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§ What is Cloud § What does it change
§ Virtualiza4on vs. cloud
§ Impact on enterprise organiza4on
§ Flavors of cloud
§ Private, public or hybrid § Is cloud cheaper?
§ Challenges of cloud compu4ng and mo4va4ng factors for adop4on
§ Principals
§ Cloud reference architecture § Private Cloud reference architecture
§ Cloud ready DC and VPDC
§ Evolu4on of infrastructure from Virtual to Cloud
2
Agenda
Cloud Reference Architecture
Cloud is not: § Virtualiza)on plus or virtualiza)on rebadged
§ Next trend in resource consolida)on
§ Sta)c, semi-‐sta)c or hard configured compute pools
§ Tweaked to suit applica)ons
§ Compute capacity constrained
§ Limited to abstrac)on of compute or app layer Cloud is:
§ A new economic and u)liza)on model
§ The key argument for adop)on of cloud is developing new services and markets
§ Separa)on of applica)ons from infrastructure and intelligent integra)on to demand
§ An organiza)onal remodeled around demand/response for delivery to mobile end points
§ A virtuous constraint that promotes business policy driven posi)ve service resource response
§ Uniform opaque environment tweaked to user generated paHerns of workloads
§ Efficiency gain and reduced process complexity in exchange for control of hard and soK IT assets
§ In flight service composi)on of opaque resources to deliver flexible fulfillment models
3
Cloud is a new informa4on processing, u4liza4on and management model
Cloud is not a variation of virtualization
Cloud: § Is the shiH of business and enabling IT to a u4lity model of defining, composing, enabling and accessing
services. It is based on delivering via Internet with mul4ple delivery, pricing and architectural op4ons behind this mode of service delivery.
It changes: § Cost models § Price models § IT organiza)on § Rela)onship of IT and business it supports § How services are defined, structured and composed § Delineates business organiza)on from IT and creates new interconnects § Facilitates and enables new business models § Accelerates delivery of services
4
What does it change?
What is Cloud?
Cloud § Distributed soK assets, including DBs & services, dynamically
configured to end points
§ Applica)ons run on an extensible fabric of virtualized plaUorm and infrastructure
§ Automated QoS and dynamic policy driven service )er management
§ Dynamic DR, BC, load balancing of hard and soK workloads
§ True Mul)-‐tenancy for hosted or mul) BU cloud plaUorm (Automated update, patch Management, security…)
§ Single view for users of available or authorized resources
§ High-‐level abstrac)on and massive standardiza)on of hard and soK components
§ Near real-‐)me policy driven resource management (provisioning, de-‐provisioning, policy enforcement, Access management…)
§ Portable applica)ons with unified management across physical resources
5
Virtualiza4on § Op)miza)on of compute resources
§ Faster Provisioning/de-‐provisioning than stand alone
§ Increased u)liza)on by of exis)ng idle capacity
§ Pre-‐configured VM provisioning
§ Compute layer unified management
§ Limited Pre-‐configured Service )er management
§ Improved HA and DR rela)ve to stand alone
§ Simpler overall management compared to stand alone
§ Imposes no structural or fundamental changes in IT organiza)onal structure
Cloud is not just changes in infra or app but how we design informa4on systems to morph from
a rigid preconfigured container, to a dynamic mediator of demand-‐response we interact with
Cloud vs. Virtualization
Cloud IT Organiza4on
§ Applica)on knowledge is distributed as a cloud app
§ Storage, memory, caching and network are converging. Team should reflect this mode of interac)ve engagement
§ With training, business users can be self sufficient in interac)on at the end point for on demand and real )me or near real )me response.
§ Chains of approvals are within the system and provisioning is instant within virtuous constraint
§ “DC” organiza)on replaces IT. Becomes one unit responsible for opera)ng a DC which may yet be all virtual so now they take on many value added business func)ons including demand op)miza)on
§ Business organiza)ons own and op)mize demand based on business intelligence
§ Enables new business and fulfillment models, releases )ed up resources (hard and soK), and opportuni)es
6
Virtual IT Organiza4on § Applica)on knowledge is concentrated to a specific
group like a tradi)onal or non-‐virtual app
§ SAN, NW, CPU are dis)nct groups in stand alone or virtual infra and teams are aligned this way
§ End users rela)onship with IT does not change. It is s)ll a process that has to follow the chain of approvals or provisioning. Faster than a few years ago but essen)ally the same
§ The rest is as it has been
IT organiza4ons have adopted virtualiza4on only to hit a barrier wall of architectural deficiency at infra, app design and organiza4onal silos. These deficiencies loom large when undertaking shiH to Cloud
Evolution of IT organization from virtual to Cloud A challenge for organization not technology
§ Ability to shiK to service provider mindset and structure is directly propor)onal to maturity of IT service management in an organiza)on. This means realis)c service level measurements against stated targets and true cost of delivering it. This cost is oKen poorly defined, understood or measured
§ Clear separa)on between provider and consumer allows for clear defini)on of responsibili)es. Cloud providers sell to consumers and that is a different rela)onship than exists in IT today
§ The real promise of cloud compu)ng lies in developing new markets and services. This requires process, flow, promo)on tracking, response management, and a slew of other ac)vity on the fly that in turn require provider to ever more flexibly and expediently enable changes in workloads , types, QoS, and physical and virtual resources. Managing this mode of interac)on at the speed of internet requires a new, more agile teams and forma)ons than what today’s enterprise IT is used to
§ This new team and organiza)on structure is already challenging many. Some will be significantly disrupted. Most will need substan)al help naviga)ng this complexity and morphing
§ Most IT ini)a)ves tend to target current pain points or new func)ons but to effec)vely leverage cloud a larger strategic view is crucial to success. Enterprise IT should adopt this approach in offering services to the business
§ Business needs to respond to customers and provider’s need to understand both paHerns to deliver the right plaUorm and tools to facilitate demand-‐response
7
Paralleling cloud technology
Evolution of IT organization to demand-response
8
Each has a place in the enterprise
Flavors of cloud
Type Consumer Service Service Coverage Customiza4on
SaaS End User Complete App Up4me, Performance,.. Minimal to none
PaaS App Owner Run4me, storage, SI,..
Availability, perf., no app coverage
Provider/plaYorm limita4ons
IaaS App Owner, Provider
vServers, Storage, NW,..
Availability, provisioning, no plaYorm or appcoverage
Minimal constraints on app within standard builds
• SaaS provides applica.ons and business processes. Cost is typically usage based and SLA predefined with minimal adjustments for a par.cular case. The consumer only sees abstrac.on of infrastructure and opera.ons
• PaaS plaAorm that includes infrastructure and opera.ons is delivered by providers at a predefined cost and SLA. The consumer is responsible for applica.on and it’s compliance to architectural framework (storage, integra.on, execu.on services, run .me)
• IaaS is SLA base infrastructure up to OS pooled along with connec.vity services standardized to provide a founda.on for PaaS and IaaS. Consumer is responsible for opera.ons above OS.
For enterprise class IT, the choice is not likely to be Cloud or no cloud, in house or hosted, SaaS, PaaS or IaaS. Rather, an exercise in due diligence to understand and make business risk adjusted, strategic investment decisions:
§ Cos)ng of various parts of business and support infrastructure and the equivalency in cloud based on data/informa)on sensi)vity, regulatory stance, business risk plus detailed and accurate cost accoun)ng.
§ Priori)za)on based on strategy, defined objec)ves , transforma)on and opportunity cost § Speed and sequence of change implementa)on based on organiza)onal maturity § Vendor, provider, and technology assessment of fit defined end state of enabling architecture
9
Right answer for most enterprise class organiza)ons is: all of the above
Private, public, or hybrid? In house or hosted?
Sourcing type Infra control scalability loca4on dedicated/shared investment
Hosted Private cloud customer capital Internal Dedicated Capital
Onsite private cloud Customer Capital/contract Internal dedicated Capita/varies by contract
Shared public Cloud Provider Minimal external shared PAYG
Dedicated public Cloud Provider Minimal/Contract external Par4al PAYG
Private cloud Appliance Provider Capital/Vendor Internal dedicate Capital/Varies by contract
10
It is not one vs. another but the right blend of cloud for op4mal transi4on to target state
Private, public or hybrid
1-‐ Enterprise infrastructure architecture and applica4on design that is 4ghtly coupled
• What does a cloud infrastructure look like and why it is so different • Why applica4ons must func4on independent of the infrastructure plaYorm • Transi4on from virtual to Cloud can leverage many exis4ng assets
2-‐ Sta4c or semi-‐sta4c system management, capacity and work flow are containerized and build on top of exis4ng app and infra constraints
• How to separate applica4ons from infrastructure and key decision factors • Leveraging integra4on point services and key decision factors • Can current enterprise middleware deliver the abstrac4on necessary for separa4on
3-‐Enterprise IT organiza4on that is formed around technology and applica4on silos
• Applica4on silos evolved with containerized apps. Virtual apps are distributed and data store driven.
• Infrastructure silos evolved along an IT Push model, by architecture and design, that creates areas of control. Cloud applica4ons are demand driven and interconnected across physical boundaries
• With transi4on to cloud tradi4onal control is exchanged for speed and agility • This organiza4onal shiH may parallel architecture of cloud. Loosely coupled parts in a DC centric
supply/demand driven approach
11
Opportuni4es to unleash new efficiencies, services and business models by the cloud face three major hurdles
Challenges of cloud for Enterprise
Decoupling applica4ons from hardware Infrastructure is a key step: § Distributed applica)on design with data stores and open API’s to leverage many available cloud services and
minimize applica)on footprint, IO, bandwidth and deliver beHer performance characteris)cs and QoS
§ Applica)on footprint is reduced by offloading the code associated with managing hardware configura)on and dependencies, as well as licensing and hardware requirements
§ Func)on specific applica)ons can operate as standalone for topical func)ons and can interact via REST/Open API’s with virtualized/cloud services to complete a flow, and transac)on s. Independence from hardware plaUorms allows ubiquitous interac)on
§ The plaUorm/hardware specific support of componen)zed applica)ons can be structured in a similar fashion via abstrac)on of the plaUorm using a similarly componen)zed construct that will support the required compute units and elas)city
§ Exis)ng hard assets can be used by segmen)ng resources based on stage of lifecycle, level of standardiza)on (Virtual and Cloud), and pooling/provisioning as a subset/)er within the new architecture. Management is thru API’s and services around them that fully integrate to Cloud/abstrac)on management layer
§ SoK assets will follow a similar methodology. Applica)on moderniza)on, virtualiza)on, and cloud transforma)on within strategic transi)on and transforma)on objec)ves in combina)on with con)nued u)liza)on targets for exis)ng assets will drive the required op)miza)on without hindering performance, func)onality or compa)bility
12
Enterprise infrastructure architecture and applica4on design that are 4ghtly coupled create a barrier to cloud adop4on because of complexity that is associated with uncertain4es that include cost and organiza4onal disrup4on
Unwind applications from infrastructure
Encapsula4on and isola4on of applica4ons to break them free from OS and data will pave the way for full virtualiza4on of the infrastructure and consolida4on, decoupled from the stack sifng on it , to deliver Portability, manageability and compa4bility necessary for transi4on to cloud .
Applica4on virtualiza4on: § Simplifies SoHware Delivery § Reduces Storage § Manage applica4ons in the extended enterprise § Stream over HTTPS for secure remote delivery § Does not require end point device management § Can integrate into exis4ng management framework § Virtual Registry buffers from underlying host OS § Launch applica.on in mobile end points, without connec.on to the network § Simplifies change management and maintenance. Can integrate without dedicated server infrastructure,
reduce/eliminate soHware conflicts, modify one app for an en4re environment, streamline patch updates…
Applica4on virtualiza4on is a primary and key step for moving from virtualiza4on to cloud
Application Virtualization
Applica.on shiK to Cloud
13
Cloud needs ver4cal and horizontal interoperability without building layer on layer to achieve it. Key decision factors:
§ Stage of asset life cycle § Level of standardiza)on, or amenability to moderniza)on (new plaUorm compa)bility)
via intelligent API’s and integra)on services § Ability and cost effec)veness of an asset in mee)ng or hindering the )melines defined
by strategic business objec)ves driving transi)on or transforma)on § Opportunity cost § Re-‐alloca)on, re-‐use, re-‐purposing opportuni)es § Performance overhead/compromise § Standard driven new acquisi)ons of hard/soK assets (CDMI, OVF…)
14
Systems and service management is mostly sta4c (or semi-‐sta4c) and containerized to perform within limita4ons of intertwined applica4on and infrastructure architecture
Standardized & unified system management
New models and capabili4es of cloud should drive the structure of suppor4ng and managing organiza4on. § A change in business decision or process should not impose changes within infrastructure and
plaUorm (and vice versa). As such that decision chain prominent in most organiza)ons should be untangled
§ Technology plaUorm becomes the DC that may be internally operated, or outsourced in exchange for a fully managed plaUorm.
§ The business plaUorm may be outsourced, depending on complexity and scale. But it is a value add ac)vity that itself is oKen a business asset
§ Business management plaUorm is the apex of enterprise’s business model support capability. This is essen)ally driven by analy)cs, market intel and emerging social enterprise plaUorms like data.com
§ The informa)on value chain and its key segments define the organiza)on and skill sets that own or support it. As data is released from the confines of infra and app dependencies to flow where demand pulls it, defining and designing the structure and architecture of that demand becomes the core around which a cloud IT organiza)on is built.
§ It invariably requires a resource shiK, the speed of which is a func)on of an organiza)on’s roadmap, risk assessment and priority
§ The challenge is to minimize disrup)on without compromising on target state and )melines
15
Unwinding business from IT
Cloud optimized organization
Due diligence: § Organiza)onal impact: from Capex to Opex driven by accurate cost analysis to establish full delivery cost , to
speed and size of shiK or strategic sequence of implementa)on, changing roles and )tles, and net impact on boHom line need evalua)on and assessment for a successful transi)on
§ TCO: despite common assump)on of savings with cloud, there is not sufficient data on overall TCO . Newcomer cloud startups hardly provide a baseline or equal comparison for classic enterprises in terms of size, complexity and risk. Public and private cloud comparisons also lack sufficient detail for ABC (ac)vity based cost accoun)ng) or other applicable methods that provide cost per unit at enterprise scale
§ How fast: Not only this is linked to organiza)onal readiness and impact assessment, but also an understanding of the delta between enterprise current state and target state. This needs an assessment of addi)onal features, func)ons and capabili)es that public cloud (google apps, AWS…) or cloud-‐in-‐a-‐box solu)ons lack because at the core they are purpose built DC’s and reaching target state on them takes )me, resources and poses risks to manage including plaUorm specific limita)ons, licensing models and scenarios, applica)on and infra varia)ons, standardiza)on, SLA and contract management…
§ The business case for using u)lity compu)ng for specific enterprises and ver)cals. And regardless of who/where IT is run, uncertain)es need clarity against the level of defined risk thresholds
16
Challenge of unknown or undefined
Level of IT maturity drives speed of cloud adop.on
17
Enterprise adop)on of cloud requires a concerted due diligence and planning to understand delta between current and target state to define transi)on and target architecture; requiring a strategic decision matrix that covers KBC and KPI and various trend analy)cs
Navigating uncertainty
Opportunity to counter risks: § Ever larger data volumes (Big Data ) coupled with intelligent analy)cs can combine to provide valuable strategic
and opera)onal informa)on from structured and ad hoc data
§ Virtualiza)on has been adopted to gain consolida)on; and oKen stagnant around 20% range due ton )ght coupling of apps and infrastructure. This barrier mi)gates gains in workload op)miza)on and consolida)on, and efficient cloud adop)on
§ This virtual barrier incubates inefficiencies that offset gains in server consolida)on & complicate cloud adop)on
§ Tools and soKware from ERPs, ISVs and third par)es that topically address some of these concerns, cannot overcome inability of server centric virtualiza)on to dynamically and elas)cally respond to the stack that sits above it
§ New business models, delivery mechanisms, elas)city and service offerings that cloud enables, create significant compe))ve opportuni)es; and considera)ons to counter threats, some)mes existen)al, for enterprises of significant size
§ Several vic)ms ranging from online video entertainment, to retail and gaming have been quite visible. The pace of this shiK is only accelera)ng.
More than opera4onal dilemmas for the C suite
Motivating factors for Cloud adoption
18
Cloud is cheap; public cloud is even cheaper § There is liHle, if any, generally available enterprise class detailed ABC (ac)vity based cos)ng) type or other
methods that clearly lay out the cost of various cloud op)ons and permuta)ons
§ Many enterprise applica)ons are not available as cloud based and when they become available the cost models and TCOs are far from known or proven, in par)cular for larger more complex enterprises. These variables impact many components ranging from performance to licensing costs including virtualiza)on
§ Formula)ng new services , capabili)es, and tes)ng can be accomplished faster & cheaper in cloud. This is inherently valuable to business. Procurement, licensing, provisioning along with resource and management costs are reason enough to leverage a cloud solu)on, but a cohesive cloud architecture, process and workflows are needed to mi)gate undue costs, risks and redundancies that can outweigh an)cipated efficiencies
§ Cloud has lowered barrier to entry; in terms of cost, quality, sophis)ca)on and then scaling. This is a significant risk to established enterprises par)cularly when offerings and services are not ‘tangible’ goods
§ Net value of cloud is in transforming enterprise to a nimble, fast thinking en)ty able to redefine and morph its services in intelligent, elas)c and right-‐sized manner. The most challenging part is geing the road map right based on architecture, structure and organiza)on impact. This is not something to be gained on the cheap but given new possibili)es to operate in an unpredictable environment, make this a cri)cal strategic investment
19
Facts vs. hype or presump4on
Cloud is cheaper
§ Service Provider Approach A Service Provider mindset evolu)on of IT department. Cloud is a shared service and its adop)on by consumers depends on clarity of performance, availability and service characteris)cs. There is a clear delinea)on between provider and consumer
§ Maximum U4liza4on of Resources This is not a recipe based op)miza)on but driven by specific characteris)cs of an organiza)on/business and its specific needs and constraints including cost, performance and QoS. It is purpose and context based u)liza)on design that leverages P2V (physical to virtual) as a star)ng step.
§ Infinite Capacity percep4on cloud service should deliver capacity as needed, limited only by consumer’s willingness to pay. This is a demand driven model of capacity management that leverages historical data, forecast, analy)cs and deep understanding of consump)on and response paHerns to define Scale Units and deployment models to be engaged when addi)onal demand is triggered or invoked based on recogni)on of paHerns.
§ Predictability Consumer of cloud expects quality & consistency from services. Delivering it requires a unified, standardized underlying infrastructure, coupled with intelligent process and service automa)on, Health State established based on detailed understanding of events, workflows, dependencies, and their correla)on. This simplifies detec)on of anomalies and automa)on of correc)ve measures and refinements. Early detec)on/warning can ini)ate applica)on migra)on, mi)ga)on, recovery steps and also supports a cohesive DR/BC plan
20
Achieving cloud starts with a service provider approach
Principals
§ Maximize automa4on, minimize human dependency Dynamic nature of cloud requires a high level of intelligent automa4on of processes and flows. Automated management systems must have deep knowledge of architectural paHerns and system health. A single manual script error or missed trigger at a cri)cal juncture, significantly diminishes up)me and consistency of an otherwise automated system. Recent Amazon east AZ and Skype global system failure are two example.
§ Driving op4mal user behavior Tiered based chargeback and billing pegged to various business requirements and overall compute capacity, with u4lity pricing based on peaks and valleys drive business unit discipline in resource consump)on so percep)on of infinite capacity does not promote crea)on of inefficient or redundant work loads
§ Up4me & failure management Consumers expect service any)me, anywhere, on any end point. An intelligent early detec4on system that can ini)ate workload adjustments and movement across the fabric to deliver resiliency without relying on 2N redundancy and security capable of protec)on while delivering to any device or endpoint. In cloud failure is an expecta)on. Early warning systems built on hi quality health states can respond to failures by moving resources and loads to minimize impact on user due to any point failure. This N+1 efficiently replaces the bulky and expensive tradi)onal 2N. Complemented with applica)on level redundancy to reach availability targets. This means a move away from stateful to stateless applica)ons that lend themselves for more effec)ve load balancing and distribu)on. During Amazon’s East AZ event, NeUlix showed how effec)ve this design approach can be.
21
A clear delinea4on of provider and consumer
Principals
22
Delivery, soHware, plaYorm, Infrastructure, opera4ons and management feeding a virtuous cycle
Cloud Reference Architecture
Intelligent infrastructure compartments interopera4ng seamlessly; horizontally and ver4cally.
Private Cloud Reference Architecture
23
Characteris.cs of layers of Cloud
• Business intelligence, metrics, assump.ons, scenarios are crunched here
• It is an intelligent applica.on with two basic forms customizable to N forms:
1-‐ A view of current state from all monitored & input sources analyzed and normalized
2-‐A view of to be: Heuris.c & algorithmic informa.on leveraging forecast, historic data, and view #1, plus business assump.ons, scenarios, game theory. This view is close to AI (art. Intel)
• It should be run as high service .er with granular access control; treated as top .er informa.on. May run on a dedicated elas.c resource pool
Mission Control: SoKware that takes input from all layers and performs Complex Event Processing and algorithmic op.miza.on to translate business decision inputs to workloads
• Virtualiza.on layer where all the machine level and VIO level V2P processing happens by the virtualiza.on technology
• Many tools operate at this level and must be cloud standards compliant
• Virtualiza4on layer where all the machine level and VIO level V2P processing happens by the virtualiza4on technology
• Tools (built in or 3rd party) must be cloud compliant
• Hardware/compute layer. Physical servers, Network, Storage
• Must be virtualiza4on capable via Cloud Standards (i.e.: CDMI, OVF… )
Interoperability and context aware communica4ons are enabling characteris4cs of cloud
24
Layers of Private Cloud
Stan
dards b
ased
, com
mon
program
ma.
c
man
agem
ent interfaces a
cross D
C plaA
orm
Common IO mgt across plaAorms
Common programma4c management & IO across DC is a key feature of Cloud PlaYorms
25
This view of Private Cloud aligns with NIST standard and defini4ons
Private Cloud Reference Architecture: Cisco, HP, EMC, IBM, Dell…
26
Interoperable compute units working in unison to deliver resources in dynamic response to demand from virtual management layer
Cloud ready Data Center Architecture
27
Compute units may be compartmentalized (VPDC) and assigned service )ers (QoS) based on business func)on, performance and priority. Also, referred to as PODs, may be a whole VPDC or a subset that facilitates quick and seamless scalability
Interoperable infrastructure compartments enable Cloud
28
Compute Resources
Data Center
Fabric
Network
Services Security
Services
Storage
Resources
Business Orchestra.on/Service Fulfillment
Cloud Orchestra.on
Cloud Infrastructure
Cloud Database
SLA
Management Event
Management
Incident
Management
Cloud OS
Systems Management – Service Support
VPDC may be a BU, organiza4on or division. It is a logical Mega unit that delivers business segmenta4on while retaining a unified physical data center architecture
Virtual Private Data Center (VPDC) Reference Architecture
29
VPDC may be the Data Center in the reference architecture, or may be a 4er driven component
VPDC may be an Enterprise, BU or team
30
Cloud IaaS
§ Composed of a single or mul4ple DCs or VDCs managed as a unified supply center responding to demand generated from sta4c or mobile end points
§ Ver4cal & horizontal interoperability standards built into HW & plaYorm.
§ Applica4on aware plaYorm: service and applica4on discovery enables automated or formulated integra4on and service assembly via Open/REST API’s
§ Extensive IO virtualiza4on and management of HW & SW along with port sharing across physical & virtual assets for true VM mobility
§ Demand/Response Load balancing of all VIO, fail over and re-‐provisioning across physical and virtual data centers
§ Tiers, QoS, and work loads driven by business users at applica4on layer that is translated to units of demand to be managed elas4cally
§ Auto detec4on & correc4on across physical and virtual resources (monitoring, re-‐provisioning, load balancing, re-‐rou4ng, disaster avoidance)
§ Integrated and unified security deliver granular visibility into each process, component and subcomponent;
• Proac.ve orchestra.on, provisioning & management – Predic4ve & analy4c resolu4on of resources constraints to maintain QoS
31
Virtual IaaS
§ Composed of a single or mul4ple DCs or VDCs managed as a unified supply center responding to demand generated from sta4c or mobile end points
§ Ver4cal & horizontal interoperability standards built into HW & plaYorm.
§ Applica4on aware plaYorm: service and applica4on discovery enables automated or formulated integra4on and service assembly via Open/REST API’s
§ Extensive IO virtualiza4on and management of HW & SW along with port sharing across physical & virtual assets for true VM mobility
§ Demand/Response Load balancing of all VIO, fail over and re-‐provisioning across physical and virtual data centers machines in the same physical/virtual cluster
§ Tiers, QoS, and work loads driven by business users at applica4on layer that is translated to units of demand to be managed elas4cally
§ Auto detec4on & correc4on across physical and virtual resources (monitoring, re-‐provisioning, load balancing, re-‐rou4ng, DR/A)
§ Integrated and unified security deliver granular visibility into each process, component and subcomponent
• Proac.ve orchestra.on, provisioning & management – Predic4ve & analy4c resolu4on of resources constraints to maintain QoS
The Delta: Virtualized vs. Cloud infra
Evolution of Infrastructure - Virtual to Cloud
32 Accenture Confiden4al
Easier consolida4on and provisioning of VMs but limited gain
Virtualizing existing infrastructure
Virtual IaaS
IaaS
PaaS
?
§ App moderniza.on and virtualiza.on brings in layers of tools, services and integra.on points that bring applica.on closer to the cloud but because they lacks the built-‐in integra.on and architecture of virtual and cloud apps, they bring added maintenance, licensing and support costs, and overall complexity.
§ Abstrac.on and management layers are limited by virtue of interdependence of apps & infra. Complexity & management index are high. Security/GRC are subject to same limita.ons
§ Lack of advanced chargeback/billing limits user behavior management
§ Overall resource efficiency is not likely to increase much, if any, and complexity will go up as added hard and soK layers for enabling advanced virtualiza.on or cloud-‐like interoperability negate much of gained efficiencies
§ True vMo.on across boundaries is not a cost or architecture effec.ve op.on
§ Delivery to any end point require more processes, workflows, integra.on, end point requirements and compute resources
33 Accenture Confiden4al
Within any given applica4on framework, apps need not be concerned with the plaYorm
Cloud infrastructure can support any platform
Cloud IaaS
Network, CPU, Storage
Cloud Infrastructure management layer I aaS
P a a S
§ Applications are freed to deliver function independent of infrastructure
§ Maximize resource utilization by sized to fit provisioning and workload lifecycle management
§ Infinite Capacity perception by utility based demand fulfillment
§ Predictability is supported by Health-state baseline simplifies anomaly detection
§ Maximize automation, minimize human dependency through early detection/warning systems and analytics driven optimization
§ Driving optimal user behavior through granular demand calibrated resource and service pricing
§ Uptime & failure management be reducing points/chance of impact of failure on availability. A shift from 2N to N+1 failure management
34
Virtualizing and standardizing exis)ng assets has many benefits; yet it is not cloud
Retrofitting stand alone and virtual
Network, CPU, Storage
Cloud Infrastructure management layer
Multiple: • standards • vendor specific hard/soft adapters • monitoring, automation • API point service needs • maintenance • Licenses • Higher complexity Higher maintenance
Standardized (OVF, CDMI..): • Full interoperability • Vendor agnostic • License efficient • Simpler maintenance • Simpler expansion (scalability) vertically and horizontally
<
Virtualized Infra Cloud Infra
35 Accenture Confiden4al
The Delta: Cloud and Virtualized infra
Evolution of IaaS from Virtual to Cloud
Cloud Infra
Network, CPU, Storage
Cloud Infrastructure management layer I aaS
PaaS
• Applica.on & Infrastructure clearly delineated • Abstrac.on layer independent & interoperable with apps & infra • Demand/response opera.ng model • Integrated security and simplified compliance • True vMo.on across boundaries • Delivery to any end point
Virtualized Infra
IaaS
PaaS
?
Through extensive VIO across the plaYorm VMs can be moved not just on servers, but across networks and DCs to drive further abstrac4on, business value, BC and DR/DA
vMotion
36
*
* vCenter image from VMW
Extensive virtualiza4on of IO is key to achieving true VM mobility, disaster avoidance and elas4city
Cloud DC Architecture- Geo/node load balancing via DC bridge and vMotion
37
With vSphere at its nucleus, VMware has extended its technology into automated provisioning, and taking on horizontal and ver)cal features of intelligent middleware and enablement of a virtual DC, organiza)on and orchestra)on of complementary workloads and resources
Instantiation via VMware
CPU Pool
CPU Pool Memory Pool Storage Pool Interconnect Pool
39
Workloads are assigned to a virtual datacenter based on priority, type, requirements (QoS).
Workload tiers, types, QoS
40
Effec4ve Virtualized Environment Cost Mapping thorough VM Profiling
Workload cost model & charge back
41
Policy driven func4onal provisioning : mapping and flowing policies -‐by ver4cal-‐ is an area of opportunity. Supports building of image libraries. Correlated to reference architecture
Organizations, vApps, vDCs
42
With vSphere at its nucleus, VMware has extended its technology, into automated provisioning, and taking on horizontal and ver)cal features of intelligent middleware for enablement of a virtual DC, ‘organiza)on’ and orchestra)on of complementary workloads and resources
Instantiation via VMware
CPU Pool
CPU Pool Memory Pool Storage Pool Interconnect Pool
44
Virtualiza4on standards at storage 4er and Virtualiza4on 4er drive interoperability & simple integra4on
VMware integration with storage network: Integration (VMware/EMC)
45
ESX Cluster A ESX Cluster B
Synchronous Access Anywhere
Cloud Infrastructure: Storage & network HA and DR/A leveraging vMotion
Data Center A Data Center B
Data Center C Data Center D
Application
Application
Application
Application
Sample VM movement across FC leveraging VMware & EMC-‐ S4ll limited to short physical distances
• Sync distances
• Async Distances
• Long distances
• DC without boundaries
Using Spring as the abstrac4on layer enables each of the applica4ons styles defined in the
previous sec4on to be portable across mul4ple plaYorms
Application Architecture Portability using Spring
1. Build your application
2. Select your runtime platform
3. Launch
Your Java Spring App vSphere
Infrastructure Platform
vFabric
Application Platform
Other Platforms Source: VMware