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Capacity
Management
for Web Operations




                         John Allspaw
                     Operations Engineering
the book I’m writing
???
Rules of Thumb

                Planning/Forecasting

               Stupid Capacity Tricks



(with some Flickr statistics sprinkled in)
Things that can cause downtime

       bugs (disguised as capacity problems)
       edge cases (disguised as capacity problems)
       security incidents
       real capacity problems*


* (should be the last thing you need to worry about)
Capacity != Performance


Forget about performance for right
now
Measure what you have right NOW
Don’t count on it getting any better
Thank You HPC Industry!

    Automated Stuff
    Scalable Metric Collection/Display




a lot of great deployment and management tricks
      come from them, adopted by web ops
Good
Measurement
   Tools
  record and
  store
  metrics in/out
  custom metrics
  easily compare
  lightweight-ish

 I
Clouds need planning too

Makes deployment and procurement
easy and quick
But clouds are still resources with
costs and limits, just like your own
stuff
Black-boxes: you may need to pay
even more attention than before
Metrics
System Statistics
Metrics
“Application” Level
                        (photos processed per minute)




                            (average processing time per photo)




 (apache requests)
                       (concurrent busy apache procs)
Metrics
App-level meets system-level




here, total CPU = ~1.12 * # busy apache procs (ymmv)
2400

photos per minute being uploaded right NOW (Tuesday afternoon)
Ceilings
    the most amount of “work” your
resources will allow before degradation
or failure
Forget Benchmarking
Find your ceilings




           what you have left

                     The End
Use real live production data
       to find ceilings




   Production: “it’s like a lab, but bigger!”
Like: database ceilings




           replication lag: bad!
Ceilings




waiting on disk sustained disk I/O wait for
  too much             >40% creates
                         slave lag*
                          *for us,YMMV
35,000
photo requests per second on a Tuesday peak
Safety Factors
Safety Factors



Ceiling * Factor of Safety = UR LIMITZ
Safety Factors




   webserver!
Safety Factors
          what you have left




                                         “safe”
                                         ceiling
                                        @85% CPU




85% total CPU = ~76 busy apache procs
Safety Factors
                         Yahoo Front Page
                     link to Chinese NewYear
                              Photos
                          (8% spike)




(photo requests/second)
Forecasting
Forecasting


Fictional Example:
    webservers
Forecasting

                         peak of the week




Fictional example: 15 webservers. 1 week.
Forecasting




...bigger sample, 6 weeks....isolate the peaks...
Forecasting

                            not too shabby




                 now



...”Add a Trendline” with some decent correlation...
Forecasting

                   this will tell you when it is
      ceiling


                                       when is this?
         what you have left




15 servers @76 busy apache proc limit = 1140 total procs
Forecasting



(1140-726) / 42.751 = 9.68


      (week #10, duh)
Forecasting Automation


Writing excel macros is boring
All we want is “days remaining”, so
all we need is the curve-fit

   Use http://fityk.sf.net to
   automate the curve-fit
Forecasting


  Fictional Example:
storage consumption
Forecasting Automation


                 this will tell
               you when this is




actual flickr storage consumption from early 2005, in GB
                    (ceiling is fictional)
Forecasting Automation
jallspaw:~]$cfityk ./fit-storage.fit                 cmd line script
1> # Fityk script. Fityk version: 0.8.2            output
2> @0 < '/home/jallspaw/storage-consumption.xy'
15 points. No explicit std. dev. Set as sqrt(y)
3> guess Quadratic
New function %_1 was created.
4> fit
Initial values: lambda=0.001 WSSR=464.564
#1: WSSR=0.90162 lambda=0.0001 d(WSSR)=-463.663 (99.8059%)
#2: WSSR=0.736787 lambda=1e-05 d(WSSR)=-0.164833 (18.2818%)
#3: WSSR=0.736763 lambda=1e-06 d(WSSR)=-2.45151e-05 (0.00332729%)
#4: WSSR=0.736763 lambda=1e-07 d(WSSR)=-3.84524e-11 (5.21909e-09%)
Fit converged.
Better fit found (WSSR = 0.736763, was 464.564, -99.8414%).
5> info formula in @0
# storage-consumption
14147.4+146.657*x+0.786854*x^2
6> quit
bye...
Forecasting Automation
fityk gave:
      y = 0.786854x2 + 146.657x + 14147.4
                  ( R2 = 99.84)
Excel gave:
        y = 0.7675x2 + 146.96x + 14147.3
                  ( R2 = 99.84)


               (SAME)
Capacity Health

12,629 nagios checks
1314 hosts
6 datacenters
4 photo “farms”
farm = 2 DCs (east/west)
High and Low Water Marks

      alert if higher




      alert if lower



Per server, squid requests per second
A good dashboard looks
                something like...

                                                                Est
                  limit/   ceiling    limit current    %       days
 type      #        box     units    (total) (peak)   peak     left
                           busy
 www       20      80                1600    1000     62.50%   36
                           procs
 shard                      I/O
           20      40                 800    220      27.50%   120
  db                        wait
 squid     18      950     req/sec 17,100 11,400 66.67%        48


(yes, fictional numbers)
Diagonal Scaling

vertically scaling your already horizontal nodes




 Image processing machines
 Replace Dell PE860s with HP
 DL140G3s
Diagonal Scaling
     example: image processing


                              4 cores




                              8 cores



(about the same CPU “usage” per box)
Diagonal Scaling
    example: image processing throughput


                            ~45 images/min @ peak




                           ~140 images/min @ peak

    (same CPU usage, but ~3x more work)
“processing” means making 4 sizes from originals
Diagonal Scaling
               example: image processing
went from:
                         3008.4         1035        23U
      23 Dell PE860s     Watts       photos/min     rack




to:
      8 HP DL140 G3s     1036.8
                         Watts
                                        1120
                                     photos/min
                                                      8U
                                                     rack
                   !!!            (75% faster, even)
3.52




terabytes will be consumed today (on a Tuesday)
2nd Order Effects
(beware the wandering bottleneck)



               LB
                          running hot,
                          so add more
             www    www




     db        search      memcached
2nd Order Effects
    (beware the wandering bottleneck)



                             LB               running great now,
                                               so more traffic!
  now
these run        www   www        www   www

   hot
            db           search                memcached
Stupid Capacity Tricks
Stupid Capacity Tricks
      quick and dirty management
                   DSH
     http://freshmeat.net/projects/dsh

[root@netmon101 ~]# cat group.of.servers

www100
www118
dbcontacts3
admin1
admin2
Stupid Capacity Tricks
         quick and dirty management


[root@netmon101 ~]# dsh -N group.of.servers

dsh> date
executing 'date'
www100:          Mon   Jun   23   14:14:53   UTC   2008
www118:          Mon   Jun   23   14:14:53   UTC   2008
dbcontacts3:     Mon   Jun   23   07:14:53   PDT   2008
admin1:          Mon   Jun   23   14:14:53   UTC   2008
admin2:          Mon   Jun   23   14:14:53   UTC   2008
dsh>
Stupid Capacity Tricks
        Turn Stuff OFF


Disable heavy-ish features of the site
          (on/off switches)
  We have 195 different things to
   disable in case of emergency.
Stupid Capacity Tricks
     Turn Stuff OFF

       uploads (photo)
       uploads (video)
       uploads by email
      various API things
    various mobile things
    various search things
         etc., etc.
Stupid Capacity Tricks
       Outages Happen

Host your outage/status/blog page in
    more than one datacenter.
Tell your users WTF is going on,
they’ll appreciate it.
Stupid Capacity Tricks
     Hit the Pause Button



Bake the dynamic into static
Some Y! properties have a big red
button to instantly bake (and un-
bake) at will
thanks
http://flickr.com/photos/bondidwhat/402089763/
http://flickr.com/photos/74876632@N00/2394833962/
http://flickr.com/photos/42311564@N00/220394633/
http://flickr.com/photos/unloveable/2422483859/
http://flickr.com/photos/absolutwade/149702085/
http://flickr.com/photos/krawiec/521836276/
http://flickr.com/photos/eschipul/1560875648/
http://flickr.com/photos/library_of_congress/2179060841/
http://flickr.com/photos/jekkyl/511187885/
http://flickr.com/photos/ab8wn/368021672/
http://flickr.com/photos/jaxxon/165559708/
http://flickr.com/photos/sparktography/75499095/
We’re Hiring!
flickr.com/jobs


Come see me!
questions?

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