BRKPAR-4121 Using Workload Automation to Optimize Hybrid Cloud Estates Ben Nye
Using Workload Automation to Optimize Hybrid Cloud Estates Ben Nye CEO
Key Drivers Digital Transformation Proliferation of Applications and Workloads Multiple Cloud Platforms Private and Public ESX, KVM, Containers, IaaS, PaaS, CaaS, FaaS Complexity, Compliance, Performance, Cost
Workloads Driving the Hybrid Cloud 400 350 380M WORKLOADS 300 250 220M WORKLOADS 63% CAGR 1 200 1 Public Cloud Workloads Workloads (M) 150 100 50 0 Sources: (1) IDC (2) Gartner (3) Morgan Stanley CIO Survey (4) Cisco Cloud Index 4 3% CAGR On Premises Workloads 2017 2020 1
Which Workloads Should Run Where and When? Private Workloads (fixed costs): Legacy apps not worth re-factoring Monolothic apps Apps with near constant demand Big data apps Performance sensitive apps Compliance and security sensitive apps Public Workloads (variable costs): Dev/Ops Apps with volatile demand profiles Apps requiring re-allocating resources Micro-services Leveraging Cloud Services (S3, ML, Redis, Serverless)
Managing a Hybrid Cloud is Challenging Expensive Skills Gap Complex Choices 80% see cloud bills 3X more than expected 14% of organizations have right skills / staff #1 challenge with transformation is complexity AWS 90 services 1.7M options 19 days
Workload Automation Simplifies Hybrid Cloud Management 1 Assessing 2 Planning & Implementing 3 Managing & Optimizing The foundation is visibility and understanding of your entire estate Plan, migrate and place/size the right workloads in the right place at the right time Continuously tune to deliver the desired state, balancing cost performance and compliance
Every Workload has Three Basic Needs Lower Cost Assure Performance Assure Performance ANY WORKLOAD ANY WHERE Maintain Compliance Maintain Compliance Maintain Desired State Lower Cost Let SMART Workloads Manage themselves! ANY CLOUD ANY TIME
Workload Automation Enables Simultaneously Delivery of Compliance, Performance, and Cost Non-Compliance Maintain Compliance Volatile Performance Assure Performance Higher Cost Lower Costs
Workload Automation Requires Comprehensive Tradeoffs Maintain Health
Workload Automation Key to Transformation PAAS FAAS EDGE IAAS SDDC 2000 2005 2010 2015 2019 2020
The Path to the Self-Driving DC Monitoring and Actioning coming together Beyond data ingest to include context intent feedback loop and AI data model Control workload across edge core cloud AS, Ent./Campus/ Wireless/IoT/Security untapped Importance of cloud native
Nearly 2000 World-Class Companies Trust Turbonomic with 4+ MM SMART Workloads Technology Financial Services Healthcare Insurance Telecom/SP Service Providers Retail Utilities/ Manufacturing System Integrators
Customer s Journey to the Hybrid Cloud Made Easy MICRO-SERVICES SLA/COST Demand-Driven SCALING Vertical and horizontal APPS PLACEMENT Initial and subsequent PLANNING Decide what, where and when IAAS VISIBILITY Workloads, Infrastructure, Cloud, Performance, Costs, Compliance COMPUTE STORAGE NETWORK CLUSTERS DATA CENTER HYBRID CLOUD
Your Platform Future Ready
Booth P1 By Entrance Demonstration
The Bottom Line + = Cisconomic! Partnership Technology Vast & Disrupted Market
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Continue Your Education Demos in the Cisco campus Walk-in Self-Paced Labs Tech Circle Meet the Engineer 1:1 meetings Related sessions BRKPAR-4121 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public 21
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