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Micheál Higgins Enterprise Solutions Architecture CloudSigma Helix Nebula Big Science in the Cloud.

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Presentation on theme: "Micheál Higgins Enterprise Solutions Architecture CloudSigma Helix Nebula Big Science in the Cloud."— Presentation transcript:

1 Micheál Higgins Enterprise Solutions Architecture CloudSigma Helix Nebula Big Science in the Cloud

2 2 A Collaboration Initiative European Cloud Computing Strategy User organisations Demand-side Commercial Service Providers Supply-side European Commission & relevant projects

3 Scientific challenges with societal impact Sponsored by user organisations Stretch what is possible with the cloud today ATLAS High Energy Physics Cloud Use Genomic Assembly in the Cloud SuperSites Exploitation Platform To support the computing capacity needs for the ATLAS experiment A new service to simplify large scale genome analysis; for a deeper insight into evolution and biodiversity To create an Earth Observation platform, focusing on earthquake and volcano research Helix Nebula

4 Helix Nebula – The European Science Cloud Concept Big Science needs to begin to use Public Clouds The European GRID is aging out Cloud-burst has a much better TCO Avoid lock-in and Procurement issues Federation and Identity Management Disintermediation of Cloud Vendor Solutions APIs Drive Image formats (KVM, ESx, Zen, etc.) Cost/Billing models Etc. Initial Membership Demand Side: CERN, ESA and EMBL Supply Side: CloudSigma, Atos, T-Systems, Logica, Interoute and 4 non-provider SMEs




8 Helix Nebula – The European Science Cloud Phase I – Flagship Proof-of-Concepts Q to Q CERN – LHC ATLAS jobs with Panda/Condor EMBL – De Novo (non-human) Genome with StarCluster ESA – SSEP Earth Observation Site Environment One-to-one tests, vendor API, vendor drive format, etc. Success criteria was binary, no performance or cost data CS successful in all 3 and continuing to run ATLAS live Phase II – PoCs with some Disintermediation Q Many-to-Many Blue Box 0.9 – remove complexity for the Customer enStratus + Integration Phase III – Expanded Membership and Disintermediation More Demand and Supply Side partners Increased Blue Box Functionality – Federated Clouds

9 Blue Box Maturity Model Release 0.9 – enStratus – January 2013 Basic Services Catalog Federation and Identity Management, Token pass-through Web Portal and API Translations Some Image Management and Cost reporting (not Billing) - as time allows Release 1.0 Service Catalog and Cube Filtering Image Factory and Transport Billing / Payment Module Embedded Monitoring On-screen Provisioning Contextualization Post 1.0 Cluster Management plug-ins (StarCluster, SGE, G-POD, etc.) Payment gateways PaaS for Science Recipes and Golden Image Management SLA / OLA Reporting Data Movement and Open Networking Ecosystems

10 The Blue Box 0.9 EC1/EC2

11 The Blue Box - Production

12 Helix Nebula – Learnings Not All Things are Public Cloud Suitable This is not the GRID Some science middleware is not cloud friendly IPs and UUIDs change at re-boot The Public Cloud is commodity hardware 2.2 to 2.3 GHz CPU is common, less in older clouds 32, 64 and 96 Gb maximum RAM sizing – no 1 Tb servers Caution: You cant eat the whole physical server Parts of De Novo are single core, massive map reduce Many science applications do not scale horizontally, yet Software innovation by the Vendors is required Putting Data in the Public Cloud is still perceived as a risk My Firewall is better than your Firewall – or is it ? Burst utilization must be somewhat predictable No, you may not have 65,000 large VMs for 2 hours later today What do you mean I have to pay for it ?!!


14 CloudSigma Public IaaS Provider since 2008 Locations (tier 4+ carrier neutral datacenters) Zurich, Switzerland (Headquarters) Las Vegas, USA Amsterdam (in-work) San Palo (planned 2012) Key Values: Open Platform and Networking Constant Innovation (big secret: all SSD storgage !!) High availability and Up Time SLAs Customer Relationships / Enterprise Architecture Team Standards Adherence (OpenNubula, Jclouds, etc.) We only sell IaaS, we partner for SaaS and PaaS The Ecosystem Concept

15 CloudSigma Features Granular Resources not Bundles CPU, Cores, RAM, Disk, SSD, GPUs, etc. all virtualized Graphic Equalizer – reboot required Allows for the tuning of the Server to the Work-load E.g. Oracle requires 1.5x to 2x Memory of Standard config HEP/HPC applications are also not Typical configurations Open Architecture KVM Hypervisor with full Virtualization, no sniffing, no root Any x68 O/S and Application (no you cant run Mac) Public Drives Library, Pay-per-use and Bring-your-own Open Networking – 2x 10GBs NICs SigmaConnect and IX – private back-haul lines Peering (e.g. Switch, Geant, etc.) No Customer Lock-in – upload and download easily


17 CloudSigma Features In-Work for the Future All SSD Storage – only S3 is magnetic JSON API Virtualized GPUs Virtualized H/W for Transcoding and Rendering Virtual Desk Top – Command and Control Additional Science Applications: Panda/Condor, etc. PaaS for Media and PaaS for Science The Ecosystem Concept Hold the Data and the World will come to the Cloud Low to Zero cost Data hosting More margin in CPU and RAM than in Storage Meta meta-data – joining the Databases Known Point + Vector + distance vs. Lat / Lon ESA EO + WHO = Mosquito outbreak predictions

18 The Easiest Way to Understand The CS Ecosystem Concept

19 Questions / Discussion

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