Increasing your predictability and decreasing your cost with AWS - Simone Brunozzi - AWS Summit 2012 Australia

AWS Summit 2012 | Sydney Increasing your predictability and decreasing your cost with AWS by Simone Brunozzi Technology Evangelist, APAC Twitter: @simon3:45pm

Today’s Agenda Use only what you need Reserved Pricing Analysis Architect for Spot Instances Leverage Application services Implement caching© 2012 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified or distributed in whole or in part without the express consent of Amazon.com, Inc.

Multiple dimensions of optimizations Cost Performance Response time Time to market High-availability Scalability Security Manageability …….

Optimizing for Cost… #1 Use only what you need (use Auto Scaling Service, modify–db)

Turn off what you don’t need (automatically)

25% SavingsOptimize by the time of day

Auto scaling : Types of ScalingScaling by Schedule • Use Scheduled Actions in Auto Scaling Service • Date • Time • Min and Max of Auto Scaling Group Size • You can create up to 125 actions, scheduled up to 31 days into the future, for each of your auto scaling groups. This gives you the ability to scale up to four times a day for a month.Scaling by Policy • Scaling up Policy - Double the group size • Scaling down Policy - Decrement by 1

www.MyWebSite.com Amazon Route 53 (DNS) media.MyWebSite.comElastic LoadBalancer Amazon Auto Scaling group : Web CloudFront Amazon EC2 Auto Scaling group : App Tier Amazon RDS Amazon Amazon S3 Availability Zone #1 RDS Availability Zone #2

50% SavingsOptimize during a year

75% SavingsOptimize during a month

Optimize by using “Reminder scripts”Disassociate your unused EIPsDelete unassociated EBS volumesDelete older EBS snapshotsLeverage S3 Object expiration

Tip – Instance Optimizer Free Memory Free CPU PUT 2 weeks Free HDD At 1-min intervals Alarm Amazon CloudWatchEC2 Instance Custom Metrics

Tip – Instance Optimizer Free Memory Free CPU PUT 2 weeks Free HDD At 1-min intervals Alarm Amazon CloudWatchEC2 Instance Custom Metrics “You could save a bunch of money by switching to a smaller instance, Click on CloudFormation Script to save”

Optimize by choosing the Right Instance TypeChoose the EC2 instance type that best matches the resourcesrequired by the application • Start with memory requirements and architecture type (32bit or 64-bit) • Then choose the closest number of virtual cores requiredScaling across AZs • Smaller sizes give more granularity for deploying to multiple AZs

Optimizing for Cost… #1 Use only what you need (use Auto Scaling Service, modify–db)

Optimizing for Cost… #1 Use only what you need (use Auto Scaling Service, modify–db) #2 Invest time in Reserved Pricing analysis (EC2, RDS)

Your Best Option: Reserved + On-Demand

Save more when you reserve On-demand Reserved 1-year and 3-year termsInstances Instances• Pay as you • One time Heavy Medium Light go low upfront Utilization RI Utilization RI Utilization RI fee + Pay as you go• Starts from $0.02/ • $23 for 1 Hour year term and $0.01/ Hour

m2.xlarge running Linux in US-East Region over 3 Year period Break-even pointUtilization Sweet Spot Feature Savings over On-Demand<10% On-Demand No Upfront Commitment10% - 40% Light Utilization RI Ideal for Disaster Recovery Up to 56% (3-Year)40% - 75% Medium Utilization RI Standard Reserved Capacity Up to 66% (3-Year)>75% Heavy Utilization RI Lowest Total Cost Up to 71% (3-Year) Ideal for Baseline Servers

RecommendationsSteady State Usage Pattern • For 100% utilization • If you plan on running for at least 6 months, invest in RI for 1-year term • If you plan on running for at least 8.7 months, invest in RI for 3-year termSpiky Predictable Usage Pattern • Baseline • 3-Year Heavy RI (for maximum savings over on-demand) • 1-Year Light RI (for lowest upfront commitment) + savings over on-demand • Peak: On-DemandUncertain and unpredictable Usage Pattern • Baseline: 3-Year Heavy RIs • Median: 1-Year or 3-Year Light RIs • Peak: On-Demand

Example: Simple 3-Tier Web Application Description Option 1 Option 2 Option 3 Option 4 2 Web servers 2 On-Demand 2 On-Demand 1 On-Demand and 1 On-Demand and 1 Reserved Medium 1 Reserved Light Utilization Utilization 2 App servers 2 On-Demand 2 On-Demand 1 On-Demand and 1 On-Demand and 1 Reserved Medium 1 Reserved Light Utilization Utilization2 Database servers 2 On-Demand 2 Reserved 2 Reserved Medium 2 Reserved Heavy Utilization Medium Utilization Utilization

Example: Simple 3-Tier Web Application Savings Option 1 Option 2 Option 3 Option 4 Calculator Calculator Calculator CalculatorMonthly Cost $702.72 $374.78 $256.20 $238.63One-Time Cost 1 Year Term - $1280.00 $1600.00 $1698.00 3 Year Term - $2000.00 $2500.00 $2612..60Total Cost 1 Year Term (x12) $8432.64 $5777.36 $4674.40 $4561.56 3 Year Term (x36) $25297.92 $15492.08 $11723.20 $11203.28Savings 1 Year Term n/a 32% 44% 45%(Over Option 1) 3 Year Term n/a 39% 54% 54%

Optimizing for Cost… #1 Use only what you need (use Auto Scaling Service, modify–db) #2 Invest time in Reserved Pricing analysis (EC2, RDS) #3 Architect for Spot Instances (bidding strategies)

Optimize by using Spot InstancesOn-demand Reserved SpotInstances Instances Instances• Pay as you • One time • Requested go low upfront Bid Price and fee + Pay as Pay as you you go go• Starts • $23 for 1 • $0.005/ from $0.02/ year term Hour as of Hour and $0.01/ today at 9

Optimize by using Spot InstancesOn-demand Reserved SpotInstances Instances Instances• Pay as you • One time • Requested go low upfront Bid Price and fee + Pay as Pay as you you go go• Starts • $23 for 1 • $0.005/ from $0.02/ year term Hour as of Hour and $0.01/ today at 9 1-year and 3-year Heavy Medium Light Utilization Utilization Utilization

Spot Use casesUse Case Types of ApplicationsBatch Processing Generic background processing (scale out computing)Hadoop Hadoop/MapReduce processing type jobs (e.g. Search, Big Data, etc.)Scientific Computing Scientific trials/simulations/analysis in chemistry, physics, and biologyVideo and Image Processing/ Transform videos into specific formatsRenderingTesting Provide testing of software, web sites, etcWeb/Data Crawling Analyzing data and processing itFinancial Hedgefund analytics, energy trading, etcHPC Utilize HPC servers to do embarrassingly parallel jobsCheap Compute Backend servers for Facebook games

Typical Spot Bidding Strategies 1. Bid near the Reserved Hourly Price 2. Bid above the Spot Price History 3. Bid near On- Demand Price 4. Bid above the On- Demand Price

Managing Interruption

Architecting for Spot Instances : Best PracticesManage interruption• Split up your work into small increments• Checkpointing: Save your work frequently and periodicallyTest Your ApplicationTrack when Spot Instances Start and StopSpot Requests• Use Persistent Requests for continuous tasks• Choose maximum price for your requests

Optimizing Video Transcoding Workloads Free Offering • Optimize for reducing cost • Acceptable Delay LimitsImplementation • Set Persistent Requests • Use on-demand Instances, if delay Maximum Bid Price < On-demand Rate Get your set reduced price for your workload

Optimizing Video Transcoding Workloads Free Offering Premium Offering • Optimize for reducing cost  Optimized for Faster response times • Acceptable Delay Limits  No DelaysImplementation Implementation • Set Persistent Requests  Invest in RIs • Use on-demand Instances, if delay  Use on-demand for Elasticity Maximum Bid Price < On-demand Rate Maximum Bid Price Get your set reduced price for your >= On-demand Rate workload Get Instant Capacity for higher price

Made for each other: MapReduce + Spot Use Case: Web crawling/Search using Hadoop type clusters. Use Reserved Instances for their DB workloads and Spot instances for their indexing clusters. Launch 100’s of instances. Bidding Strategy: Bid a little above the On- Demand price to prevent interruption. Interruption Strategy: Restart the cluster if interrupted 66% Savings over On-Demand

Optimizing for Cost… #1 Use only what you need (use Auto Scaling Service, modify–db) #2 Invest time in Reserved Pricing analysis (EC2, RDS) #3 Architect for Spot Instances (bidding strategies)

Optimizing for Cost… #1 Use only what you need (use Auto Scaling Service, modify–db) #2 Invest time in Reserved Pricing analysis (EC2, RDS) #3 Architect for Spot Instances (bidding strategies) #4 Leverage Application Services (SNS, SQS, SWF, SES)

Optimize by converting ancillary instances into services Monitoring: CloudWatch Notiﬁcations: SNS Queuing: SQS SendMail: SES Load Balancing: ELB Workﬂow: SWF Search: CloudSearch

Elastic Load BalancingSoftware LB on EC2 Elastic Load BalancingPros Pros Application-tier load balancer Elastic and Fault-tolerant Auto scaling Monitoring includedCons SPOF Cons Elasticity has to be implemented manually For Internet-facing traffic only Not as cost-effective

$0.025 per hour DNS Elastic Load Web Servers Balancer Availability Zone vs.$0.08 per hour(small instance) EC2 instance DNS + software LB Web Servers Availability Zone

Application ServicesSoftware on EC2 SNS, SQS, SES, SWFPros Pros Custom features Pay as you go ScalabilityCons Availability Requires an instance High performance SPOF Limited to one AZ DIY administration

Consumers Producer SQS queue $0.01 per10,000 Requests ($0.000001 per Request) vs. $0.08 per hour (small instance) Producer EC2 instance Consumers + software queue

Optimizing for Cost… #1 Use only what you need (use Auto Scaling Service, modify–db) #2 Invest time in Reserved Pricing analysis (EC2, RDS) #3 Architect for Spot Instances (bidding strategies) #4 Leverage Application Services (SNS, SQS, SWF, SES)

Optimizing for Cost… #1 Use only what you need (use Auto Scaling Service, modify–db) #2 Invest time in Reserved Pricing analysis (EC2, RDS) #3 Architect for Spot Instances (bidding strategies) #4 Leverage Application Services (SNS, SQS, SWF, SES) #5 Implement Caching (ElastiCache, CloudFront)

caching Optimize for performance and costby page caching and edge-caching static content

Recap#1 Use only what you need (use Auto Scaling Service, modify–db) #2 Invest time in Reserved Pricing analysis (EC2, RDS) #3 Architect for Spot Instances (bidding strategies) #4 Leverage Application Services (SNS, SQS, SWF, SES) #5 Implement Caching (ElastiCache, CloudFront)

Thank You!Increasing your predictability and decreasing your cost with AWS by Simone Brunozzi Technology Evangelist, APAC Twitter: @simon

Increasing your predictability and decreasing your cost with AWS - Simone Brunozzi - AWS Summit 2012 Australia

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Increasing your predictability and decreasing your cost with AWS - Simone Brunozzi - AWS Summit 2012 Australia Presentation Transcript