Adrian WhiteOptimizing Your AW2 Applications and Usage to Reduce CostsSolutions Architect, AWSDavid HarrisonVP of Engineering, Freelancer.comGuest presenter:
Agenda• Objective– Review the spectrum of ways to save money on your AWS application• Tenet: Fit the cloud to your product and business model– Use Only What You Need (and pay only for what you use!)– Measure and Manage– Scale Opportunistically• Customer Case Study– Freelancer.com
Use Only What You NeedAnd pay only for what you use!
Scale on demandRigid On-Premise ResourcesWasteCustomerDissatisfactionActual demandPredicted DemandCapacityTimeElastic Cloud ResourcesActual demandResources scaled to demandCapacityTimeVS
Use only what you need: AWS cost savings opportunities• Right-size your cloud resources– Use resources that suit your needs (instance types, storage options, etc.)– Improve performance: reduce churn, underutilization, bottlenecks– Lower costs: maximize your output per dollar, don’t pay for performance you don’trequire• Fit your payment model to your business model– Do you value flexibility or predictability?– Use a portfolio of payment models• Measure and manage your application and cloud resources– Monitor your applications to identify new savings opportunities
Right-size your cloud resources: broad EC2 selection• An instance type forevery purpose• Assess your memory& CPU requirements– Fit your applicationto the resource– Fit the resource toyour application• Only use a largerinstance whenneeded
Optimize your storage choice too: S3 & Glacier• S3 and Glacier are both:– Secure– Flexible– Low-cost– Scalable: over 2 trillion customer objects– Durable: 99.999999999% (11 “9”s)AmazonGlacier
Choosing between S3 and Glacier• Simple Storage Service (S3)– Designed to serve static content at high volumes, low latency, frequent access– Low cost: as low as 5.5¢ per GB-month (or 3.7¢ for reduced redundancy)• Glacier– Designed for long-term cold storage: infrequent access, long retrieval times (3-5hrs)– Extremely low-cost: 1¢ per GB-month• Tips:– Optimize access: Reduce payload size, # of accesses (e.g., consolidated logs)– Monitor for unexpected access/growth patterns: e.g., misconfigured log archiving– Set Lifecycle Policies: object expiration dates; auto-move S3 files to GlacierIllumina, the leading provider of DNA sequencinginstruments, uses Glacier to store large blocks ofgenomic data all over the world
Fit your payment model to your business model: EC2 pricing plansOn-DemandInstancesReservedInstancesSpotInstancesPay as you go for computingpowerFlat hourly rate, no up-frontcommitmentsPay an up-front fee for acapacity reservation and a lowerhourly rate (up to 72% savings)1- or 3-year termsRI Marketplace: sell RIs you nolonger need; buy RIs at adiscountPay what you want for spare EC2capacity: your instances run ifyour bid exceeds the Spot pricePotential for large scale at lowcost: When they’re available,take advantage of 1,000s of SpotInstances at up to 90% savings10:0010:0510:1010:15
Use a spectrum of payment modelsFor example:Frontend Applicationson On-Demand/Reserved Instances+Backend Applications*on Spot Instances* e.g., batch video transcoding
Reserved Instance Marketplace: Buy and Sell Your RIs• Benefits for Buyers:– Same underlying EC2 hardware– Buy RIs at a discount from AWS price– Increased selection of term lengths &prices• Benefits for Sellers:– Moving to a new AWS region– Changing your instance type– Switching operating systems– Selling capacity when project ends
Measure and Manage“If you cannot measure it, you cannot improve it.”- Lord Kelvin
Overview of AWS Monitoring and Management Services• AWS provides detailed cloud monitoring and management– Consolidated Billing (see “Account Activity” navigation panel)– CloudWatch (see AWS Management Console)– Billing Alerts (see “Account Activity” navigation panel)– Trusted Advisor (see “Support Center”)– Other APIs: tags, programmatic access, etc.• 3rd party services are also available
Consolidated Billing: Single payer for a group of accounts• One Bill for multiple accounts• Easy Tracking of account charges(e.g., download CSV of cost data)• Group Activities by PayingAccount (e.g., Dev, Stage, Test,Prod)• Volume Discounts can be reachedfaster with combined usage• Reserved Instances are sharedacross accounts (including RDSReserved DBs)• AWS Credits are combined tominimize your bill
Consolidated Billing Demo (1/3)• Get an overall summary totalfor all your users andaccounts:
Consolidated Billing Demo (2/3)• From your payment accountlogin, view details of eachlinked account in one place
Consolidated Billing Demo (3/3)• Drill down into detail’s of eachaccount• Download a CSV file for lineitem details, then analyze viaspreadsheet, pivot tables, etc.
Amazon CloudWatch• Overview– Monitoring for AWS cloud resources and applications• AWS Resources: EC2, RDS, EBS, ELB, SQS, SNS, DynamoDB, EMR, Auto Scaling…• Custom metrics from your application (use Put API call)– Gain insight, set alarms and notifications, react immediately– Start using within minutes, auto-scale with your application• Sophisticated Automation– Use CloudWatch metrics with Auto Scaling to dynamically scale EC2 instances
Use CloudWatch to monitor & manage resource usage• Monitor your resource utilization– Are you using the right instance type?– Have you left instances idle?– Is your instance usage level or bursty?• Manage your resource utilization– Move bursty workloads to other instances– Rebalance your worker nodes– Scale nodes automatically with Auto Scaling
Use CloudWatch to create Billing Alerts• Billing Alerts notify you when estimated charges reach a given threshold• Use Billing Alerts to track an individual developer, or your whole business• Easily setup your billing alarm and actions
Trusted Advisor: Enterprise Strength Monitoring/Optimization• Monitors and recommendsoptimizations for:– Cost– Security– Fault Tolerance– Performance• Available to customers withBusiness and Enterprise-level supporthttp://aws.amazon.com/premiumsupport/trustedadvisor/
Scale OpportunisticallyOpportunity favors the prepared application
Time-to-Result Case 1: Value of result quickly diminishesExample:EngineeringsimulationDelay Loss ofproductivity,project slips
Time-to-Result Case 2: Result is valuable…until it’s notExample:Weekendregression testsDelay Minimalimpact until8:00AM Monday
Consider Spot Instances for greater savings and scale• Spot in a nutshell– Spot instances run when Your Bid ≥ Spot Price– Spot instances = Spare EC2 instances– Spot instances might be interrupted at any time• Benefits– Savings: Up to 90% off On Demand– Scale: Access up to 1,000s of EC2 instances• To use Spot– Decide on a bid price– Launch via Console, API, Auto Scaling– Monitor Bid Statuses via Console/API
What applications work on Spot?• Good Spot applications are:– Delayable: to balance SLA/cost– Scalable: “embarrassingly parallel”– Fault-tolerant: can be terminated without losing all work– Portable across regions, AZs, instance types• Examples:– MapReduce (Hadoop, Amazon EMR)– Scientific Computing (Monte Carlo simulations)– Batch Processing (video transcoding)– Financial Computing (high-frequency trading algorithm backtesting)– and many others…Lucky Oyster crawled 3.4B Web Pages,building a 400M entry index in around14 hours for $100 (>85% savings)!
• Auto Scaling auto-sizes your cluster based on preset triggers and schedules• Integrates with CloudWatch metrics• Use Auto Scaling to– Improve customer experience, application performance– Maximize CPU/IO/Memory utilization– Optimize other metricsUse Auto Scaling to dynamically scale your appScale with Real-Time Demand
Follow the Money vs. Follow the Customer• Optimize utilization– Auto Scale on utilization metrics: CPU, memory, requests, connections, …• Optimize price paid– Scale with Spot instances when Spot prices are low– e.g., Run batch processes off-peak (nights, weekends) when Spot prices are lower
Follow the Money vs. Follow the Customer• Optimize customer experience with Auto Scaling• Example 1: Scale resources to meet customer demand– Video service Auto Scales instances to respond to customer web service requests• Example 2: Scale resources to ensure fresh results– A scientific paper search engine Auto Scales on queue depth (# of new docs to crawl)– 10 instances steady state and up to 5,000+ to ensure minimum throughput time• Example 3: Scale resources preemptively before large demand– A TV show marketing site scales up before the show and back down after
Cost-Saving Examples• Achieve potentiallylarge savings byprofiling yourapplication andpaying only forwhat you need:Base Case Savings ExamplesYou run 10 m3.2xlarge’sOn-Demand 24x7:10 instancesX $1.00/inst-hoursX 24 hours/dayX ~30.5 days/month= $7,320/monthIf you need to run 100% of the time, indefinitely:10x 3-yr Heavy RIs @ 100% Utilization= $2,731/month (63% savings)If you can layer RIs and On Demand to meet demand:4x 3-yr Heavy RIs @ 100% Utilization4x 3-yr Light RIs @ 15% Utilization2x On-Demand @ 5% Utilization= $1,843/month (75% savings)If you Auto Scale from 2 to 10 instances aroundprimetime TV (6-11pm, Mon-Fri):2x 3-yr Heavy RIs @ 100% Utilization8x 3-yr Light RIs @ 15% Utilization= $1,683/month (77% savings)If you can use 40x Spot Instances at 25% up-time:= $840/month (89% savings)
World domination withoutthe price tag, Freelancer.comDavid HarrisonVice President of EngineeringFreelancer.email@example.com@davelharrison @freelancer
Use Only What You Need• No premature scaling commitment on host capacity (start small and scale up)• Use on-demand instances early on, you can always shut them down!• Use `pay for what you eat` services – S3
Performance / Cost efficiency• Speed doesn’t always == increased $We use S3 as a persistent object store!• Some data needs to be hot, some doesn’t• Make sure you’re optimizing for your high value patterns
Reserved Instances• Great way to optimize cost for committed resources youknow you need• On-demand vs. shorter 1 year reserves vs. 3 year reserves
Focus your engineering resources where it counts• Focus your resources on the things that are critical to your success, don’t worryabout the things you don’t have to• Avoid re-building common patterns (unless you really want to!)– RDS– S3– ELB• Your staff’s time is precious, use automated build / configuration tools to makethe most of it!
Automate Your Cleanup• Scripted cleaning of snapshots• Automated monitoring of long lived instances in staging environments• Age based expiry of some S3 objects (logs etc)• Monitoring !
Conclusion (Part I):Fit the cloud to your product and business model• Use Only What You Need (and pay only for what you use!)• Measure and Manage• Scale Opportunistically
An example putting it all together: saving on Batch Processinghttp://aws.amazon.com/architecture/3. ScaleOpportunistically:Auto Scale workernodes based on sizeof input queue1. Pay Onlyfor What YouUse: Right-size yourcloudresources2. Monitor andManage your systemwith CloudWatch,Billing Alerts, TrustedAdvisor
Conclusion (Part II):Use the cloud to create new products & business modelsOn-Premises• Failure isexpensive• Experimentinfrequently• Less InnovationOptimized Cloud• Failure isinexpensive• Experiment earlyand often• More Innovation