The document discusses steps towards autonomous operations (AIOps) through the use of artificial intelligence. It notes four challenges in traditional operations including lack of information, information overload, inability to correlate data, and identifying dynamic trends. The key to AIOps is setting up systems to observe infrastructure and applications, collect and store all available data, query and mine patterns in the data, and generate alerts, notifications and automatic remediation. This allows for predictive and preventative insights that reduce manual operations work and improve service quality. An example from Edmunds.com showed how container stability prediction reduced user issues by 95% and on-call time.

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AIOps: steps towards autonomous
operations
E N T 3 0 1 - R
Ajit Zadgaonkar
Global DevOps Leader
AWS Professional
Services
Stephen Felisan
CIO, Edmunds.com

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First, a little about me…
Likes
• Operational efficiency
• Architecting for operability
• Making new mistakes
Dislikes
• Engineering Vs business breakdowns
• Processes killing creativity
• Alert fatigue
Ajit Zadgaonkar
AWS Professional Services

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Agenda
The battle of Ops world
AiOps
See it in action
Words of Wisdom

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What we are really trying to achieve …
Infrastructure
Support
Innovation
Infrastructure
Support
Innovation
Innovation
Support
✅

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Efficiency expressed in numbers …
440x
Shorter Lead Times
60x
Fewer Failures
21%
Less unplanned rework
44%
More new Work
* Source: Puppet State of DevOps Report

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Nay Ops : Aye Ops

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4 Challenges in Ops
Lack of Information
Information overload
Data correlation
Dynamic Trends

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Ops done better
Root cause identification
Freedom from white noise
Data correlation map
Proactive remediation

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The Key metric : 1. MTTR
The right Needle in the haystack

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The Key metric : 2. Proactive Actions
# problems auto~magically avoided

13. “Innovation and operations don’t have
to be inversely proportional”
Ajit Zadgaonkar
AI believer, Ops sufferer

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How to get life back in 4 steps ?

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Step 1. Set up for Observability
Infrastructure Logs
Platform Logs
Application Logs
Code telemetry
Events
Vended Metrics
API and Users

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Step 2. Set up delivery, Collection, and Storage
ingestion

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Step 3. Querying and patterns mining

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Step 4.
Alerting, Notification, and remediation

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AiOps
Predictive &
Preventive Insights
Patterns,
tools & data
ingestion
Threat intel
Budgets
Planned events
Purposeful Actions
Timely
Recovery
Decisive
Response
New Pattern
discovery
Continuous Learning
Infrastructure Logs
Platform Logs
Application Logs
Code telemetry
Events

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Take Ah! Ops to AiOPs
Track every resource possible
Alert on services, availability, and response times
Capture, learn, and improve
Socialize insights with everyone on the team
Plan metrics and monitoring, track patterns

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Nay Ops : Aye Ops : AIOps

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How Edmunds.com optimized Ops
Stephen Felisan, CIO, Edmunds.com

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Container Stability Prediction
• Removes bad containers
• Focuses on actions and
remediation
• Started with Tensor Flow, moving
to ML
Outcomes:
*Improved user experience
*95% reduction in on-call

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Breakout repeats
Tuesday, November 27
AIOps: steps towards autonomous operations
1:00 PM – 2:00 PM | Mirage, Montego D
Thursday, November 29
AIOps: steps towards autonomous operations
2:30 PM – 3:30 PM | Venetian, Level 4, Lando 4202

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Related breakouts
Tuesday, November 27
How to Ace Digital Transformation: Best Practices and Lessons Learned - ARC322
7:00 PM –8:00 PM | Aria East, Plaza Level, Orovada 3, T1
Tuesday, November 27
Moving to DevOps the Amazon Way - DEV210-R
8:30 AM – 9:3 0AM | Bellagio, Level 1, Grand Ballroom 2, T1
Monday, November 26
Enterprise DevOps: Patterns of Efficiency - ENT311
3:15 PM– 4:15 PM | Bellagio, Level 1, Bellagio Ballroom 6

31. Thank you!
© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Ajit Zadgaonkar
zadajit@amazon.com

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