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Building on AWS:
Optimizing & Delivering
Adrian De Luca
Head of Solution Architecture, APAC, AWS
The Foundation
On-Boarding &
Provisioning
Data
Partitioning
Identity
Deployment
Agility
CI/CD Distributed
Making it Sing
Billing Metering
Granular
Scale
Cost
Optimized
Policy Driven
Tenant
Experience
Thinking Beyond Agility & Delivery
Real-Time Tenant Experience Optimization
Idle Tenants
Active Tenants
Busy Tenants
Tenant Id Last Accessed
Tenant-3 1/1/2015 12:01:24
Tenant-1 1/1/2015 11:51:01
Tenant-5 1/1/2015 10:41:53
Building A Tenant-Optimized Cache
Tenant 1 Tenant 2 Tenant 3
Tenant Cache Status
Cache
Manager
1
Data Access
2
3 5
7
6
4
Sizing Your Cache
Tenant Id Weight Last Accessed
Tenant-4 9 1/1/2016 09:03:01
Tenant-2 6 1/1/2016 09:41:53
Tenant-1 1 1/1/2016 08:39:24
Tenant-9 6 1/1/2016 08:25:51
Tenant-1 4 1/1/2016 08:22:43
Tenant-1 9 1/1/2016 07:19:11
Top Tenant Cache
How many tenants should be
cached?
Cache Size # Busy Tenants
Tenant Optimization Considerations
• It’s all about making the “right” tenants successful
• Make optimization a real-time, dynamic mechanism
• Focus on improving experience while limiting the footprint
• Find the balance between complexity and value
• Expect to continually tune your “most active tenant”
algorithms
• Surface optimization metrics on your operational views
Data Partitioning and Storage Optimization
• Tenants come all shapes and sizes
• The data profile for each tenant can vary
significantly
• Treating all tenants the same can impact scale,
performance, and cost
Creating a Compute Bottleneck
Storage
Instance
CustomerID AccountID Name StartDate
8482994 429391818 Jake Young 12-02-2014
9782838 782839234 Mary Toms 11-14-2011
3948299 919499919 Lisa Lewis 03-01-2011
Tenant1-Customer
CustomerID AccountID Name StartDate
8482994 429391818 Jake Young 12-02-2014
9782838 782839234 Mary Toms 11-14-2011
3948299 919499919 Lisa Lewis 03-01-2011
Tenant2-Customer
Tenants
• CPU
• Memory
• IO
Sharding a Shard
Tenant-1
Shard-1
Shard-2
Shard-3
ShardID AccountID Name
Shard-3 429391818 Jake Young
Shard-6 782839234 Mary Toms
Shard-1 919499919 Lisa Lewis
Shard-3 434452444 Bob Jones
Shard-5 845341445 Lisa Smith
Shard-2 525323564 Tom Wall
Shard-5 525555321 Eva Walters
Shard-1 134567643 Kim Williams
Shard-6 356273627 Tim Hawk
Tenant-2
Shard-5
Shard-6
A more intelligent, tenant aware partitioning scheme
Shard Analytics
Sharding with DynamoDB
Partition Key Attributes
TenantID
Tenant1
CustomerTable
{
ShardCount: 4,
ShardSize: [4, 9, 4, 5],
ShardIds: [“93”, “932”, “21”, “36”]
}
Partition Key Attributes
ShardID
93
CustomerID
492300009
Name
Bob Jones
ShardID
221
CustomerID
983019391
Name
Jane Thomas
ShardID
21
CustomerID
3492098u7
Name
Sally Smith
ShardID
932
CustomerID
115830489
Name
Randy Hanson
ShardID
93
CustomerID
819492229
Name
Wendy Watts
ShardID
36
CustomerID
480002194
Name
Henry Hanks
• Let shard count grow dynamically
• Continually evaluate shard size
Tenant Lookup Table
Customer Table
Sharding With RDS
TenantID Name StartDate
Tenant-1 Bob Smith 01-12-2012
Tenant-4 Sue Jones 09-01-2015
Shard-1
Instance
Shard-2
Instance
TenantID Name StartDate
Tenant-2 Lisa Louis 11-21-2014
Tenant-3 Tom Tucker 06-09-2012
Customer Table
Customer Table
TenantID ShardID
Tenant-1 Shard-1
Tenant-2 Shard-2
Tenant-3 Shard-2
Tenant-4 Shard-1
Tenant-Shard Mapping
Partitioning Optimization Considerations
• Tenant data is not going to be evenly distributed
• Uneven data distribution can artificially increase costs
• Each storage service may require a unique solution
• Distributing data will add complexity to your solution
• Sharding should be a dynamic, metrics driven process
• Sharding strategies are often domain specific
Using Tenant Policies for Optimization
Tenant 1 Tenant 2
API’s
Tenant
Policies
Services
Data Access
• Tenant policies can be applied at
all layers in your architecture
• Policies can be used to alter and
optimize tenant experience
• Policies can enable more
granular tiering
Tier-Driven Optimization
Data Access
Catalog
Service
Order
Service
Tax
Service
Tenant Policies
{
“TenantID”: “29304”,
“Plan”: “Gold”
},
{
“TenantID”: “91039”,
“Plan”: “Platinum”
}
DynamoDB RDS S3
API
Tier StorageLimit
API
SLA
Gold 500 GB 5MS
Platinum 2 TB 2MS
Workflow-Driven Optimization
Tenant 1
DynamoDB RDS S3
1. Get orders from yesterday
2. Get orders for last 30 days
3. Get all orders
Data Access
Tenant 2
DynamoDB RDS
Data Access
Tenant
Policies
1
2
3 1,2 3
Tenant Policy Considerations
• Think more granularly about tenant loads
• Provide centralized management of policies
• Context can change how a request is processed
• Align the resource profile with the application need
• Leverage the diversity of AWS services
• Policies create new opportunities for tiering and cost
optimization
SaaS Load Optimization
• Aligning resource consumption
with multi-tenant load profile
• Achieving “just enough”
infrastructure
• Minimizing costs
• What does idle look like?
• Think about cost per tenant
Picking the Right Services
Checkout
Taxation
Order = Unit of Scale
Shipping
Order Service
Checkout
Taxation
Order = Unit of Scale
Shipping
Order Service
Single Tenant Load Multi-Tenant Load
Checkout Service
Taxation Service
Shipping Service
Independent Services
Serverless SaaS with AWS Lambda
Order REST API
Order Service
Update Create
Delete Find
Ship Cancel
Update Create Delete Find Ship Cancel
REST API
• Load & cost distributed across REST calls
• Cleaner model for agile deployment
• Management and scale offloaded to AWS
• Gateway to throttle tenants
• Larger failure surface area
• Scaling is your responsibility
• More dependencies
REST API
Severless SaaS: Optimization + Isolation
Web Tier
App Tier
Web Tier
App Tier
Tenant 1
REST API
Tenant 2Tenant 1 Tenant 2
Serverless IsolationEC2 Isolation
• Cost
• Management
• Deployment
• Provisioning
Tradeoffs
Load Optimization Considerations
• Multi-tenant loads are more difficult to profile
• Load optimization relies on granular metrics
• Live on the edge, but never impact scale or experience
• Severless represents an opportunity to optimize both
load and cost
Monitoring & Management
• SaaS sets a higher bar for management & monitoring
• Views of both infrastructure and application health
• Ability to view health and activity with tenant context
• Instrumenting logs with application and tenant metrics
• Support for tenant policies for alerts/alarms
Management & Monitoring
S3
CloudWatch
AWS Config
CloudTrailTenantContext
Splunk
Sumologic
Kibana
• Create custom views that aggregate
and summarize cross-tenant activity
• Proactively identify cross-tenant issues
• Introduce cross tenant policies
Application Services
Catalog
Service
Order
Service
Ratings
Service
Tax
Service
Resource Metrics
Application Activity
Aggregating Usage & Health Analytics
Storage MetricsApp Service Metrics Compute Metrics
• Analyze tenant flows
• Assess consumption
metrics
Page Load Metrics User Clicks REST Calls
Metering Enables Tiering
Sign Up
Silver
$49 / month
Sign Up
Bronze
$29 / month
Sign Up
Gold
$99 / month
Features
Users
Billing
AWS Quick Start for SaaS
https://aws.amazon.com/quickstart/saas/identity-with-cognito/
In Summary
• Bring the best experience to those that need it
• Leverage tenet profiles to drive optimization
• Factor tenant data distribution into your partitioning
model
• Take advantage of AWS service diversity
• Metrics and monitoring essential to optimization
• Make cost part of your optimization strategy
THANK YOU

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Build on AWS: Optimizing and Scaling.

  • 1. Building on AWS: Optimizing & Delivering Adrian De Luca Head of Solution Architecture, APAC, AWS
  • 2. The Foundation On-Boarding & Provisioning Data Partitioning Identity Deployment Agility CI/CD Distributed Making it Sing Billing Metering Granular Scale Cost Optimized Policy Driven Tenant Experience Thinking Beyond Agility & Delivery
  • 3. Real-Time Tenant Experience Optimization Idle Tenants Active Tenants Busy Tenants
  • 4. Tenant Id Last Accessed Tenant-3 1/1/2015 12:01:24 Tenant-1 1/1/2015 11:51:01 Tenant-5 1/1/2015 10:41:53 Building A Tenant-Optimized Cache Tenant 1 Tenant 2 Tenant 3 Tenant Cache Status Cache Manager 1 Data Access 2 3 5 7 6 4
  • 5. Sizing Your Cache Tenant Id Weight Last Accessed Tenant-4 9 1/1/2016 09:03:01 Tenant-2 6 1/1/2016 09:41:53 Tenant-1 1 1/1/2016 08:39:24 Tenant-9 6 1/1/2016 08:25:51 Tenant-1 4 1/1/2016 08:22:43 Tenant-1 9 1/1/2016 07:19:11 Top Tenant Cache How many tenants should be cached? Cache Size # Busy Tenants
  • 6. Tenant Optimization Considerations • It’s all about making the “right” tenants successful • Make optimization a real-time, dynamic mechanism • Focus on improving experience while limiting the footprint • Find the balance between complexity and value • Expect to continually tune your “most active tenant” algorithms • Surface optimization metrics on your operational views
  • 7. Data Partitioning and Storage Optimization • Tenants come all shapes and sizes • The data profile for each tenant can vary significantly • Treating all tenants the same can impact scale, performance, and cost
  • 8. Creating a Compute Bottleneck Storage Instance CustomerID AccountID Name StartDate 8482994 429391818 Jake Young 12-02-2014 9782838 782839234 Mary Toms 11-14-2011 3948299 919499919 Lisa Lewis 03-01-2011 Tenant1-Customer CustomerID AccountID Name StartDate 8482994 429391818 Jake Young 12-02-2014 9782838 782839234 Mary Toms 11-14-2011 3948299 919499919 Lisa Lewis 03-01-2011 Tenant2-Customer Tenants • CPU • Memory • IO
  • 9. Sharding a Shard Tenant-1 Shard-1 Shard-2 Shard-3 ShardID AccountID Name Shard-3 429391818 Jake Young Shard-6 782839234 Mary Toms Shard-1 919499919 Lisa Lewis Shard-3 434452444 Bob Jones Shard-5 845341445 Lisa Smith Shard-2 525323564 Tom Wall Shard-5 525555321 Eva Walters Shard-1 134567643 Kim Williams Shard-6 356273627 Tim Hawk Tenant-2 Shard-5 Shard-6 A more intelligent, tenant aware partitioning scheme Shard Analytics
  • 10. Sharding with DynamoDB Partition Key Attributes TenantID Tenant1 CustomerTable { ShardCount: 4, ShardSize: [4, 9, 4, 5], ShardIds: [“93”, “932”, “21”, “36”] } Partition Key Attributes ShardID 93 CustomerID 492300009 Name Bob Jones ShardID 221 CustomerID 983019391 Name Jane Thomas ShardID 21 CustomerID 3492098u7 Name Sally Smith ShardID 932 CustomerID 115830489 Name Randy Hanson ShardID 93 CustomerID 819492229 Name Wendy Watts ShardID 36 CustomerID 480002194 Name Henry Hanks • Let shard count grow dynamically • Continually evaluate shard size Tenant Lookup Table Customer Table
  • 11. Sharding With RDS TenantID Name StartDate Tenant-1 Bob Smith 01-12-2012 Tenant-4 Sue Jones 09-01-2015 Shard-1 Instance Shard-2 Instance TenantID Name StartDate Tenant-2 Lisa Louis 11-21-2014 Tenant-3 Tom Tucker 06-09-2012 Customer Table Customer Table TenantID ShardID Tenant-1 Shard-1 Tenant-2 Shard-2 Tenant-3 Shard-2 Tenant-4 Shard-1 Tenant-Shard Mapping
  • 12. Partitioning Optimization Considerations • Tenant data is not going to be evenly distributed • Uneven data distribution can artificially increase costs • Each storage service may require a unique solution • Distributing data will add complexity to your solution • Sharding should be a dynamic, metrics driven process • Sharding strategies are often domain specific
  • 13. Using Tenant Policies for Optimization Tenant 1 Tenant 2 API’s Tenant Policies Services Data Access • Tenant policies can be applied at all layers in your architecture • Policies can be used to alter and optimize tenant experience • Policies can enable more granular tiering
  • 14. Tier-Driven Optimization Data Access Catalog Service Order Service Tax Service Tenant Policies { “TenantID”: “29304”, “Plan”: “Gold” }, { “TenantID”: “91039”, “Plan”: “Platinum” } DynamoDB RDS S3 API Tier StorageLimit API SLA Gold 500 GB 5MS Platinum 2 TB 2MS
  • 15. Workflow-Driven Optimization Tenant 1 DynamoDB RDS S3 1. Get orders from yesterday 2. Get orders for last 30 days 3. Get all orders Data Access Tenant 2 DynamoDB RDS Data Access Tenant Policies 1 2 3 1,2 3
  • 16. Tenant Policy Considerations • Think more granularly about tenant loads • Provide centralized management of policies • Context can change how a request is processed • Align the resource profile with the application need • Leverage the diversity of AWS services • Policies create new opportunities for tiering and cost optimization
  • 17. SaaS Load Optimization • Aligning resource consumption with multi-tenant load profile • Achieving “just enough” infrastructure • Minimizing costs • What does idle look like? • Think about cost per tenant
  • 18. Picking the Right Services Checkout Taxation Order = Unit of Scale Shipping Order Service Checkout Taxation Order = Unit of Scale Shipping Order Service Single Tenant Load Multi-Tenant Load Checkout Service Taxation Service Shipping Service Independent Services
  • 19. Serverless SaaS with AWS Lambda Order REST API Order Service Update Create Delete Find Ship Cancel Update Create Delete Find Ship Cancel REST API • Load & cost distributed across REST calls • Cleaner model for agile deployment • Management and scale offloaded to AWS • Gateway to throttle tenants • Larger failure surface area • Scaling is your responsibility • More dependencies
  • 20. REST API Severless SaaS: Optimization + Isolation Web Tier App Tier Web Tier App Tier Tenant 1 REST API Tenant 2Tenant 1 Tenant 2 Serverless IsolationEC2 Isolation • Cost • Management • Deployment • Provisioning Tradeoffs
  • 21. Load Optimization Considerations • Multi-tenant loads are more difficult to profile • Load optimization relies on granular metrics • Live on the edge, but never impact scale or experience • Severless represents an opportunity to optimize both load and cost
  • 22. Monitoring & Management • SaaS sets a higher bar for management & monitoring • Views of both infrastructure and application health • Ability to view health and activity with tenant context • Instrumenting logs with application and tenant metrics • Support for tenant policies for alerts/alarms
  • 23. Management & Monitoring S3 CloudWatch AWS Config CloudTrailTenantContext Splunk Sumologic Kibana • Create custom views that aggregate and summarize cross-tenant activity • Proactively identify cross-tenant issues • Introduce cross tenant policies Application Services Catalog Service Order Service Ratings Service Tax Service
  • 24. Resource Metrics Application Activity Aggregating Usage & Health Analytics Storage MetricsApp Service Metrics Compute Metrics • Analyze tenant flows • Assess consumption metrics Page Load Metrics User Clicks REST Calls
  • 25. Metering Enables Tiering Sign Up Silver $49 / month Sign Up Bronze $29 / month Sign Up Gold $99 / month Features Users
  • 27. AWS Quick Start for SaaS https://aws.amazon.com/quickstart/saas/identity-with-cognito/
  • 28. In Summary • Bring the best experience to those that need it • Leverage tenet profiles to drive optimization • Factor tenant data distribution into your partitioning model • Take advantage of AWS service diversity • Metrics and monitoring essential to optimization • Make cost part of your optimization strategy