More Related Content Similar to Making AIOps-Driven Network Performance Management a Reality (20) More from Enterprise Management Associates (20) Making AIOps-Driven Network Performance Management a Reality1. Making AIOps-Driven
Network Performance
Management a Reality
Shamus McGillicuddy
Vice President of Research
EMA
Jason Carrier
Senior Product Manager
IBM SevOne NPM
Jeremy Hughes
Product Manager
IBM Cloud Pak for Watson AIOps
Jacob Yackenovich
Program Director of Product Management
IBM Cloud Pak for Watson AIOps
3. | @ema_research
© 2022 Enterprise Management Associates, Inc. 3
Shamus McGillicuddy
Vice President of Research
Jason Carrier
Senior Product Manager
Jeremy Hughes
Product Manager
IBM Cloud Pak for Watson AIOps
Jacob Yackenovich
Program Director of Product Management
IBM Cloud Pak for Watson AIOps
Shamus is the vice president of
research at Enterprise
Management Associates (EMA),
where he leads the network
infrastructure and operations
practice. He has more than 15
years of experience in the IT
industry. His research focuses on
all aspects of managing
enterprise networks, including
network automation, AIOps-
driven network operations,
multi-cloud networking, and
WAN transformation.
Jason is currently a senior
product manager on the
SevOne team, responsible for
Streaming Telemetry Solutions
and integration with Watson
AIOps. He has specialized
experience in network
performance management,
network automation, and the IT
service management market
segments.
Jeremy has 17 years of
experience in the WebSphere
product ecosystem bringing
new technologies and
WebSphere integrations to
market. He led the integration
of Enterprise OSGi technology
into WebSphere; the integration
of IBM's Liberty app server
runtime with open source and
industry standard DevOps tools
such as Chef, Puppet, and
Maven.
With over 20 years of
experience, Jacob is currently
the program director of
product management for the
IBM Cloud Pak for Watson
AIOps. His experience in IT spans
engineering, architecture, and
product management roles. He
holds several patents in IT
analytics and resource
reconciliation.
4. | @ema_research
What is AIOps-Driven Network Performance Management?
© 2022 Enterprise Management Associates, Inc. 4
Artificial Intelligence for
IT operations
Products and product features
that use AI and machine learning
algorithms, big data, and other
advanced analytics to enhance IT
management tools and processes
What should you expect from a solution?
• Ingest, normalize, and analyze a variety of network and
non-network data
• Discern what data is relevant to a given event or job
• Detect and recognize patterns in data
• Discover insights or draw conclusions from patterns
• Communicate insights to human operators via reports, alerts,
natural language communication
• Automate the network via AIOps-derived insights
5. | @ema_research
The Business Value of Applying AIOps to
Network Management
© 2022 Enterprise Management Associates, Inc. 5
90% of research participants agree:
• Applying AIOps to network management can lead to “better business
outcomes for my overall enterprise.”
• Stronger agreement from people who are:
• Most experienced with AIOps solutions
• Most effective with evaluating AIOps solutions
Most important benefits
• Network optimization (44%)
• Operational efficiency (41%)
• Improved security/compliance (40%) - ranked higher by
successful users
• Network resiliency (37%)
• Cost reduction (32%)
6. | @ema_research
Domain-Specific Versus Domain-Agnostic AIOps
© 2022 Enterprise Management Associates, Inc. 6
How IT orgs procure AIOps for network management
• 26% – Network team adopting domain-specific AIOps solutions
• 25% – IT organization adopting domain-agnostic AIOps solutions
• 46% – IT Organization adopting domain-specific and domain-agnostic
Beyond the IT organization
• 83% of companies have initiatives to apply AI to the entire business
• 71% of these AI initiatives are influencing and driving AIOps interest
7. | @ema_research
Optimizing Network Management Tools
© 2022 Enterprise Management Associates, Inc. 7
91% of enterprises expect AIOps to address
network management tool problems
• Conflicting/inaccurate data or insights (43%)
• Lack of real-time insights (42%)
• Cross-tool fragmentation (39%)
• Tools lacking big-picture views (35%)
• Usability issues (35%)
• Lack of drilldowns in dashboards and reports (31%)
• Poorly defined workflows (23%)
8. | @ema_research
Top Use Cases for AIOps-Driven Network Management
© 2022 Enterprise Management Associates, Inc. 8
“We were trying to understand a
network flow that looked like a DDoS
attack. We had a look at it through
our data lake [using standard
analytics tools], and it took three
hours to get an answer.
In parallel – as an experiment – I had
someone tackle the same problem
with our AIOps tool, which was able
to do it in 22 minutes. It reduced the
amount of time that we spent simply
structuring queries and mining data.”
Network Operations Manager,
$10+ Billion High-Tech Manufacturer
Anomaly
detection
(56%)
Automated
security incident
remediation
(55%)
Intelligent
alerting/escalation
(53%)
Automated IT
service problem
remediation
(52%)
Automated root
cause analysis
(44%)
Automation of
threshold and
monitoring settings
(44%)
9. | @ema_research
Only 30% of NetOps Teams Believe They’ve Been Fully Successful with AIOps
© 2022 Enterprise Management Associates, Inc. 9
“We’ve tried to get it implemented, but it
hasn’t been done. It’s not easy to implement
and build out, and I think that’s where it got
bogged down in my company.”
A network architect with a
$10+ billion retailer
Top technical challenges
1. Network complexity (30%)
2. Data quality (28%)
Top business issues
1. Security or compliance risk (42%)
2. Budget shortfalls (30%)
3. Network team skills gaps (29%)
4. Time to value (21%)
“TCO is a big concern. Maybe I spend $15,000
to install a solution, but it costs me $100,000 a
year to keep it running and delivering value.
How much storage will the data consume?
Also, complexity of deployment is a problem
and complexity of maintenance. I worry that I
will have a team of two or three people
keeping it running.”
Network operations manager,
$10+ billion high technology manufacturer
10. How are Ops teams
succeeding with
AI/ML in network
performance
management
today?
12. How does IBM plan
to transform network
performance
management with
AIOps?
13. IBM Network Performance Management & AIOps Solutions
Wholistic
Application Context
ChatOps &
Collaboration
Next Best Action
and Automation
Anomaly
Detection
Infrastructure
Automation
Watson AI and machine learning
I BM Cloud Pak for
Watson AI Ops
IBM Automation Foundation
CI/CD, tickets, logs, metrics, events, topology, digital experience, organizational, cost and budget, energy
IBM SevOne Network Performance Management
ML-based
Advanced Analytics
Advanced
Visualization/Workflow
IT Operations
Integration
All
the Network Data
SD-WAN, MPLS WAN, WI-FI, Campus, Branch, SDN, Multi-Cloud Datacenter, Hybrid, Servers, Databases,4G/5G
Enterprise, Communication Services Provider and Managed Services Provider Networks
Let’s continue the
conversation
Join our IBM SevOne NPM
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