This is a presentation that NuoDB CTO, Seth Proctor gave at a Breakfast Seminar Seth has 15+ years of experience in the research, design and implementation of scalable systems. His particular focus is on how to make technology scale and how to make users scale effectively with their systems.

1. Architecting for the Cloud
Seth Proctor, CTO
@technicallyseth

2. What’s unique about “cloud”?

3. Cloud architecture
On-demand
Scale-out for capacity & availability
Public infrastructure; dynamic provisioning
Flexible
Commodity
Hybrid (public & private)
Simple
Monitoring & management
Platform APIs and automation
Resilient

4. Why a different architecture?
Greater capacity
Cost-effectiveness
Higher availability and better failure-
handling
Lower latencies for global
deployment

5. Challenges
Distribution brings challenges
Lots of failures happen with frequency
More difficult to get a global view
Security & data lifecycle is harder
Everything else about “distributed computing”
Still, we can scale most layers
Load-balancers & name services at the top
Horizontally-scaled app servers
Caches & CDNs for content
Redundant disks and object stores

6. Scaling the database is the
real challenge

7. Migrating to “the cloud”
Modern architectures are commodity,
on-demand and virtualized
Enterprise applications need
availability and transactions
If cloud-scaling breaks global
consistency migration isn’t possible
7

8. Traditional database design
RDBMS architectures start at the disk
Vertical scale follows
Caching helps, but often breaks consistency
HA systems become very expensive
Schema & operation is hard to evolve
Hard to harness commodity
infrastructure
Not designed to scale-out

9. Common options
Replication
Active-passive or (gulp) multi-master
Replicated data but visible delays & conflict
Sharding
Split one database into many sub-sets
More capacity but hard to evolve and relate
Abandon consistency
Push correctness & conflict to the application
Simpler core architecture but painful for
applications and hard to reconcile failures

10. Consistency

11. Side-effects
Applications are tied to deployment
A key motivator for dev-ops
Complex for on-demand changes, failures
More, independent pieces
Harder to interpret failures
Complexity

12. Global operation
Many motivations
Disaster Recovery
Lower-latency for distributed users
Data access & storage residency rules
Trade-offs between latencies and
safety
Storage may be a separate concern
from interaction

13. The database is not the disk

14. Evolution of “operational”
Hybrid Tasks
Hybrid analytics for real-time insight
Document & SQL for flexibility
Graph views to ask hypothetical questions
and model and track lifecycle
These imply that …
Data-sets are larger
Access and cache patterns are variable
Latencies have more impact
14

15. Global requirements
Global Operation
Active in multiple locations & globally
consistent
Data Residence & Governance
Where is your data on-disk and in-memory
SLAs as Policy for Automation
Reactive or proactive
Resilient
Multiple Models

16. Cloud is the evolution from
“client-server” to “distributed”

17. Distributed Database Designs
17
Approach Shared Disk
Shared-Nothing/
Sharded
Synchronous
Replication
Durable
Distributed Cache
Key Idea Sharing a file system.
Independent databases
for disjoint subsets of
data.
Committing data
transactionally to multiple
locations before
returning.
Replicating data in
memory on-demand.
Topology
Example
Oracle RAC
DB2 Pure Scale
MySQL Cluster
and most NoSQL/NewSQL
solutions
Google F1

18. A Durable, Distributed Cache
Caching puts a database in-memory
Optimizations focus on memory, not disk
Caches are transient, on-demand and
hierarchical by nature
Distribution means independence
Equivalent peers that coordinate to provide a
single logical entity
Drives service resiliency
Durability provides safety
Decisions about replication, location and
resource allocation are operational
18

19. Peer to Peer Architecture
P
P P
S3Disk
, ...
P
P NuoDB Database Peer Process
Provisioned, Manageable Resources
Peer to Peer Communications
SQL
Client
Management
Client
SQL Front-End
SQL Optimizer
Transaction Handling
Object Caching
Object Coordination
Durability
P

20. NuoDB is designed for
Global operations
On-demand capacity
Continuous availability
Policy-driven deployment
Multi-tenancy
Multiple models

21. NuoDB is a single, logical service
with global consistency

22. Scaling YCSB

23. Scaling DBT-2
23

24. Summary
Look for distributed architectures
with on-demand capabilities
Layer & abstract to support evolution
and react gracefully to failures
Assume your needs will evolve; plan
with scale in mind

25. http://dev.nuodb.com

26. Questions?