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How Does AIOps Benefit DevOps Pipeline and Software Quality? - DevOps Next
© 2020 Perforce Software, Inc.
How Does AIOps Benefit
the DevOps Pipeline and
Software Quality?
E R A N K I N S B R U N E R
3 | DevOps Next 2020 perforce.com
Confidentiality Statement
The information contained in this document is strictly confidential, privileged, and
only for the information of the intended recipient. The information contained in this
document may not be otherwise used, disclosed, copied, altered, or distributed
without the prior written consent of Perforce Software, Inc.
ABOUT ME:
Eran Kinsbruner
• Chief Evangelist, Product Manager, and Author at Perfecto by Perforce
• Blogger, Inventor, and Speaker
• 20+ years in software development & testing
• Author of:
• The Digital Quality Handbook
• Continuous Testing for DevOps Professionals
• Accelerating Software Quality
• Twitter: @ek121268
5 | DevOps Next 2020 perforce.com
Today’s Agenda
1
2
Introduction and Importance of AIOps in DevOps
Key Pillars of AIOps Solutions
3 Quantifying the Value of AIOps
Q&A5
4 Future of AIOps in DevOps
6 | DevOps Next 2020 perforce.com
AIOps, (artificial intelligence for IT operations) is the application of artificial intelligence (AI) to enhance IT operations.
Specifically, AIOps uses big data, analytics, and machine learning capabilities to do the following:
• Collect and aggregate the huge and ever-increasing volumes of operations data generated by multiple IT
infrastructure components, applications, and performance-monitoring tools.
• Intelligently sift ‘signals’ out of the ‘noise’ to identify significant events and patterns related to system performance
and availability issues (detect business anomalies).
• Automatically diagnose root causes and report them to IT for rapid response and remediation — or, in some cases,
automatically resolve these issues without human intervention.
Introduction to AIOps
7 | DevOps Next 2020 perforce.com
• Enhance organizations digital transformation
• Achieve faster MTTR (focus on real issues instead of noise)
• Go from reactive to proactive to predictive management (predictive alerting)
• Modernize your IT operations and your IT operations team (focus on innovation rather then KTLO)
AIOps Benefits
Source: Nextel Case Study
8 | DevOps Next 2020 perforce.com
AIOps Objectives
Source: AppDynamics
9 | DevOps Next 2020 perforce.com
AIOps – Predict and Prevent Ops Issues With ML
Source: Splunk
10 | DevOps Next 2020 perforce.com
• Automated pattern discovery
and prediction
• ZIF uses ML and predictive
techniques to identify an event that
can turn into a high severity incident
even before it reached the service
desk agent
• ZIF can perform Level-0 Triaging
of incidents and assign it to the
appropriate desk agent
• AI voice
assistance
AIOps Example
Source: Gavstech
11 | DevOps Next 2020 perforce.com
AIOps Solution Example
Source: https://www.validatek.com/technologies/ai-ops
• Key Features:
• Event correlation
• Noise reduction (filters, blacklisting,
etc.)
• Collaboration between security and
operations
• Ecosystem automation (auto-
ticketing, auto-diagnostics,
escalation, etc.)
• Flexible implementation options
(SaaS, on-premise, hybrid)
• Integration with third party tools
(Splunk, Remedy, SolarWinds)
12 | DevOps Next 2020 perforce.com
• Historical analysis of issues (e.g. service tickets).
• Current and older performance analysis.
• High-risk product anomalies that were detected.
• Outages and other service-related issues.
• Key user journey analysis.
• Pattern discovery and correlation.
• Market-specific KPIs and analytics (benchmarks).
• Product specific inputs.
AIOps Input Data
13 | DevOps Next 2020 perforce.com
AIOps Maturity Model and Components
Science Logic Definition of AIOps and its Maturity Model https://sciencelogic.com/solutions/aiops
14 | DevOps Next 2020 perforce.com
APM + ITIM + ITSM =AIOPS
APM – Application Performance Management
ITIM – IT Infrastructure Monitoring
ITSM – IT Service Monitoring
15 | DevOps Next 2020 perforce.com
AIOPS Within DevOps Processes
Source: Medium.com
16 | DevOps Next 2020 perforce.com
APM – Current State of the Market
Anomalies detection, grouping, & correlation Real-time proactive detection
17 | DevOps Next 2020 perforce.com
APM – Current State of the Market
Incident Intelligence
18 | DevOps Next 2020 perforce.com
• Builds leave a trail of unnecessary
files behind them, which can
quickly amount to TBs of data. A
cleanup script was created to scan
through the build data and remove
these files, and the team built a
dashboard to monitor its activity —
the amount of data cleaned as well
as the processes left behind.
ITIM – Current State of the Market
19 | DevOps Next 2020 perforce.com
ITIM – Current State of the Market
20 | DevOps Next 2020 perforce.com
ITSM – Current State of the Market
Incident management for managing and
tracking incidents
Problem management for managing problem
investigations from detection to eradication,
through the ITIL subprocesses of problem
control, error control, and proactive problem
analysis.
Change and release management for tracking
scheduled and planned infrastructure
changes.
Service-level management for tracking
service-level commitments with customers
and from vendors, so management can
pinpoint weaknesses and take corrective
action.
21 | DevOps Next 2020 perforce.com
ITSM – Current State of the Market
22 | DevOps Next 2020 perforce.com
Future of AIOps
• Integral part of DevOps and IT management
• Shorter DevOps and production issues cycles
• Higher code quality continuously, more emphasis on shift-right processes
• Better cross-function collaboration (Dev, QA, Ops, Business)
© 2020 Perforce Software, Inc.
Expert Panel & Closing Keynote
UP NEXT…
Thank You!

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How Does AIOps Benefit DevOps Pipeline and Software Quality? - DevOps Next

  • 2. © 2020 Perforce Software, Inc. How Does AIOps Benefit the DevOps Pipeline and Software Quality? E R A N K I N S B R U N E R
  • 3. 3 | DevOps Next 2020 perforce.com Confidentiality Statement The information contained in this document is strictly confidential, privileged, and only for the information of the intended recipient. The information contained in this document may not be otherwise used, disclosed, copied, altered, or distributed without the prior written consent of Perforce Software, Inc.
  • 4. ABOUT ME: Eran Kinsbruner • Chief Evangelist, Product Manager, and Author at Perfecto by Perforce • Blogger, Inventor, and Speaker • 20+ years in software development & testing • Author of: • The Digital Quality Handbook • Continuous Testing for DevOps Professionals • Accelerating Software Quality • Twitter: @ek121268
  • 5. 5 | DevOps Next 2020 perforce.com Today’s Agenda 1 2 Introduction and Importance of AIOps in DevOps Key Pillars of AIOps Solutions 3 Quantifying the Value of AIOps Q&A5 4 Future of AIOps in DevOps
  • 6. 6 | DevOps Next 2020 perforce.com AIOps, (artificial intelligence for IT operations) is the application of artificial intelligence (AI) to enhance IT operations. Specifically, AIOps uses big data, analytics, and machine learning capabilities to do the following: • Collect and aggregate the huge and ever-increasing volumes of operations data generated by multiple IT infrastructure components, applications, and performance-monitoring tools. • Intelligently sift ‘signals’ out of the ‘noise’ to identify significant events and patterns related to system performance and availability issues (detect business anomalies). • Automatically diagnose root causes and report them to IT for rapid response and remediation — or, in some cases, automatically resolve these issues without human intervention. Introduction to AIOps
  • 7. 7 | DevOps Next 2020 perforce.com • Enhance organizations digital transformation • Achieve faster MTTR (focus on real issues instead of noise) • Go from reactive to proactive to predictive management (predictive alerting) • Modernize your IT operations and your IT operations team (focus on innovation rather then KTLO) AIOps Benefits Source: Nextel Case Study
  • 8. 8 | DevOps Next 2020 perforce.com AIOps Objectives Source: AppDynamics
  • 9. 9 | DevOps Next 2020 perforce.com AIOps – Predict and Prevent Ops Issues With ML Source: Splunk
  • 10. 10 | DevOps Next 2020 perforce.com • Automated pattern discovery and prediction • ZIF uses ML and predictive techniques to identify an event that can turn into a high severity incident even before it reached the service desk agent • ZIF can perform Level-0 Triaging of incidents and assign it to the appropriate desk agent • AI voice assistance AIOps Example Source: Gavstech
  • 11. 11 | DevOps Next 2020 perforce.com AIOps Solution Example Source: https://www.validatek.com/technologies/ai-ops • Key Features: • Event correlation • Noise reduction (filters, blacklisting, etc.) • Collaboration between security and operations • Ecosystem automation (auto- ticketing, auto-diagnostics, escalation, etc.) • Flexible implementation options (SaaS, on-premise, hybrid) • Integration with third party tools (Splunk, Remedy, SolarWinds)
  • 12. 12 | DevOps Next 2020 perforce.com • Historical analysis of issues (e.g. service tickets). • Current and older performance analysis. • High-risk product anomalies that were detected. • Outages and other service-related issues. • Key user journey analysis. • Pattern discovery and correlation. • Market-specific KPIs and analytics (benchmarks). • Product specific inputs. AIOps Input Data
  • 13. 13 | DevOps Next 2020 perforce.com AIOps Maturity Model and Components Science Logic Definition of AIOps and its Maturity Model https://sciencelogic.com/solutions/aiops
  • 14. 14 | DevOps Next 2020 perforce.com APM + ITIM + ITSM =AIOPS APM – Application Performance Management ITIM – IT Infrastructure Monitoring ITSM – IT Service Monitoring
  • 15. 15 | DevOps Next 2020 perforce.com AIOPS Within DevOps Processes Source: Medium.com
  • 16. 16 | DevOps Next 2020 perforce.com APM – Current State of the Market Anomalies detection, grouping, & correlation Real-time proactive detection
  • 17. 17 | DevOps Next 2020 perforce.com APM – Current State of the Market Incident Intelligence
  • 18. 18 | DevOps Next 2020 perforce.com • Builds leave a trail of unnecessary files behind them, which can quickly amount to TBs of data. A cleanup script was created to scan through the build data and remove these files, and the team built a dashboard to monitor its activity — the amount of data cleaned as well as the processes left behind. ITIM – Current State of the Market
  • 19. 19 | DevOps Next 2020 perforce.com ITIM – Current State of the Market
  • 20. 20 | DevOps Next 2020 perforce.com ITSM – Current State of the Market Incident management for managing and tracking incidents Problem management for managing problem investigations from detection to eradication, through the ITIL subprocesses of problem control, error control, and proactive problem analysis. Change and release management for tracking scheduled and planned infrastructure changes. Service-level management for tracking service-level commitments with customers and from vendors, so management can pinpoint weaknesses and take corrective action.
  • 21. 21 | DevOps Next 2020 perforce.com ITSM – Current State of the Market
  • 22. 22 | DevOps Next 2020 perforce.com Future of AIOps • Integral part of DevOps and IT management • Shorter DevOps and production issues cycles • Higher code quality continuously, more emphasis on shift-right processes • Better cross-function collaboration (Dev, QA, Ops, Business)
  • 23. © 2020 Perforce Software, Inc. Expert Panel & Closing Keynote UP NEXT…