Presentation of the future of cloud storage at Scality SDS Day in London (The Shard) in September 2017. Topics covered include private/public cloud and software-defined storage.

1. Tuesday, January 2, 2018
Chris M Evans
Data Mobility in a
Multi-Cloud World
SDS Day London 2017
Chris Evans
Consultant/Blogger Architecting IT

2. Focus on Data
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3. Data creation is more dispersed than ever before
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• 4.9 billion mobile users (3.5 billion
actively using the Internet)*
• 1.9GB average monthly data used by
smartphones*
• 3.7 billion Internet users*
• Global e-commerce market $1.915
trillion in 2016 ($1,189 per user)*
• 225 billion emails sent per day in
2017 **
* Digital in 2017: Global Overview report
** Radicati Group Email statistics report 2015-2019)

4. • Mobile devices & Tablets
• Websites & Ecommerce – purchasing
behaviour, website usage
• IoT – Sensors & monitoring devices
• Healthcare (scanning, X-ray)
• Security – border control, facial
recognition, biometrics
• Video/Audio – call centres, Social Media
Data Sources
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5. The Walled Garden of the data
centre has gone
• Multiple data centres
• Public cloud(s)
• Mobile devices
• At the “edge” (IoT)
We are creating many data silos
Data Silos
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6. Scality Confidential 5
Goodbye Storage
Administrator
Hello Data
Manager

7. The Death of Traditional Storage
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8. Perennial
Challenges
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9. • Public cloud offers cheap compute but…
 Hard to get data in/out of the public cloud at speed
 Storage in the cloud has issues
• Businesses want to keep all their data
 No clear view on what future value of data means
 Keep everything forever as a fall-back position
• Businesses want analytics
 Generate competitive advantage
New and old problems
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10. • Server virtualisation made applications more
mobile
 VM and data move as a unit
 vMotion and 3rd party tools to move data into public cloud
• Containers separate data and application
 Rapid application deployment in any location
 Data injected into the container or accessed via persistent storage
• Cloud-Native app deployment
 Cattle versus pets
Applications are more mobile
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11. • Transformation to service-based private cloud
• Adoption of public cloud services (AWS/Azure)
 MSPs and bespoke services also offered – e.g. data in Switzerland
• Maturity Stage 1 – use of one cloud
 Learning how to consume and manage services
• Maturity Stage 2 – use of multiple clouds
 Use of cloud providers for specific functionality (e.g. Google for analytics)
• Maturity Stage 3 – brokerage of cloud resources
 Data and services actively balanced across multiple providers
The world is moving multi-cloud
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12. • Block
 Good for OLTP and transactional workloads, low latency but not high
scalability
 Performance benefiting from the use of flash and NVMe
 No metadata or platform intelligence
• File
 Good for unstructured data and some performance workloads like HPC
 Relatively scalable, with some metadata and platform intelligence
• Object
 Very high scalability, good for capacity and non-latency sensitive workloads
 Rich metadata, good for immutable data types and large objects
 More difficult to interface with (Typically API)
Storage is moving multi-protocol
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13. • Where is my data?
 Can I identify all of my data sources/resources?
• Data Protection
 Backup/restore, business continuity
• Security
 Blurred DC boundary opens risk of data breaches
 Equifax (143m), Ebay (145m), Yahoo (500m)
• Governance
 GDPR & Data Protection Directive
 Industry specific rules (finance, healthcare)
Existing data management rules still apply
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14. • Cloud vendors provide no native interfaces to the
underlying storage offerings
 Can’t run AWS EFS across on/offsite for example
 Can’t replicate S3 or block storage outside of AWS
• Cloud vendors offer disparate services
 AWS S3 and Azure blob storage not compatible
 S3 is de-facto purely for AWS dominance – not a standard
• Data Mobility still needs standard features
 QoS, data protection (backup/restore)
• Mass migration of data between clouds is expensive
and time consuming
But…
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15. Perfect World
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16. • Single View of Data
 “Global namespace”
 Single security model
• Hardware independence
 Run on bespoke (vendor), commodity or in the cloud
• Consistency
 Real-time updates across all locations and views
• Performance
 Little or no impact from data latency and transfer
Is SDS the answer to global data visibility?
Storage (or Data) Nirvana
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17. Businesses want data
mobility, but real cloud-
bursting is still a myth
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18. Rethinking SDS
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19. My vendor is ripping me off, I
can save on hardware and buy
cheap, commodity servers and
storage
The old view of SDS
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20. • Hardware Abstraction
 Separate functionality from the physical media
• Service consistency
 Provide the same features, regardless of the deployment model
 Same features, regardless of on-premises or public cloud
• Service integration
 Use native platform services (like replication, snapshots)
Most important – single place for metadata
The new view of SDS
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21. Typically, seen as a way to save on hardware costs, however
also allows:
• Deployment across multiple form factors and architectures
 Linux/Windows, x86, ARM
• Ongoing hardware optimisation
 Replace/refresh with latest components
 Use current technology without having to wait for vendor rollout
SDS - Hardware Abstraction
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22. • Deliver a consistent set of features, regardless
of hardware platform
• Extend features to the public cloud
• Same operational look and feel
• Deliver a consistent performance experience
SDS – Service Consistency
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23. • Use native features of the software platform,
irrespective of deployment point
• Exploit efficiency of native data services
 Replication, snapshots
 Deduplication, compression
• Standardise on APIs and Interfaces
 NFS, S3
SDS – Service Integration
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24. • Caching Solutions
 NAS Caching, VM Caching, DB Caching, Storage Gateways
• Global/Scale Out Data
 Global NAS, Scale-out block, scale-out NAS
• Data Protection
 Replication, VM Backup, CDP, Database Replication
• Data Migration
 App Ingest
• Data Consolidation
 Copy Data Management, Secondary Storage
Deployment Models
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25. • Good for getting a single workload into
public cloud
• Don’t always provide ”write anywhere”
capability
• Issues with consistency in multi-site
configurations
• Metadata doesn’t always follow the data
Example – Avere Systems
Caching Solutions
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26. • Solutions offered for object, file and block
• Block solutions have issues with data integrity
of shared LUNs/volumes
• Metadata consistency and data sync is a
complex problem
• File solutions hard to develop
Examples, Hedvig, Portworx, Zenko, Elastifile
Global Scale-out
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27. • Use data protection features to deliver data
mobility
• Vendors offer hardware/software integration
using VSAs and cloud appliances
• Data protection is point-in-time, not real-time
copying and synchronisation of data
 Usually uni-directional, usually one copy read only
 Snapshot replication is based on PiT copying
Data Protection
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28. • Ingest services like AWS DMS are good for one-way
migrations
 Lots of manual work to make the import work
 Data synchronicity lost during migration (no easy way to catch up
“deltas”)
• Consolidation services like secondary storage also lose
consistency
 Typically based on PiT VM image copies, so crash consistent
 Some solutions providing app consistency
Migration & Consolidation
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29. Data Mobility solutions are
like opinions – Everyone has
one…
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30. Conclusion
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31. • True data mobility requires data to appear to be
available “everywhere, anytime”
• Global data availability is hard due to latency,
throughput issues
• SDS points the way to implementing true data mobility
by removing hardware dependencies and supporting
cloud
• Metadata is key – must be portable and distributed
• Physical sync of data is required, but not essential
Conclusions
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