S111477 scale-in-cloud-jburg-v1909d

IBM Spectrum Scale
on the Cloud
Tony Pearson
IBM Master Inventor,
Senior IT Management Consultant,
TechU Content Manager
2019 IBM Systems Technical University
10-12 Sep 2019 | Johannesburg, SA

Session Abstract
— Many of you may think that Spectrum Scale is an on-premise solution only.
— This session will dispel that myth - we'll describe various ways Spectrum
Scale can be consumed in various clouds. Spectrum Scale can run on
Amazon; will run in future on Google Cloud; can tier data to AWS and
Azure.
— Learn about the full breadth of Spectrum Scale in the cloud to deploy fully
managed and custom designed solutions addressing extreme speed
requirements or more moderate POSIX compliant storage efficiency
requirements.
— Hear how you can use Spectrum Scale in these clouds today, and how you
can connect your current Spectrum Scale on-premise installations to these
clouds for true Hybrid cloud capability.
— A basic understanding of Spectrum Scale concepts is assumed
IBM Systems Technical University © Copyright IBM Corporation 2019 2

Disk
TapeStorage Rich
Servers
Client workstations
Users and applications
Compute
Farm
Single name space
Flash
NFS
HDFS
Connector
POSIX SMB/CIFS
OpenStack
Cinder
Glance
Manila
IBM Spectrum Scale
Automated data placement and data migration
On/Off Premises
Object
S3
Swift
Active = Hot+Warm = “Online” Archive = Cold = “Offline”
Object Storage
SAS
SAP
DB2
Oracle
MQ
etc.
Mainframe
Hadoop
Cloud
Providers
Docker
Kubernetes
Spark
Site A
Site B
Site C
iSCSI
Block
IBM Spectrum Scale – Scalable File and Object Store

Spectrum Scale in the Cloud
Today’s Agenda
• Spectrum Scale on Cloud - Vision
• Key Spectrum Scale Cloud Solutions
• Spectrum Scale on Amazon Web Services
• Transparent Cloud Tiering - tiering data to either
AWS or Azure
4IBM Systems Technical University © Copyright IBM Corporation 2019

Spectrum Scale On Cloud – Vision for Cloud Readiness
Workload Support
• Analytics & Cognitive
• High Performance Computing
• AI Data Pipeline
Workload Ecosystem
• Containers
• CaaS
• Ephemeral and Persistent Volumes
• Storage Enabler for Containers (SEC)
• Container Storage Interface (CSI)
• Hybrid Use Cases
• Cloud Burst
• Multi Cloud Data Sharing
• Archive
• High Performance Tier
5

Spectrum Scale On Cloud – Vision for Offerings
User Deployed – Build your own cluster
• IBM Cloud
Spectrum Scale Solutions
• IBM Spectrum Scale on AWS
Private Cloud Solutions
• IBM Cloud Private (ICP)
• Others
Partner Solutions
Trials
• AWS Quickstart
• Google (soon)
6

Spectrum Scale On Cloud – Vision for Ecosystem Integration
User Interface (Look and Feel)
Resource Provisioning and Initialization
• Provision Virtual Machines, Storage etc. and initialize
Deployment Automation and Orchestration
• AWS Cloud Formation etc.
Spectrum Scale Cluster Creation and Configuration
• Cluster Creation, File system Creation. Feature
enablement and configuration
Digital Business Integration
Service & Support Processes
Durability & Elasticity
7

Spectrum Scale on AWS
• Bring your own license
• Available Sept. 28 2018
• Data Management Edition
• 3 months trial license
• Available Sept. 13 2017
• Data Management Edition
Spectrum Scale Trial link Spectrum Scale Marketplace link
Run an entire Spectrum Scale cluster within the Amazon Web Services cloud!
8

Spectrum Scale on Amazon Web Services – value proposition

Spectrum Scale on Amazon Web Services – what’s available
Wow! A cluster of 16 EC2 Spectrum Scale instances can be launched and configured with a shared
filesystem mounted on all nodes in less than an hour (and does not require any Spectrum Scale Admin
Skills).
“Bring your own (existing Spectrum Scale Data Management Edition) license”

Spectrum Scale on Amazon Web Services – ideal usage case guidelines
Gives you ability to easily and quickly create and use a Highly Available Spectrum Scale cluster filesystem on
AWS infrastructure w/ POSIX semantics
• Targeted for HPC use cases (scalable bandwidth to capacity ratio) on AWS
o Ideal for use cases that can use a newly deployed cluster
o Data will be ingested by user into the new cluster
o Data will be exported after application use by user cluster termination after application is done
o Target is HPC use case where “extended” features of Spectrum Scale not required (i.e. Protocol nodes)
o Optimize cost of AWS resources by shutting down some pieces of the cluster deployed is manual (we
provide tools to optimize resource usage – you as customer must use those tools. Initial offering doesn’t
yet use auto-scaling to manage resources)
• Provides a Spectrum Scale global namespace across a set of EC2 instances
• Provides an AMI (Amazon Machine Image boot image) with Spectrum Scale 5.0.2 Data Management edition
installed on RHEL and GPL layer built
• Provides a AWS Cloud Formation script that deploys a cluster of EC2 instances using the provided AMI and
deploys Spectrum Scale using simple input to create a filesystem mounted on the launched instances
• You as a AWS customer pay Amazon for EC2 resources used and RHEL and other software you consume
• BYOL Data Management Edition licensed version of Scale is launched from the AWS Marketplace

Easy configuration through cloud formation
Spectrum Scale Listing On AWS Marketplace

Spectrum Scale on AWS – Architecture
 Solution based on EC2 instances and EBS volumes
 NSD servers separate from “Compute” nodes that
will mount the shared filesystem
 NSD servers using AWS EBS storage for Spectrum
Scale
 Data is replicated across multiple availability zones
 Support for creation of new VPCs or launching
instances into existing VPCs.
 Connection to these instances only via a Bastion
Host (as per AWS best practices)
 Focuses on simplicity/usability of deployment (e.g.
reduced config. options) and leverages Amazon
features such as Cloud Formation templates and
AMIs (Amazon Machine Image)
This diagram describes the deployment of the Multi Availability Zone configuration (2 AZs)
In single Availability Zone deployments, all resources are deployed into the same Availability Zone

Some AWS Terms Defined (Part 1 or 2)
AWS instance: a ‘node’ on AWS-- a virtual machine running on AWS hardware*
• Spectrum Scale clusters are comprised of AWS EC2 instances running Spectrum Scale 5.0.2.1 on
RHEL
Amazon Machine Image (AMI): An AMI stores the data needed to launch AWS instances. It includes:
• Launch permissions that control which AWS accounts can access the AMI to launch instances. You
must subscribe to the IBM Spectrum Scale BYOL Marketplace Offering to have access to launch the
AMI from the AWS Spectrum Scale Marketplace page
• A block device mapping defining the volumes attached to a launched instance
• A template for the root volume for the instance. Our AMI includes the RHEL operating system, IBM
Spectrum Scale, with the GPL layer pre-built
• Our AMI is backed by EBS (Amazon Web Services’ Elastic Block Storage), which means the root
device for instances launched by the AMI will always use EBS volumes. IBM does not support the
use of Amazon instance store volumes with Spectrum Scale instance root device volumes or NSD
volumes)
* Notes: In general IBM does have any way of mapping virtual resources (e.g., instances or EBS volumes) to their underlying AWS physical
hardware (e.g., the memory, CPU and disks). Thus IBM Spectrum Scale on AWS can’t figure out which EC2 instances might share the same
physical CPUs, memory, etc.

CloudFormation: according to Amazon, "AWS CloudFormation is a service that helps you model and set
up your Amazon Web Services resources”.
• CloudFormation templates define resources, like EC2 instances and EBS volumes, and allow these
resources to be provisioned and configured
• The Spectrum Scale Marketplace page has links to an IBM created CloudFormation template that will
provision resources on AWS, using AMIs that already have Spectrum Scale installed, and then
configure a Spectrum Scale cluster using these resources
EBS Volume: An Amazon EBS volume is a basically a virtual disk*, providing block storage that can be
attached to a single EC2 instance (at any given point)
• The AMI stores the root volume and that is transferred to an EBS volume on every node that is
deployed in a Spectrum Scale cluster.
• NSD Servers on AWS will use EBS Volumes for Spectrum Scale file system NSDs
• Amazon provides mirroring for these NSD volumes, and AWS claims “99.999% availability” (this an
AWS AFR (annual failure rate) number). AWS and your AWS design is responsible for data durability of
data on EBS volumes, even in configurations in which we replicate the volumes contents across AZs.
More AWS Terms Defined Part 2 of 2)

Spectrum Scale on AWS – other AWS services and components
16IBM Systems Technical University © Copyright IBM Corporation 2019

EC2 Instance
(NSD Server)
EBS
volume
EBS
volume
[. . . ]
Spectrum Scale on AWS: Running on EC2 Instances Backed by EBS
EC2 Instance
(NSD Server)
EBS
volume
EBS
volume
[. . . ]
Network EBS connection
[. . . Additional servers]
EC2 Instance
(NSD Client)
EC2 Instance
(NSD Client)
EC2 Instance
(NSD Client)
Network Connection tor Non-EBS traffic
[. . . Additional clients]
[. . . Additional clients]
17

Successful Stack Creation

Sample timings for Cluster Creation (testing results from Sept. 5/18)
Cluster Stack Analysis Start time End time Execution time Comments
Cluster Stack 11:27:41 AM 12:46:29 PM 1:18:48UTC -7
Scaling gtoup + instance create 11:27:41 UTC 64 T2.Medium instances
CFI init inside instance 6:31:51 PM 7:45:41 PM 1:13:50UTC
aws_init_setup 6:31:51 PM 6:34:07 PM 0:02:16UTC Create nodelist.txt file
aws_passwordless_setup 6:34:08 PM 6:34:10 PM 0:00:02UTC 64 nodes
aws_nsd_server_setup - AZ1 6:34:11 PM 7:09:57 PM 0:35:46UTC
Create, 40 * 10 GB EBS volumes, attach (5 per
instance)
aws_nsd_server_setup - AZ2 6:34:23 PM 7:10:17 PM 0:35:54UTC
Create, 40 * 10 GB EBS volumes, attach (5 per
instance)
aws_cluster_setup 7:09:58 PM 7:20:13 PM 0:10:15UTC sleeps for 100s twice
aws_add_compute_nodes 7:20:13 PM 7:26:31 PM 0:06:18UTC
aws_filesystem_setup 7:26:31 PM 7:29:20 PM 0:02:49UTC
aws_mount_setup 7:29:24 PM 7:29:54 PM 0:00:30UTC
aws_zimon_setup 7:29:54 PM 7:30:28 PM 0:00:34UTC
aws_tunning_aids_setup 7:30:28 PM 7:41:36 PM 0:11:08UTC Scope of improvement
aws_verification_setup 7:41:36 PM 7:45:41 PM 0:04:05UTC
Stack name Start Time End Time Execution Time
VPC Stack 11:19:09 AM 11:22:04 AM 0:02:55UTC -7
Bastion Node Stack 11:22:19 AM 11:27:28 AM 0:05:09UTC -7
Cluster Stack 11:27:41 AM 12:46:29 PM 1:18:48UTC -7
Total Create Time 11:19:09 AM 12:46:29 PM 1:27:20
64 nodes –
80 EBS volumes
deployed in 87 minutes

AWS EC2 Instance View of Spectrum Scale Cluster

Demonstration use case: Scaling in the Cloud

Demonstration use case: Cloudburst

Hybrid Cloud Workflows – Bursting to the Cloud:
Data Agility and Collaboration with IBM Spectrum Scale
IBM Cloud
Connect via VPN over WAN
Available
2. Data Mobility via IBM
Spectrum Scale
Advanced File
Management (tech
preview)1. On-Premises Private Cloud
Using:
• IBM Cloud Private
• IBM Cloud Automation
Manager for multicloud self
service environment
• IBM Spectrum Scale
4. Archive to S3 within
AWS
3. Automated deployment
using IBM Cloud
Automation Manager
leveraging AWS EC2
instance and EBS
volumes. Deployed in 3-
node cluster.
Available
5. Deployed leveraging
BareMetal servers and
block storage. Deployed
in 2-node cluster.
6. Archive to IBM COS

On-Premise Private Cloud
IBM cloud
1
2
AFM home
AFM Cache
AFM Cache
Spectrum Scale AFMSpectrum Scale AFM
1. On-Premises Private Cloud Using:
 IBM Spectrum Scale
 IBM Cloud Private
 IBM Cloud Automation Manager for
multicloud self service environment
3
4
5
2. IBM Spectrum Scale automated
deployment using IBM Cloud
Automation Manager leveraging AWS
EC2 instance and EBS volumes. Data
mobility via IBM Spectrum scale
Active File Management for
collaboration
3. Backup/Archive to S3 within AWS
4. Deployed using IBM Bare Metal
servers and block storage. Data
mobility via IBM Spectrum scale
Active File Management for Data
analytics using IBM Cloud Private for
Data and Watson analytics.
5. Backup/Archive to IBM COS
Hybrid Cloud Workflows using IBM Spectrum Scale AFM

Transparent Cloud Tiering TCT Is Used Across IBM Storage
Cloud
Tiering
DS8000
Policy
DFSMS
Cloud Storage
TS7700
Cloud
Tiering
Cloud
Tiering
Spectrum Scale provides
policy driven data movement to
from the Cloud using TCT
• Managed data placement or
migration of cold data

Spectrum Scale Transparent Cloud Tiering (TCT)
26
Swift/S3
NFS
SMB
Hadoop
Docker
Kubernetes
POSIX
Transparent
Data
Metadata is managed by Spectrum Scale Cloud appears as external storage pool
Auto-tiering & migration
Store as Buckets
Ensure data integrity
Transparent
Cloud Tiering
IBM Systems Technical University © Copyright IBM Corporation 2019

Protocol mapping vs. Transparent Cloud Tiering
— Protocol Mapping
— Pros
• Simple Architecture
• No cache storage
— Cons
• All writes&reads have
to be mapped
• No cache for high-
performance read/write
• Often vendor mix
required
NFS/SMB
Protocol
Mapper
NFS/SMB
Protocol Node
TCT
NFS/SMB
Clients
NSD Server Cache
Meta
Data
Transparent Cloud Tiering
Pros
 High performance write
operations
 High performance read
for cached data
 Public cloud-ready
Cons
 More complex
architecture
 Cache storage required
 Increased response time
for non-cached data
…
Object Storage

Spectrum Scale TCT Value
— Extend Spectrum Scale to private or public cloud
• Open object store interfaces drive new Data
Economics
• Public Cloud:
o IBM Cloud Object Storage
o Amazon S3
o Microsoft Azure
• Private Cloud or on-premises:
o IBM Cloud Object Storage
o OpenStack Swift
— Transparent to end-users using Spectrum Scale
— Enhancing Object Storage choice
• Spectrum Scale as High-Performance, unified file&object
• IBM Cloud Object Storage as cost-optimized, scalable
object storage
Encrypted Ingegrity
Check

Recommended Environment for Spectrum Scale TCT
29
— Requires Spectrum Scale Advanced Edition or Data
Management Edition
— Prerequisite expectations / best practices:
 Appropriate median file sizes (>1MB, the larger, the better)
 Stable data for long-term retention
 Files unlikely to be updated or deleted (reads are ok)
 Sufficient Object Storage capacity
 Appropriate network connectivity to cloud storage
IBM Systems Technical University © Copyright IBM Corporation 2019

Cloud Object
Storage Provider 2
Cloud Service Node
Class
Cloud Service Node Class
Cloud Object Storage
Provider 1
Cloud Account
Node3 Node 5 Node 7 Node 8 Node 9
CES Protocol nodes
NSD Storage nodes
File System
Spectrum Scale
Cluster
File SetFile System
Node1
Cloud
Service
Node
Cloud
Service
Node
Cloud
Service
Node
Cloud
Service
Node
Node 6Node 4Node 2
Container
Cloud
Client
Container
Cloud
Service
Node
Cloud
Service
Node
Cloud Account
Container
Cloud
Client
Cloud
Client
Cloud Account
Container
Node 1
Remote
Mounted
Cloud
Client
Spectrum Scale
Cluster
Transparent Cloud Tiering Example

IBM Spectrum Scale Cloud Data Sharing
Swift/S3
Swift/S3
NFS
SMB
Hadoop
Docker
Kubernetes
POSIX
Traditional
Applications
Native Cloud
Applications

IBM Spectrum Scale Cloud Data Sharing details
— IBM Cloud Object Storage serves as
• Central data repository
• Data distribution point
• Data is accessible for native cloud applications through IBM COS S3 API
— Sharing can occur between object storage and many Spectrum Scale
Clusters
— Shared Data may originate in either the cloud or Spectrum Scale
— Data may be moved or copied between Spectrum Scale clusters and object
storage
— Efficient sharing mode: Special stubbed move available, so metdata only is
stored on Spectrum Scale with data imported transparently when a file is
requested
— One or more Spectrum Scale clusters can push to the cloud
— Spectrum Scale can pull data on demand

• Can now do Transparent Cloud Tiering to Microsoft Azure
– With the same features as S3 support
• Direct client high performance recalls
– Allows clients to issue recalls directly without having to go through the TCT
server nodes
• Asynchronous import support on COS
– COS Event-driven import of data from object storage
Spectrum Scale TCT capabilities in the latest Spectrum Scale 5.0.3

Cloud Object Storage
Provider 2
Cloud Service Node Class Cloud Service Node Class
Cloud Object
Storage Provider
1
Cloud Account
Node3 Node 7 Node 8 Node 9
CES Protocol nodes
NSD Storage nodes Spectrum Scale
Cluster
File SetFile System
Node1
Cloud
Service
Node
Cloud
Service
Node
Node 6Node 2
Cloud
Client
Container
Cloud
Service
Node
Cloud
Service
Node
Cloud Account
Container
Cloud
Client
Cloud
Client
Direct Client Transparent Recall Overview
1
2
3
4
Gateway recalls
1. LWE recall
received
2. Client forwards
to cloud service
node
3. Object read
4. Transfer from
cloud service
node to client
node
Direct recalls
1. LWE recall
received
2. Object read
1
2
Direct Recall Key Benefits
• Efficient
• Performance scales with
cluster size

— An AWS solution architect can to deploy a global namespace,
with flexible capacity to performance ratio in less than an
hour, without any knowledge of Spectrum Scale.
— An AWS solution administrator can dynamically start, stop,
add, and remove compute and data resources associated with
my global namespace, with limited knowledge of Spectrum
Scale.
— An AWS solution administrator, within an hour, can do either
disruptive or non-disruptive (in terms of the cluster, e.g.
rolling) upgrades of the Operating System and Spectrum
Software on my cluster, with limited knowledge of Spectrum
Scale, while still keeping existing applications and data in
place.
Summary – Value of Spectrum Scale on Amazon Web Services

Thank you!
Tony Pearson
tpearson@us.ibm.com
+1-520-799-4309
Please complete the Session
Evaluation!

Spectrum Scale User Group
— The Spectrum Scale User Group is free to join and open to all using, interested in using or
integrating Spectrum Scale. Check out the links below for upcoming meetings.
— In addition to the User Group hosting their own meetings, IBM will host Spectrum Scale
User Group meetings at most IBM Systems Technical Universities in 2019.
— Join the User Group activities. Join the mailing list. Meet peers. Get access to experts
from partners and IBM. Check out the Presentations link, free download of excellent
material.
— Web page: http://www.spectrumscale.org/
— Presentations: http://www.spectrumscale.org/presentations/
— Mailing list: http://www.spectrumscale.org/join/
Contact: http://www.spectrumscale.org/committee/
YouTube channel for Spectrum Scale User Group:
https://www.youtube.com/watch?v=iX440e__VHE&list=PLrdepxEIEyCp1TqZ2z3WfGOgqO9oY01xY
http://www.spectrumscaleug.org/category/posts-meetings/

Join or browse the Spectrum Scale UG mailing list!
Example of
User Group
content
https://www.spectrumscale.org/pipermail/gpfsug-discuss/
URL to gpfsug-
Archives

• Enhanced IBM Knowledge Center with all details for Spectrum Scale on Amazon
Web Services
• https://www.ibm.com/support/knowledgecenter/en/STXKQY_AWS_SHR/com.ibm.spectrum.scale.aws.v5r01.doc/bl1cld_aws_kclanding.htm
• https://www.ibm.com/support/knowledgecenter/STXKQY_AWS_SHR/com.ibm.spectrum.scale.aws.v5r01.doc/pdf/scale_aws.pdf
• YouTube: Deploying IBM Spectrum Scale Quick Start on AWS: https://www.youtube.com/watch?v=kc8JPAEzkPE
• Enabling Hybrid Cloud Storage using Transparent Cloud Tiering Redpaper
published May 2018
• http://www.redbooks.ibm.com/abstracts/redp5411.html?Open
• Spectrum Scale Cloud Blogs on IBM Developerworks
• https://developer.ibm.com/storage/2018/10/02/hpc-storage-aws-ibm-spectrum-scale/
• https://developer.ibm.com/storage/search/?q=spectrum+scale+cloud
39
IBM Spectrum Scale in the Cloud: more information

Special Thanks
I would like to thank the following colleagues
who contributed charts, insights, and review
comments for these presentation materials
— Chris Maestas

About the Speaker
41
Tony Pearson is a Master Inventor, Senior IT Management Consultant, and Content Manager for the
IBM Systems Technical University events. Tony joined IBM Corporation in 1986 in Tucson, Arizona,
USA, and has lived there ever since. Tony presents briefings on storage topics covering the entire IBM
Storage product line, IBM Spectrum Storage software products, and topics related to Cloud Computing,
Analytics and Cognitive Solutions. He interacts with clients, speaks at conferences and events, and
leads client workshops to help clients with strategic planning for IBM’s integrated set of storage
management software, hardware, and virtualization solutions.
Tony writes the “Inside System Storage” blog, which is read by thousands of clients, IBM sales reps and
IBM Business Partners every week. This blog was rated one of the top 10 blogs for the IT storage
industry by “Networking World” magazine, and #1 most read IBM blog on IBM’s developerWorks. The
blog has been published in series of books, Inside System Storage: Volume I through V.
Over the past years, Tony has worked in development, marketing and consulting for various IBM
Systems hardware and software products. Tony has a Bachelor of Science degree in Software
Engineering, and a Master of Science degree in Electrical Engineering, both from the University of
Arizona. Tony is an inventor or co-inventor of 19 patents in the field of IBM Systems and electronic data
storage.
9000 S. Rita Road
Bldg 9032 Floor 1
Tucson, AZ 85744
+1 520-799-4309 (Office)
tpearson@us.ibm.com
Tony Pearson
Master Inventor
Senior Management
Consultant, IBM Systems
La Services
IBM Storage
IBM Systems
Technical University

My Social Media Presence
42
Blog*:
ibm.co/Pearson
LinkedIn:
https://www.linkedin.com/in/az990tony
Books:
www.lulu.com/spotlight/990_tony
IBM Expert Network on Slideshare:
www.slideshare.net/az990tony
Twitter:
twitter.com/az990tony
Facebook:
www.facebook.com/tony.pearson.16121
Instagram:
www.instagram.com/az990tony/
Email:
tpearson@us.ibm.com
* Not a typo. This is short URL for https://www.ibm.com/developerworks/mydeveloperworks/blogs/InsideSystemStorage/
IBM Systems
Technical University

Notices and disclaimers
— © 2019 International Business Machines Corporation. No part of
this document may be reproduced or transmitted in any form
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disclosure restricted by GSA ADP Schedule Contract with IBM.
— Information in these presentations (including information
relating to products that have not yet been announced by IBM)
has been reviewed for accuracy as of the date of
initial publication and could include unintentional technical or
typographical errors. IBM shall have no responsibility to update
this information. This document is distributed “as is” without
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information, including but not limited to, loss of data, business
interruption, loss of profit or loss of opportunity.
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In some cases, a product may not be new and may have been
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— Performance data contained herein was generally obtained in a
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— customers have used IBM products and the results they may have
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