Cloud Performance Considerations

Transcription

1 Dr. Stefan Pappe - Distinguished Engineer - Leader Cloud Service Specialty Area Dr. Curtis Hrischuk Cloud Performance Leader IBM Global Technology Services Cloud Performance Considerations

2 Disclaimer This document represents the author's views and opinions. It does not necessarily represent IBM's position or strategies. 2

3 Agenda Why cloud computing What is cloud computing What are the business perspectives What is different about the cloud Open questions 3

4 IT Costs are Increasing Costs to manage systems has doubled since 2000 Costs to power and cool systems has doubled since 2000 Devices accessing data over networks doubling every 2.5 years Bandwidth consumed doubling every 1.5 years Data Doubling every 18 months1 Server processing capacity doubling every 3 years2 10G Ethernet ports tripling over the next 5 years Spending (US$B) $300 $250 $200 $150 $100 $50 $0 Power and cooling costs Server mgmt and admin costs New spending Installed Base (M Units) Source: IDC, WW TB Capacity Shipped on Enterprise Disk Storage Systems 2 Server processing consumption doubles every 3 years 4 4

5 What s Driving Cloud Computing? 1. Cost Reduction: 1. Efficiency: virtual resources for hardware utilization (memory, disk, machines) 2. Sharing of hardware/maintenance: multitenancy for cost reduction 3. Automation: automate mundane tasks 4. Commodity hardware for most public clouds Cloud: Highly virtualized with many users sharing the same hardware vs. 2. Technology Maturity Cycle 1. New: Wow, it works! 2. Commercialization: Will it make money long term? 3. Good enough : Functionality is good enough for majority of users. Users have a lower tolerance for poor ease of use, care less about the technical details, etc. 4. Standardization: If users don t care about technical details, we can standardize and virtualize. 5. Business: Focus higher in the solution stack Cloud: Companies who are moving to the cloud are focusing on their business, not technology. 3. Payment model: Pay per use to reduce bar of adoption 1. Pay up front for all required capital 2. Finance terms (deferred financial cost) 3. Pay per use (for public cloud). 5 Cloud: Pay per use with immediate time to value vs. vs.

6 Is Cloud Computing Growing Mind share Market share 6

7 Agenda Why cloud computing What is cloud computing What are the business perspectives What is different about the cloud Open questions 7

8 What is Different about the Cloud Data center Grid Cloud Server Server Server Server Server Server Customers buy hw and sw 10 s to 100 s hw s Servers are in silos Enterprise applications Few failures Heterogeneous hw Customers buy hw and sw 100 s to 1000 s hw s Shared s Mostly batch apps Need to account for failures Homogenous hw Customers rent hw and sw 1000s to 10,000 s hw s Elastic capacity (+/- s) Enterprise and other apps Constant failures Commodity hw Quality of Experience (QoE) is very important to customers Users run on virtualized hw By 2012, one out five businesses will own no IT assets at all. Gartner 01/18/

9 Is Performance Important to the Success of the Cloud Cloud Performance Five of the 10 obstacles and opportunities for cloud computing are related to quality-of-service aspects such as availability, performance, capacity or scalability. Obstacle # 1 Availability of service discusses availability risks for cloud computing as a result of e.g. programming errors, overload of common services or Distributed Denial of Service (DDoS) attacks Obstacle # 4 Data transfer bottlenecks discusses the growing data intensity of applications and how this impacts data transfer rates and costs in the cloud Obstacle # 5 Performance unpredictability discusses performance risks caused by e.g. inefficiencies in I/O sharing and by high performance computing Obstacle # 6 Scalable storage discusses the difficulties of applying cloud computing to solutions requiring highly scalable persistent storage Obstacle # 8 Scaling quickly discusses the difficulties of quickly scaling up and down in response to load without violating service level agreements. From "Above the Clouds: A Berkeley View of Cloud Computing." 9

10 Agenda Why cloud computing What is cloud computing What are the business perspectives What is different about the cloud Open questions 10

11 IBM offers highly integrated cloud solutions for different client requirements regarding workloads, service levels and delivery models Workloads determine type and fit of Cloud Services high pain high gain low gain low pain Service Level expectations require different Cloud Management Services Availability Redundancy Monitoring End to End Process Mgmt Core Infrastructure Services Server Management Storage Management Security, Patch, Risk ITSM Run Tier Problem/Change Audit Checking Software License Mgmt Management Compliance Checking MW and DBMS Services Network Connectivity Help Desk Business Continuity Tier 1 Tier 2 Tier 3 Tier 4 Different Cloud Delivery Models accommodate different needs regarding architectural control, operations and asset ownership Enterprise Data Center Private Cloud Enterprise Data Center Managed Private Cloud IBM operated Enterprise Hosted Private Cloud IBM owned and operated Enterprise A Enterprise B Shared Cloud Services Enterprise C User A User D User B User C User E Public Cloud Services Delivery Model 1 Delivery Model 2 Delivery Model 3 Delivery Model 4 Delivery Model 5 11

12 What are the Layers in the Cloud Business Processes Collaboration Industry s Software as a Service CRM/ERP/HR Middleware High Volume Transactions Database Web 2.0 Runtime Development Tooling Java Runtime Platform as a Service Data Center Servers Networking Storage Fabric Shared virtualized, dynamic provisioning Infrastructure as a Service 12

13 Agenda Why cloud computing What is cloud computing What are the business perspectives What is different about the cloud Open questions 13

14 Is the Cloud More Complex: Virtualization Operating System queue new queue new queue Hypervisor Operating System queue queue queue Multiple hardware and software queues in a normal Virtualization adds two new queues (guest OS and hypervisor) which is a network of software queues Memory and disk space are fixed resources that are shared even more Hypervisor must cap resource usage to prevent starvation and provide QoS guarantees 14

15 Is the Cloud More Complex: Scale Out and Network Functions Hypervisor Hypervisor Hypervisor Operating System Operating System Operating System new queue Network Attached Storage new queue Network Attached Storage Network is a critical resource for persistent storage, input and output traffic Network attached storage is a shared pool of multiple storage pods 15

16 Is the Cloud More Complex: Virtual Machine Mobility Cloud Performance Hypervisor Hypervisor Hypervisor Operating System Operating System Operating System Network Attached Storage Network Attached Storage VMs leave, appear, move, grow Workload classes appear, change, move, go way 16 VMs have different processor power sizes

17 IBM CloudBurst Appliance U 0 Main No U PANEL 1U PANEL EXP3000 EXP3000 EXP3000 EXP A F R EXP3000 B R F EXP x3650m2 Mgt Node 1U GB Ethernet Sw 1U GB Ethernet Sw DS DS U Kbd. 1U PANEL Mon. 18 Blade Center Comp. 17 C D Mgt PS1 Fan 1 PS3 GbE 16 F R R F Mgt PS2 Fan 2 PS4 GbE PDU PDU Blade Center Comp. Mgt PS1 Fan 1 Mgt PS2 Fan 2 PS3 PS4 GbE GbE PDU PDU Compute, Network, and Storage resources are integrated into the appliance HS22 Blade HS22 Blade 10G SM Bay 2 HS22 Blade HS22 Blade 10pt FC SM Midplane Midplane Bay 3 Bay 4 Cntl A Cntl DS3400 B 10pt FC SM Customer Network 10G SM Bay 1 4 AMM2 AMM2 x3650 M2 The image 24 pt 1Gps Ethernet Sw 24 pt 1Gps Ethernet Sw 17

18 How is Cloud Performance Analysis Done Dynamic modeling required to characterize non-locality due to feedback between layered subsystems Classical queuing theory is not that helpful Discrete event simulation approaches are needed Servers Switches NAS bottleneck shows up at s Backpressure NAS 18 A bo0leneck at the NAS may slow the execu9on at the due to backpressure caused by a feedback chain through network!

19 Agenda Why cloud computing What is cloud computing What are the business perspectives What is different about the cloud Open questions 19

20 The Cloud Performance Challenge Cloud computing is a new paradigm which will have new performance challenges - It incorporates prior component performance challenges too - Hybrid clouds expand this further (e.g., network hops / latency) - Customer expectations will require education Quality of Experience (QoE) depends upon (hybrid) cloud service performance Excellent QoE accelerates adoption and is a functional requirement QoE crosses boundaries of internet, network, system, application performance and resilience Competitive pressure will require competitive performance from all vendors to keep customers IaaS and PaaS paradigms allow customers to move (e.g., price, QoE, etc) e.g., Amazon EC2 and IBM Compute Cloud can run the same software QoS and SLA s are an important differentiator Performance of the cloud will evolve to near real-time business Communication needs are near real-time for correctness Complex event processing needs to be done quickly to be useful Great engineering comes from creating predictable results at predictable costs If you re not measuring, you re not engineering Rico Mariani, Chief Architect of Visual Studio, Microsoft Corp. 20

21 Open Question: Comparing Cloud Performance It can t!! There aren t any industry defined benchmarks because the workload classes vary greatly and have dynamic lifetimes And a benchmark needs to include cost and availability as key factors Perhaps a benchmark framework needed that workloads are plugged into? Perhaps a meta-benchmark analysis needed to provide a score? 21

22 Open Question: Central storage vs. Local Disks vs Combination vs New Central shared storage (SAN or NFS) J Provisioning is fast J Live migration is supported L VM disk I/O is slow due to disk and network contentions Local disks J VM disk I/O is fast L Provisioning is slow due to network image copying L No live migration is supported Central shared storage Host machine Repository Host machine Image repository Image 1 Copy Image 2 Virtual disk store Root disk Data disk Hypervisor Host OS Image repository Image 1 Image 2 Copy Hypervisor Host OS Data disk Root disk Data disk 22 How to combine these approaches for the best performance?

23 Open Question: Optimal Approaches for Bin Packing and Moving VMs When deploying services in a cloud, a balance must be found between performance and capacity of the service, and the memory available on nodes. This is further complicated if the number of replicas of an application is limited, for instance by the available number of licenses. The analysis of interference between services must scale to large numbers of host nodes, applications, replicas of applications, and classes of users. This paper combines a multi-dimensional packing heuristic and network flow optimization to satisfy simultaneous constraints on throughputs, processor utilizations, memory availability and license availability, at a minimum cost and with a minimum of host processors. Jim Zhanwen Li, John Chinneck, Murray Woodside, and Marin Litoiu Deployment of Services in a Cloud Subject to Memory and License Constraints. In Proceedings of the 2009 IEEE International Conference on Cloud Computing (CLOUD '09). 23

24 Open Question: Performance Fault Diagnosis and Analysis Cloud Performance Intermittent backpressure causes lower level hw and/or sw to slow down The problem may appear to move if it is caused by a VM and the VM moves The problem may appear to move if it is caused by a VM and the problem VM dies The problem may appear to move if it is caused by a VM and the problem VM starts up The problem may appear to move if it is caused by hw and the VM moves Several VMs may show the same symptom separated in space and time What data and how much to monitor, with 10 4 à 10 5 elements Expert system / analytics are needed to help in the identification of problems Extend analysis to predict hw failures before the occur 24

25 Open Question: The CAP Theorem and Performance Cloud Performance Three properties of shared-data, distributed systems 1. Consistency: one update is made, all obs are updated 2. Availability: all database transactions should be processed accurately and promptly 3. Tolerance: tolerant to network Partitions CAP Theorem Only two properties can be achieved at any time Network partitions is given in distribute systems Have to pick one between consistency and availability How will distributed architectures change to optimize for each pair of properties Eventual consistency, non-relational databases? Lynch, Nancy, and Seth Gilbert. Brewer's conjecture and the feasibility of consistent, available, partition-tolerant web services. ACM SIGACT News, v. 33 issue 2, 2002, p For a general description see: 25

26 Selected Performance Activities IBM Cloud Cloud Performance Cloud Service Consumer e.g. Provisioning image copy instance creation partitioning Cloud Service Provider Cloud Services e.g. Run Time Performance Cloud Service Developer Integration of storage, hypervisor, network components Dedicated nodes Cloud Service Integration Tools Virtualized Infrastructure Server, Storage, Network, Facilities Common Cloud Management Platform BSS Business Support Services Service Development Tools Consumer In-house IT OSS Operational Support Services e.g. Service Activation process optimization Security & Resiliency 26

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