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Capacity
Planning
in
the
Cloud

   an
ini2al
peek
into
a
new
world


       CMG08
Panel
Session

      Adrian
Cockcro=
‐
N...
What
is
Cloud
Compu2ng?

hGp://www.slideshare.net/StuC/cloud‐compu2ng‐for‐architects‐qcon‐2008‐tutorial‐presenta2on

What
is
Capacity
Planning

•  We
care
about
CPU,
Memory,
Network
and

   Disk
resources,
and
Applica2on
response

   2mes
...
Capacity
Planning
Norms

•    Capacity
is
expensive

•    Capacity
takes
2me
to
buy
and
provision

•    Capacity
only
incr...
Capacity
Planning
in
Clouds

•    Capacity
is
expensive

•    Capacity
takes
2me
to
buy
and
provision

•    Capacity
only
...
Capacity
is
expensive

         hGp://aws.amazon.com/s3/
&
hGp://aws.amazon.com/ec2/          

•  Storage
(Amazon
S3)


 ...
Capacity
comes
in
big
chunks,
paid
up
front


•  Capacity
takes
2me
to
buy
and
provision

   –  No
minimum
price,
monthly
...
Systems
are
clearly
defined
assets


•  You
are
running
in
a
“stateless”
mul2‐tenanted

   virtual
image
that
can
die
or
be...
Systems
can
be
instrumented
in
detail


•  Need
to
use
stateless
monitoring
tools

•  e.g.
Ganglia
–
automa2c
configura2on
...
Ganglia
–
www.ganglia.info

•  Web
based
RRDtool
GUI

•  Good
management
of
clusters
of
systems
and
devices,
useful

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

December
11,
2008
   Adrian
Cockcro=
and
Mario
Jauvin

December
11,
2008
   Adrian
Cockcro=
and
Mario
Jauvin

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Capacity Planning for Cloud Computing

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Capacity Planning for Cloud Computing

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

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

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

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

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


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