Cloud Economics, from Genesis to Scale
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Cloud Economics, from Genesis to Scale
- 1. Rotem Yossef AWS Business Development Manager Cloud Economics June 15, 2016 From Genesis to Scale Vittaly Tavor VP Product Cloudyn Amir Arama Head of SaaS Cloud Strategy HPE
- 2. In the beginning . . . …there was TCO
- 3. What is TCO? Definition: Comparative total cost of ownership analysis (acquisition and operating costs) for running an infrastructure environment end-to-end on-premises vs. on AWS. Used for: 1) Comparing the costs of running an entire infrastructure environment or specific workload on-premises or in a co-location facility vs. on AWS 2) Budgeting and building the business case for moving to AWS
- 4. How do customers lower their TCO with AWS? Over 50 to date 1 “Average of 400 servers replaced per customer” Replace up-front capital expense with lower “pay for what you use” variable cost model 3 Periodic Price Reductions Economies of scale allow AWS to continually lower costs 2 Pricing model choice to support variable & stable workloads On-Demand Reserved Spot Dedicated Source: IDC Whitepaper, sponsored by Amazon, “The Business Value of Amazon Web Services Accelerates Over Time.” December 2013
- 5. Analysts have shown AWS reduces costs over long term Source: IDC, Quantifying the Business Value of Amazon Web Services (May, 2015) https://aws.amazon.com/resources/analyst-reports/IDC-business-value-aws/
- 6. Comparing TCO is not easy (But We’re Going to Try) ≠
- 7. TCO The Way IT orgs Typically See it Storage Costs Server Costs Hardware – Server, (+Maintenance) Software - OS, Virtualization Licenses (+Maintenance) Hardware – Storage Disks Network Hardware – LAN Switches, Load Balancer Bandwidth costs Server Admin Virtualization Admin4 Diagram doesn’t include every cost item. E.g. software costs can include database, management, middle tier software costs. Facilities cost can include costs associated with upgrades, maintenance, building security, taxes etc. IT labor costs can include security admin and application admin costs. Network Costs IT Labor Costs 1 2 3 illustrative
- 8. Real Life = Acquisition costs + operations costs illustrative Hardware – Server, Rack Chassis PDUs, ToR Switches (+Maintenance) Software - OS, Virtualization Licenses (+Maintenance) Facilities Cost Hardware – Storage Disks, SAN/FC Switches Storage Admin costs Network Hardware – LAN Switches, Load Balancer Bandwidth costs Network Admin costs Server Admin Virtualization Admin Diagram doesn’t include every cost item. E.g. software costs can include database, management, middle tier software costs. Facilities cost can include costs associated with upgrades, maintenance, building security, taxes etc. IT labor costs can include security admin and application admin costs. Space Power Cooling Facilities Cost Space Power Cooling Facilities Cost Space Power Cooling Server Costs Storage Costs Network Costs IT Labor Costs Storage Costs Server Costs 4 Network Costs IT Labor Costs 1 2 3
- 9. When Performing a TCO analysis • Build the TCO comparison collaboratively with the customer in multiple iterations, take the “No surprises” approach • Make sure you have the right stakeholders in the room to discuss TCO (Finance, Procurement, IT support, Engineering) • Avoid Comparing a duplicate of customer’s on-premise environment – problematic apples-to-apples comparisons of machines • Assign cost/value to non-tangibles such as agility, opportunity costs
- 10. Resources to get you started AWS TCO Calculator https://awstcocalculator.com Case studies and research http://aws.amazon.com/economics/
- 11. So you’re feeling pretty good.
- 12. Until your CFO shows up with the bill.
- 13. Cost optimization is… going from… to… pay for what you use pay for what you need
- 14. The four pillars of cost optimization Right-sizing Reserved Instances Increase elasticity Measure, monitor, and improve
- 15. Right-sizing Right-sizing • Selecting the cheapest instance available while meeting performance requirements • Looking at CPU, RAM, storage, and network utilization to identify potential instances that can be downsized • Leveraging Amazon CloudWatch metrics and setting up custom RAM metrics Rule of thumb: Right size, then reserve. (But if you’re in a pinch, reserve first.)
- 16. Reserved Instances Step 1: RI Coverage • Cover always-on resources. Step 2: RI Utilization • Leverage RI flexibility to increase utilization. • Merge and split RIs as needed. Rule of thumb: Target 70–80% always-on coverage and 95% RI utilization rate.
- 17. Increase elasticity Turn off nonproduction instances • Look for dev/test, nonproduction instances that are running always-on and turn them off. Autoscale production • Use Auto Scaling to scale up and down based on demand and usage (for example, spikes). Rule of thumb: Shoot for 20–30% of Amazon EC2 instances running on demand to be able to handle elasticity needs.
- 18. Using right-sizing and elasticity to lower cost More smaller instances vs. fewer larger instances 29 m4.large @ $0.12 /hr $2,505.60 / mo* 59 t2.medium @ $0.052/hr $2,208.96 / mo* *Assumes Linux instances in US-East at 720 hours per month
- 19. Use Spot to Increase Elasticity Savings • Be Fault Tolerant • Workloads should be Stateless • Loosely Coupled workloads preferred • If possible, deploy to Multiple AZs • Instance Flexibility is king • Take advantage of the 2 minutes warning • There is always Spot capacity available Save up to 90% compared to On-Demand
- 20. Novartis, Cycle Computing & AWS Spot Instances Goal: Screen 10 million compounds against a common cancer target Estimated on-prem costs: $40M Estimated computational time: 39 Years
- 21. Solution: Use 10,600 AWS Spot Instances Outcome: 3 promising compounds identified Cost: $4,232 Time: 9 Hours Novartis, Cycle Computing & AWS Spot Instances
- 22. • Be Fault Tolerant • Workloads should be Stateless • Loosely Coupled workloads preferred • If possible, deploy to Multiple AZs • Instant Flexibility is king • Take advantage of the 2 minutes warning • There is always Spot capacity available Use Spot to Increase Elasticity Savings Save up to 90% compared to On-Demand What could you do with a 10,000 core data center that costs $100 per hour, with one click?
- 23. Cost optimization governance (Remember the fourth pillar?)
- 24. AWS options
- 26. HPE Software Public Cloud Governance Process Amir Arama – HPE SaaS Public Cloud Strategy & Solution Vittaly Tavor – Cloudyn co-founder & VP Product May 2016
- 28. Public Cloud Governance AWS Accounts Structure HPE Master Billing Account BU 1 Prod Non-prod BU 2 Prod Non-prod BU 3 Prod Non-prod BU4 Prod Non-prod BU 5 Prod Non-prod BU 6 Prod Non-prod BU 7 Prod Non-prod HPE Public Cloud Team Cross Charge BU’s Cloudyn: Cloud Mgmt. Tool • All AWS accounts will be linked to HPE SW Master Billing Account. • BU-level cross charges will be generated by HPE Public Cloud Team using Cloudyn. • RIs will be purchased centrally and allocated using Cloudyn. • Cross-charge will include the use of shared resources. • Cloudyn will be the billing source. 29
- 29. Cloudyn Manages Cloud Deployments Allowing customers to fully realize their cloud potential 34
- 30. Cloudyn Governs Your Cloud 35 • Full visibility into your spend • Accountability of your business units • Compliance with your policies • Reporting to your managers
- 31. Cloudyn Optimizes Your Cloud 36 Typical customer saves: • 30-50% on EC2 Sizing • 25-30% on Ris • 5-10% on unused resource elimination
- 32. Cloudyn Ensures the Highest ROI 37 We let you assess the impact of your decisions: • ROI on your Spot instances • ROI on your RI purchases
- 34. rotem@amazon.com
Editor's Notes
- How many know AWS? Who uses RI? The presentation will be uploaded to Youtube after the summit
- Cost is the conversation starter when it comes to cloud. There are many pieces to cost conversation when it comes to AWS and your own infrastructure. The first advantage you get in the cloud is that you don’t have to lay out capital expense for hardware and infrastructure before you know the demand. In essence you convert your capital expense into variable expense. And then that variable expense on AWS is lower than what most companies can do on their own because AWS runs at a massive scale and we pass that scale to our customers in the form of lower pricing. There are multiple pricing models in AWS, so you can optimize your spend depending on what your workloads requirements are. And the more you use AWS, the less your costs are. We have tiered pricing and for customers doing large data center migrations, we have negotiated custom pricing to make their transitions cost-effective. #3 – As of 1/28/16 – 51 discounts
- In an IDC study, they interviewed a group of our clients to get a sense of the results they get from using AWS. The results were quite favorable, with the aggregate numbers showing significant business benefits, ROI and payback period. We encourage you to read this full report to get the full details- it’s available online. Q&A: Q: How many clients? A: 11 Q: Was AWS involved? A: AWS commissioned the clients yet had no further invlovement
- Clients typically have partial understanding of their real costs and seems to draw something that looks like this slide, yet…
- Real life is more complex and looks more like this slide. Power, cooling, and facilities are often high level allocations by corporate facilities or even “Provided for free” to the data center by the corporate, making it difficult to account for or calculate its impact on a specific deployment. I n many cases complete asset inventories and hardware utilization are unknown Limited mapping of applications to specific physical or virtual hardware Limited tracking/visibility into hardware utilization and performance (servers, racks, UPS, power). Chargeback and allocation to business units are often not understood or actionable therefor making it hard to tie specific workloads to associated costs
- Cost Optimization is a function of the new business model that the Cloud has brought about. By making services genuinely pay for what you use, there’s huge opportunity for customers to be lean with what they use and reduce their spend dramatically. CO should be done early on
- We see infra for Dev and Test team single timezone Really easy turn off when bed Easier still if non prod separate account In a moment we’ll look at tools large customers use
- Do not manage the cloud like you would a DC. This is a new operational model. 14% savings from using t2s vs. m4s above.
- Spot is one of AWS’s unique offerings, working with it the right way can turn it into a very powerful and cost saving tool. Amazon EC2 Spot instances are spare EC2 instances that you can bid on to run your cloud computing applications. Spot instances are available at lower prices than On-Demand, so you can significantly reduce the cost of running your applications, grow your application’s compute capacity and throughput for the same budget, and enable new types of cloud computing applications. The way it works is very simple: 1. Spot price fluctuates based on supply and demand 2. You’ll never pay more than your bid, in fact you’ll only ever pay the market price. When the market price exceeds your bid you get 2 minutes to wrap up. Best practices: Fault tolerance - The ability for a system to remain in operation even if some of the components used to build the system fail Stateless - Store state in reliable resilient external data stores such as DynamoDB. Store state outside of the instance Loosely coupled – System is broken down into various components with least amount of dependency on the others and can be run independently of others. Reduces the risk of one service impacting the whole system Multi AZ deployment – more Azs == more Spot pools and less likelihood for a need to failover Instance type flexibility – if you need an XL and only have 2XL available at 90% discount, it is still 80% of the cost of XL – would you say no to this? Failover in 2 minutes – when market price goes above your bid, you’ll have 2 minutes to failover to a Spot from another pool Bottom line – Save up to 90% on compute workloads, higher than any RI with no commitment! Emphasize the messaging: “What could your customers do with a 10,000 core data center that costs $100 per hour, with one click?” Good example : Novartis saved ~$8M for a single research
- Spot is one of AWS’s unique offerings, working with it the right way can turn it into a very powerful and cost saving tool. Amazon EC2 Spot instances are spare EC2 instances that you can bid on to run your cloud computing applications. Spot instances are available at lower prices than On-Demand, so you can significantly reduce the cost of running your applications, grow your application’s compute capacity and throughput for the same budget, and enable new types of cloud computing applications. The way it works is very simple: 1. Spot price fluctuates based on supply and demand 2. You’ll never pay more than your bid, in fact you’ll only ever pay the market price. When the market price exceeds your bid you get 2 minutes to wrap up. Best practices: Fault tolerance - The ability for a system to remain in operation even if some of the components used to build the system fail Stateless - Store state in reliable resilient external data stores such as DynamoDB. Store state outside of the instance Loosely coupled – System is broken down into various components with least amount of dependency on the others and can be run independently of others. Reduces the risk of one service impacting the whole system Multi AZ deployment – more Azs == more Spot pools and less likelihood for a need to failover Instance type flexibility – if you need an XL and only have 2XL available at 90% discount, it is still 80% of the cost of XL – would you say no to this? Failover in 2 minutes – when market price goes above your bid, you’ll have 2 minutes to failover to a Spot from another pool Bottom line – Save up to 90% on compute workloads, higher than any RI with no commitment! Emphasize the messaging: “What could your customers do with a 10,000 core data center that costs $100 per hour, with one click?” Good example : Novartis saved ~$8M for a single research
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