NVIDIA's User Experience Streaming Analytics: Data Intelligence with the Elastic Stack at Scale

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Satish Varma Dandu Software Manager Data Engineering & Data Science Niranjan Nataraja Lead Data Scientist Elastic{ON} - 2017

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2 AGENDA Ø Kratos Data Platform as–a-Service Ø Multi-Tenancy Ø GeForce Now Cloud Gaming Ø Use Cases Ø Quality of Experience Ø Operations Ø Business Ø Kratos Visual Logging

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3 Ø Data Platform security has been implemented with VPCs in AWS Ø Dashboard access using NVIDIA LDAP Security Ø Offers HA with no data-loss Ø Always On Architecture Ø Data replication High Availability Ø Handles 1M events/sec Ø Auto-scales the cluster automatically Scale Ø Log-to-Analytics Ø Kibana, JDBC access Ø Accessing data using BI tools Self Service Kratos Data Platform as-a-Service

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4 ARCHITECTURE 10K FEET API Gateway S3 Kafka Cluster ELK Cluster Spark + Presto Cluster BI Tools Real Time Events Batch logs

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5 Kratos – Data Platform Stats

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6 GEFORCE NOW

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7 GeForce Now

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8 GEFORCE NOW

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9 Kratos Visual Logging *Images created from quickmeme.com

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10 Kratos Visual Logging Ø Visual Logging is an extension & backward compatible to existing logging frameworks like log4j, log4net, pylog Ø Provides default meta-data out-of-the-box

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11 Use case #1: Dev-to-Search

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12 Use case #2: Zero-Engineering Visualizations/Charts

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13 Use case #3: Zero-Engineering Dashboards Ø Devs can log in a particular format and we can build some automated dashboards for yield, duration, error codes etc.

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14 Use case #4: Zero-Engineering BI Ø Kratos Visual logging offers JDBC support. So BI tools like Tableau, AWS Quick Sight can be used to query data directly Ø Engineers & Analysts can write sql queries to make data decisions from the log data directly

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15 NVIDIA Kratos Team Ø Jarod Maupin Ø Nixs Nataraja Ø Rohan Somvanshi Ø Ed Clune Ø Rohit Kulkarni Ø Satish Dandu Ø Contact : [email protected], [email protected]

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16 Thanks Q&A