The document outlines the agenda for CloudCamp Chicago held on December 13, 2012, featuring various speakers discussing topics such as Node.js on AWS, APIs in cloud environments, big data with Hadoop, and managing private clouds. Each speaker highlighted the benefits and challenges related to their subjects, advocating for tools like Node.js and Hadoop for scalable applications and data analysis. Additionally, an unpanel discussion focused on cloud security and visibility concerns in relation to control over cloud services.

1. Sponsored by
Welcome to
Cloud Chicago
Hosted by
Live Tweet on the second
screen by using:
#cloudcamp
@cloudcamp_chi
1
Thursday, December 13, 12

2. Agenda
6:00pm Registration, Food, Drinks and
Networking
6:30 Opening Remarks, Patrick Kerpan, CoehsiveFT
6:45 Lightning Talks
Dave Falck, Model Metrics: node.js on AWS
Paul Mantz, CohesiveFT: Working with APIs
Bob Chojnacki, Jellyvision Labs: Hadoop on AWS
Karl Zimmerman, Steadfast: Keep control with the Private Cloud
7:45 Unpanel: “Who’s in Control of Your Cloud? Security and
Visibility”
Emceed by Mike Dorosh, IBM & Patrick Kerpan, CoehsiveFT
8:30 Breakout Sessions
9:00 Wrap Up - Drinks, anyone?
#cloudcamp
@cloudcamp_chi
Thursday, December 13, 12

3. Sponsored by
Dave Falck, Customer Solutions Engineer Hosted by
#cloudcamp
@cloudcamp_chi
Thursday, December 13, 12

4. Node.js
+
AWS
@davidfalck

5. Why
the
Node.js
Buzz?
* LinkedIn’s
entire
mobile
software
stack
is
completely
built
in
Node
* Why?
Scale.
* Huge
performance
gains
compared
to
what
they
were
using
before
(Ruby
on
Rails)
* Went
from
running
15
servers
with
15
instances
(virtual
servers)
on
each
physical
machine,
to
just
four
instances
that
can
handle
double
the
traffic.

6. What
is
Node.js?
* Javascript
platform
based
on
Google
Chrome
V8
JS
Engine
* Ryan
Dahl
(Joyent)
* Event-­‐driven,
non-­‐blocking
I/O
model
to
allow
your
applications
to
scale
while
keeping
you
from
having
to
deal
with
threads,
polling,
timeouts,
and
event
loops
* FAST
* Used
for
real-­‐time,
data-­‐intensive
apps
(mobile!)
* POPULAR

7. Node.js
on
GitHub

8. Hello
World
var
http
=
require('http');
http.createServer(function
(req,
res)
{
res.writeHead(200,
{'Content-­‐Type':
'text/plain'});
res.end('Hello
Worldn');
}).listen(1337,
'127.0.0.1');

9. What
makes
Node.js
so
fast?
* Thread-­‐based
networking
is
inefficient
and
difficult
* Node
shows
much
better
memory
efficiency
under
high-­‐
loads
than
systems
which
allocate
2mb
thread
stacks
for
each
connection.
* Users
of
Node
are
free
from
worries
of
dead-­‐locking
the
process
(*there
are
no
locks*)
* Almost
no
function
in
Node
directly
performs
I/O,
so
the
process
never
blocks.
* Because
nothing
blocks,
less-­‐than-­‐expert
programmers
are
able
to
develop
fast
systems

10. Under
the
Node.js
hood
Javascript?

11. Under
the
Node.js
hood
* Javascript!
* Platform
independent
* Easy
to
use
* Ubiquitous
* Google
Chrome’s
V8
Javascript
Engine
* Translates
JS
into
machine
code
(not
interpreted)

12. When
not
to
use
Node.js
* Node.js
is
not
ideal
for
CPU
intensive
jobs
like
sorting,
transformations,
number
crunching,
analytics…
* Traditional
CRUD
web
apps
that
need
to
be
highly
concurrent,
performance
degradation
will
occur
when
the
data
is
needed
to
be
transformed…
* You
can
offload
processing
to
another
language
that
is
better
at
making
use
of
the
CPU
* Cultural
fit?
Too
new?
You
decide…

13. Node.js
+
AWS
* Dec
6th:
AWS
released
developer
preview
of
node.js
libraries
to
access
AWS:
* DynamoDB
* S3
* EC2
* SWS
* Allows
you
to
manage
parallel
calls
to
several
AWS
web
services

14. Node.js
+
Other
Clouds
* Azure
* Joyent
* EngineYard
* Heroku

15. More
info
* http://nodejs.org
* http://en.wikipedia.org/wiki/Nodejs
* http://aws.typepad.com/aws/2012/12/aws-­‐sdk-­‐for-­‐
nodejs-­‐now-­‐available-­‐in-­‐preview-­‐form.html
* http://www.jamesward.com/2011/06/21/getting-­‐
started-­‐with-­‐node-­‐js-­‐on-­‐the-­‐cloud/
* http://venturebeat.com/2011/08/16/linkedin-­‐node/

16. Sponsored by
Paul Mantz, Software Engineer Hosted by
#cloudcamp
@cloudcamp_chi
Thursday, December 13, 12

17. APIs in Cloud Environments
Paul Mantz
Copyright CohesiveFT - Dec 13, 2012 1
Thursday, December 13, 12

18. API Command-Line Clients
• Benefits to Creating API Command-Line Clients
• Lowers barrier of entry
• Familiar to technical consumers
• Advanced usage cases
• Integrates into existing toolsets
Copyright CohesiveFT - Dec 13, 2012 2
Thursday, December 13, 12

19. API Command-Line Clients
Excellent Internal Developer Tool
• Excellent for testing and rapid development
• Useful operations tool
Copyright CohesiveFT - Dec 13, 2012 3
Thursday, December 13, 12

20. API Command-Line Clients
Reference Implementation
• Gives developers an example to integrate the API
• Helps users model workflows
• DSL
Copyright CohesiveFT - Dec 13, 2012 4
Thursday, December 13, 12

21. API Command-Line Clients
Excellent Demo Tool
• Quick installation, often one file
Copyright CohesiveFT - Dec 13, 2012 5
Thursday, December 13, 12

22. Sponsored by
Bob Chojnacki, Programmer Hosted by
#cloudcamp
@cloudcamp_chi
Thursday, December 13, 12

23. Big
Data
in
the
Cloud
A
Journey
into
the
unknown

24. Who
Jellyvision
is
and
why
are
analy9cs
important
to
us
• We
create
interac9ve
experiences
– Desktop
– Mobile
• …
which
ask
ques9ons,
inform
people,
generate
leads
• “Virtual
Advisors”
• We
also
collect
analy9cs
in
real
9me
to
generate
reports
about:
– How
people
answered
a
ques9on
– Where
they
dropped
out
– Lots
of
impressive
stats!

25. The
Problem
• Longer
term
projects
and
high
volume
projects
causing
MySQL
to
bust
at
the
seams
• Some
types
of
reports
taking
too
long,
or
causing
MySQL
to
crash
if
we
include
too
much
data
• In
all
fairness,
we
could
probably
tune
MySQL,
throw
it
on
bigger
servers,
more
memory
• Diminishing
returns
• MySQL
is
fine
for
collec9ng
the
data…

26. The
Solu9on
• Hadoop!
• Why
Hadoop?
Lots
of
possibili9es
out
there,
but
which
one
to
use?
Cassandra,
CouchDB,
Hadoop,
Membase,
MongoDB,
Neo4j,
…
• Big
Data
meetups
tended
to
have
lots
of
people
using
Hadoop
• And
I
knew
others
using
it.
• And
Hortonworks
had
a
fancy
point
and
click
solu9on
I
could
use
to
get
started
quickly

27. Op9ons
with
op9ons
• Now
that
I
picked
Hadoop,
I
had
several
op9ons,
and
op9ons
within
op9ons
to
use
to
analyze
my
data:
– Hive,
Pig,
MapReduce,
Java,
R
• I
knew
Java
• MapReduce
seemed
to
make
sense
• I’ll
probably
play
with
Hive
and
Pig
next

28. It’s
All
About
The
Data
• Visit
data
• Event
data
• Denormaliza9on
of
data
• Generated
a
ton
of
fake
data:
– Started
with
600K
visits,
3M
events
– Moved
up
to
1.8M
visits,
60M
events

29. Make
it
so
• First
experience:
Hortonworks
Virtual
Sandbox
– Single
node
AMI
at
Amazon
– Hadoop
1.0
– 600K
visits,
3M
events
• On
our
exis9ng
placorm
we
needed
to
break
reports
up
into
smaller
chunks
for
some
data
because
MySQL
could
not
handle
it.
• Results!
What
would
have
taken
hours,
took
only
5
minutes
on
a
single
node
Hadoop
"cluster”
• In
reality,
some
of
the
queries
I
could
also
run
with
command-­‐line
tools
(wc,
grep,
awk)
on
the
data
considerably
faster
than
even
Hadoop.
• Important
lessons
learned
so
far:
– Think
outside
the
RDBMS:
they
are
great,
but
it
may
not
make
sense
for
all
types
data

30. Looking
at
more
real
data
• Now,
lets
generate
data
that
is
much
closer
to
some
of
our
product
• Instead
of
one
ques9on
and
answer,
how
about
15
ques9ons?
Add
in
some
other
events
gives
a
total
of
34
events.
• Throw
in
some
people
returning,
some
of
them
mul9ple
9mes
• Throw
in
some
people
who
don't
start
the
conversa9on,
etc.
• Run
my
lijle
auto-­‐data-­‐generator
and
BOOM!
20
million
events
and
4.4GB
later
I
have
my
data…
• …
which
took
up
too
much
disk
space
to
run
on
the
demo
system
I
was
using.
Might
as
well
turbo-­‐charge
this
puppy...

31. More
disk
space!
• Full
install
of
Hadoop
(Hortonworks
HDP)
• Single
node
• 600K
visits,
20M
events
– 6m
29s,
~30s
aner
map
phase
completed
• 1.8M
visits,
60M
events
– 18m
3s,
~90s
aner
map
phase
completed

32. More
nodes
• 3
nodes:
11m
• 4
nodes:
9m
16s
• Yay!
Nodes!

33. Caveats
• Not
using
Hadoop
to
its
fullest
/
basically
a
weekend
job
• Algorithms
employed
in
this
example
probably
won't
end
up
it
a
book
alongside
Knuth’s

34. Next
steps
• Make
sure
results
on
real
data
lines
up
• Integrate
with
team
to
generate
reports
they
need

35. End
stuff
• Thanks
to
the
folks
at
Hortonworks
who
answered
my
fran9c
and
spas9c
ques9ons.

36. Sponsored by
Karl Zimmerman, President Hosted by
#cloudcamp
@cloudcamp_chi
Thursday, December 13, 12

37. Keep Your Control.
Private Cloud with Karl Zimmerman, CEO of Steadfast.

38. Private Cloud:
What do we mean?
Private cloud is a form of cloud computing where the
customer has some control/ownership of the service
implementation. It is a scalable, elastic IaaS solution
based on cloud computing but with more control over
resources.

39. Private Cloud:
What are the advantages?
Security
Availability
No vendor lock-in
Ease of management

40. Private Cloud:
Security
Dedicated & segregated resources
More options to integrate with existing security

41. Private Cloud:
Availability
Understanding and control of the infrastructure
Get the resources you need, when you need them
You're not subject to the whims of other users

42. Private Cloud:
Vendor Lock-In
No "secret sauce."
Utilize true open source

43. Private Cloud:
Management
Easier to find employees with general IT knowledge
Utilize a broader array of tools and software
Get support/assistance from multiple levels

44. Private Cloud:
To Summarize
Private cloud can deliver what you need out of a public
cloud, but giving you more control. Losing control over
security, availability and issues like vendor lock-in and
management vanish into thin air like, well, a cloud. And the
fact that it doesn’t have to cost you more is a plus, too.

45. Sponsored by
Unpanel: “Who’s in Control of Your
Cloud? Security and Visibility”
Hosted by
Emceed by:
Mike Dorosh, Program Manager –Cloud Technical Partnerships, IBM
& Patrick Kerpan CEO, CoehsiveFT
#cloudcamp
@cloudcamp_chi
Thursday, December 13, 12

46. #cloudcamp
@cloudcamp_chi
Thursday, December 13, 12