AIOps, IT Analytics, and Business Performance: What’s Needed and What Works

IT & DATA MANAGEMENT RESEARCH, INDUSTRY
ANALYSIS & CONSULTING
Dennis Drogseth
VP of Research
EMA
AIOps, IT Analytics, and Business
Performance: What’s Needed and What Works
Bernd Harzog
CEO
APM Experts
Marty Pejko
COO
Centerity

IT & DATA MANAGEMENT RESEARCH,
INDUSTRY ANALYSIS & CONSULTING
Watch the On-Demand Webinar
Slide 2
• AIOps, IT Analytics, and Business Performance: What’s
Needed and What Works On-Demand webinar is available here:
http://info.enterprisemanagement.com/aiops-itanalytics-
businessperformance-webinar-centerity
• Check out upcoming webinars from EMA here:
http://www.enterprisemanagement.com/freeResearch

Featured Speakers
Dennis Nils Drogseth, Vice President, EMA
Dennis joined EMA in 1998 and currently manages the New Hampshire office.
Dennis brings several years of experience in various aspects of marketing and
business planning for service management solutions. He supports EMA through
leadership in IT Service Management (ITSM), CMDB systems, as well as
megatrends like advanced operations analytics, cross-domain automation systems,
IT-to-business alignment, and service-centric financial optimization.
Bernd Harzog, CEO, APM Experts
Bernd assists global enterprises with management and monitoring software purchase
decisions and implementation strategies. Clients have included Credit Suisse,
Deutsche Bank, Chevron, UBS, Nordea Bank, and Allianz Insurance. APM Experts
also provides product strategy and marketing strategy services to monitoring and
performance management vendors.
Marty Pejko, COO, Centerity
Marty has over 25 years of technology experience in enterprise software, security,
networking, and communications. Marty formerly worked as VP of Global Channels
for Guardium (acquired by IBM), as VP of Global Channel Sales for Network
Intelligence (acquired by EMC/RSA), as VP of Business Development for
International Sales for Quantum Bridge Communications (acquired by Motorola) and
as Corporate Counsel for GeoTel Communications (acquired by Cisco).

ANALYSIS & CONSULTING4 © 2019 Enterprise Management Associates
Logistics
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will be available at ww.enterprisemanagement.com
• Log questions in the chat panel located on the
lower left-hand corner of your screen
• Questions will be addressed during the Q&A
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QUESTIONS
EVENT RECORDING
A PDF of the speaker slides will be distributed to
all attendees
PDF SLIDES

APM Experts Digitization Overview
Bernd Harzog
CEO – APM Experts
bernd.harzog@apmexperts.com

1980-2005
Bernd’s Background
• Invented Microsoft SNA
Server for Windows NT
• Gartner Research
Director for Intel
System Software
• 2 Patents for
self-learning
performance analytics
at Netuitive
• CEO at RTO Software
(Citrix Performance
Management) – sold
company to Citrix
• CEO of OpsDataStore
– An AIOps Platform
• CEO of APM Experts –
Consultant to the
leaders in the
monitoring industry
PRODUCT SELECTION CONSULTANT
APM EXPERTS (2005 – 2019)
PRODUCT STRATEGY CONSULTANT

The Business Imperative - Digitization
Enterprises are digitizing
(implementing in
software) key constituent
facing services
This requires thinking and
operating like a software
vendor, not an enterprise
IT organization
Software vendors treat
revenue generating
“services” as products,
not projects
As a result of digitization,
the demand to implement
business functionality in
software is infinite

As a Result We Continue to See More Innovation, Diversity,
Complexity, Change and Dynamic Behaviors at All Layers of the Stack
Accelerate delivery of
code into production
Everything virtualized
Many Clouds
Shifts in application
architecture
Proliferation of
data architectures
In many different
services and
containers
In many different
languages

An Unprecedented Situation
• Digitization is an unprecedented business imperative for enterprises to compete
and execute online as software vendors (Time to Market, Agility, Quality of
Service, End User Experience)
• An unprecedented pace of innovation in processes and technology to support the
business imperative of digitization
• The need for continuous availability and performance is driving dynamic behavior
in virtualized and cloud based compute, networking and storage services
• Dynamic behavior in virtualization and cloud platforms, in Kubernetes and
applications and containers complicates understanding the truth
• Time to market pressures are leading to unprecedented levels of diversity in the
software stack with continuous changes on a release by release basis
• Time to market and agility pressures are causing applications to be architected
around microservices and released multiple times a day with CI/CD processes
• Monitoring is now a very hard problem

The Resulting Requirements
• The entire stack must now be monitored in real time (1 Min – 1 Sec) to be
able to detect service quality issues in time
• AI (AIOps) must be deployed to cope with the deluge of incoming monitoring
data and automatically understand normal vs. abnormal
• Relationships across the stack must be determined in real time
• What talks to what (traces and flows)
• What runs on what
• What is a member of what
• AIOps and relationships must be leveraged for automated root cause
• The results of monitoring must be made relevant to business constituents

Private Cloud (VMware) Relationships Model
Application ContainerTransaction
Virtual
Server
Datastore
Service
Business
View
Micro-
service
Physical
Server
Process
LUN
Raid
Group
Disk
Group
Disk
K8
Node
K8
Pod
Cluster
Datacenter
Virtual
Network

Public Cloud (AWS) Relationships Model
Application ContainerTransaction
EC2
Instance
EBS
Volume
Service
Business
View
Micro –
service
Elastic
NIC
Process
Subnet VPC Region
S3
Bucket
S3
K8
Node
K8
Pod

• Gartner expects AI to pervade every aspect of managing IT including APM, IT Infrastructure Monitoring, Cloud
Platform Monitoring, Performance Management, Capacity Management, the delivery tool chain (CI/CD), and IT
Service Management
• Gartner also expects the emergence of AIOps platforms which combine data from multiple sources to deliver
enhanced value
AIOps Overview
Gartner's AIOps
Platform
Architecture
AIOps Platform
Data Types

Approaches to AIOps
There are many different approaches to AI
and ML
Rule based – works only for constrained
and limited use cases and difficult to
maintain
Neural Net based – requires training –
problematic in dynamic environments
Unsupervised Self Learning – difficult to
focus upon desired KPI’s
Supervised Self Learning – Combines
human expertise with Machine Learning
Automation is only possible when based
upon a deterministic foundation

AIOps Use Cases
Automated Baselining, Anomaly Detection and Root Cause
Automated Workload Management (Contention Avoidance)
Eliminate CPU, Memory, Network I/O and Disk I/O contention
Correctly size VM’s and Cloud Images
Place VM’s in the best Hosts and Clusters
Automated Cloud Cost Management
Optimize cost by right-sizing cloud images
Optimize cost by choosing the optimal price plan
Automated Event Management
De-duplicate events
Support a collaborative (DevOps) problem resolution process
AIOPs Platforms
Automated Performance Optimization and Remediation
Automatically learn the performance characteristics of the
application and the entire supporting stack
Automatically optimize for a chosen KPI (performance, efficiency)

Dennis Drogseth
Vice President
Enterprise Management Associates
AIOps, IT Analytics and Business
Performance: What’s Needed and What Works

ANALYSIS & CONSULTINGSlide 17 © 2019 Enterprise Management Associates, Inc.
Agenda
• Demographics
• The changing infrastructure, application and business landscape
• What is AIOps? And which data is becoming most critical for optimizing
business performance through advanced analytics and why
• The critical importance of real-time, multi-layer topology and
dependency insights
• Roles, metrics and anticipated process changes
• Rules of the road for succeeding
• And well-tested reasons for failure

Respondent Base and Geography
300 respondents:
• 191 in North America
• 109 in Europe
Balanced company size
• 35% small; 30% mid-tier; 35%
large enterprises
Strong executive presence with 40%
VP and above
• Examined 4 groups:
• Executive (not including CISO)
31%
• Security (including CISO) 21%
• ITSM/operations 20%
• Technical support (data scientist,
data management, engineering,
etc.) 20%

The Changing Infrastructure, Application
and Business Landscape

© 2019 Enterprise Management Associates, Inc.
63%
31%
6%
0%
0%
0% 10% 20% 30% 40% 50% 60% 70%
Very High Priority. Digital transformation has
been a top priority for both IT and the business
for a year or more
High Priority. We are well underway with
digital transformation
Serious Planning. We have identified budgets
and priorities for our digital transformation
Initial Planning. We are beginning to look at
digital transformation as a top priority
Not at all. Digital transformation is not a focus
Sample Size = 300
DIGITAL TRANSFORMATION IS NO LONGER PURELY A
VISION FOR THE FUTURE. IT’S REAL TODAY!
To what degree has your organization pursued a digital transformation initiative?

“Digital transformation”
targets optimizing business or
organizational effectiveness via
digital investments and IT services.
“IT transformation”
is directed at optimizing IT
performance to more effectively
address business or organizational
needs and outcomes.
Slide 21 © 2019 Enterprise Management Associates, Inc.
DIGITAL OR IT TRANSFORMATION?
Which applies most to you?

IT Is More Easily Transformed than the
Business
BASE: (IT Transformation: N=131; Digital Transformation: N=306)
Very or Extremely Successful
79% of IT Transformation
69% of Digital Transformation
1%
5%
15%
45%
34%
0%
4%
26%
54%
15%
0 0.2 0.4 0.6
Largely…
Only…
Successful…
Very…
Extremely…
How successful have you been to date with your
digital or IT transformation initiative(s)?
Digital Transformation IT Transformation

23 © 2019 Enterprise Management Associates
DIGITAL TRANSFORMATION COMES WITH CHALLENGES
Digital Transformation
• Lack of effectively defined
processes
• Poor communication across IT
and lack of vision (tied)
As perceived by IT stakeholders
• Organizational and political
issues
• Ineffective IT
leadership/inaccurate or
incomplete data (tied)
IT Transformation
• Organizational and political
issues
• Ineffective IT leadership
As perceived by business
stakeholders
• Lack of a clear and compelling
vision/lack of effective process
(tied)
• Ineffective IT
leadership/warring siloed tools
(tied)

Extremely Successful in Both Areas Were:
• Extremely Successful deployments were more likely to:
• Be 50/50 partners between IT and business stakeholders –
• and 8 times more likely to have formally defined teams for IT-to-business dialogs on application priorities
• Leverage best practices
• Work with partners
• Leverage more metrics in support of measuring their transformational efforts
• Have a balanced focus between DevOps and agile
• Have operational metrics
• Have financial or maturity metrics
• Have business metrics
• Extremely Successful were more likely to view technology as a “driver” and had significantly higher
adoption rates of technologies overall.

Moving to Cloud Is on the Upswing, But It Has Its Challenges
How is cloud impacting IT?
1. Cloud and virtualization have made asset management challenging
2. Cloud is shortening review cycles for managing change
3. Cloud is changing how we approach release management (shorter
lifecycles)
4. Cloud is changing how we’re organized
5. Cloud is requiring higher levels of automation in provisioning services
6. Cloud is pushing us to pay more attention to SecOps
7. Cloud is putting pressures on us to justify costs

DEVOPS IS DEMANDING…
• Cross-silo teaming
• A more transparent IT
• A more technology-aware IT
• A more application-aware IT
• A more business-aware IT
• A more dynamic IT
• About 25% of IT organizations are delivering new code multiple times a day
• About 20% are delivering new code daily
• About 20% are delivering new code multiple times a week

Internet of Things (IoT) and AIOps
71% were currently deploying analytics in support of IoT
• Only 3% had no plans to deploy
• 69% of the 71% viewed these as fully integrated with their AIA/AIOps strategy
Prioritized use cases were:
• Manufacturing
• Facilities
• Utilities
• Other vertically-specific needs
• Transportation/fleets

What is AIOps, and Which Data Is
Becoming Most Critical

Advanced IT Analytics (AIA) and AIOps Confluence
1. Assimilation of data from cross-domain sources in high data
volumes for cross-domain insights
2. Access multiple data types, e.g., events, KPIs, logs, flow,
configuration data, etc.
3. Capabilities for self-learning to deliver predictive, and/ or
prescriptive and/or if/then actionable insights
4. Support for a wide range of advanced heuristics
5. Potential use as a strategic overlay that may assimilate
multiple monitoring investments
6. Support for private cloud and public cloud
7. The ability to support multiple use cases

Use Case Priorities

Data Sources Are Key to Effective AIOps
Accessed data sources showed an increase to an average of
more than twelve (12.65) in Q3 2018 versus five in Q1 2016.
The top ten data sources in the new research were:
1. Internet of Things
2. Spreadsheets
3. Transaction data
4. Configuration/metadata
5. Logfiles/access logs
6. Endpoint agent data (byte code instrumentation)
7. Business process impacts
8. Record of API calls
9. Incident records
10. User-behavior-specific data

The Average Response Indicated that AIA
Investments Should Assimilate About 23 Monitoring
or Other Tools
1%
9%
14%
17%
21%
15%
8%
13%
3%
None
1-5
6-10
11-20
21-30
31-40
41-50
More…
Don't know
How many monitoring or other management tools would you
expect to integrate into your organizations IT analytics solutions
directly or through an aggregated data store?
None 1-5 6-10 11-20 21-30 31-40 41-50 More than 50 Don't know
Sample Size = 300

The Critical Importance of Real-time, Multi-
layer Topology and Dependency Insights

ANALYSIS & CONSULTING34 © 2019 Enterprise Management Associates, Inc.
Accurate Topology and Inventory Can Be a
Nightmare of Confusion
On average, respondents indicated using 11 different discovery or inventory tools
• 10% 3 or fewer
• 21% 20 or more (7% had more than 40)
And on average, respondents spent 15 hours a week reconciling different data sets for
discovery
Most frequent interval for updates?
• 21% in real time
• 24% multiple times a day, 21% daily
• 17% multiple times a week
(11% weekly and 4% monthly)

Interdependencies
Top Five Interdependencies (average of
5 per respondent)
• Infrastructure-to-application
• Endpoint-to-infrastructure
• Infrastructure-to-infrastructure
• Infrastructure-to-business services
• Application-to-business services
Top Four Sources
• Application dependency mapping for
cost
• Application dependency mapping for
change
• Service modeling dashboard for
business impact
• Service modeling/topology provided
through analytic tool

Click to Interdependencies: A Deeper Dive
What interdependencies does your organization view as critical for its IT analytics-related
initiatives?
49%
46%
43%
43%
42%
41%
39%
39%
38%
36%
36%
29%
2%
0%
0% 10% 20% 30% 40% 50% 60%
Infrastructure to application
Endpoint to infrastructure
Infrastructure to infrastructure
Infrastructure to business services
Application to business services
Application component to application…
Container-based interdependencies
Endpoint to application
Application to application (application…
Interdependencies across public and hybrid…
Business process to application
Non-virtualized to virtualized infrastructure
We are not interested in capturing…
Other
Sample Size = 300, Valid Cases = 300, Total Mentions = 1,451

Roles, Process Changes, and Metrics

ADVANCED IT ANALYTICS CAN UNITE A
WIDE RANGE OF STAKEHOLDERS
The top seven domain
stakeholders were:
• Applications
management/support
• Cloud management
• Database management
• Security/compliance
• Systems
• Software
engineering/development
• Network
The top eight cross-domain
stakeholders were:
• IT operations/cross-domain
(tied with) executive IT
• ITSM (beyond the service
desk)
• Data analyst/data scientist
• Infrastructure management
• Line of business (not central
IT)
• Agile/DevOps teams
• Engineering
• Configuration management
The top five business
stakeholders were:
• Business operations
• Business
development/planning
• Customer experience
management
• Executive (non-IT)
• Online operations

A Deeper Look at Business Stakeholder Roles
title style
Which of the following non-IT-related roles does your organization expect to support as an
extension of its IT analytics?
51%
49%
49%
48%
45%
45%
42%
41%
39%
38%
2%
0%
0% 10% 20% 30% 40% 50% 60%
Business operations
Business development/planning
Customer experience management
Executive non-IT
Online operations
Supply chain management
Marketing
Line of business
Partner management
Sales
None - we don't expect our analytics…
Other non-IT (Please specify)

Best Practices Correlate Strongly with
AIOps Success
• When asked, 63% of IT organizations were leveraging best
practices in support of AIOps adoptions
• 35% had plans to work with best practices
• Only 1% felt best practices didn’t apply to analytics/AIOps
adoptions
• Then, when compared with success rates:
• 85% of those who were ‘extremely successful’ were
leveraging best practices
• And 14% of the ‘extremely successful’ had plans to
leverage best practices

Top Best Practices
• ISO/ Security 27001/27002
• Regularity compliance (SOX, RSMA, HIPAA)
• IT Balanced Scorecard
• COBIT Control Objectives for Information and Related
Technology
• Service Integration and Management
• ISO 19770-1
• CIS benchmarks for AWS
• Knowledge-Centered Support (KCS)
• Six Sigma
• Continuous Operations
• ITIL v2, v3

Optimizing IT Services for Business Performance
Depends on the Versatility to Support a Wide Range of
Business Metrics
What business impact metrics does your organization view as important as extensions of
your IT analytic investments (for now or within the next 12 months)?
33%
33%
31%
31%
30%
30%
29%
29%
29%
28%
28%
27%
27%
27%
26%
26%
26%
26%
25%
23%
4%
0%
0% 5% 10% 15% 20% 25% 30% 35%
Revenue (through IT services)
Business activity metrics (BAM)
Improved business efficiencies due to…
Business process efficiency/impacts
Industry compliance-related metrics
Internal service-level agreement (SLA)…
Cost of service delivery (internal)
Cost of service delivery (external, service…
Cost-related external SLAs (with service…
Service desk OpEx cost savings
Operations OpEx cost savings due to…
Other OpEx cost savings
Cost and overhead savings from capacity…
Metrics to show application usage for cost…
Time to create, develop, deliver, or update…
Brand-related impacts
Conversions from competitive websites
Supply chain-related outcomes
Compliance metrics (e.g., PCI)
Social media feedback
None - we're not currently capturing business…
Other

Rules of the Road for Succeeding
And well-tested reasons for failure

Eight Well-Tested Reasons for Failure
1. Resistance to change
2. Failures to communicate
3. Failures in leadership
4. No clear use-case priorities
5. Trying to do everything at once
6. Failures to realistically assess existing levels of strength and
weakness (maturity assessments)
7. Failures to assess existing technology needs based on your
own unique environment
8. Cultural divides between business and IT leadership

Leadership, Overhead and Roadblocks for AIOps
52% were driven by the executive suite (VP and above)
The average deployment required more than 2 FTEs for ongoing
administrative support
Top five roadblocks were
• Data quality issues
• Products not fully baked yet
• Data relevance/ lack of context
• Tools are too complex to
administer
• Internal resources – getting
budget and people

Eight Points for Optimizing AIOps for Business
Performance
1. Executive leadership/commitment is key
2. Prepare to support an expanding number of stakeholders
inside and outside of IT
3. Create ‘dialog teams’ between IT and the business to
proactively address business outcomes
4. Prioritize richer data insights from a more diverse set of
reconciled sources for service management decision making
5. Invest in analytics and automation
6. Prepare for toolset consolidation as it impacts core IT
processes and stakeholder alerting
7. Metrics count—including both performance and governance—
so stay current and hep to drive the metrics process
8. Plan to progress in stages: don’t try to boil the ocean all at
once

All information within this document is confidential and commercially sensitive to
Centerity and must not be copied or disclosed to any third party without the prior
written consent of Centerity.
DYNAMIC SERVICE VIEWS INTO YOUR
CRITICAL BUSINESS SERVICES
Marty Pejko, COO

A business focused approach to understanding the “stack”
Centerity – Company Profile
Dynamic Service Views ensure that business objectives for critical digital services are met
CUSTOMERS
PARTNERS
Copyright © 2019, Centerity Systems, Inc.
MANAGEMENT
Roi Keren
CEO
Marty Pejko
COO
Michael Braverman
Dir. N. America
Sales
Eyal Dalit
GM - EMEA
Maxim Reizelman
Dir. Technology
Matan Reinman
VP Bus. Dev.
Eran Molot
VP R&D
BostonBoston Israel

The Problem The Solution
Network
Monitor
Storage
Monitor
Transaction
Monitor
Server
Monitor
Virtualization
Monitor
OS
Monitor
IT
Operations
Log
Monitor
Container
Monitor
Franken-monitors fail
to provide any business
visibility
NetworkComputeStorageOSApplications
Consolidated
Dynamic Service
Views for each
critical Digital
Business Service

Data Collection
• Agentless
• Agent-Based
• Any API
• Comprehensive
• Real-Time
Key Metrics
• Availability
• Performance
• Throughput
• Error Rate
• Business State
Real-Time Relationship Engine
• Transaction Flow Mapping
• Infrastructure Dependency Mapping
• Virtualization & Cloud Grouping
• Automatic Discovery
Service Level Engine
• Leverages all metrics, logs & events
• Calculates Business Service Levels
Analytics Engine
• Dynamic Baselines
• Automatic Anomaly Detection
• Dependency Based Root Cause
Analysis
Dynamic Service
Views
• All Services
• Drill Down
• Root Cause
• Cross-Stack
Alerts and
Notifications
• Email
• SMS
• PagerDuty
• ServiceNow
• Slack
Business
Executive
Product
Manager
IT Operations
The Centerity Platform
PLATFORM CAPABILITIES
Real-Time Streaming • Role-Based Access Control • Multi-Tenancy • Scaling • High Availability
Custom
Queries
Events
Metrics
Logs
!
DEPLOYMENT OPTIONS
Bare Metal • Private Cloud • Hybrid Cloud • Public Cloud • Multi-Cloud
Integrations
• APM –
AppDynamics,
Dynatrace,
Riverbed, Nastel
• Virtualization –
VMware
• Cloud – AWS
• Middleware – Java,
.NET, SQL,
NOSQL, Docker,
Kubernetes
• Operating Systems
– Windows, Linux,
Solaris, HPUX, AIX
• Networking – All
TCP/IP, SNMP,
Netflow
• Storage – EMC,
NetApp, HP
Apps &
Business
Services
• SAP
• Medical
• Retail
Store
• Custom
Web
• Custom
Mobile
• IOT
• Digital
• Legacy

Emergency
Response
Medical
RecordsE-Commerce
Automatic Discovery, Dependency Mapping, Business Service Creation, Anomaly
Detection
Business Service Analytics for Business Impact
Dynamic Business
Service Views.
E.R.CRME-C
MEDIIoTERP
Additional Layers
Application Layer
Server Layer
1 2 3 4 5 6
Storage Layer
1 2 3 4 5 6
Network Layer
1 2 3 4 65
Device Layers

Medical
Records
Emergency
Response
Understand the Impacts Across the Entire Stack upon Key Business Services
Composition of a Dynamic Business Service View
E-
Commerce
5%
10%
15%
Weight
X%
Response Time
Throughput
Error Rate
KPI
92%
67%
86%
25%
20%
15%
X%
5%
97%
Tech Layer

5353

5454

5555
Viewing enterprise metrics through the lens of business implication.
Achieving Digital, Organizational and Human Efficiencies.
Dynamic Business Service Views
Busines
s
Technolo
gy
Emergency
Communications
Partner Portal
Digital Marketing
Store Operations
Insurance - Digital
Commerce Health Care Systems

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