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Copyright	
  ©	
  2014	
  Splunk	
  Inc.	
  
Mustafa	
  Ahamed	
  
Director,	
  Product	
  Management	
  
Eric	
  Woo	
  
Senior	
  SoEware	
  Engineer	
  
Anirban	
  Rahut	
  
Senior	
  SoEware	
  Engineer	
  
	
  
	
  
What’s	
  New	
  In	
  Search	
  
Head	
  Clustering	
  
Disclaimer	
  
2	
  
During	
  the	
  course	
  of	
  this	
  presentaLon,	
  we	
  may	
  make	
  forward-­‐looking	
  statements	
  regarding	
  future	
  events	
  or	
  the	
  
expected	
  performance	
  of	
  the	
  company.	
  We	
  cauLon	
  you	
  that	
  such	
  statements	
  reflect	
  our	
  current	
  expectaLons	
  and	
  
esLmates	
  based	
  on	
  factors	
  currently	
  known	
  to	
  us	
  and	
  that	
  actual	
  events	
  or	
  results	
  could	
  differ	
  materially.	
  For	
  
important	
  factors	
  that	
  may	
  cause	
  actual	
  results	
  to	
  differ	
  from	
  those	
  contained	
  in	
  our	
  forward-­‐looking	
  statements,	
  
please	
  review	
  our	
  filings	
  with	
  the	
  SEC.	
  The	
  forward-­‐looking	
  statements	
  made	
  in	
  the	
  this	
  presentaLon	
  are	
  being	
  made	
  as	
  
of	
  the	
  Lme	
  and	
  date	
  of	
  its	
  live	
  presentaLon.	
  If	
  reviewed	
  aEer	
  its	
  live	
  presentaLon,	
  this	
  presentaLon	
  may	
  not	
  contain	
  
current	
  or	
  accurate	
  informaLon.	
  We	
  do	
  not	
  assume	
  any	
  obligaLon	
  to	
  update	
  any	
  forward-­‐looking	
  statements	
  we	
  may	
  
make.	
  In	
  addiLon,	
  any	
  informaLon	
  about	
  our	
  roadmap	
  outlines	
  our	
  general	
  product	
  direcLon	
  and	
  is	
  subject	
  to	
  change	
  
at	
  any	
  Lme	
  without	
  noLce.	
  It	
  is	
  for	
  informaLonal	
  purposes	
  only,	
  and	
  shall	
  not	
  be	
  incorporated	
  into	
  any	
  contract	
  or	
  
other	
  commitment.	
  Splunk	
  undertakes	
  no	
  obligaLon	
  either	
  to	
  develop	
  the	
  features	
  or	
  funcLonality	
  described	
  or	
  to	
  
include	
  any	
  such	
  feature	
  or	
  funcLonality	
  in	
  a	
  future	
  release.	
  
Agenda	
  
!   What	
  is	
  Search	
  Head	
  Clustering?	
  
!   Business	
  Benefits	
  of	
  Search	
  Head	
  Clustering	
  
!   SHC	
  ConfiguraLon	
  /	
  ReplicaLon	
  
!   App	
  Deployment	
  
!   Tips	
  and	
  Tricks	
  	
  
–  MigraLon	
  	
  
!   Q&A	
  
	
  
3	
  
Search	
  Head	
  Clustering	
  	
  
Ability	
  to	
  group	
  search	
  heads	
  into	
  a	
  cluster	
  in	
  order	
  	
  to	
  provide	
  	
  	
  
Highly	
  Available	
  and	
  Scalable	
  search	
  services	
  
4	
  
MISSION	
  
CRITICAL	
  
ENTERPRISE	
  
5	
  
	
  
Horizontal	
  Scaling	
  	
  
	
  	
  
	
  
Always-­‐on	
  Search	
  Services	
  	
  
	
  
	
  
Consistent	
  User	
  Experience	
  
	
  
	
  
Easy	
  to	
  add	
  /	
  manage	
  
premium	
  contents	
  (apps)	
  
Business	
  Benefits	
  of	
  SHC	
  
SHP	
  	
  	
  vs.	
  	
  	
  SHC	
  
SHC	
  SHP	
  
•  Available	
  since	
  v4.2	
  
•  Sharing	
  configuraLons	
  through	
  NFS	
  
•  Single	
  point	
  of	
  failure	
  
•  Performance	
  issues	
  
•  No	
  NFS	
  
•  ReplicaLon	
  using	
  local	
  storage	
  
•  Commodity	
  hardware	
  
6	
  
NFS	
  
 	
  
1.  No	
  Single	
  Point	
  of	
  
Failures	
  
2.  “One	
  ConfiguraLon”	
  
across	
  SH	
  
3.  Horizontal	
  Scaling	
  
7	
  
1.  Dynamic	
  Captain	
  
2.  AutomaLc	
  Config	
  	
  
replicaLon	
  across	
  SH	
  
3.  Ability	
  to	
  add/remove	
  
nodes	
  on	
  running	
  cluster	
  
Design	
  Goals	
   ImplementaLon	
  
SHC	
  –	
  How	
  Does	
  it	
  Work?	
  
8	
  
1.  Group	
  search	
  heads	
  into	
  a	
  cluster	
  
2.  A	
  captain	
  gets	
  elected	
  dynamically	
  
3.  User	
  created	
  reports/dashboards	
  automaLcally	
  
replicated	
  to	
  other	
  search	
  heads	
  
1	
   2	
  
3	
  
Anatomy	
  &	
  Cluster	
  
Bring	
  up	
  
Search	
  Head	
  Cluster	
  Bring	
  Up	
  
10	
  
captain	
  
config-­‐log	
  
{s1,s2,	
  ...,	
  sn}	
  
•  Bootstrap	
  captain	
  
•  Bring-­‐up	
  members	
  
•  Captain	
  establishes	
  authority	
  
•  Members	
  join/register	
  
•  CLI	
  based	
  cluster	
  scale/shrink	
  
	
  	
  	
  ...	
  
members	
  
Job	
  Scheduling	
  
Use	
  Case	
  
12	
  
!   Scale	
  search	
  capacity	
  
!   Enable	
  more	
  reports,	
  dashboards,	
  alerts	
  
!   Load	
  balance	
  user	
  sessions	
  (onboarding)	
  
•  Captain	
  is	
  job	
  scheduler	
  
•  Eliminates	
  job-­‐server	
  need	
  
•  Load-­‐based	
  heurisLc	
  
Job	
  Scheduling	
  OrchestraLon	
  
13	
  
captain	
  
scheduler	
  
	
  	
  	
  ...	
  
search	
  
	
  	
  	
  1	
  
search	
  
	
  	
  	
  2	
  
LOAD	
  
SUCC	
  
FAIL	
  
load	
  
balancer	
  
search	
  
	
  	
  3	
  	
  
Details	
  
14	
  
!   Captain	
  updates	
  RA/DM	
  summaries	
  on	
  indexers.	
  
!   Scheduler	
  limits	
  honored	
  across	
  the	
  cluster	
  
!   Real	
  Lme	
  scheduled	
  searches	
  run	
  one	
  instance	
  across	
  cluster	
  
!   Auto-­‐failover	
  –	
  New	
  captain	
  becomes	
  scheduler	
  
!   captain_is_adhoc_searchhead	
  knob	
  to	
  reduce	
  captain	
  load	
  
Alerts	
  &	
  Suppression	
  
15	
  
!   Alerts	
  fired	
  when	
  results	
  of	
  search	
  meet	
  alerLng	
  criteria	
  
–  Historical	
  Searches	
  –	
  within	
  10	
  seconds	
  aEer	
  job	
  completes	
  
–  RealTime	
  searches	
  –	
  ongoing	
  basis	
  
!   Captain	
  merges	
  and	
  maintains	
  global	
  view	
  of	
  alerts	
  
!   Suppression	
  informaLon	
  centralized	
  by	
  the	
  captain	
  
!   Merged	
  Alerts/Suppression	
  sent	
  back	
  to	
  members	
  
High	
  Availability	
  of	
  
Search	
  Results	
  
Search	
  Results	
  primer	
  
17	
  
Search	
  -­‐	
  HEAD	
  
indexers	
  
stream	
  results	
  
reduce	
  
map	
  
Other	
  Names	
  
1.  search	
  results	
  
2.  search	
  arLfact	
  
3.  dispatch	
  directory	
  
4.  SID	
  
$SPLUNK_HOME/var/
run/splunk/dispatch/
scheduler__admin__sear
ch__mysearch_at_14107
08600_345	
  
sourcetype	
  =	
  access_combined	
  	
  |	
  stats	
  count	
  by	
  clienLp	
  
Dispatch	
  dir	
  needs	
  to	
  be	
  replicated	
  to	
  	
  
mulCple	
  nodes	
  to	
  tolerate	
  node	
  failures	
  
ArLfact	
  ReplicaLon	
  
18	
  
	
  	
  	
  ...	
  
succ	
  
succ	
  
•  Captain	
  orchestrates	
  replicaLon	
  
•  Default	
  replicaLon_factor=3	
  
•  Success	
  failure	
  ACK’d	
  to	
  captain	
  
•  Asynch	
  Replicate	
  on	
  Proxy	
  	
  
•  ReplicaLon	
  policy	
  enforced	
  by	
  fixups	
   replica-­‐1	
  	
  
replica-­‐2	
  	
  
succ	
  
captain	
  
replicate	
  
orig	
  
 	
  	
  ArLfact	
  Proxy-­‐ing	
  
19	
  
!   ReplicaLon	
  Guarantees	
  HA&DR	
  but...	
  
!   SID	
  not	
  available	
  on	
  all	
  nodes	
  *locally*	
  
!   RealTime	
  searches	
  are	
  not	
  replicated	
  
!   We	
  use	
  proxy-­‐ing	
  to	
  fill	
  these	
  gaps	
  
!   Proxying	
  on	
  REST	
  request	
  
	
  
captain	
  
over	
  HB	
  
locaLon	
  	
  
log	
  
r1	
  
proxy	
  
orig	
  
AuthenCcaCon	
  is	
  
cluster	
  aware!!	
  
HB	
  =	
  Heartbeat	
  
r2	
  
async	
  
replicate	
  
Adhoc	
  Search	
  Management	
  
20	
  
!   Adhoc	
  search	
  -­‐	
  interacLve	
  search	
  run	
  from	
  a	
  user	
  session	
  
!   Adhoc	
  searches	
  not	
  replicated	
  	
  
!   Captain,	
  however	
  will	
  have	
  global	
  knowledge	
  of	
  all	
  searches	
  
!   GET	
  services/search/jobs	
  will	
  return	
  the	
  global	
  list	
  of	
  searches	
  
!   You	
  can	
  proxy	
  and	
  access	
  adhoc	
  searches	
  from	
  any	
  node	
  
Reaping	
  of	
  Search	
  ArLfacts	
  
21	
  
!   Reaping	
  –	
  DeleLon	
  of	
  search	
  results	
  when	
  TTL	
  (Lme	
  to	
  live)	
  expires	
  
!   Search	
  ArLfacts	
  reaped	
  from	
  the	
  origin	
  node	
  
!   Captain	
  orchestrates	
  reaps	
  of	
  the	
  replicas	
  
Auto	
  Failover	
  
HA	
  &	
  Auto-­‐Failover	
  
23	
  
Design	
  Goals	
  
1.  No	
  Single	
  Point	
  of	
  Failure	
  
2.  ConLnuous	
  UpLme	
  
3.  Consistent	
  User	
  Experience	
  
ImplementaLon	
  
1.  Dynamic	
  Captain	
  elecLon	
  
2.  Auto	
  Failover	
  
3.  Proxying	
  for	
  consistent	
  view	
  
Dynamic	
  Captain	
  
24	
  
!   RaE	
  Consensus	
  Protocol	
  from	
  Stanford	
  
–  Diego	
  Ongaro	
  &	
  John	
  Osterhout	
  
–  Acknowledge	
  Diego	
  Ongaro	
  for	
  help!	
  
!   SHC	
  uses	
  RAFT	
  for	
  LE	
  and	
  Auto	
  Failover	
  
RV	
  =	
  	
   	
  Request	
  Vote	
  	
  	
  
LE	
  =	
   	
  Leader	
  ElecLon	
  
SHC	
  =	
  	
  Search	
  Head	
  Clustering	
  
	
  
S4	
  
S2	
  
S5	
  
S3	
  
S1	
  
captain	
  
new	
  	
  
captain	
  
Auto-­‐Failover	
  
25	
  
new	
  captain	
  
	
  	
  	
  ...	
  
members	
  
old	
  captain	
  
arLfacts	
  
running	
  jobs	
  
alerts,	
  etc	
  
search	
  load	
  
scheduler	
  
Fixups	
  
ConfiguraLon	
  
Management	
  
ConfiguraLon	
  Files	
  
!   Custom	
  user	
  content	
  
–  Reports	
  
–  Dashboards	
  
!   Search-­‐Lme	
  knowledge	
  
–  Field	
  extracLons	
  
–  Event	
  types	
  
–  Macros	
  
!   System	
  configuraLons	
  
–  Inputs,	
  forwarding,	
  authenLcaLon	
  
Goal	
  
28	
  
!   Consistent	
  user	
  experience	
  across	
  all	
  search	
  heads	
  
!   Changes	
  made	
  on	
  one	
  member	
  are	
  reflected	
  on	
  all	
  members	
  
ConfiguraLon	
  Changes	
  
29	
  
!   Users	
  customize	
  search	
  and	
  UI	
  configuraLons	
  via	
  UI/CLI/REST	
  
–  Save	
  report	
  
–  Add	
  panel	
  to	
  dashboards	
  
–  Create	
  field	
  extracLon	
  
!   Administrators	
  modify	
  system	
  configuraLons	
  
–  Configure	
  forwarding	
  
–  Deploy	
  centralized	
  authenLcaLon	
  (e.g.	
  LDAP)	
  
–  Install	
  enLrely	
  new	
  app	
  or	
  hand-­‐edited	
  configuraLon	
  
Search	
  and	
  UI	
  ConfiguraLons	
  
30	
  
!   Changes	
  to	
  search	
  and	
  UI	
  configuraLons	
  are	
  replicated	
  across	
  the	
  
search	
  head	
  cluster	
  automaLcally	
  
!   Goal:	
  eventual	
  consistency	
  
ConfiguraLon	
  ReplicaLon	
  
31	
  
my_dashboard.xml	
  
C	
  
Concurrent	
  Changes	
  
32	
  
C	
  
Custom	
  App	
  Content	
  
33	
  
!   App	
  devs	
  may	
  "opt-­‐in"	
  their	
  custom	
  configuraLons	
  for	
  replicaLon	
  
under	
  search	
  head	
  clustering	
  
!   Example	
  server.conf	
  from	
  an	
  app	
  would	
  look	
  like:	
  
	
  [shclustering]	
  
	
  conf_replicaLon_include.my_custom_file	
  =	
  true	
  
System	
  ConfiguraLons	
  
34	
  
!   Recall:	
  only	
  changes	
  to	
  search	
  and	
  UI	
  configuraLons	
  are	
  replicated	
  
across	
  the	
  search	
  head	
  cluster	
  automaLcally	
  
!   hanges	
  to	
  system	
  configuraLons	
  are	
  not	
  replicated	
  automaLcally	
  
because	
  of	
  their	
  high	
  potenLal	
  impact	
  
!   How	
  are	
  system	
  configuraLons	
  kept	
  consistent	
  then?	
  
!   Deployer:	
  a	
  single,	
  well-­‐controlled	
  instance	
  outside	
  of	
  the	
  cluster	
  
!   ConfiguraLons	
  should	
  be	
  tested	
  on	
  dev/QA	
  instances	
  prior	
  to	
  deploy	
  
D	
  
ConfiguraLon	
  Deployment	
  
35	
  
UI	
  
36	
  
Tips	
  &	
  Tricks	
  
Best	
  PracLces	
  	
  
!   Deployer	
  Instance	
  
–  Can	
  piggyback	
  Cluster	
  Master	
  or	
  Deployment	
  Server	
  
–  RecommendaLon	
  is	
  to	
  run	
  Deployer	
  on	
  separate	
  instance	
  
!   Run	
  CLI	
  to	
  get	
  status	
  about	
  SHC	
  
–  ./splunk	
  show	
  shcluster-­‐status	
  
	
  
	
  
38	
  
Summary	
  
Key	
  Benefits	
  of	
  SHC	
  
40	
  
	
  
Horizontal	
  Scaling	
  	
  
	
  	
  
	
  
Always-­‐on	
  Search	
  Services	
  	
  
	
  
	
  
Consistent	
  User	
  Experience	
  
	
  
	
  
Easy	
  to	
  add	
  /	
  manage	
  
premium	
  contents	
  (apps)	
  
Q	
  &	
  A	
  
THANK	
  YOU	
  

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Conf2014_SearchHeadClustering

  • 1. Copyright  ©  2014  Splunk  Inc.   Mustafa  Ahamed   Director,  Product  Management   Eric  Woo   Senior  SoEware  Engineer   Anirban  Rahut   Senior  SoEware  Engineer       What’s  New  In  Search   Head  Clustering  
  • 2. Disclaimer   2   During  the  course  of  this  presentaLon,  we  may  make  forward-­‐looking  statements  regarding  future  events  or  the   expected  performance  of  the  company.  We  cauLon  you  that  such  statements  reflect  our  current  expectaLons  and   esLmates  based  on  factors  currently  known  to  us  and  that  actual  events  or  results  could  differ  materially.  For   important  factors  that  may  cause  actual  results  to  differ  from  those  contained  in  our  forward-­‐looking  statements,   please  review  our  filings  with  the  SEC.  The  forward-­‐looking  statements  made  in  the  this  presentaLon  are  being  made  as   of  the  Lme  and  date  of  its  live  presentaLon.  If  reviewed  aEer  its  live  presentaLon,  this  presentaLon  may  not  contain   current  or  accurate  informaLon.  We  do  not  assume  any  obligaLon  to  update  any  forward-­‐looking  statements  we  may   make.  In  addiLon,  any  informaLon  about  our  roadmap  outlines  our  general  product  direcLon  and  is  subject  to  change   at  any  Lme  without  noLce.  It  is  for  informaLonal  purposes  only,  and  shall  not  be  incorporated  into  any  contract  or   other  commitment.  Splunk  undertakes  no  obligaLon  either  to  develop  the  features  or  funcLonality  described  or  to   include  any  such  feature  or  funcLonality  in  a  future  release.  
  • 3. Agenda   !   What  is  Search  Head  Clustering?   !   Business  Benefits  of  Search  Head  Clustering   !   SHC  ConfiguraLon  /  ReplicaLon   !   App  Deployment   !   Tips  and  Tricks     –  MigraLon     !   Q&A     3  
  • 4. Search  Head  Clustering     Ability  to  group  search  heads  into  a  cluster  in  order    to  provide       Highly  Available  and  Scalable  search  services   4   MISSION   CRITICAL   ENTERPRISE  
  • 5. 5     Horizontal  Scaling           Always-­‐on  Search  Services         Consistent  User  Experience       Easy  to  add  /  manage   premium  contents  (apps)   Business  Benefits  of  SHC  
  • 6. SHP      vs.      SHC   SHC  SHP   •  Available  since  v4.2   •  Sharing  configuraLons  through  NFS   •  Single  point  of  failure   •  Performance  issues   •  No  NFS   •  ReplicaLon  using  local  storage   •  Commodity  hardware   6   NFS  
  • 7.     1.  No  Single  Point  of   Failures   2.  “One  ConfiguraLon”   across  SH   3.  Horizontal  Scaling   7   1.  Dynamic  Captain   2.  AutomaLc  Config     replicaLon  across  SH   3.  Ability  to  add/remove   nodes  on  running  cluster   Design  Goals   ImplementaLon  
  • 8. SHC  –  How  Does  it  Work?   8   1.  Group  search  heads  into  a  cluster   2.  A  captain  gets  elected  dynamically   3.  User  created  reports/dashboards  automaLcally   replicated  to  other  search  heads   1   2   3  
  • 9. Anatomy  &  Cluster   Bring  up  
  • 10. Search  Head  Cluster  Bring  Up   10   captain   config-­‐log   {s1,s2,  ...,  sn}   •  Bootstrap  captain   •  Bring-­‐up  members   •  Captain  establishes  authority   •  Members  join/register   •  CLI  based  cluster  scale/shrink        ...   members  
  • 12. Use  Case   12   !   Scale  search  capacity   !   Enable  more  reports,  dashboards,  alerts   !   Load  balance  user  sessions  (onboarding)  
  • 13. •  Captain  is  job  scheduler   •  Eliminates  job-­‐server  need   •  Load-­‐based  heurisLc   Job  Scheduling  OrchestraLon   13   captain   scheduler        ...   search        1   search        2   LOAD   SUCC   FAIL   load   balancer   search      3    
  • 14. Details   14   !   Captain  updates  RA/DM  summaries  on  indexers.   !   Scheduler  limits  honored  across  the  cluster   !   Real  Lme  scheduled  searches  run  one  instance  across  cluster   !   Auto-­‐failover  –  New  captain  becomes  scheduler   !   captain_is_adhoc_searchhead  knob  to  reduce  captain  load  
  • 15. Alerts  &  Suppression   15   !   Alerts  fired  when  results  of  search  meet  alerLng  criteria   –  Historical  Searches  –  within  10  seconds  aEer  job  completes   –  RealTime  searches  –  ongoing  basis   !   Captain  merges  and  maintains  global  view  of  alerts   !   Suppression  informaLon  centralized  by  the  captain   !   Merged  Alerts/Suppression  sent  back  to  members  
  • 16. High  Availability  of   Search  Results  
  • 17. Search  Results  primer   17   Search  -­‐  HEAD   indexers   stream  results   reduce   map   Other  Names   1.  search  results   2.  search  arLfact   3.  dispatch  directory   4.  SID   $SPLUNK_HOME/var/ run/splunk/dispatch/ scheduler__admin__sear ch__mysearch_at_14107 08600_345   sourcetype  =  access_combined    |  stats  count  by  clienLp   Dispatch  dir  needs  to  be  replicated  to     mulCple  nodes  to  tolerate  node  failures  
  • 18. ArLfact  ReplicaLon   18        ...   succ   succ   •  Captain  orchestrates  replicaLon   •  Default  replicaLon_factor=3   •  Success  failure  ACK’d  to  captain   •  Asynch  Replicate  on  Proxy     •  ReplicaLon  policy  enforced  by  fixups   replica-­‐1     replica-­‐2     succ   captain   replicate   orig  
  • 19.      ArLfact  Proxy-­‐ing   19   !   ReplicaLon  Guarantees  HA&DR  but...   !   SID  not  available  on  all  nodes  *locally*   !   RealTime  searches  are  not  replicated   !   We  use  proxy-­‐ing  to  fill  these  gaps   !   Proxying  on  REST  request     captain   over  HB   locaLon     log   r1   proxy   orig   AuthenCcaCon  is   cluster  aware!!   HB  =  Heartbeat   r2   async   replicate  
  • 20. Adhoc  Search  Management   20   !   Adhoc  search  -­‐  interacLve  search  run  from  a  user  session   !   Adhoc  searches  not  replicated     !   Captain,  however  will  have  global  knowledge  of  all  searches   !   GET  services/search/jobs  will  return  the  global  list  of  searches   !   You  can  proxy  and  access  adhoc  searches  from  any  node  
  • 21. Reaping  of  Search  ArLfacts   21   !   Reaping  –  DeleLon  of  search  results  when  TTL  (Lme  to  live)  expires   !   Search  ArLfacts  reaped  from  the  origin  node   !   Captain  orchestrates  reaps  of  the  replicas  
  • 23. HA  &  Auto-­‐Failover   23   Design  Goals   1.  No  Single  Point  of  Failure   2.  ConLnuous  UpLme   3.  Consistent  User  Experience   ImplementaLon   1.  Dynamic  Captain  elecLon   2.  Auto  Failover   3.  Proxying  for  consistent  view  
  • 24. Dynamic  Captain   24   !   RaE  Consensus  Protocol  from  Stanford   –  Diego  Ongaro  &  John  Osterhout   –  Acknowledge  Diego  Ongaro  for  help!   !   SHC  uses  RAFT  for  LE  and  Auto  Failover   RV  =      Request  Vote       LE  =    Leader  ElecLon   SHC  =    Search  Head  Clustering     S4   S2   S5   S3   S1   captain   new     captain  
  • 25. Auto-­‐Failover   25   new  captain        ...   members   old  captain   arLfacts   running  jobs   alerts,  etc   search  load   scheduler   Fixups  
  • 27. ConfiguraLon  Files   !   Custom  user  content   –  Reports   –  Dashboards   !   Search-­‐Lme  knowledge   –  Field  extracLons   –  Event  types   –  Macros   !   System  configuraLons   –  Inputs,  forwarding,  authenLcaLon  
  • 28. Goal   28   !   Consistent  user  experience  across  all  search  heads   !   Changes  made  on  one  member  are  reflected  on  all  members  
  • 29. ConfiguraLon  Changes   29   !   Users  customize  search  and  UI  configuraLons  via  UI/CLI/REST   –  Save  report   –  Add  panel  to  dashboards   –  Create  field  extracLon   !   Administrators  modify  system  configuraLons   –  Configure  forwarding   –  Deploy  centralized  authenLcaLon  (e.g.  LDAP)   –  Install  enLrely  new  app  or  hand-­‐edited  configuraLon  
  • 30. Search  and  UI  ConfiguraLons   30   !   Changes  to  search  and  UI  configuraLons  are  replicated  across  the   search  head  cluster  automaLcally   !   Goal:  eventual  consistency  
  • 31. ConfiguraLon  ReplicaLon   31   my_dashboard.xml   C  
  • 33. Custom  App  Content   33   !   App  devs  may  "opt-­‐in"  their  custom  configuraLons  for  replicaLon   under  search  head  clustering   !   Example  server.conf  from  an  app  would  look  like:    [shclustering]    conf_replicaLon_include.my_custom_file  =  true  
  • 34. System  ConfiguraLons   34   !   Recall:  only  changes  to  search  and  UI  configuraLons  are  replicated   across  the  search  head  cluster  automaLcally   !   hanges  to  system  configuraLons  are  not  replicated  automaLcally   because  of  their  high  potenLal  impact   !   How  are  system  configuraLons  kept  consistent  then?  
  • 35. !   Deployer:  a  single,  well-­‐controlled  instance  outside  of  the  cluster   !   ConfiguraLons  should  be  tested  on  dev/QA  instances  prior  to  deploy   D   ConfiguraLon  Deployment   35  
  • 38. Best  PracLces     !   Deployer  Instance   –  Can  piggyback  Cluster  Master  or  Deployment  Server   –  RecommendaLon  is  to  run  Deployer  on  separate  instance   !   Run  CLI  to  get  status  about  SHC   –  ./splunk  show  shcluster-­‐status       38  
  • 40. Key  Benefits  of  SHC   40     Horizontal  Scaling           Always-­‐on  Search  Services         Consistent  User  Experience       Easy  to  add  /  manage   premium  contents  (apps)  
  • 41. Q  &  A