Analytics in the Cloud

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Abigayle Horn
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1 Intelligent Abstraction Intelligent Predictive Analytics Intelligent Action Analytics in the Cloud Peter McCallum Vice President Datacenter Solution Architecture 2016 FalconStor Software. All Rights Reserved

2 Agenda Brief Background Discuss how Infrastructure Analytics helps: Define appropriate SLAs/SLOs Maintain End to End QOS Optimize provisioning and availability Support Billing and budget FreeStor s Platform role in CSP/MSP service offerings FalconStor Confidential - All Rights Reserved 2

Drivers For Change IT has become devalued as a partner to business CIO role shifts from technologist to resource and service broker Questionable business practices and me too products have saturated

3 Drivers For Change IT has become devalued as a partner to business CIO role shifts from technologist to resource and service broker Questionable business practices and me too products have saturated the marketplace with ineffective solutions for a long time Not enough impactful innovation Shift of value has fallen to the developers and data scientists Cloud has shifted accountability FalconStor Confidential - All Rights Reserved 3

4 Cloud Offering Challenges Individualized (Client) Business Focus Appropriate SLAs/SLOs Breadth of offerings Competitive price model Security Agility Maturity FalconStor Confidential - All Rights Reserved 4

Analytics: Your Time Has Come Analysis of tightly or loosely coupled datasets (structured or unstructured) from various sources with the goal of deriving actionable correlations or

5 Analytics: Your Time Has Come Analysis of tightly or loosely coupled datasets (structured or unstructured) from various sources with the goal of deriving actionable correlations or predictive outcomes of patterns within the refined datasets. Structured Un-Structured Correlation Trending Intelligent Action Streams FalconStor Confidential - All Rights Reserved 5

Infrastructure Analytics: quick overview Goals: fix problems Identify bottlenecks Predict growth Predict problems Key Data Categories: Performance Capacity Latency/time on task

6 Infrastructure Analytics: quick overview Goals: fix problems Identify bottlenecks Predict growth Predict problems Key Data Categories: Performance Capacity Latency/time on task Throughput Load Maintenance (errors/faults) Current Examples: QOS Auto-Tiering Dynamic Cache SMART drive technology Load analytics (SDN) FalconStor Confidential - All Rights Reserved 6

7 Service Level Agreement SLA/SLO Service Level Agreement Contractual agreement outlining a specific service agreement between parties Service Level Objective(s) Individual services or metrics outlined in an SLA SLO 1: Performance SLO 2: Security SLO 3: Availability SLO 4: etc.. Integrated Infrastructure Analytics Enables: appropriate SLAs based on historical SLO performance Monitoring and Reporting on SLA/SLO compliance in real-time Monitoring for overachievement and suggest higher-tier ($) service for customer Global alignment of SLAs to actual historical use-cases and trends FalconStor Confidential - All Rights Reserved 7

End-to-End QOS CSP/MSP QOS defines an SLO for minimum and maximum performance in a service offering Application performance Compute capabilities/scale/balance Transport (network/interconnect) Storage

8 End-to-End QOS CSP/MSP QOS defines an SLO for minimum and maximum performance in a service offering Application performance Compute capabilities/scale/balance Transport (network/interconnect) Storage (latency, performance) Application OS Hypervisor Network Storage Infrastructure Analytics (Single or Cascaded) Enables: Correlation across multiple sets of performance counters (in each infrastructure strata) Real-time monitoring for threshold proximity or violation Alerts and/or workflow execution to notify or act upon the violation Historical data to predict and suggest better service tiers based on patterns FalconStor Confidential - All Rights Reserved 8

9 Provisioning and Availability How to standardize and automate service deployment for maximum efficiency and least cost? How to provide enough redundancy/availabilty to protect SLAs, but not over-engineer How to improve breadth of service offerings and options for customers, but still standardize? A combination of Software-Defined-Storage (SDS) and Analytics enables: API-based (scriptable) deployment templates analytics-based Automation (thin-to-thick, on-demand cache, on-demand workload shifts) periodic heuristic performance modeling transparency of downstream and upstream infrastructure (Allows wider set of service offerings to customers while maintaining internal standards) FalconStor Confidential - All Rights Reserved 9

Budget and Billing SDS + Analytics enables: alignment of SLAs/SLOs to real customer requirements and historical capabilities trending analysis for pro-active budgeting support for both CAPEX and OPEX

10 Budget and Billing SDS + Analytics enables: alignment of SLAs/SLOs to real customer requirements and historical capabilities trending analysis for pro-active budgeting support for both CAPEX and OPEX models predictive utilization metrics to constrain budget (consumption models) QOS to avoid under-delivering and over-engineering (current trend) Auto-tiering to highlight the VALUE of data in performance calculations Commoditization to force a higher-level value in purchasing (value vs. cheap) FalconStor Confidential - All Rights Reserved 10

11 FreeStor Vision FreeStor delivers enterprise-class software-defined, intelligent data services combined with predictive analytics across any primary or secondary storage hardware; in the cloud or on-premise FalconStor Confidential - All Rights Reserved 11

12 How is FalconStor Driving this Vision with FreeStor? Storage hardware and interconnect commoditization Vendor-agnostic platform Decoupled Architecture (scale compute and storage separately) Silo breakdown (reduce number of tools and maintenance plans) Wide infrastructure analytics (across vendors!) RestAPI integration Integration to Self-Service portals and Billing systems FalconStor Confidential - All Rights Reserved 12

13 Customer 3 Customer 2 Customer 1 Customer 4 PaaS Management Console/API layer Security Analytics/Discovery Engine(s) VTL (AaaS) BUaaS/AaaS System-Level Traditional Backup Local and Remote Physical and Virtual RaaS Local and Remote Physical and Virtual Any-to-Any Clone/Audit/Recover IaaS Legacy to Modern VAR/SI-enabled Full BaaS/RaaS integration What Does a FreeStor MSP/CSP MaaS/On-boarding Migration/Refresh Cloud On-boarding Services and Temporary IaaS Platform Act Like? Internal Compute Internal IT Co-located Physical and Virtual Compute (IaaS) Shared Virtual Compute (IaaS/RaaS) FREESTOR (PaaS) Shared Storage Cloud Internal IaaS SaaS/ DBaaS FDR Dedupe Single platform support for internal IT, Colocation, and managed services simultaneously Support for shared or isolated environments Wide support for diverse Application, OS, Hypervisor, and platform environments Local and Remote management and recovery Hot, Warm, or Cold recovery environments Support for temporary workloads Variable topologies for massive performance scalability and reliability Optimizes traditional BU and allows for automated snapshot-based, application aware recovery Best-in-breed replication technology FalconStor Confidential 13

THANK YOU Intelligent Abstraction Intelligent Predictive Analytics Intelligent Action Intelligent Abstraction Intelligent Predictive Analytics Intelligent Action Corporate Headquarters FalconStor

15 THANK YOU Intelligent Abstraction Intelligent Predictive Analytics Intelligent Action Intelligent Abstraction Intelligent Predictive Analytics Intelligent Action Corporate Headquarters FalconStor Software, Inc. 2 Huntington Quadrangle, S251, Melville, NY Tel: Support: salesinfo@falconstor.com EMEA Headquarters FalconStor Software, GmbH Landsberger Str Munich, Germany Tel: salesemea@falconstor.com Asia Headquarters Room 1901, PICC Office Tower, No. 2, Jian Guo Men Wai Street Chaoyang District Beijing, China Tel: salesasia@falconstor.com FalconStor Software, Inc All Rights Reserved. - FalconStor, FalconStor Software, FreeStor, and Intelligent Abstraction are trademarks or registered trademarks of FalconStor Software, Inc., in the U.S. and other countries. All other company and product names contained herein may be trademarks of their respective holders

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