From Grid To Cloud Online Gaming High Scalability SIG Presented by:Simon Waterer Solution Architect, Platform Computing July 2009
Are Compute Grids Morphing Into Clouds? 13/07/2009 2 How Many Of You Are Using Compute Grid Technology? Do Cloud Infrastructures Share Features Found In Grids?
Platform in the Gaming Industry 13/07/2009 3 Feed Handler, Grid Client TIP-EX Trader/Modeller Wholesale Channel Compute Grid Data Cache Client Web Site Client Mobile ………. Oracle Excel Instances Running on The Grid
Running Excel On the Grid Grid Client Spreadsheet serialised at client and passed by grid middleware to grid node Dialog Sniffer used for debugging spreadsheets that are to be run on the grid Scheduler Grid Service/Engine Grid Node/Host. Multiple Service/Engines run per CPU/core Excel Instance
The Advantages of Grid? Handles allocation of resources Automatic Shared Resources Handle Failures The grid provides redundancy So What? Run more workload using fewer resources 13/07/2009 5
Phases of Grid Adoption 13/07/2009 8 A A A A A A A A A A A A A A A A A A A A A A A A Phase 1 Phase 2 Phase 3 Phase 4 LOB LOB LOB LOB LOB LOB LOB LOB A Phase 1:Silo Grid – Grid enable application running on a commodity cluster Phase 2:LOB Grid – Resource sharing among multiple applications Phase 3:Enterprise Analytics Grid – Utility computing; enterprise scale and management Phase 4:Enterprise Grid – Beyond analytics: commercial applications on grid
Grid As A Service 13/07/2009 9 Dev/Test
Developers and testers get environments in 15 minutes, instead of waiting 2 weeks
IT administrators eliminate manual setup and repurposing work
Automated tracking of utilization with accurate billing to the LOB’s for what they use
Integrated cloud for Test/Dev through to production application deployment
Self-service environment reservation with automated, policy-driven VM placement
7/13/2009 10 Feb Contract: 16 machines Feb Contract: 6 machines Feb Contract: 12 machines LOB C LOB B LOB A Jan Contract: 12 machines Jan Contract: 14 machines Jan Contract: 10 machines Self-Service Resource Re-allocation Self-Service Resource Re-allocation Compute Grid Dev Network UAT Network Prod Network Free Pool Dev/UAT/Production & Production/Production Sharing 10
Bursting to non-HPC Servers
Calendar-driven startup/shutdown of VMs
Dynamic addition of non-HPC VMs to HPC Grid
Non-HPC servers HPC Grid VM VM VM VM 11
Cloud Bursting For Peak Demand Web 2.0Partner App
Public Clouds used for cloud-bursting applications
DetectWhenResources Are Exhausted ProvisioiningAdaptor Grid Infrastructure Private Data Centre Web 2.0Customer App GridOverflow Pool Public Clouds 12 12 13/07/2009
Public & Private Cloud Grid
Dynamic workload using static resources
Policy-based scheduling
VM Cluster
Homogeneous server consolidation
Limited apps
Basic VM mgmt
Enterprise Workgroup / LOB 3 Paths to Cloud Adoption Scope of sharing Cloud – “A pool of abstracted, highly scalable, and managed infrastructure capable of hosting end-customer applications and billed by consumption” (Forrester) Client/Server Silos Time 2015 2009 2003 13
Public Cloud Company X Private Cloud Company Y Private and Public Cloud Public Cloud by Service Providers
Non-mission critical SLAs
In-house IT has limited scale, scope or expertise --- SMEs
Private Cloud by Corporate IT
Maximize value of underutilized resources
Mission critical SLAs
High security & compliance requirements
Enterprise-specific services
14
Enterprise Adoption of Cloud $ $ $ $ $ $ Private Cloud Augmented by Public Cloud
IT delivering faster services with uniform UIs
Increased utilization of existing resources
Controlled overflow to Public clouds to meet unpredictable workload spikes
Lower CapEx & OpEx
Company X 15
7/13/2009 16 Different Cloud Services Software-as-a-Service (SaaS) Platform-as-a-Service (PaaS) Infrastructure-as-a-Service (IaaS) Private Public
IaaS Usage Model Cloud Admin User Application Manager ESX
From the Gaming Scalability event, June 2009 in Lon more
From the Gaming Scalability event, June 2009 in London (http://gamingscalability.org).
Simon will discuss some of the key components of a compute grid infrastructure and highlight some of the key challenges organisations have to meet as their compute grids expand. Simon will also discuss one organisation within the spread betting industry who has recently started using grid technology. Finally Simon will describe how compute grids within the capital markets are beginning to resemble private clouds, and how the underlying infrastructure needs to change to enable these organisation to support a much wider range of applications running on the grid.
Simon Waterer is a Senior Solutions Architect with Platform Computing, a leading provider of HPC software. Since joining Platform, Simon has worked with a number of clients within the capital markets and insurance industry to understand their grid computing requirements. Recently Simon has worked with leading organisations within the spread betting industry who also have distributed processing requirements. Prior to working with grid technology Simon has had experience working with a number of other middleware technologies including data caching, messaging middleware and event stream processing. less
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