Cloudy Inside: Use of Cloud Computing in Ground Systems Development

GSAW 2011 Cloud Computing

 Business considerations for a Ground System COTS vendor – Mission Critical applications • Any deployment, even a bug fix, must be tested in an integrated environment – Multiple Projects • The COTS model depends on having multiple customers to drive product evolution with new license purchases and support • Every customer’s concept of operations, and technical requirements, are different – Multiple Products • To be competitive the product suite must cover several application areas – Long support horizons • Customers are on separate upgrade cycles • Long periods of inactivity are punctuated by urgent requests Bottom line: Need to support customers efficiently and responsively.

GSAW 2011 2011/03/01 Page 2 © GMV, 2011 Cluster LRO Hipparcos ISO GMV‘s Footprint Huygens Integral XMM Mars Express BepiColombo COROT Darwin Rosetta Exomars SMART-1 SMOS Gaia Soho Hesrchel/Planck GOCE CRYOSAT LISA CRYOSAT 2 ERS-1/2 Venus Express Galileo constellation SEOSAT Envisat / Arabsat 4C JWST / Arabsat 4C GALILEO IOV-1 EPS/METOP Glory / Arabsat 4C GALILEO IOV-2 ACE GLORY LRO GALILEO IOV-3 SEOSAR OCO GALILEO IOV-4 ADM/Aeolus Earthcare Proba 3

EGPM Hispasat 1E ERM /Eurobird 4/ Eurobird 9 Giotto Minisob Mars Sample Return Smila Mars Next Spectra / W5 / W6 / W7 Ulyses DirecTV 10 SPOT KASAT MEASAT 1 DirecTV 11 Swarm MEASAT 3 DirecTV 1R Wales Nilesat 201 MEASAT 1R DirecTV 4S Amazonas 1 MEASAT 3B Amazonas 2 Azersat/Africasat-1a Brasilesat C3 Amazonas 3 Optus C1 SBS 6 Intelsat 5 Optus D3 Intelsat 10

IS-IR Galaxy 10R Brasilesat B1 IS-3R Galaxy 11 Brasilesat B2 Galaxy 13 Brasilesat B3 Intelsat 6B /Astra 3B Galaxy 3C Brasilesat B4 IS-9 Thor VI Galaxy 4R Intelsat 2

SCC & FDS / MPS / W2A / W2M LEASAT 10

FDS / MPS /Hot Bird 6 /Hot Bird 7 SCC /Hot Bird 9 NSS12 MA /Hot Bird 10 PMR

PDS/SOC/GMS

COSMO/Skymed ATV FUEGO Helios

SCC: Satellite Control Centre (real time monitoring & control) FDS / MPS: Flight dynamics / Mission Planning System LDCM Globalstar constelation MA: Mission analysis PMR: Payload management & reconfiguration PDS/SOC/GMS: Payload Data Segment / Science Operations Centre, Ground Mission Segment

GSAW 2011 2011/03/01 Page 3 © GMV, 2011 Example Configuration

 Three simultaneous projects – A (products X & Y, Red Hat Linux 4 32 bit) – B (products X & Z, Red Hat Linux 4 64 bit) – C (products Y & Z, SUSE Linux 10 32 bit)  Three versions per project – Deployed – Acceptance testing – Next release  Three machines per version – Build – Server – Client

GSAW 2011 2011/03/01 Page 4 © GMV, 2011 One Year Later

 Project A has entered long-term maintenance  Project B is upgrading to SUSE Linux 11 64 bit – Deployed version will remain on SUSE 10 for one more year  Project C has added redundancy requirements and will require a second server

GSAW 2011 2011/03/01 Page 5 © GMV, 2011 Mismatch

 The numbers of required environments increases monotonically – Projects stay in support for a very long time  Computer resource requirements are proportional to current workload – Developers and testers transition to new projects as old ones ramp down (i.e. team size is relatively constant) – New software versions tend to require more resources than old  Space, power and money are scarce resources – Filling the office space with computers is not sustainable – Constantly reconfiguring the existing computers is not efficient

How do we scale the computing resources with the workload, and not with the environment count?

GSAW 2011 2011/03/01 Page 6 © GMV, 2011 Enter the cloud

 Enabling factors – All configurations run on compatible hardware • 64 bit Intel processors (Core 2 and later) • New hardware is backwards compatible (i.e. old instruction sets supported) – Available hardware exceeds required performance for all roles • Installable memory • Number of processor cores – Hardware price/performance grows as fast as the workload • Lab workload grows with the requirements of new software versions, not with the number of projects  Approach: – Size hardware for the current workload – Configure a set of virtual machines for each project/version • Includes simulators for spacecraft and network link delays – Run the appropriate sets of virtual machines for the current work • Automatic load balancing, or fixed configurations, as required

Running Stored Environments Environments

Cloud

Moore's Law Wins • Assumptions 300 • 4 new projects/year, 1 year 250 duration 200 required (new & • Old projects require 1 month 150 maint) maintenance every year

100 Per cloud machine • 3 machines/project memory (GB) memory 50 • 2 GB + 20%/year memory 0 requirement per machine 1 2 3 4 5 6 7 8 9 • Memory capacity doubles every two years (Moore’s law) Cumulative Cost • Individual machine $700 (2GB), 80000 Cloud server $5000 (16 GB) 70000 60000 50000 40000 30000 20000 10000 0 1 2 3 4 5 6 7 8 9

Cloud cost Machine cost

 Ground Systems development has characteristics that cause proliferation of lab environments (build and test) – High degree of project-specific customization – Long-lived deployments  Cloud computing enables efficient reuse of hardware – Similarly to how the team’s resources are allocated to projects according to their level of activity – Saves space, power and money  This enables GMV to support a growing customer base efficiently and responsively

To the cloud!