Dr. Tsengdar Lee Acting CTO for IT August 16, 2011 Advancing Science at NASA through Cloud...

Dr. Tsengdar Lee

Acting CTO for IT

August 16, 2011

Advancing Science at NASA through Cloud Computing:Examples from Nebula

Nebula Case Examples-- August 16, 2011

Nebula Pioneers a New Frontier for Cloud Computing

One of the first cloud computing

platforms built by the Federal

Government for the Federal

Government Over 300 users at 9 Centers

+ JPL + HQ White House was first client


Nebula Pioneers a New Frontier for Cloud Computing

Nebula developed to provide: “Instant-on” IT Infrastructure Automated provisioning capabilities, and Quick scale-up services

All Necessary to…

Process large datasets quickly, easily share them with colleagues and ultimately store them securely at a good price


Why NASA Created Nebula

In 2008, limited commercial cloud offerings could not meet NASA requirements for:

Security Network performance for managing data in and out of the

cloud Private cloud customization capabilities Limit vendor lock-In


Nebula Principles


Open and public APIs, everywhere Open-source platform, apps, and data Full transparency»Open source code and documentation releases

Reference platform»Cloud model for Federal Government

Nebula IaaS Services


Software to provision virtual machines on standard hardware at massive scale

Software to reliably store billions of objects distributed across standard hardware


Previous Options for NASA Scientists

Science-scale

application developm

ent

Very large data set processing

Compute intensive

processing

Timely sharing of

results with

collaborators and

the public

Missions

BUILD IT

Build my own IT infrastructure that may/may not comply with Federal/Agency IT security standards.

BUY IT

Go through a lengthy procurement and provisioning process for basic IT services

DO NOTHING

The current basic IT services model is cost prohibitive and I cannot afford to process my data and share with collaborators and the public at large.

Current Options*Requirements*


Supercomputing (grid)

Tasks are distributed among subset of nodes of supercomputer All data is accessible to all nodes via high-speed interconnects Failure of a node results in failure of a job Nodes cannot be added or removed during Job

Cloud (batch)


Work separated into many individual tasks

Each task is performed with only the subset of data needed

Failed tasks can be restarted by re-issuing tasks to new node

Nodes may be added and removed as needed/ available

Nebula Case Examples


SERVIR integrates satellite observations, ground-based data and forecast models to monitor environment changes and improveresponse to natural disasters

SPoRT transitions unique NASA satelliteobservations and capabilities to NOAA to predict short-term weather events

iRODS is an open-source, data grid softwaresolution to manage, share, search and distribute large, diverse scientific datasets

SERVIR & SPoRT: Modeling Capabilities

Application Concept:»Create Nebula images that are capable of supporting the

research and operational goals of both SERVIR & SPoRT.»Potential Benefits:

• Rapid deployment of standard models to respond to natural disasters without disrupting other activities.

• Reduces the installation and maintenance of IT resources at remote or offsite location


SERVIR: Weather Forecasting Severe weather is natural hazard of interest to both SERVIR

and SPoRT Use the Weather Research and Forecasting (WRF) Model to

produce high-resolution, short-term forecasts Instances can be used to:»Use one instance for single region»Share resources for a high-resolution run or a larger

forecast domain»Provide rapid response to new events or research

opportunities without impacting other resourcesNebula Case Examples-- August 16, 2011

A True Nebula Story…


On April 27th tornadoes devastated parts of Central and Northern Alabama including a large stretch of downtown Tuscaloosa.


S

SPoRT used Nebula to process datasets provided to National Weather Service through Google Earth to verify path length and width of tornado combining spectral channels to obtain false color imagery of damages impacting vegetation and ecology


Nebula hosted tiling application with large hi-res images

Rapidly configured

Tiles created pushed back to local web server

Made available via Google Earth


EF-4 Tornado marked in orange

EF-4 Tornado identified in red

EF-5 Tornado marked in purple

Broad view of tiled ASTER images and Tornado tracks heading northeast on March 27

Comments from SERVIR & SPoRT

“Our Linux machines were busy processing data from other tasks and could not be interrupted… But even if they could… They would not have been as easily configurable as Nebula.”

“Nebula gave us the chance to ‘play in a sandbox’ where configuration testing was easy and fast and could be used without disrupting other local systems.”


That’s Fantastic!

NASA SPoRT says they’re pleased with Nebula’s scalability capabilities….

“An earlier test run of my forecast model ran

for 54 consecutive days without issue before I brought it down. That’s fantastic!”

Andrew Molthan

Senior Meteorologist

Servir and SPoRT

NASA Marshall Space Flight Center


Technology – Integrated Rule-Oriented Data System (iRODS)

Targets large repositories and digital preservation Supports the federation of independent, distributed collections Supports server-side workflows that are implemented by

chaining execution rules together based on data policies Includes features such as domain-specific validation,

automatic replication, and digital signature/checksum computation

Validates assertions about data such as integrity and authenticity


NCCS Develops iRODS DMS for Climate Studies

NASA Center for Climate Simulation (NCCS) provides compute engines, analytics, data sharing, long-term storage, networking and other high-end computing services for Earth science community

NCCS completed a pilot project to develop an iRODS-based Data Management System (DMS) to handle massive amounts of observations and model data used in climate and weather studies

DMS team used Nebula to host DMS prototype with goal of managing and publishing climate simulation data using iRODS with a distributed set of Nebula instances


Steps for iRODS Distributed Data Storage and Management

Modern Era Retrospective-Analysis for Research and Applications (MERRA) data placed under iRODS control

MERRA data stored on file system and registered with iRODS Registration process stored metadata about MERRA files in

iRODS database Entire catalog of monthly MERRA products resulted in

ingestion of 360 files that occupy 47 GB Data was shared between two instances


iRODS Results By eliminating the need to explicitly switch an iRODS client

between distinct grids, federation allowed perusal or download of data from multiple iRODs depositories through a single interface

Upon completion, users could examine,

search for, and download simulation

data from either Nebula instance though

a single iRODS web interface



Thank You

Dr. Tsengdar Lee Acting CTO for IT August 16, 2011 Advancing Science at NASA through Cloud...

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