant

Data

Sources

Powerful Analytics

Change Centric

Less issues

Faster

resolution

More

efficiency

2

1

3

4

EVOLVEN BLENDED ANALYTICS


CHANGES – THE SECRET INGREDIENT


CHANGE CENTRIC CAUSAL ANALYSIS

Time

Risk

Fix

RCA

Incident

Change

Incident

resolved

Alert


DON’T WAIT FOR INCIDENTS TO HAPPEN,

PREVENT THEM

Time

Risk

Fix

RCAIncident

resolved

Evolven tracks and analyzes changes

as they happen to prevent incidents

(instead of waiting for symptoms alert

to show)

Incident

Prevented

FixAnalysis

Risk

detectedIncident

Alert

Change


LEVERAGE EARLY DETECTION OF THE TRUE

ROOT CAUSE TO SLASH RCA TIME

Time

Risk

Fix

RCAIncident

resolved

Evolven tracks,

correlates and

analyzes changes

to slash RCA time

Change

detected AlertIncident

Change correlated

and risk analyzed

Incident

Resolved

Fix

Change


EVERY CHANGE COUNTS

2 The Entire EnvironmentApplications, underlying software infrastructure, virtual and physical

infrastructure stack

All Change TypesConfiguration, Capacity, Data, Workload, Code

1

3

4

Evolven – the only vendor to collect, correlate and analyze all

changes, end-to-end, at most granular level

Most Granular LevelDown to individual parameter values, database schema elements,

application master data values etc.

Near Real-Time


POWERFUL ANALYTICS

Data Cleansing

and Correlation

• Reduce noise - Eliminate irrelevant, low

significance data

• Cluster similar events and KPIs for more

accurate and efficient analysis

• Normalize data from each data source to

allow correlation

• Correlate data within and between multiple

data sources

Analytics Engine

• Calculate risk scores for each change

dimension and blended data sources

• Machine Learning based anomaly

detection

• Leverage OOB and custom knowledge

base and SME input to fine tune analysis

Consistency: Inconsistent with

similar systems

Policy: Not compliant

with expected policy

Host Type: Happened in

production environment

Time Anomaly: Typically

overnight changes happened

at noon

Loneliness: Change

happened outside of most

change clusters


KEY USE CASES

DevOps

Analytics

50% cut in MTTR

25% faster, error-free

releases

35% drop in number

of incidents

• Know what changed

• Automatically correlate symptoms, IT context and changes

• Analyze risk to zoom-in on true root cause

• Validate the infrastructure readiness

• Know what released

• Early detection of post release stability issues

• Identify high risk changes early on

• Detect anomaly or recognize pattern

• Validate environment consistency (prod vs DR; new server

vs golden baseline; across cluster )

Accelerate

Troubleshooting

Prevent

Incidents

Automated

Audit

75% less manual

effort

• End-to-end audit-trail of changes

• Automatic detection of unauthorized changes

• Alerting on high risk changes


Demo


Appendix


Symptoms

Changes

IT Context

APM

Log

Service Desk

Deployment

CMDB

Config. | Capacity | Data | Code | Workload

BSM

UCMDB

* Can’t find your IT operations tool? No problem. Evolven easily integrates with 3rd party tools.

BLENDED DATA FEEDS


Windows HP-UX

SUPPORTED TECHNOLOGIES

IBM AIX

Oracle Solaris

Linux CentOS

Linux Red Hat

Linux Red Hat

Fedora

Linux SUSE

Operating Systems

Wizard-based custom application support

New application support in minutes

Custom Applications

HTTP Servers

Apache Microsoft IIS IBM HTTP Server

Active Directory

Microsoft Active

DirectoryOpen LDAP

Sun Java System

Directory

Others

Documentum SharePointTibco BPM

Apache TomcatIBM WebSphere JBoss

Pivotal-tc

JettyOracle WebLogic webMethods

Application Servers

Oracle

DB2MySQL

Sybase

Microsoft

SQLServer

Databases

Windows Components

Microsoft

COM/DCOM .NET FrameworkWindows Cluster

Virtualization

VMWare vCenterCitrix XenAppMicrosoft Terminal

Server

IBM WebSphere

Message Broker

IBM WebSphere

MQ

Oracle Tuxedo

IBM WebSphere

ICS

Microsoft Exchange

Messaging

Apache MQ


BOOST THE POWER OF EXISTING TOOLS

WITH EVOLVEN IT OPERATIONS ANALYTICS

BSM Dashboard

CMDB

Automation

Service Desk

Cloud

ManagementEVOLVEN

• High Risk Changes

• High Risk Diffs

• Alerts

• Correlate Symptoms

With Changes in States

• Verify Infra Readiness

• Validate Changes

• Monitor Change Life-Cycle

• Use Service Maps

• In-depth CI Config

• Refresh Data

• Map Detailed Actual Changes

To CRs

• Detect Unauthorized Changes

• Investigate Incidents

• Consolidate Stack View

• Correlate Changes/Diffs

• Prioritize w/Analytics

ITOA

APM | Log


DELIVERING TANGIBLE RESULTS

40%

decrease in incidents

6 months ROI

““Use of Evolven to ensure time-to-

market and stability of a major

application paid for the product in 6

months”.

“"Thanks to Evolven, what took weeksnow takes hours or less."

A Top 10

Banking Group

Learn More About Enterprise Management Associates

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Keep up to date on upcoming webinars and get free research!

http://www.enterprisemanagement.com/freeResearch


Learn More About Enterprise Management Associates


Keep up to date on upcoming webinars and get free research!



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How Blended Analytics Can Transform IT Efficiency and Value