IBM SVC, IBM Storwize storage cost reduction with proper planning This sounds very reasonable, but often it is just difficult to implement. Let´s have a closer look on a typical top level target system for storage planning.

1. storage
Download
Whitepaper
in
English
and
German
language
http://bvqwiki.sva.de/x/WQDy
QR-­‐Code
BVQ
whitepaper:
Reduction
of
storage
cost
-­‐
made
easy!
Michael
Pirker,
SVA
GmbH

2. BVQ whitepaper: Reduction of storage cost - made easy!
- 1 -
Actually,
this
is
a
very
simple
question:
"why
buy
expensive
storage,
if
it
is
possible
to
achieve
the
same
with
a
much
cheaper
storage?"
This
sounds
very
reasonable,
but
often
it
is
just
difficult
to
implement.
Let´s
have
a
closer
look
on
a
typical
top
level
target
system
for
storage
planning:
1. Reliability
/
safety
The
storage
must
be
reliable
–
data
loss
is
not
allowed
to
happen
at
any
time.
2. Reliability
/
performance
efficiency
At
all
times
the
storage
system
needs
to
have
enough
performance
reserves.
Bottlenecks
which
are
generated
by
too
weakly
dimensioned
storage
systems
should
be
excluded
at
any
time.
3. Expandability
The
growth
of
the
storage
system
is
a
fact
and
demands
more
capacity
and
a
higher
performance
from
year
to
year.
So
the
system´s
expandability
should
be
kept
easy.
4. Cost
/
follow-­‐up
cost
These
goals
have
to
be
achieved
with
the
smallest
cost-­‐effort
possible.
During
the
planning
period,
follow-­‐up
cost
for
maintenance,
space
requirements
and
energy
consumption
have
to
be
considered.
The
parameters
reliability
/
safety
can
nowadays
be
achieved
on
different
cost
levels
with
various
storage
classes.
Low
range
storage,
which
previously
was
perceived
to
have
the
same
technical
unreliability
like
SATA,
has
been
improved
in
its
quality.
In
contrast
however,
the
parameters
of
reliability
/
performance
is
usually
still
diametrically
opposed
to
the
cost.
Especially
if
one
considers
the
unknown,
a
general
unknown
parameter
which
obviously
has
an
important
role
in
every
storage
planning
-­‐
the
uncertainty
of
the
performance
planning.
The
justified
concern,
to
run
into
a
performance
bottleneck
today
or
tomorrow,
misleads
many
responsible
employees
to
oversize
their
storage
environments
consciously.
A
supporting
component
is
certainly
also
the
currently
much
exaggerated
usage
of
SSD
storage,
which
is
touted
as
a
panacea
to
cure
all
performance
problems
in
the
world.
Although
SSD
is
getting
cheaper,
it
still
costs
a
multiple
of
disk
storage.
In
general,
information
about
the
current
load
and
empirical
data
which
might
arise
from
observations
is
lacking.
Where
this
reliable
information
is
lacking
an
estimate
is
made
associated
in
large
parts
with
security
thinking.
In
this
way,
spoken
metaphorically,
expensive
storage
palaces
with
golden
doorknobs
are
built
where
actually
a
solid
planned
multi-­‐family
house

3. BVQ whitepaper: Reduction of storage cost - made easy!
- 2 -
would
have
been
sufficient.
Two
customer
examples
from
big
to
small
This
2.5
PB
system
consists
of
6
SVC
clusters.
The
IO
density
analysis
shows
that
almost
all
volumes
in
the
cluster
don´t
benefit
from
the
obtained
performance
opportunities
which
are
provided
by
the
used
storage
systems.
Since
almost
all
storage
pools
are
occupied
by
more
than
80%
they
have
to
be
extended
in
the
near
future.
The
clear
recommendation
here
is
to
invest
into
cheaper
storage
in
the
next
expansion
step.
Fig.
1:
in
this
graphical
representation
of
the
storage
system
an
excellent
overview
about
all
volumes
and
how
they
are
supported
by
the
used
technology
is
given.
Blue
areas
indicate
that
here
the
technology
and
the
associated
financial
resources
are
significantly
oversized.
For
this
reason
blue
areas
are
preferred
candidates
for
cheaper
storage
classes.
In
this
example
the
2.5PB
can
be
recognized
at
a
glance
and
it
is
possible
to
estimate
that
at
least
60%
to
70%
or
about
1.7PB
can
be
stored
in
more
favorable
storage
in
the
future.
The
picture
gets
even
clearer,
if
an
analysis
is
subsequently
executed
to
mark
only
volumes
having
a
performance
characteristic
which
can
be
provided
by
a
low
range
storage.
Here
you
can
see
exactly
where
the
journey
should
go
for
this
customer.
All
marked
capacities
are
candidates
for
cheaper
storage
classes.

4. BVQ whitepaper: Reduction of storage cost - made easy!
- 3 -
Fig.
2:
one
more
time
the
analyzed
2.5PB
environment
to
find
out
which
storage
areas
are
suitable
for
dedicated
low
range
storage.
With
the
knowledge
that
the
majority
of
the
used
storage
types
come
from
the
15k
class,
the
potential
savings
in
this
environment
can
be
easily
calculated.
The
same
happens
even
in
smaller
environments
with
32TB
instead
of
2.5PB.
In
the
following
the
IO
density
analysis
of
a
smaller
Storwize
is
displayed.
This
image
was
made
with
BVQ
version
3.0,
in
which
the
storage
level
of
20%
to
80%
was
parted
into
smaller
steps.
Again
it
gets
obvious
that
surprisingly
just
a
few
IOs
are
needed
in
the
storage
backend.
Reasons
for
this
are
on
the
one
hand
lower
requirements
as
expected,
or
on
the
other
hand
the
very
positive
impact
of
the
cache.
Fig.
3:
the
color-­‐coding
of
the
IO
density
analysis
(heatmap).
The
particularly
high
quality
of
the
BVQ
heatmap
analysis
is
the
fact
that
with
the
consideration
of
IOs,
their
current
cache
efficiency,
RW
conditions
and
other
factors
the
cache-­‐load
is
calculated.
Therefore
the
results
describe
a
backend
IO
and
thus
nothing
else
than
the
volume´s
load
on
the
backend
storage.

5. BVQ whitepaper: Reduction of storage cost - made easy!
- 4 -
Fig.
4:
a
relatively
small
environment
with
exactly
the
same
results.
The
only
difference
is
that
the
dimension
of
the
saving
potential
increases
with
the
capacity.
Again,
it
can
be
assumed
that
70%
of
the
data
are
stored
too
expensively.
But
even
here
an
analysis
is
worthwhile
because
the
cost
and
follow-­‐up
cost
for
maintenance
and
operation
will
exceed
by
far
the
cost
for
analysis
including
software
cost.
The
sharpness
was
reduced
in
this
image
to
protect
the
customer-­‐specific
data.
But
it
is
still
obvious
that
far
more
than
70%
of
all
capacities
utilize
the
existing
performance
potential
with
just
less
than
50%.

6. BVQ whitepaper: Reduction of storage cost - made easy!
- 5 -
Die
BVQ
heatmap
is
the
key
to
success
The
BVQ
heatmap
is
our
tool
to
quickly
establish
an
appropriate
overview
about
the
storage´s
performance
utilization.
The
heatmap
can
be
applied
to
all
levels
of
the
system.
A
consideration
of
the
backend
storage
arrays,
the
single
managed
disks
or
even
higher
grouped
objects
like
the
level
of
applications
or
entire
data
centers
(BVQ
Accounting
Package)
is
possible.
Fig.
5:
a
classic
example
of
the
heatmap
analysis
which
enabled
extremely
high
cost
savings
for
one
of
our
customers.
Via
the
analysis
it
was
possible
to
detect
very
quickly
that
an
extension
of
the
very
high
quality
enterprise
systems
was
not
necessary.
More
than
60%
of
the
systems´
capacities
could
be
released.
The
investment
was
completely
turned
into
nearline.
Comparable
to
a
pipe,
60%
of
the
high-­‐end
storage
volumes
were
moved
to
the
midrange
or
the
new
nearline
class
depending
on
the
requirement.
The
specificity
of
the
heatmap
is
the
fact
that
it
may
be
calculated
on
the
basis
of
different
time
periods.
It
displays
a
comparison
between
the
current
load
and
theoretically
achievable
values.
In
the
new
third
version
of
BVQ
the
treemap
can
be
set
together
with
the
heatmap
to
any
period
in
the
past.
This
makes
it
infinitely
useful
when
it
is
used
during
a
bottleneck
analysis.
It
makes
it
possible
to
determine
at
a
glance
that
not
the
existing
infrastructure
but
another
effect
is
responsible
for
a
bottleneck.

7. BVQ whitepaper: Reduction of storage cost - made easy!
- 6 -
What
are
the
financial
implications
of
such
analyses?
If
such
scenarios
are
calculated
with
a
three-­‐set
the
conclusion
can
quickly
be
made
that
this
form
of
analysis
is
worthwhile
and
it
would
be
a
careless
neglection,
if
it
is
not
performed.
The
attempt
to
express
the
benefits
in
financial
dimensions
is
very
difficult
and
the
result
can
only
be
expressed
as
a
conservative
estimation.
1. Storage
prices
are
extremely
volatile
and
may
differ
depending
on
the
customer
(regardless
from
manufacturer)
2. For
a
first
cost
estimation
a
difference
between
near-­‐line
and
high-­‐end
storage
of
properly
€
700
or
$
900
is
assumed.
3. Please
use
your
own
cost
differences
in
order
to
calculate
your
potential
savings!
Situation
–
major
customer
wants
to
scale
from
2.5PB
to
3PB
• The
analysis
shows
that
there
is
no
need
any
more
to
procure
high-­‐performance
storage
because
many
areas
can
be
moved
to
low-­‐cost
storage
• Now
100%
highly
capacitive
will
be
procured
instead
of
the
usual
procurement
of
70%
high-­‐performance
and
30%
highly
capacitive
• This
allows
potential
replacement
cost
savings
for
the
70%
high-­‐performance
of
(with
a
assumption
of
700
€
price
difference):
o 500TB
*
70%
*
€
700
results
in
€
245.000
o 500TB
*
70%
*
$
900
results
in
$
315.000
• Further
savings
in
the
procurement
o Discs
have
a
higher
capacity,
so
fewer
discs
and
less
enclosures
are
needed
• Future
savings
of
current
expenses
o Less
need
for
space
because
of
reduced
enclosures
o Reduced
energy
cost
o Reduced
maintenance
cost
o Reduced
management
cost

8. BVQ whitepaper: Reduction of storage cost - made easy!
- 7 -
And
the
savings
are
not
even
finished
yet!
As
pointed
out
not
only
reduced
procurement
cost
arise
but
also
reduced
follow-­‐up
cost.
Because
of
the
possible
extension
from
3PB
to
3.5PB
in
the
following
year,
the
savings
effect
is
even
accelerated
over
the
years.
How
much
can
be
saved
in
a
much
smaller
environment?
Simplified
the
savings
are
proportional
to
the
size
of
the
storage
environment.
If
the
customer
mentioned
above
can
save
€
245000
in
the
first
step,
then
it
should
be
possible
to
save
€
100000
to
the
same
extent
in
an
environment
with
1PB.
In
the
30TB
environment
from
the
second
example,
in
this
way
only
€
3,000
will
arise
calculated
with
our
formula
(the
first
year).
However,
it
must
be
considered
that
€
700
price
difference
cannot
be
expected
here,
because
smaller
customers
generally
have
higher
storage
prices.
Not
to
forget:
also
the
analytical
instruments
are
much
cheaper
here
than
for
large
environments.
And
what
is
the
key
to
gain
all
this?
The
key
elements
are
the
transparency
and
the
analytical
methods
which
are
enabled
by
BVQ.
BVQ
is
the
only
product
which
is
able
to
represent
these
relationships
for
SVC
and
Storwize
with
this
high
clarity
and
speed.
The
saving-­‐effects
achieved
by
a
BVQ
solution
are
not
just
limited
to
reduced
procurement
and
operation
cost.
More
saving
effects
like:
1. Reduce
operational
risks
2. Avoid
performance
bottlenecks
or
quickly
control
them
3. Proactive
problems
avoidance
4. Creation
of
added-­‐value
for
the
storage

9. BVQ whitepaper: Reduction of storage cost - made easy!
- 8 -
BVQ
web
pages
BVQ
in
the
WWW
• BVQ
website
http://www.bvq-­‐software.com/
(English)
http://www.bvq-­‐software.de/
(German)
http://bvqwiki.sva.de
(technical
wiki
with
download)
• SVA
website
of
SVA
GmbH
http://www.sva.de/
• International
websites
Developer
work
documents
and
presentations
https://www.ibm.com/developerworks/mydeveloperworks/...
http://tinyurl.com/BVQ-­‐Documents
If
you
are
interested
in
BVQ
a
demo
or
a
performance
analysis,
please
contact
us
via:
http://tinyurl.com/CALL-­‐BVQ
If
you
are
an
IBM
business
partner
with
SVC
or
Storwize
customer
installations
and
you
want
to
sell
BVQ,
please
contact
us
via:
bvq@sva.de
BVQ
is
a
product
from
SVA
System
Vertrieb
Alexander
GmbH