AI in The Data AI Centre in the Data Centre

Transcription

1 AI in The Data AI Centre in the Data Centre Walter Van Hoolst Technology Architect HPE Nimble Storage Walter Van Hoolst Technology Architect HPE Nimble Storage April 24,

2 We re in the third-wave of the flash revolution the New Normal 61% Have already deployed all-flash in some level and are increasing use Wave 1: Performance Wave 2: Economics Wave 3: New Normal Niche workloads Adding SSDs to arrays and Optimizing only for performance Mainstream Lower-cost SSDs and data reduction drives cost to HDD levels Flashanomics Flash by default. Moving beyond just looking at array features Source: 2017 IT Pro Research Study Sponsored by HPE

3 But I&O Leaders Must Look Beyond the Box Predictive Cloud Ready Timeless Predictive Analytics to anticipate and prevent issues across the infrastructure stack Ubiquitous scale with data mobility between systems, sites, and the public cloud Architectural and financial flexibility to go anywhere with futureproofed platforms and guaranteed availability

4 Business Impact is Severe You can t afford an app data gap Apps Loading Data

5 Endless Fire-fighting with Lost Nights and Weekends Reacting to unexpected problems Spending countless hours interpreting graphs and logs Calling vendor support adds to the frustration Disruptions, business impact, and wasted time

6 There is no one cause Cross-stack Best Practices VM/Container/DB Compute Storage Related 46 % Storage 54 % Non-Storage Cross-stack Resource Contention Network Storage Cross-stack Interoperability Source: InfoSight analysis HPE customer base

7 Rich Telemetry Cloud Analytics Global Learning Predictive Analytics can close the app-data gap

8 InfoSight collects and analyzes more sensor data points every four hours, than there are stars in our galaxy >250B sensor values >2B log events >100MM configuration variables 370T Data points since 2010

9 Our Vision is the Autonomous Data Center Self-Driving Self-Healing Self-Optimizing Storage Servers Networking Converged Powered by HPE InfoSight: AI for the Data Center

10 HPE InfoSight: AI for the Data Center Collecting and Analyzing Millions of Sensors per Second Customer Impact Predictive Support Automation Proactive Management Continuous Improvement Preemptive Recommendations Cloud-Based AI Platform Predictive Analytics Engine Global Learning Recommendation Engine Cross-Stack Telemetry Compute Network Storage

11 Predictive Support Automation 11

12 See Once, Prevent for All Learning from the installed base Host, VM, network issues Interoperability issues HPE InfoSight Configuration issues Storage-related issues Not using best practices

13 Blacklist Updates Associated with Known Problems HPE Nimble Storage v = Blacklisted Release Release Update Path Every array has a customized update path based on its unique configuration Every update available is safe and free of known problems

14 Problem Prevented Before the Customer Knew About the Issue! Issue: InfoSight detected a controller went down unexpectedly Impact None because of built-in redundancy and no single point of failure Diagnostics Proactive Analysis found a bug. Nimble engineers created the fix and pushed it out in 24 hours Prevention 40 Customers were automatically provided a nondisruptive update to avoid potential impact

15 InfoSight Prevented 600 Systems from Having an ESX Issue! Issue: Massive application slow-down Impact 10x lower Throughput and higher latency, rendering host unusable Diagnostics Illegal iscsi command in ESX created huge performance issue after NimbleOS upgrade. Rapidly created a workaround until the vendor fixed the bug. Prevention 600 systems that would have experienced the issue were blacklisted

16 Preemptive Recommendations 16

17 Preemptive Recommendations in Use Everyday Rerouting

18 Preemptive Recommendations for Your Data Center Prevent Issues Before They Occur Improve Performance Proactively Optimize Available Resources Example: Change network setting at port 3 to avoid failover issue Example: Apply QoS to vol1 to improve performance on vol2 Example: Move VM3 to Host2 as Host1 is oversubscribed Eliminating the Guesswork in Managing Infrastructure

19 HPE InfoSight Recommendations Go Beyond the Obvious Pareto Principle for Infrastructure Problems Simple and Common 80% of the Issues 20% of the Pain Complex and Unique 20% of the Issues 80% of the Pain Requires Analytics & Automation Easy! Requires an AI Recommendation Engine Hard! Frequency Pain Simple Types of Problems Complex

20 Architecting the AI Recommendation Engine AI Recommendation Engine 1 2 Predictive Models Recommendation 3 Global System Telemetry Machine-Learned PEAK Team (Data Scientists) Expert-Informed Prioritization Matrix Customer Environments (Automatic) 20

21 AI Recommendation Example: Prediction Diagnostics Recommendation Data availability disruption due to obscure memory leak Signature matching 60+ memory allocation sensors forecasted over time, correlated across the installed base 40 Customers Received an automatic case sent to apply non-disruptive update to avoid impact

22 Real Benefits 22

23 Non-Stop Availability with InfoSight Predictive Analytics Prevent issues and avoid downtime Cross-stack rapid root cause analysis Predict future needs and simplify planning Inoculate install base once issue found Multi-tenant SaaS Portal Predictive Analytics <1 minute Issues detected before you do Measured uptime Hold time to speak to level 3 engineer Source: HPE Nimble Storage

24 Independent Research on the Impact of HPE InfoSight 79% lower IT OpEX 73% fewer storage trouble tickets 85% less time spent troubleshooting storage 69% faster TTR when needing Level 3 support Enterprises save time and money with HPE InfoSight

25 Cross-Stack Analytics for VMware Environments VMs/DBs/Apps Noisy Neighbor Determine if VMs are hogging resources from another VM Host & Memory Analytics Visibility into host CPU and memory metrics Compute Network Latency Attribution Identify root cause across host, storage, or SAN Storage Inactive VMs Visibility into inactive VMs to repurpose/reclaim resources Top Performing VMs Visibility into Top 10 VMs by IOPs and Latency

26 HPE InfoSight Extends to 3PAR + 3PAR Rich Telemetry Extensive data collected in every array Data collection since 2002 No need to retrofit HPE InfoSight Data Science Expertise Existing code and sophisticated models leveraged from HPE InfoSight Rapid acceleration of predictive algorithms 26

27 First Release of HPE InfoSight for 3PAR Available for All Customers with an Active Support Contract at No Cost Cross-Stack Analytics Global Visibility Predictive Support Foundation Cross-Stack Analytics Global Visibility Predictive Support Foundation Pinpoints bottlenecks between storage and VMs. Optimizes virtual resources Cloud-based capacity/performance analytics, health checks and best practices Analytics infrastructure and PEAK team to predict problems and automate resolution 27

28 HPE InfoSight: AI for the Data Center Extending HPE InfoSight Across HPE Storage Servers Networking Converged 28

29 HPE is providing the storage foundation for Hybrid IT Predictive Cloud Ready Timeless Predictive Analytics HPE InfoSight for HPE Nimble Storage HPE InfoSight (v1.0) for HPE 3PAR HPE Cloud Volumes HPE StoreOnce Cloud Bank Storage Scale-out file & object for cloud storage archives % availability and data compaction guarantee SCM / NVMe Ready Consume IT Flex Capacity and HPEFS

30 Thank You! Any Questions? 30