End to-End Monitoring for ITSM and DevOps

6/15/201
8
Oracle Confidential – Internal/Restricted/Highly
Restricted
1
End-to-End Monitoring, ITSM and DevOps
An eG Innovations Shift-Left Webinar
A
Shift-Left Series
Webinar
www.eginnovations.com
Dev Test Stage Prod

© eG Innovations, Inc | www.eginnovations.com
Moderator
• Wendy Howard, Technical Consultant
• Wendy.Howard@eginnovations.com

Logistics
Please submit your questions at any time
during the webinar using the questions
panel on the GoToWebinar client.
This webinar is being recorded. You will
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A copy of this presentation is posted on
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http://www.slideshare.net/eginnovations/

Today’s Presenter
Copyright eG Innovations 4
• John Worthington, Director Product Marketing
• John.Worthington@eGInnovations.com
• 201.826.1374

About the Shift Left Series..
The Shift-Left Series webinars
focus on ITSM, DevOps and
emergence of converged
application and infrastructure
performance management
A
Shift-Left Series
Webinar
Dev Test Stage Prod

Today’s agenda
• Introduction
• End-to-end monitoring and
the importance of domain
expertise
• Monitoring, observability
and analytics
• Monitoring in ITSM and
DevOps environments
• Conclusion

About eG Innovations
Faster diagnosis and resolution of
performance problems
Enhanced service delivery and user
satisfaction
Maximum business productivity
and cost savings
Accelerated IT deployments and
production rollouts
Transform IT Service Delivery
into Business Advantage
Worldwide Locations
Global Headquarters: Singapore
US Headquarters: New Jersey
Founded in 2001
eG Innovations is a provider of enterprise-class IT performance management
software that delivers end-to-end monitoring, diagnosis, reporting, and
analytics across physical, virtual, cloud, and hybrid IT environments

What we do...
eG Enterprise takes measurements at every layer of every component of an
end-to-end IT service, learns the norms of all measurements, and through
patented analytics automatically isolates which layer of which component is
the source of an anomaly.
Today we do this across any cloud deployment model and from code to
bare metal.
Thorough coverage,
across every layer
and every tier.
Immediate, actionable
insights across dynamic
and distributed
infrastructures
Rapid troubleshooting
and remediation via
automated problem
diagnosis

End-to-end Monitoring and the
Importance of Domain Expertise

• Enterprises are looking to cloud service providers to outsource
costs and risks...
Cloud Service Providers
In a cloud, you release control of so many areas that it’s important to retain simplicity
in the areas you can still control. Whether you move your on-premises infrastructure to
the cloud or create new solutions there, make sure you do the availability math ... and
are prepared for the chaos.
When debugging a broken system, you should first look at your infrastructure tests
... . Testing should expose any infrastructure components that are not configured
properly or are not providing the expected performance. Just because you don’t
manage the underlying infrastructure doesn’t mean the infrastructure
cannot be the cause of your problems.
– Cloud Native Infrastructure, O’Reilly Media
...but this doesn’t mean infrastructure has disappeared!

Cloud Native Realities
• 'Cloud native’ refers to applications or services that are
container-packaged, dynamically scheduled and micro
services-oriented
• Bare metal (physical infrastructure) and virtual machines will
coexist with container technology; hyperconverged
infrastructures can provide flexibility to leverage both
approaches
“there are still a lot of enterprise workloads -- 44% by IBM's estimate -- that will
remain on dedicated servers, said Arvind Krishna, senior vice president for hybrid cloud
at IBM and director of IBM Research. For many businesses, it's too disruptive to refactor
applications for cloud computing.”
– TechTarget

Operating Models
• Applications ≠ Services
– A services-oriented approach is
paramount
– Services provide the context
needed to understand business
impacts and dependencies
– A single digital business
service could have multiple
different ecosystems and
infrastructure
– Performance monitoring will
need to address multiple
operating models and supplier
relationships
APM and Digital Business Services
Business Transaction Health
Application Health
Infrastructure Health
Create Order Create Invoice Ship Product
Digital Business Service
Real User Monitoring | Synthetic Monitoring | Business Transaction Tracing
Order Service Invoice Service Logistics Service
Legacy Data Ctr Private Cloud Public Cloud
Topology Discovery | Code-Level Correlation
Pre-Emptive Alerting | Automated Diagnostics | Capacity Planning | Right Sizing
Digital User Experience
APM Solutions
must address
business
transaction,
application and
infrastructure
health
IaaS PaaS SaaS
Waterfall | Agile | ITSM / DevOps | Continuous Delivery
Physical Infrastructure | Virtualization | SDDC | Cloud Native
Multi-Mode Operating Models

Converged Application/Infrastructure Health
Legacy
Digital Business Service Workloads
• Workloads include
applications and their
supporting ecosystems
• Not all workloads are
suitable for migration to the
cloud
– Application characteristics
– Cloud service model (IaaS,
PaaS, SaaS)
– Cloud deployment model
(Public, Private, Hybrid)
Private/
Hybrid
Public
Order
App
Invoice
App
Logistics
App
Workload 1 Workload 2 Workload 3
Segment 1 Segment 2 Segment 3
End-to-End Digital Business Service
Cloud Resource Pools

End-to-End Monitoring and the Importance of Domain
Expertise
• All applications are not the same
Application Types Examples
Web applications Typically, custom applications built on technologies such as
Java, .NET, PHP, Python, Node.js, Rails, etc.
Packaged enterprise
applications
SAP, Siebel, PeopleSoft, SharePoint, Atlassian Confluence,
Salesforce, etc.
Desktop-based applications Microsoft Office, QuickBooks, Graphics tools, etc.
Mobile applications Applications natively built to run on mobile platforms
Middleware applications Application servers, message queues
Backend applications Databases
Infrastructure applications Active Directory, DNS, DHCP, etc.
VDI applications Citrix, VMware Horizon, Microsoft RDS

APM: Why One Size Does Not Fit All
• Monitoring of an application should broadly cover health,
availability, response time, and usage
• Detailed performance metrics in each category above are
dependent on the nature and domain of the application
– i.e., metrics that apply for SAP may not apply for a .NET-based web
application;
– performance monitoring of a database would be entirely different
from VDI application (such as Citrix)
• Domain expertise is needed
– How the application functions, protocols it uses, inter-application
dependencies, single/multi-threaded, common failure modes, etc.
Understand the scope of your digital business services and the
underpinning ecosystems needed to support them!

Monitoring, Observability
And Analytics

Monitor and Control Loops
• Monitor and control loops1 can be simple...
1 ITIL v3 Service Operations, page 123

• ...or complex!

• Digital business services
have end-to-end and top-
to-bottom dependencies
• Deviations from normal
behavior can ripple across
these dependencies
• This is inclusive of
applications and
infrastructure regardless of
deployment model
T
O
P
-
T
O
-
B
O
T
T
O
M
END-TO-END

ITSM Monitor and Control Loop
• Service Strategy defines
architectures and
standards
• Service Design defines
norms along with
monitoring and control
mechanisms
• Monitor and control loops
are within an
organizational context;
design must bridge strategy
and operations

Monitoring and Observability
• Monitoring provides
critical feedback to design
and development
Monitoring
Observability
• Digital Business Services
that are designed with
observability in mind
provide mechanisms that
build telemetry into the
service that can trigger
self-healing through
embedded analytics and
automated diagnostics.

Monitoring and Observability
• In practice, the service
management monitor and
control loop is a ‘yin-yang’
relationship between
observability and
monitoring.
• They are complementary,
interconnected,
interdependent and they
may give rise to each other
as they interrelate to one
another
The cycles of feedback generated by service management’s complex
control loops are dependent on observability and monitoring!

Analytics, Monitoring and Observability
Fastest
Faster
Fast
Accelerating Development Pipeline..
As the business asks for more
rapid development pipelines
(i.e., continuous delivery)...
....the cycles of monitoring
and observability
accelerate...
...which drives the need for
analytics...

Analytics, Monitoring and Observability
...but like monitoring, Analytics is a very broad area and could
include discovery, interpretation and communication of
meaningful patterns in [almost any] data1!
– People, Process, Technology
– Business (Risk, Portfolio, Marketing, etc.) and IT (InfoSec, Operations,
Software, etc.)
1Wikipedia
Accelerating Development Pipeline..
Since managing the end user experience is
the basis of competition in the digital
services world...
...performance monitoring of digital
business services has become a front-burner
issue!

Performance Analytics, Monitoring and Observability
• A One-Size-Fits-All approach
to analytics may not address
the critical requirements of
performance monitoring and
observability for digital
business services
– People
– Process
– Technology
T
O
P
-
T
O
-
B
O
T
T
O
M
END-TO-END
Process and People analytics may
involve ITSM, Business
Intelligence or even Forensic
Analysis (InfoSec) tools

Application Health
Infrastructure Health
Create Order Create Invoice Ship Product
Real User Monitoring | Synthetic Monitoring | Business Transaction Tracing
Order Service Invoice Service Logistics Service
Legacy Data Ctr Private Cloud Public Cloud
Topology Discovery | Code-Level Correlation
Pre-Emptive Alerting | Automated Diagnostics | Capacity Planning | Right Sizing
 User
experience
 Business
transactions
 Application
performance
 Infrastructure
performance
Customer
Experience Is
the New
Competitive
Battlefield1
1Gartner
...don’t be confused by
buzzwords like algorithmic IT
operations, or advanced IT
analytics...

• Descriptive Analytics
– data aggregation and data mining to provide insight into the past and
answer: “What has happened?”
• Pre-correlated alerts indicate
root-cause and provide
meaningful notifications that are
actionable
• i.e., what just happened?
• Historical analysis and trending
• How do we compare to prior
baselines?
• When will we reach
maximum capacity?
Critical Code-Level Correlation
The Devil’s
in the
Details!
Capacity Planning & Optimization
Dynamic Baselining
Migration Analysis

• Predictive Analytics
– statistical models and forecasts techniques to understand the future
and answer: “What could happen?”
• Pre-correlated alerts also indicate
effects and provide early warning
• i.e., what could happen if no
action is taken?
MinorX
Aberdeen research has shown that by implementing IT monitoring and analysis platforms that
have a complete, end-to-end view of all systems and applications, along with predictive
analytics that can detect problems before they happen, organizations have high uptime,
excellent performance, and are able to reduce costs and overcome the challenges of a modern IT
operation.
Preemptive Problem Detection and Alerting
Application Topology Discovery & Visualization
Cloud Performance Assurance
Automatic Thresholding & Dynamic Baselining

• Prescriptive Analytics
– optimization and simulation algorithms to advice on possible
outcomes and answer: “What should we do?”
• Simulated transactions and user
experience monitoring leverage
analytics for determining possible
outcomes
• Site-specific knowledge
management provide for context
sensitive search
• Situationally-aware self-help
embedded in the monitor
Right Sizing and Optimization
Auditing and Configuration Change Tracking
Knowledge Sharing
Simulation

• Other Relevant Use Cases
– Log Analytics
• Business and IT use cases in risk management, compliance, security analysis,
market intelligence, e-commerce personalization, and fraud detection
– Embedded Analytics
• Integrates analytic content and capabilities within a process
• Often used in Business Intelligence applications
– Provides relevant information and analytical tools designed for a specific task
– Provides information in the context of a decision or action
– Enables more efficient use of applications by users
These use cases have some applicability to monitoring the performance
of digital business services, however they may fall short of what’s
needed for a complete solution

Demonstration
Video
NOTE: The video's audio feed will be played through Computer audio
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If you are not hearing the audio properly (whether you are connected
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plugged in).

End-to-End Monitoring,
ITSM and DevOps
Getting from Here to There with
converged application and
infrastructure performance
monitoring

Customer Experience Is the New Competitive Battlefield
• 73% of businesses are experiencing productivity losses
due to slow application performance
‘Slow’ is the New Down
“58% reported that monitoring IT performance from
user perspective as a strategic goal for IT
transformation” – Digital Enterprise Journal

Service Definition Still Matters
• Understanding and defining
IT services has been– and will
remain– critical to success
– The basis of ITSM
– Fundamental to DevOps –
define value from customer
perspective
– Cloud workload attributes are
similar to – if not the same– as
ITIL’s Service Design Package
Legacy
Private/
Hybrid
Public
Order
App
Invoice
App
Logistics
App
Workload 1 Workload 2 Workload 3
Segment 1 Segment 2 Segment 3
End-to-End Digital Business Service
Cloud Resource Pools
Customers who define and implement monitoring requirements from a
pure technology perspective will continue to have their attempts at IT
transformation frustrated.

Key Monitoring Considerations
• Your approach to IT analytics should account for existing IT services
and differentiate between IT and business analysis
• Analytics must account for cross-domain characteristics (every layer,
every component) and incorporate domain expertise
• Ability to collect data from a wide variety of data sources and use
appropriate collection methods
• Flexibility to adapt to multiple operating models
Mainframe Client-Server
Web
Virtualization
Cloud
Mobile
Containers
Performance
expectations
Increasing Velocity
Hardware/Physical Resources
NET
WEB
APP
DB
Legacy
Virtual Infrastructure
APP APP APP
DB
Virtualized
Resource Management /
Scheduling
Containers / Packaging
Service Layer
Application Framework /
Business Logic
Cloud Native
IT Operating Model
Maturity
Quality
Gap
Digital business services could be
comprised of multiple application
ecosystems
• Front end ‘Systems of Innovation’
• Web-based ‘Systems of Differentiation’
• Back-end ‘Systems of Record’
IT analytics should encompass all
these ecosystem components
System of
Innovation
System of
Differentiation
System of
Record
Remember monitor and control loops are within an organizational context–
this suggests that process capability/maturity will play a factor

APM in the Digital Enterprise
• The data and metrics collected at instrumentation points across the
application ecosystem are essential to performance monitoring and
root cause analysis.
• However, analytics capable of transforming data and metrics into an
application-focused report or dashboards are what separates actual
application monitoring from relatively simple silo monitoring.
• Analytics add the context necessary to understand the role of each
moving part in the end-to-end execution environment, a viewpoint
that is absolutely critical for rapid— and eventually automated—
problem determination and resolution.
• Without this context, these solutions would simply be operational data
stores versus true tools capable of insight into application ecosystems
Sturm, Rick; Pollard, Carol; Craig, Julie. Application Performance Management (APM) in the Digital Enterprise: Managing
Applications for Cloud, Mobile, IoT and eBusiness (Kindle Locations 4086-4091). Elsevier Science. Kindle Edition.

Importance of APM/IPM Convergence
Digital
Business
Services
Simply put, monitoring digital
business services must account
for the entire service:
• Heterogeneous
components
• Multi-vendor devices
• Legacy or Cloud
• End User Experience
• Code to Bare Metal
Continuous monitoring is
enabled by convergence of
application and infrastructure

Importance of APM/IPM Convergence
Digital
Business
Services
Dev Test Stage Prod
Unified Monitoring

Getting from Here to There
• Anticipate stakeholder challenges
• Focus on services, rather than
technologies
–Digital Workspaces
–APM Approaches
–End-to-End Approaches
Getting from Here to There with
converged application and
infrastructure performance
monitoring

The Digital Workspace Approach
• Digital workspaces such as Citrix Workspace and VMware
Horizon deliver applications and/or desktops to end users
• If the workspace is slow, so is the digital business service
• If you cannot logon to the workspace, the digital business
service is down
• ‘Bottom-up’ approach
• Enables rapid ROI and a foundation to build on
May risk effective linkage to the business (i.e.,
limited to domain) if a service view is not taken

The APM Approach
• Target an application for real user monitoring and transaction
tracing
• Enables service teams working in pre-production to improve
performance testing (i.e., shift-left)
• ‘Top-Down’ approach
• Auto-diagnosis capability expands as underlying infrastructure
is instrumented
Will not fully exercise converged APM/IPM

The Digital Business Service Approach
• Target a complete business service for unified monitoring
• Allows enterprise to exercise converged application and
infrastructure performance monitoring ‘day 1’
• ‘Top-Down’ approach
• Service targeting is critical
Beware of stakeholder complexity and
organizational maturity constraints

Multiple Operating Model Challenges
Monitoring challenges are
different based on:
• Lifecycle Stages
• Environments and technologies
• Operating Models
Monitoring flexibility needed to
address end-to-end IT services
that may span multiple operating
models and technologies
ITIL©
DevOps
Service
Design
Service
Transition
Service
Operation
Plan &
Build
Release Operate
Lifecycle
Stages
Environments
Dev Test
Pre-
Prod
Prod
Build Test Stage
Accept
Test
Deploy to
Prod
Validation
Test
Continuous Integration
Continuous Deployment
Continuous Delivery
Need rapid, more frequent
testing & monitoring
Need increasing monitoring
depth and reach
Testing and Monitoring Across the Lifecycle
Mainframe Client-Server
Web
Virtualization
Cloud
Mobile
Containers
Performance
expectations
Increasing Velocity
NET
W EB
APP
DB
Legacy
H a r dw a re /Phy sical R esou rce s
V ir tua l In fr astr u ctur e
A PP A PP A PP
D B
Virtualized
Har dware/Physical Resources
R esour ce M anagement /
Scheduling
Containers / Packaging
Service Layer
Ap plicatio n Frame work /
Bus ine ss Logic
Cloud Native
IT Operating Model
Maturity
Quality
Gap

End-to-End Monitoring Moves You From ROI to VOI
Initial Installation Investment:
• Supporting IT services / infrastructure
• Limited organizational scope
• Rapid ROI / Payback
Return-on-Investment
83%
Users saw value within a month
of installing eG Enterprise
Source: TechValidate
72%
Users reported that eG Enterprise
helped reduce the time to identify the
root-cause of application performance
problems
70%
Users stated that eG Enterprise helped
identify the cause of complex
application performance problems that
involve multiple domains
Incremental
Implementation
Investments:
Customer-facing IT services
Increasing organizational scope
Compounding benefits associated with IT transformation
Accelerated flow, culture change
Improved QOS
Self-healing correlation, improved availability
Value-of-Investment

Free Trial
http://www.eginnovations.com/freetrial
Send an Email
info@eginnovations.com
Call Us
+1 (866) 526 6700
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End to-End Monitoring for ITSM and DevOps

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