AWS APAC Webinar Series: How to Reduce Your Spend on AWS
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AWS has different pricing models to match your needs. One example is the different instance types available such as On-Demand, Reserved and Spot Instances. Customers can develop cost-saving strategies based upon their usage patterns, models and growth expectations. In some cases, a set of larger instances can be cheaper than multiple small instances. Learn how to size your AWS applications to maximize your use and minimize your spend. Companies such as Pinterest take very active roles to constantly reduce their spend; learn how they do it and develop your own cost-saving approaches.
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AWS APAC Webinar Series: How to Reduce Your Spend on AWS
- 1. How to Reduce Your Spend Joe Ziegler Startup Business Development Manager APAC @jiyosub On AWS APAC Webinar Series | AWS 201
- 2. How do the benefits of AWS help to reduce my spend?
- 3. Elastic On Demand Pay as you go Focus on YOUR business
- 4. Traditional IT capacity Capacity Time Your IT needs Elastic Capacity
- 5. On and Off Fast Growth Variable Peaks Predictable Peaks Elastic Capacity
- 6. On and Off Fast Growth Predictable PeaksVariable Peaks WASTE CUSTOMER DISSATISFACTION Elastic Capacity
- 7. When you turn off your cloud resources, you actually stop paying for them
- 8. Elastic cloud capacity Traditional IT capacity Your IT needs Time Capacity Elastic Capacity
- 9. Fast GrowthOn and Off Predictable peaksVariable peaks Elastic Capacity
- 11. Hardware, Software, Database, Network : Procurement, Installation, Maintenance and Administration Costs
- 12. Economies of Scale Pricing Models Cost Aware Architecting
- 13. Economies of Scale Pricing Models Cost Aware Architecting
- 14. Powering the Most Popular Internet Businesses
- 15. Free steak campaign Facebook page Mars exploration ops Consumer social app Ticket pricing optimization SAP & Sharepoint Securities Trading Data Archiving Gene sequencing Marketing web site Interactive TV apps Financial markets analytics R&D data analysis Consumer social app Big data analytics Web site & media sharing Disaster recovery Media streaming Web and mobile apps Streaming webcasts Facebook app Consumer social app Every Imaginable Use Case
- 16. Every Day… AWS adds the equivalent server capacity to power Amazon when it was a global, $5.2B enterprise in 2003 2003 $5.2B retail business 7,800 employees A whole lot of servers…
- 17. The AWS Price Reduction Philosophy Ecosystem Global Footprint New Features New Services Infrastructure Innovation More AWS Usage More Infrastructure Economies of Scale Lower Infrastructure Costs Reduced Prices More Customers
- 18. Economies of Scale Pricing Models Cost Aware Architecting
- 19. AWS Pricing Philosophy • Pay as you go – No minimum commitments or long-term contracts required – Capex -> Opex – Turn off when you don’t need it • Pay less per unit when you use more – Tiered Pricing and Volume Discounts • Pay even less when you reserve – Reserved pricing • Pay even less as AWS grows – Efficiencies, optimizations and economies of scale result in passing the savings back to you in the form of lower pricing
- 20. Pay less when you use more
- 21. On-Demand Pay for compute capacity by the hour with no long- term commitments For spiky workloads, or to define needs Cost Optimization using different purchase models Reserved Make a low, one- time payment and receive a significant discount on the hourly charge For committed utilization Spot Bid for unused capacity, charged at a Spot Price which fluctuates based on supply and demand For time-insensitive or transient workloads Free Tier Get Started on AWS with free usage & no commitment For POCs and getting started
- 25. Utilise the Free Tier Time Scale Scenario Small team with initial idea for Mobile app 3 months to get to launch Unknown customer/problem/solution No cash….
- 26. • Internal testing with your team • 2 Tier Web - Database Servers • Use t1.micro Instances Dev / Test Environment Time Scale Average Spend $0 p/m
- 27. • Release to small group of ‘core testers’ • 2 Tier Web & Database Servers • 2 x t1.micro Instances Alpha Release Time Scale Average Spend $15 p/m
- 28. • First public release – limited audience • Master / Slave DB setup • m1.small Instances • Auto-Scaling Instances (2 Instance minimum) Beta Release / MVP Time Scale Average Spend $235 p/m
- 29. Getting to MVP for $250 Time Scale Total Spend to MVP $250 $235$15$0 • 3 months dev/test/release • Serving Beta customers • Ready for full production and scale
- 30. Reserved Instance Pricing Make a low, one-time payment and receive a significant discount on the hourly charge For committed utilization •Light Utilization RI •Medium Utilization RI •High Utilization RI •1-year •3-year 2 Terms3 Versions
- 31. Reserved Instance Pricing Utilization RI option Savings over On-Demand <10% On-Demand 10% - 40% Light Utilization RI Up to 56% 40% - 75% Medium Utilization RI Up to 66% >75% Heavy Utilization RI Up to 71%
- 36. February 2013 48.7 million users globally Raised $200M (Total = $338M) $2.5B valuation
- 37. • Most traffic happens in the afternoons and evenings, so they reduce the number of instances at night by 40%. • At peak traffic $52 an hour is spent on EC2 and at night, during off peak, the spend is as little as $15 an hour. Saving per hour = 71%
- 38. Save more money by using Spot Instances Up to 85% savings over On Demand pricing Spot market for under- utilized capacity Requested Bid Price and Pay as you go Spot Price < On-Demand Price
- 39. Use Case Types of Applications Batch 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 biology Video and Image Processing/Rendering Transform videos into specific formats Testing Provide testing of software, web sites, etc Web/Data Crawling Analyzing data and processing it Financial Hedgefund analytics, energy trading, etc HPC Utilize HPC servers to do embarrassingly parallel jobs Cheap Compute Backend servers for Facebook games Use Cases for Spot Pricing
- 41. Optimizing Video Transcoding Workloads for a FREEMIUM model Free Offering Optimize for reducing cost Acceptable Delay Limits Implementation – Leverage spot pricing – Maximum Bid Price – < On-demand Rate – Use on-demand Instances, if delay Get strongly reduced price for your workload Premium Offering Optimized for Faster response No Delays Implementation – Invest in Reserved Instances – Use on-demand for Elasticity Get Instant Capacity for higher price
- 42. Economies of Scale Pricing Models Cost Aware Architecting
- 43. “Give me 4 fault tolerant algorithms and I can pick the best one almost with my eyes closed. If you then ask me which one is best for the business, in terms of dollar costs, I would be clueless...” Werner Vogels, CTO, Amazon
- 44. Cost optimization through ‘Cost Aware Architecting’ …by leveraging:Reduce Cost of… Compute 1. S3 & CloudFront for Caching & Offloading Storage 5. Storing derivative objects in S3 ‘Reduced Redundancy’ Database 6. Read Replicas and/or ElastiCache Test & Dev 7. Rapid proto-typing & Lean Dev/Test 2. Auto-Scaling done Right 3. Leverage Managed Services 4. Sizing your Application for AWS
- 45. 1. S3 & CloudFront for Caching & Offloading • Reduce your compute demand and costs • Improve end-user experience • Increase reliability and durability Cost Aware Architecting to Reduce costs of EC2
- 46. 1. S3 & CloudFront for Caching & Offloading Cost Aware Architecting to Reduce costs of EC2
- 47. 1. S3 & CloudFront for Caching & Offloading Cost Aware Architecting to Reduce costs of EC2
- 48. 1. S3 & CloudFront for Caching & Offloading Cost Aware Architecting to Reduce costs of EC2
- 49. 1. S3 & CloudFront for Caching & Offloading Cost Aware Architecting to Reduce costs of EC2
- 51. 2. Auto-Scaling done Right with Real Time reaction response • Elastic Load Balancing and (event-driven) Auto Scaling • Notification of pending news flash (with audible alarm) • On-demand ramp up of capacity (6 mins.) • Subscriber alert push delivered • Mass response traffic handled (followed by ramp down) Cost Aware Architecting to Reduce costs of EC2
- 52. BuUuk for Singapore Press Holding (SPH)
- 53. 2. Auto-Scaling done Right with Real Time reaction response Cost Aware Architecting to Reduce costs of EC2 Straits TimesBuuuk
- 54. 2. Auto-Scaling done Right with Real Time reaction response Cost Aware Architecting to Reduce costs of EC2
- 55. 2. Auto-Scaling done Right with Real Time reaction response Cost Aware Architecting to Reduce costs of EC2
- 56. 2. Auto-Scaling done Right with Real Time reaction response Cost Aware Architecting to Reduce costs of EC2
- 57. 2. Auto-Scaling done Right with Real Time reaction response Cost Aware Architecting to Reduce costs of EC2
- 58. 3. Leverage Managed Services Cost Aware Architecting to Reduce costs of EC2 Rabbit MQ, MSMQ Cron Running a mail server Running a NoSQL cluster Running MySQL on EC2 Memcached Encoding Server VS Simple Queuing Service Simple Workflow Service Simple Email Service Dynamo DB Relational Database Service ElastiCache Elastic Transcoder
- 59. 4. Sizing your Application for AWS Cost Aware Architecting to Reduce costs of EC2
- 60. 256 128 64 32 16 8 4 2 1 1 2 4 8 16 32 64 128 256 High I/O 4XL 60.5 GB 35 EC2 Compute Units 16 virtual cores 2*1024 GB SSD-based local instance storage EC2 Compute Units Memory(GB) Small 1.7 GB, 1 EC2 Compute Unit 1 virtual core Micro 613 MB Up to 2 ECUs (for short bursts) Large 7.5 GB 4 EC2 Compute Units 2 virtual cores $0.32/0.46 Hi-Mem XL 17.1 GB 6.5 EC2 Compute Units 2 virtual cores Hi-Mem 2XL 34.2 GB 13 EC2 Compute Units 4 virtual cores Hi-Mem 4XL 68.4 GB 26 EC2 Compute Units 8 virtual cores High-CPU Med 1.7 GB 5 EC2 Compute Units 2 virtual cores High-CPU XL 7 GB 20 EC2 Compute Units 8 virtual cores Medium 3.7 GB, 2 EC2 Compute Units 1 virtual core M3 XL 15 GB 13 EC2 Compute Units 4 virtual cores EBS storage only M3 2XL 30 GB 26 EC2 Compute Units 8 virtual cores EBS storage only Extra Large 15 GB 8 EC2 Compute Units 4 virtual cores 10 GB Inter-Instance Network Cluster GPU 4XL 22 GB 33.5 EC2 Compute Units, 2 x NVIDIA Tesla “Fermi” M2050 GPUs Cluster Compute 4XL 23 GB 33.5 EC2 Compute Units Cluster Compute 8XL 60.5 GB 88 EC2 Compute Units High Storage 8XL 117 GB 35 EC2 Compute Units, 24 * 2 TB ephemeral drives 10 GB Ethernet Hi-Mem Cluster Compute 8XL 244 GB 88 EC2 Compute Units 16 virtual cores 240 GB SSD
- 61. 5. Storing derivative objects in S3 ‘Reduced Redundancy’ • Original vs. derived assets : 33% savings • Single reference and consistency • Control, accurate logs and tracking Cost Aware Architecting to Reduce costs of S3 Reduced Redundancy Storage ‘RRS’
- 62. 6. Read Replicas and/or ElastiCache (‘Database Smarts’) • Scale out and share work • Optimal performance, minimize load • Enhance reliability, ensure data safety • Cost reduction Cost Aware Architecting to Reduce costs of DB
- 66. 7. Rapid proto-typing & Lean Dev/Test • Inexpensive idea validation • Seamless switch over and versioning • Rapid dev / test agility Cost Aware Architecting to Reduce costs of Test/Dev
- 67. Bringing this all Together Enterprise software provider in APAC Focused on SaaS for storage, security, collaboration, etc. Backed by leading VC’s in the region Strong growth – winning customers globally Focused on profitability & reducing unit costs Worked closely with the AWS team to optimize its architecture
- 68. Margin Growth -10% price drop in S3 -20% RI purchase -22% Migration Cassandra to Dynamo -18% Price drop in S3 of 25% 54% reduction in unit costs “Based on a True Story”
- 69. New Customers Amazon EC2 Amazon RDS Amazon ELB Amazon S3 Amazon EBS For All Customers Amazon SQS/SNS Amazon DynamoDB Amazon SES Amazon SWF And more… AWS Elastic Beanstalk AWS CloudFormation AWS IAM Auto Scaling Consolidated Billing No Charge for Inbound Data Transfer Data Transfer between Instances within an Availability Zone Free Usage Tier Did you know? Free Services Data Transfer
- 70. Trusted Advisor
- 71. Survey Please fill out the survey at the end for $25 USD in AWS Credits
- 72. Thank You Joe Ziegler Startup Business Development Manager APAC @jiyosub APAC Webinar Series | AWS 201