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An IDC InfoBrief sponsored by ServiceNow and Accenture | September 2019 Using AIOps and Cognitive Patterns to Optimize Operations # US45524119TM
An IDC InfoBrief sponsored by ServiceNow and Accenture | September 2019
Using AIOps and Cognitive Patterns to Optimize Operations
# US45524119TM
IDC InfoBrief | Using AIOps and Cognitive Patterns to Optimize Operations
Sponsored by ServiceNow and Accenture | Page 2
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What Is AIOps?The application of analytic capabilities (i.e., Machine Learning, Artificial Intelligence, Natural Language Processing, etc.) on IT operations data sources to automatically solve specific operational challenges, often describing, diagnosing, or recommending a course of action to allow IT to be more proactive. Business services becoming more distributed and interconnected.
• Automatic data ingestion, and the selection of relevant data to solve a specific operational question
• Cognitive pattern capabilities providing the ability to make decisions like humans, but not for humans, until there’s evidence and trust
• Automatic pattern matching to reduce errors and noise
• Application of logic to data, to suggest a reasoning
• Automatic topology data and workflow analysis to have service context awareness
• Automatic machine-driven actions and recommendations that can include humans, digital robots, and runbooks, etc., to accelerate communication processes, and a proactive IT posture
• Improved access to accurate data to accelerate new demand requests for digital services from the business
IDC InfoBrief | Using AIOps and Cognitive Patterns to Optimize Operations
Sponsored by ServiceNow and Accenture | Page 3
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• Business services becoming more distributed and interconnected
• An explosion in the amount of data and resources to be managed
• Multicloud world (private, hybrid, public, SaaS, etc.) adoption
• Containerized, cloud-native architectures
• DevOps and Agile development methodologies and processes
• Software-Defined Infrastructure
• Customer demand from great experiences
• Continuous customer demand for great experiences with shorter timeline
IT Operations Struggle with Increasing Service Complexity, and Rising Customer Expectations
IDC InfoBrief | Using AIOps and Cognitive Patterns to Optimize Operations
Sponsored by ServiceNow and Accenture | Page 4
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Team Silos• Development• Cloud operations• Infrastructure Platform teams • Cloud Architecture• Business operations
Fragmented Tools and Data• Application Performance• Networking• Systems management • Cloud management • Business operations
Leads to• Poor communications • Ineffective root cause analytics• Event storms • Slow response times • No service views • Inaccurate service maps • 2:00 a.m. war rooms• Tribal knowledge • Awkward service desk and customer engagement • Uneducated decision making
Fragmented Tools and Teams Slow IT Operations
All of which prevents IT Operations from moving faster and smarter across any cloud.
IDC InfoBrief | Using AIOps and Cognitive Patterns to Optimize Operations
Sponsored by ServiceNow and Accenture | Page 5
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Source: IDC FutureScape: Worldwide Digital Transformation (DX) 2018 Predictions; IDC IT Operations Analytics Survey, IDC 2016
Traditional Tools Slow IT Operations: What’s Needed to Resolve These Challenges?
Key AIOps capabilities:• Real-time event correlation, with service context• Use context-aware proactive indicators• Enable service health visualization and KPIs• Deliver self-healing remediation• Cognitive pattern capabilities• Access to accurate data for business collaboration
As organizations increasingly adopt multicloud IT environments, cloud-based systems management platforms must:• Automate processes• Drive faster time to resolution• Provide service maps, and deep layers of
visibility• Scale ability to manage complex infrastructure• Simplify through unified management, tied to
the customer experience
IDC InfoBrief | Using AIOps and Cognitive Patterns to Optimize Operations
Sponsored by ServiceNow and Accenture | Page 6
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Artificial intelligence (AI) can be used to apply algorithms to IT operations and enhance current data analytics capabilities to improve outcomes.
Machine learning can be used to automatically analyze and process the vast quantity of events and data being generated by today’s IT environments—learning patterns and applying logic for faster correlation and root-cause analysis.
Outcomes:
• Prevention of future problems and downtime
• Faster triage to point to the root cause
• Optimized processes for manageable scaling and increased complexity
• Dramatically increased agility
• Proactive notification of risk to business partners
Using AIOps Technology Increases Operational Efficiency
IDC InfoBrief | Using AIOps and Cognitive Patterns to Optimize Operations
Sponsored by ServiceNow and Accenture | Page 7
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Source: IDC FutureScape: Worldwide Digital Transformation (DX) 2018 Predictions; IDC IT Operations Analytics Survey, IDC 2016
Scale and Speed Time-to-Problem Identification and Resolution
In a Cloud-based World, AIOps Enables IT Operations Management to Scale
of enterprises expect to buy net new IT Operations Analytics solutions where
top reasons include:
89%current solutions won’t scale sufficiently
44%current solutions don’t support API integrations
42%want to move from on-premise to cloud service operational analytics
54%
IDC InfoBrief | Using AIOps and Cognitive Patterns to Optimize Operations
Sponsored by ServiceNow and Accenture | Page 8
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AIOps Is Different from Traditional Approaches
Traditional Approach• Limited data collection• Manually-defined rules and thresholds • Static service maps• Slow data collection capabilities• Limited automation• No ability to understand data context• Limited data correlation• High number of irrelevant events
AIOps Approach• Large volume data collection • Cognitive pattern-matching and scale-out data normalization • Data correlation with service context• Automated pattern discovery • Automatic data and event processing • Decrease in non-relevant data from proactive analysis• Event correlation mapped to impacted services • Role-based visualization • ML and AI embedded in product • Provide operational service on a single enterprise platform
IDC InfoBrief | Using AIOps and Cognitive Patterns to Optimize Operations
Sponsored by ServiceNow and Accenture | Page 9
# US45524119TM
IT Operations Require a Robust AIOps Engine to Deliver Sustainable Business Outcomes
AIOps Engine Requirements • Machine Learning (ML)• Natural Language processing • Historical and real-time data
analysis/correlation• Service context• Knowledge from human behavior—
semi-supervised operator inputs• Cognitive pattern capabilities
AIOps Engine Output • ML applied to historical and real-time pattern identification• Topology alert correlation across business services • Dynamic thresholding • Event noise reduction • Alert correlation/anomaly detection• Intelligent incident routing
DeliversService Aware
Outcomes• Faster problem ID and resolution• Prevention of service problems • Improved customer experience
IDC InfoBrief | Using AIOps and Cognitive Patterns to Optimize Operations
Sponsored by ServiceNow and Accenture | Page 10
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Important Criteria for AIOps:
Key Success Criteria and Expected KPIs for AIOps
Analysis in context of business services:
• Analyze data at scale
• Detect potential problems and make proactive recommendations
• Quickly perform root cause analysis
• Prioritize remediation by business service
Holistic Service Views:
• Service views that collect and correlate incident, event, and change management data sources
• Accurate, updated service maps
• Cognitive pattern matching
Health Status: • Advanced event suppression,
with tight integration into problem identification and resolution processes
• Knowledge and use of historical incident and problem data
• Use of Machine Learning to reduce event noise and provide service health information
KPIs Associated with AIOps:• Service ticket
reduction • Faster Mean
Time to Repair (MTTR)
• Reduction of P1 incidents
• Service availability improvement
IDC InfoBrief | Using AIOps and Cognitive Patterns to Optimize Operations
Sponsored by ServiceNow and Accenture | Page 11
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Top reasons executives deploy AIOps management software:
• Minimize downtime of business services
• Improve productivity with real-time visibility of business services
• Agility to keep up with the rate of technology change
• Identify and solve problems faster; prevent future problems
• Optimize operational processes
• Scale to manage increasing complexity and data volumes
• Use cognitive pattern technology to reduce event noise
Why Are IT Executives Investing in AIOps Capabilities?
# US45524119TM
IDC InfoBrief | Using AIOps and Cognitive Patterns to Optimize Operations
Sponsored by ServiceNow and Accenture | Page 12
• Integrate historical and real-time data across problem, change, and incident management data pools
• Visibility into private, hybrid, and public cloud resources
• Drive faster time to problem identification and resolution
As service complexity rises:
• Insight into data pools becomes paramount to problem identification and resolution
• Cognitive pattern analytics driven decisions to better identify and solve problems, and drive continuous improvement
• Integrated operational processes that enable tight alignment between customer experience and service availability
• Simplified communications across teams
In a Cloud-based World, AIOps Delivers Faster, More Accurate Visibility and Control
IDC InfoBrief | Using AIOps and Cognitive Patterns to Optimize Operations
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How Accenture & ServiceNow Can HelpA well-executed AIOps strategy can help unlock the value of cloud IT Transformation, as well as align and drive towards cognitive patterns that deliver high-performance business outcomes through agility and speed to innovation.
IT Transformation
AIOps Use CasesCommon challenges lead to a collection of prescribed, experience solutions – The How
Analytics combined with automation provide the foundation for the impactful cultural transformation
Machine Learning can enable the combined system(s) to generate the trend analysis to move from reactive to proactive activities
Leveraging a single platform to deliver high performance services and a single system of record for IT – The What
Intelligent Data Lifecycle Management
Establish complete visibility across your
operations estate
Enhance trust in IT
Intelligent Infrastructure Management
Deliver business service health with AIOps
Improve operationalproficiency
DevOps Analytics
Optimize spend on cloud usage and software
Retire archaictoolsValue Driven Outcomes
that reduce cost while also enhancing productivity – The Why
MESSAGE FROM THE SPONSORS
IDC InfoBrief | Using AIOps and Cognitive Patterns to Optimize Operations
Sponsored by ServiceNow and Accenture | Page 14
# US45524119TM
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