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Lessons Learned while Exploring Cloud-Native Architectures for NASA EOSDIS Applications and Systems

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Lessons Learned while Exploring

Cloud-Native Architectures for

NASA EOSDIS Applications and

Systems

Dan Pilone ([email protected])

NASA EED2 Program

The material is based upon work supported by the National Aeronautics and Space

Administration under Contract Number NNG15HZ39C

(2)

Landsat 9 PACE NI-SAR SWOT TEMPO JPSS-2 (NOAA) RBI, OMPS-Limb GRACE-FO (2) ICESat-2 CYGNSS ISS SORCE,

TCTE (NOAA)NISTAR, EPIC(NOAA’S DSCOVR)

QuikSCAT EO-1 Landsat 7 (USGS) Terra Aqua CloudSat CALIPSO Aura SMAP Suomi NPP (NOAA) Landsat 8 (USGS) GPM OCO-2 GRACE (2) OSTM/Jason 2 (NOAA) Formulation Implementation Primary Ops Extended Ops

Earth Science Instruments on ISS:

RapidScat, CATS,

LIS, SAGE III (on ISS), TSIS-1, OCO-3, ECOSTRESS,

GEDI, CLARREO-PF Sentinel-6A/B

(3)
(4)
(5)

15+ years of Earth Science Data

Deletion of MODIS Collection 4 Products Landsat-7 Data Migrated from LPDAAC to USGS Addition of AQUARIUS and ICEBRIDGE products Addition of ALOS PALSAR & UAVSAR products

ICESat MEASURES 2006 MEASURES 2012

TERRA AQUA AURA

Addition of SNPP CERES&OMPS

Total EOSDIS Accumulated Data Archive Volume

(Petabytes)

(6)

EOSDIS Archive Growth Estimate

(Prime + Extended)

2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Cumulative Archive Size (PB) 13.8 20.0 27.0 34.8 42.7 65.0 118.0 170.5 223.1 275.6 328.2

Archive Growth Rate (PB) 4.9 6.2 7.0 7.9 7.9 22.4 52.9 52.6 52.6 52.6 52.6

0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0 400.0

PB

Archive Growth Rate (PB) Cumulative Archive Size (PB)

(7)

Cloud Evolution (ExCEL) Project

7

ExCEL Efforts and Project Prototypes

NASA Compliant General Application Platform (NGAP), an operational, dev-ops, and sandbox AWS cloud based operating environment.

NGAP

AWS/NGAP Web Object Storage (WSO) prototyping large volumes of mission data dynamically between AWS S3, S3-IA, and Glacier object storage. Managed out of Alaska Satellite Facility

ASF WOS Prototype

NASA Earth Science data search by keyword and advanced filters such as time and space

Earthdata Search Client to Cloud

Prototype addressing core EOSDIS capabilities including data ingest, archive, management, and distribution of large volumes of EOS data.

Cumulus

Integrated prototype of science product generation and delivery from a DAAC system focused on coupling ASF DAAC and JPL ARIA systems.

NISAR Preparation Prototype

Easy-to-use Python tools packaged to support EOSDIS cross-DAAC science workflows and analytics over large volumes of EOS data in AWS.

CATEES

Earth Code Collaborative (ECC) study to determine cloud ready capabilities to migrate into AWS/NGAP platform.

ECC to Cloud Study

ExCEL

Project

1

2

3

4

5

6

7

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Cloud Evolution (ExCEL) Project

8

Migrating GIBS to the AWS/NGAP Cloud based on recommendations made in the “GIBS in the Cloud Study”

GIBS in the Cloud

Study to determine and recommendmigrating the Earthdata Login into AWS/NGAP cloud environment

Earthdata Login to Cloud Study

Migration of the Common Metadata Repository, into the AWS/NGAP platform based on recommendations made in the CMR to Cloud study.

CMR to Cloud

Study to determine and recommend a cloud native integration of OPeNDAP accessing HDF5 and netCDF4 data on AWS/NGAP platform.

OPeNDAP/HDF Cloud Studies

Prototype to accelerate end-user analysis of remote sensing data, highly parallel to better enable science discovery

NEXUS

ExCEL

Project

Network Prototypes

Network prototypes to support to test security, monitoring, logging, and to perform R&D testing to support all ExCEL project prototypes.

ExCEL

Project

8

9

10

11

12

13

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Cloud Evolution (ExCEL) Project

9

ExCEL Go/No-Go

(01) Full Scale Deployment (?)

Full scale enterprise deployment of EOSDIS services and infrastructure to the cloud

(02) Partial Deployment (?)

Select deployment of EOSDIS services and/or infrastructure to the cloud

(03) Cloud Stand-down (?)

No EOSDIS services or infrastructure operationally migrated to the cloud

(04) Decision Point (?)

More prototyping required, or cloud hybrid, or other next steps based on ExCEL prototyping and business analysis results

03

04

01

02

Determining Project Success

Project success is determined by viable

outcomes of fully completed project prototypes and business analysis.

or

-Technical and business results of the ExCEL project needed for stretegic decision on EOSDIS and the cloud.

(10)

Lessons Learned

• Technical

• Cost

(11)

ENABLE CLOUD NATIVE

ARCHITECTURES BY STRONGLY

PREFERRING CLOUD SERVICES

(12)

GIBS-in-the-Cloud Service Swap

Handlers

Generation

Ops

Console

MRF Gen

Product

Config

Product

Configs

Inventory

ZooKeeper

Subscription

Service

CM

Manager

Authentication

SigEvent

Server

Infrastructure

Install

S3

Dynamo /

SQS

SNS / SQS

Cloud

Formation

Scheduler /

Dispatcher

IAM / NAMS

CloudWatch

Cloud

Formation

Cumulus

Dashboard

Custom Software

External NASA/GIBS Library

Cloud Services

Data

(13)

GIBS-in-the-Cloud Ingest and Processing

Handlers

Generation

MRF Gen

Product

Config

Dispatcher

(106 LoC)

Scheduler

(66 LoC)

AWS

Infrastructure

(14)

Discover

Sync

Process

Provider

Discover

HTTP Tiles

Sync HTTP

URLS

Generate

MRF

MRF Storage

Source Image

Storage

Execution Flow

Data store

Data fetch

Scheduler

MRF Locks

Ingest: MODAPS Tiles

(15)

AWS HAS VERY LOW INTERNAL

LATENCY – BUT TRUST NOTHING.

(16)

On premises

implementation showed

consistent performance

during load testing vs

more sporadic latencies

in AWS.

(17)

INVOLVE SECURITY FROM

THE VERY BEGINNING

(18)

Layer security thoughout the architecture

NGAP Services

(Monitoring, Logging, Security, Autoscaling, Billing, etc.)

OCIO GP-MCE*

(AWS Reseller)

*General Purpose Managed Compute Environment

NGAP Builder

(Creates “slug” from

ECC-hosted codebases)

NGAP-compliant AMI

(Application)

NGAP-compliant AMI

(Application)

NGAP-compliant AMI

(Application)

Usable cloud “platform”

ECC

(Code

testing,

tracking,

deployment)

App

Source

Code

NGAP Base AMI

(Secure)

(19)

MODELING TOTAL COST OF

OWNERSHIP (TCO) IS

EXTREMELY COMPLICATED

(20)
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November announcements as of

the 7th…

(22)

This is before considering…

• User behavior

• Staff cost savings

• Development cost savings

• Inter-region costs

• Data lifecycle modeling

• Application migration costs – both in and out

• Managing “consumption” based cost model

(23)

EXPLORE ALTERNATIVE

ARCHITECTURES FOR POSSIBLE

COST SAVINGS

(24)
(25)

GO HANDS-ON QUICKLY

(26)
(27)
(28)

Summary

• Enable cloud native architectures by strongly

preferring cloud services

• AWS has very low internal latency, but trust

nothing.

• Involve security from the very beginning

• Modeling TCO is extremely complicated

• Explore alternative architectures for possible

cost savings

(29)

Questions?

Dan Pilone

(30)

This material is based upon work

supported by the National Aeronautics

and Space Administration under

Contract Number NNG15HZ39C.

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