Capacity planning in the cloud presents new challenges compared to traditional systems. Cloud resources are priced based on usage so capacity can be dynamically scaled without long lead times. However, cloud systems are distributed across data centers so visibility and control is reduced. Monitoring tools need to be stateless to handle cloud volatility and gather metrics without predefined assets.

1. Capacity Planning in the Cloud
an ini2al peek into a new world
CMG08 Panel Session
Adrian Cockcro= ‐ Ne@lix
Paul Strong – eBay

2. What is Cloud Compu2ng?
hGp://www.slideshare.net/StuC/cloud‐compu2ng‐for‐architects‐qcon‐2008‐tutorial‐presenta2on

3. What is Capacity Planning
• We care about CPU, Memory, Network and
Disk resources, and Applica2on response
2mes
• We need to know how much of each resource
we are using now, and will use in the future
• We need to know how much headroom we
have to handle higher loads
• We want to understand how headroom varies,
and how it relates to applica2on response
2mes and throughput

4. Capacity Planning Norms
• Capacity is expensive
• Capacity takes 2me to buy and provision
• Capacity only increases, can’t be shrunk easily
• Capacity comes in big chunks, paid up front
• Planning errors can cause big problems
• Systems are clearly defined assets
• Systems can be instrumented in detail

5. Capacity Planning in Clouds
• Capacity is expensive
• Capacity takes 2me to buy and provision
• Capacity only increases, can’t be shrunk easily
• Capacity comes in big chunks, paid up front
• Planning errors can cause big problems
• Systems are clearly defined assets
• Systems can be instrumented in detail

6. Capacity is expensive
hGp://aws.amazon.com/s3/ & hGp://aws.amazon.com/ec2/
• Storage (Amazon S3)
– $0.150 per GB – first 50 TB / month of storage used
– $0.120 per GB – storage used / month over 500 TB
• Data Transfer (Amazon S3)
– $0.100 per GB – all data transfer in
– $0.170 per GB – first 10 TB / month data transfer out
– $0.100 per GB – data transfer out / month over 150 TB
• Requests (Amazon S3 Storage access is via hGp)
– $0.01 per 1,000 PUT, COPY, POST, or LIST requests
– $0.01 per 10,000 GET and all other requests
– $0 per DELETE
• CPU (Amazon EC2)
– Small (Default) $0.10 per hour to Extra Large $0.80 per hour
• Network (Amazon EC2)
– Inbound/Outbound around $0.10 per GB

7. Capacity comes in big chunks, paid up front
• Capacity takes 2me to buy and provision
– No minimum price, monthly billing
– “Amazon EC2 enables you to increase or decrease
capacity within minutes, not hours or days. You can
commission one, hundreds or even thousands of
server instances simultaneously”
• Capacity only increases, can’t be shrunk easily
– Pay for what is actually used
• Planning errors can cause big problems
– Size only for what you need now

8. Systems are clearly defined assets
• You are running in a “stateless” mul2‐tenanted
virtual image that can die or be taken away
and replaced at any 2me
• You don’t know exactly where it is
• You can choose to locate “USA” or “Europe”
• You can specify zones that will not share
components to avoid common mode failures

9. Systems can be instrumented in detail
• Need to use stateless monitoring tools
• e.g. Ganglia – automa2c configura2on
– Mul2cast replicated monitoring state
– No need to pre‐define metrics and nodes

10. Ganglia – www.ganglia.info
• Web based RRDtool GUI
• Good management of clusters of systems and devices, useful
for hundreds to thousands of nodes in a hierarchy of clusters
• Provides many summary sta2s2c plots at cluster level and
collects detailed configura2on data
• XML based data representa2on
• Uses low overhead network protocol (mul2cast or unicast)
• In common use at hundreds of large HPC Grid sites, less visibly
in use at some large commercial sites
• hGp://wiki.apache.org/hadoop/AmazonEC2 includes ganglia
as a standard feature of Hadoop on EC2.
December 11, 2008 Adrian Cockcro= and Mario Jauvin

11. December 11, 2008 Adrian Cockcro= and Mario Jauvin

12. December 11, 2008 Adrian Cockcro= and Mario Jauvin

13. December 11, 2008 Adrian Cockcro= and Mario Jauvin