A Storage Architecture for A Storage Architecture for Resilient - - PowerPoint PPT Presentation

▶
a storage architecture for a storage architecture for
SMART_READER_LITE
LIVE PREVIEW

A Storage Architecture for A Storage Architecture for Resilient - - PowerPoint PPT Presentation

Oct 24, 2023 415 likes •590 views

A Storage Architecture for A Storage Architecture for Resilient Assured Data Resilient Assured Data Paul Manno Paul Manno Georgia Tech / PACE Georgia Tech / PACE Date May 2019 Date May 2019 Research Computing at Georgia Tech Research

slide-1
SLIDE 1

Paul Manno Paul Manno Georgia Tech / PACE Georgia Tech / PACE Date May 2019 Date May 2019

A Storage Architecture for A Storage Architecture for Resilient Assured Data Resilient Assured Data

slide-2
SLIDE 2

Research Computing at Georgia Tech Research Computing at Georgia Tech

  • Georgia Tech: Founded 1885
  • PACE
  • Partnership for an Advanced

Computing Environment

  • 14 years (almost)
  • 1200+ Researchers
  • 50,000+ x86 cores
  • 10PB storage
  • 14 FTEs (and hiring!)
  • OSG, NSF, Big Data Hub, etc.
  • Many research areas
  • LIGO
  • NSF
  • OSG
  • Health
slide-3
SLIDE 3

Georgia Tech: The New Georgia Tech: The New

  • John Portman & Associates
  • CODA tower
  • 645,000 sq-ft office tower
  • Opened March 2019
  • Tallest “spiral” staircase in the world
  • First dual-cab elevators in North America
  • Collaborative space
  • Databank, Inc.
  • Data Center
  • 60,000 sq-ft usable
  • 10+ MW
  • Open June 2019
slide-4
SLIDE 4
  • What is ”…Resilient Assured Data”
  • We want it all: Speed, Availability, Accuracy, and Low cost!
  • Probably expect availability as top priority
  • Followed by speed vs cost and accuracy?
  • What about security?
  • Do you need data secured at rest
  • Do you need data secured in flight
  • Do you require geo
  • diversity?
  • Across a campus / town / country / world

SOME Definitions SOME Definitions

slide-5
SLIDE 5
  • Simple example: Archive Tier of Storage
  • We have a need to store a bunch of cool or cold data for “a while”
  • Cost should be low
  • Maintenance requirements should be low or minimal
  • Convenient for multiple operating systems, platforms
  • Speed needs to be “acceptable”
  • Data could be recalled even after several years
  • Types of information to be kept
  • POSIX files?
  • Objects?
  • Metadata?

Design Thoughts Design Thoughts

slide-6
SLIDE 6

More Design Considerations More Design Considerations

  • Method(s) of access
  • Computing platforms to support?
  • Automation opportunities
  • Long term options
  • On-Prem “cloud”
  • Data Center
  • Maintenance
  • Public cloud
  • Networking
  • Cost

Google-searched image used without permission

slide-7
SLIDE 7

One Archive Solution (There Are Several) One Archive Solution (There Are Several)

  • User Interface: Globus
  • Common across all platforms
  • Capable, extendable, reliable
  • NFS Client and Storage
  • Inexpensive, reliable, efficient
  • Highly Available HSM
  • … more on this in a moment
  • Replicated Object Storage
  • Commonly available
  • On-Prem, Off-Prem, Hybrid

Globus Server NFS client HA HSM Device NFS Storage NFS NFS Replicated Object Storage

slide-8
SLIDE 8

The Archive Parts The Archive Parts – Globus User Interface Globus User Interface

  • Why Globus?
  • Long history of reliable transfers
  • XSEDE standard
  • Parallelizes transfers (configurable)
  • Auto-resume on interrupted transfers
  • Local and Wide-Area network support
  • Notification of success/failure
  • Platform agnostic
  • Transfers available via web front-end
  • Works to/from local system
  • Works to/from 3 rd party systems
  • Agnostic authentication
  • Just about anything
  • Shibboleth included
slide-9
SLIDE 9

The Archive Parts The Archive Parts – NFS Storage NFS Storage

  • Network File System (NFS)
  • NFS Service v3 or v4
  • Caching (can be important)
  • POSIX
  • based
  • Not seen by user (in this design)
  • HA service available
  • NFS Client v3 or v4
  • Caching (can be important)
  • POSIX
  • based
  • Not seen by user (in this design)
  • Multiple clients can use one server
  • Caches help some operations

NFS Client System NFS Server System Cache Globus Server Cache Storage

10 GbE

  • r more

NFS Client System NFS Server System

slide-10
SLIDE 10

The Archive Parts The Archive Parts – Replicated Object Storage (part 1) Replicated Object Storage (part 1)

  • Why object storage?
  • Binary Large

OBjects (BLOB)

  • Easystorage add / delete / move
  • Geographic Dispersion
  • On-Prem Object storage
  • Off-Prem Object storage
  • Hybrid Object storage
  • Speed considerations
  • Objects known by
  • Object ID, Version, etc.

And Many More!

slide-11
SLIDE 11

The Archive Parts The Archive Parts – Replicated Object Storage (part 2) Replicated Object Storage (part 2)

  • Object push
  • New object ID
  • Typically, versioning is on
  • Object-id re-use?
  • Replications
  • Accepted is 3 copies but …
  • Object read
  • Get object from wherever available
  • Source optimization
  • Size doesn’t really matter
  • Do you know data is “good”?
  • Metadata attributes
  • POSIX information
  • Versions
  • User information
  • Checksums, et. al.
  • 3 copies, compare data
  • Encryption (many options)
  • At rest
  • In flight
  • In memory
slide-12
SLIDE 12

The Archive Parts The Archive Parts – HA HSM Device HA HSM Device

  • Some last definitions
  • Primary Storage
  • Secondary Storage
  • Tiered Storage
  • Highly Available
  • Virtual IP addresses
  • Multiple units must synchronize
  • Hierarchical Storage Management
  • The ”magic” happens here
  • Policy-based decisions
  • Multi-tier storage options
  • Transparent to users

Transparent to users

HA HSM Device NFS Obj NAS Cloud Data Requests P P P

slide-13
SLIDE 13

The Archive Parts The Archive Parts – What About Scale? What About Scale?

  • Depends on the HSM
  • Some can be clustered
  • Some are built-into file system
  • Some are “bump in the wire”
  • One HSM (Infinite IO) claims
  • Clustered operation
  • 3,000,000 MD requests per second
  • Many billions of files
  • What about performance?
  • Secondary storage varies latency
  • Performance varies by network
  • Objects are relatively quick
  • Archive vs Backup
  • Archive
  • Long Term Retention (years)
  • Versions are helpful
  • How to “refresh” technology?
  • Backup
  • Think business continuity
  • Versions are essential
  • Backup is not just copy
  • Size of “things” to stored
  • Scans, Videos, Source Data
  • Becomes PB very quickly
slide-14
SLIDE 14

How is this massive? How is this massive?

  • Sizes of data to be stored
  • Grow to 100s of PB of storage
  • Many billions of objects
  • Replication of objects
  • Can be

any geography

  • Clustered HSM update lag
  • Built-in HSM solutions
  • May work better
  • May be less-flexible
  • Data Lakes (vs. Data Swamps)
  • Flexibility is key
slide-15
SLIDE 15

Lessons Learned (so far) Lessons Learned (so far)

  • Change is ”bad”
  • Users don’t want things to change
  • Procedures are often rigid
  • Transparency is key
  • Change is “good”
  • Accept technology updates
  • Newer / Faster / Better / Stronger
  • Transparency is key
  • Pricing of off -prem storage
  • Pricing models vary considerably
  • Ingress/egress charges vary
  • Be sure to ask carefully
  • Users like Globus ok
  • The GUI is intuitive
  • There is support
  • Users like point-and-click
  • Data Management
  • Requirements vary
  • Inspect terms carefully
  • Often locations can’t change
slide-16
SLIDE 16

Questions and Discussion Questions and Discussion

Many options to discuss … What are your thoughts?

Paul Manno Cyberinfrastructure Lead Georgia Institute of Technology 756 West Peachtree Street, Northwest Atlanta, GA 30332-0700