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Cloud Computing Introduction - 2018
Cloud computing is a style of computing in which scalable and elastic IT capabilities are delivered as a service using internet technologies. Key aspects include resources that are scalable and metered by use, and may be single-tenant or multi-tenant and hosted remotely or on-premises. Self-service interfaces like web UIs and APIs are exposed directly to customers. Cloud services can provide software, platforms, infrastructure, integration capabilities, and everything as a service (XaaS). The major cloud providers offer various capabilities and are competing on features, price, and services beyond basic compute and storage.
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Cloud Computing Introduction - 2018
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- 2. Cloud Computing Cloud computingis a style of computing in which scalable and elastic IT-enabled capabilities are delivered as a service using internet technologies Some Key Aspects The resources are scalable and elastic in near real time, and metered by use The resources may be single-tenant or multi-tenant, and hosted by the service provider or on-premises in the data center Self-Service interfaces are exposed directly to the customer, including web-based UI and APIs Source: Gartner 2017
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- 4. Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations Software as a Service Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations On Premise SaaS-Software as a Service Rapid Deployment - it can be up and running in just matter of hours Specialized Offering - there are SaaS solution for almost every business need Difficult Differentiation - its low entry barrier allows nearly any competitor adopt the same technology Speed & New Capabilities Customization - large and/or complex enhancements reduce benefit, increase cost and foster vendor-lock The Business acceleration & the Consumerization of IT
- 5. Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations Infrastructure as a Service Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations On Premise IaaS-Infraestructure as a Service Location - it has the capability to be close to the user instead to be centralized Flexibility- it provides the freedom to deploy any system no matter the requirements. Lift and Shift approach Consistency - the divergence on OS and Runtime configuration increase operation complexity Cost Savings & Consolidation Operations - there is still the need to manage foundation software components Be able to grow without capital investments
- 6. Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations Platform as a Service Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations On Premise PaaS- Platform as a Service Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations On Premise I Architecture - optimized for the cloud to achieve benefits that are difficult in monolithic and on-premise apps Cost - the vendors are moving to very efficient models for billing based on utilization, e.g. pay per compute by second Migration - existing apps require significant code refactoring or rewriting Focus & App Development Maturity - the software practices around cloud optimized apps are an addition step in the learning cloud Buy the commodity. Build the meaningful
- 7. Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations Integration as a Service Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations On Premise iPaaS- Integration as a Service Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations On Premise I Abstraction - provide a High Cohesion/Low Coupling integration capability Connectivity - Based on APIs and connectors, it is capable to connect and orchestrated almost any system Logic - risk to implement business logic in the middleware instead the application layer Consistency and Reducibility Infrastructure - Since it is more likely to be based on IaaS than PaaS, costs need to be kept under review The next generation of integration software
- 8. Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations Software as a Service Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations Platform asa Service Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations Integration as a Service Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations Infrastructure as a Service Network Storage Servers Virtualization OS Middleware Runtime Data Applications Customizations On Premise XaaS - Everything as a Service
- 9. Cloud Services -The 3 Big Players ■ Each platform has their own characteristics and benefits based on the customer profile ■ The platforms are competing in features but also price ■ Less granular billing models – per hour to per second ■ Storage is one of the key cost drivers compared to compute ■ There is more than compute and storage – Management, integration, AI & Machine Learning, IoT, Development Tools As in any competition, the customer ALWAYS win Source: Magic Quadrant for Cloud Infrastructure as a Service, Worldwide - Gartner 2017 The Cloud War - Amazon vs Microsoft vs Google
- 10. One More Thing- AaaS & DaaS Analytics as a Service & Data as a Service The challenge is related how to transfer data to the AaaS AaaS Unlock the big data potential without the need to set-up and operate servers and platforms ■ Some of the SaaS solutions already includes strong Analytics solutions ■ Normally most of the Analytics platform are deployed on premise, requiring a high investment on hardware ■ Lately many cloud provider are adding Analytics capabilities to their offering. From Big Data platforms to Stream Analytics, from Data Lakes to Machine Learning & AI The challenge is how to expose data for unspecific - ALL - consumers DaaS Break the silos barriers enabling share data across and beyond the company ■ Most of the data oriented solutions for Analytics or Reporting capabilities follows a bottom-up architecture ■ The challenge arise when the data itself become a product and it needs to be available to the consumers ■ Typically just research oriented companies offers Data as a product but as the platforms grow, more companies are enabling this model
- 11. Further Reading Open courseavailable online - Self Paced SAP Cloud Platform Essentials (Update Q3/2017) Extending SAP S/4HANA with SAP HANA Cloud Platform Microsoft Azure Virtual Machines Microsoft Azure App Services Architecting Distributed Cloud Applications AWS Cloud Practitioner Essentials AWS Developer: Building on AWS
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