CLOUDIFY YOUR
BUSINESS
Wayne walls
cloud evangelist
Wednesday, August 21, 13
Wednesday, August 21, 13
3
Self-Service
Wednesday, August 21, 13
4
On-Demand
Wednesday, August 21, 13
5
Metered
Wednesday, August 21, 13
6
Resource Pooling
Wednesday, August 21, 13
7
Broad Network Access
Wednesday, August 21, 13
NIST SAys...
8
Wednesday, August 21, 13
NIST says...
9
Wednesday, August 21, 13
NIST says...
10
Wednesday, August 21, 13
11
Wednesday, August 21, 13
12
Financial Services 
Data Analysis & Forecasting
MapReduce Data Analytics
Distributed, Web 2.0 Apps
REVOLUTIONARY
Wednes...
13
SAP
PeopleSoft
SharePoint
SQL
Home Grown
Client-Server Based
EVOLUTIONARY
Wednesday, August 21, 13
14
Big Promise of Cloud
Wednesday, August 21, 13
15
Scale!
Wednesday, August 21, 13
16
High-Availability vs Service Resiliency
Wednesday, August 21, 13
17
What is HA?
Active/Passive
Active/Active
Wednesday, August 21, 13
18
:Problem:
Single Point of Failure
Wednesday, August 21, 13
19
:Solution:
MAKE TWO OF ‘EM!
Wednesday, August 21, 13
20
Hammer & Nail Solution
Wednesday, August 21, 13
21
High-Availability has Problems
Wednesday, August 21, 13
22
Fails In Terrible Ways &
Doesn’t Really Scale
Wednesday, August 21, 13
23
Two Options to “HA”
Wednesday, August 21, 13
24
Take a non-distributed system and drop HA
on top of it
Option #1
Wednesday, August 21, 13
25
NFS
Wednesday, August 21, 13
26
Mean Time Between Failures
(MTBF)
Wednesday, August 21, 13
27
Wednesday, August 21, 13
28
Mean Time To Recovery
(MTTR)
Wednesday, August 21, 13
29
Expected failures of a traditional HA system are
catastrophic
Wednesday, August 21, 13
29
Expected failures of a traditional HA system are
catastrophic
Wednesday, August 21, 13
29
Expected failures of a traditional HA system are
catastrophic
System not designed to be distributed
Wednesday, August 2...
29
Expected failures of a traditional HA system are
catastrophic
System not designed to be distributed
Wednesday, August 2...
29
Expected failures of a traditional HA system are
catastrophic
System not designed to be distributed
Failure forces it t...
29
Expected failures of a traditional HA system are
catastrophic
System not designed to be distributed
Failure forces it t...
29
Expected failures of a traditional HA system are
catastrophic
System not designed to be distributed
Failure forces it t...
29
Expected failures of a traditional HA system are
catastrophic
System not designed to be distributed
Failure forces it t...
29
Expected failures of a traditional HA system are
catastrophic
System not designed to be distributed
Failure forces it t...
30
Take a distributed system and make the right
tradeoffs
Option #2
Wednesday, August 21, 13
31
Service Resiliency
Wednesday, August 21, 13
32
Examples
Wednesday, August 21, 13
33
Percona XtraDB
Cassandra
Riak
Wednesday, August 21, 13
34
Ceph
GlusterFS
Wednesday, August 21, 13
35
Constant Health Checks
Wednesday, August 21, 13
36
What is in a Running Application?
Wednesday, August 21, 13
37
Availability vs Reliability
Wednesday, August 21, 13
38
Wednesday, August 21, 13
38
Reliability is the likelihood that a given component or system will be
functioning when needed as measured over a given...
38
Reliability is the likelihood that a given component or system will be
functioning when needed as measured over a given...
39
Server Service
Wednesday, August 21, 13
40
Hardware does not get a pass...
Wednesday, August 21, 13
41
Think availability from the service
layer(s) perspective
Wednesday, August 21, 13
42
Wednesday, August 21, 13
43
Apps in a Cloudy World
Wednesday, August 21, 13
44
Greenfield vs Legacy
Wednesday, August 21, 13
45
Greenfield
Wednesday, August 21, 13
45
Greenfield
1. Focus on the service, not the server
Wednesday, August 21, 13
45
Greenfield
1. Focus on the service, not the server
2. Identify & tear apart stateless and stateful parts of your applic...
45
Greenfield
1. Focus on the service, not the server
2. Identify & tear apart stateless and stateful parts of your applic...
45
Greenfield
1. Focus on the service, not the server
2. Identify & tear apart stateless and stateful parts of your applic...
45
Greenfield
1. Focus on the service, not the server
2. Identify & tear apart stateless and stateful parts of your applic...
46
Legacy
Wednesday, August 21, 13
46
Legacy
1. Cloud Instances != server
Wednesday, August 21, 13
46
Legacy
1. Cloud Instances != server
2. Plan to reduce mean time to recovery (MTTR)
Wednesday, August 21, 13
46
Legacy
1. Cloud Instances != server
2. Plan to reduce mean time to recovery (MTTR)
3. "We're HA, we're all good." -> Wr...
46
Legacy
1. Cloud Instances != server
2. Plan to reduce mean time to recovery (MTTR)
3. "We're HA, we're all good." -> Wr...
46
Legacy
1. Cloud Instances != server
2. Plan to reduce mean time to recovery (MTTR)
3. "We're HA, we're all good." -> Wr...
Thank You!
Wednesday, August 21, 13
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Cloudify Your Business

  1. 1. CLOUDIFY YOUR BUSINESS Wayne walls cloud evangelist Wednesday, August 21, 13
  2. 2. Wednesday, August 21, 13
  3. 3. 3 Self-Service Wednesday, August 21, 13
  4. 4. 4 On-Demand Wednesday, August 21, 13
  5. 5. 5 Metered Wednesday, August 21, 13
  6. 6. 6 Resource Pooling Wednesday, August 21, 13
  7. 7. 7 Broad Network Access Wednesday, August 21, 13
  8. 8. NIST SAys... 8 Wednesday, August 21, 13
  9. 9. NIST says... 9 Wednesday, August 21, 13
  10. 10. NIST says... 10 Wednesday, August 21, 13
  11. 11. 11 Wednesday, August 21, 13
  12. 12. 12 Financial Services  Data Analysis & Forecasting MapReduce Data Analytics Distributed, Web 2.0 Apps REVOLUTIONARY Wednesday, August 21, 13
  13. 13. 13 SAP PeopleSoft SharePoint SQL Home Grown Client-Server Based EVOLUTIONARY Wednesday, August 21, 13
  14. 14. 14 Big Promise of Cloud Wednesday, August 21, 13
  15. 15. 15 Scale! Wednesday, August 21, 13
  16. 16. 16 High-Availability vs Service Resiliency Wednesday, August 21, 13
  17. 17. 17 What is HA? Active/Passive Active/Active Wednesday, August 21, 13
  18. 18. 18 :Problem: Single Point of Failure Wednesday, August 21, 13
  19. 19. 19 :Solution: MAKE TWO OF ‘EM! Wednesday, August 21, 13
  20. 20. 20 Hammer & Nail Solution Wednesday, August 21, 13
  21. 21. 21 High-Availability has Problems Wednesday, August 21, 13
  22. 22. 22 Fails In Terrible Ways & Doesn’t Really Scale Wednesday, August 21, 13
  23. 23. 23 Two Options to “HA” Wednesday, August 21, 13
  24. 24. 24 Take a non-distributed system and drop HA on top of it Option #1 Wednesday, August 21, 13
  25. 25. 25 NFS Wednesday, August 21, 13
  26. 26. 26 Mean Time Between Failures (MTBF) Wednesday, August 21, 13
  27. 27. 27 Wednesday, August 21, 13
  28. 28. 28 Mean Time To Recovery (MTTR) Wednesday, August 21, 13
  29. 29. 29 Expected failures of a traditional HA system are catastrophic Wednesday, August 21, 13
  30. 30. 29 Expected failures of a traditional HA system are catastrophic Wednesday, August 21, 13
  31. 31. 29 Expected failures of a traditional HA system are catastrophic System not designed to be distributed Wednesday, August 21, 13
  32. 32. 29 Expected failures of a traditional HA system are catastrophic System not designed to be distributed Wednesday, August 21, 13
  33. 33. 29 Expected failures of a traditional HA system are catastrophic System not designed to be distributed Failure forces it to be distributed Wednesday, August 21, 13
  34. 34. 29 Expected failures of a traditional HA system are catastrophic System not designed to be distributed Failure forces it to be distributed Wednesday, August 21, 13
  35. 35. 29 Expected failures of a traditional HA system are catastrophic System not designed to be distributed Failure forces it to be distributed Cannot take distributed failure conditions into account Wednesday, August 21, 13
  36. 36. 29 Expected failures of a traditional HA system are catastrophic System not designed to be distributed Failure forces it to be distributed Cannot take distributed failure conditions into account Wednesday, August 21, 13
  37. 37. 29 Expected failures of a traditional HA system are catastrophic System not designed to be distributed Failure forces it to be distributed Cannot take distributed failure conditions into account Best case scenario: complete failure Wednesday, August 21, 13
  38. 38. 30 Take a distributed system and make the right tradeoffs Option #2 Wednesday, August 21, 13
  39. 39. 31 Service Resiliency Wednesday, August 21, 13
  40. 40. 32 Examples Wednesday, August 21, 13
  41. 41. 33 Percona XtraDB Cassandra Riak Wednesday, August 21, 13
  42. 42. 34 Ceph GlusterFS Wednesday, August 21, 13
  43. 43. 35 Constant Health Checks Wednesday, August 21, 13
  44. 44. 36 What is in a Running Application? Wednesday, August 21, 13
  45. 45. 37 Availability vs Reliability Wednesday, August 21, 13
  46. 46. 38 Wednesday, August 21, 13
  47. 47. 38 Reliability is the likelihood that a given component or system will be functioning when needed as measured over a given period of time. Wednesday, August 21, 13
  48. 48. 38 Reliability is the likelihood that a given component or system will be functioning when needed as measured over a given period of time. Availability is the percentage of times that a given system will be functioning as required. Wednesday, August 21, 13
  49. 49. 39 Server Service Wednesday, August 21, 13
  50. 50. 40 Hardware does not get a pass... Wednesday, August 21, 13
  51. 51. 41 Think availability from the service layer(s) perspective Wednesday, August 21, 13
  52. 52. 42 Wednesday, August 21, 13
  53. 53. 43 Apps in a Cloudy World Wednesday, August 21, 13
  54. 54. 44 Greenfield vs Legacy Wednesday, August 21, 13
  55. 55. 45 Greenfield Wednesday, August 21, 13
  56. 56. 45 Greenfield 1. Focus on the service, not the server Wednesday, August 21, 13
  57. 57. 45 Greenfield 1. Focus on the service, not the server 2. Identify & tear apart stateless and stateful parts of your application Wednesday, August 21, 13
  58. 58. 45 Greenfield 1. Focus on the service, not the server 2. Identify & tear apart stateless and stateful parts of your application 3. Make stateful parts redundant using distributed data stores Wednesday, August 21, 13
  59. 59. 45 Greenfield 1. Focus on the service, not the server 2. Identify & tear apart stateless and stateful parts of your application 3. Make stateful parts redundant using distributed data stores 4. Know the dependencies of your system and the impact of failure Wednesday, August 21, 13
  60. 60. 45 Greenfield 1. Focus on the service, not the server 2. Identify & tear apart stateless and stateful parts of your application 3. Make stateful parts redundant using distributed data stores 4. Know the dependencies of your system and the impact of failure 5. Use micro-services to make dependencies explicit Wednesday, August 21, 13
  61. 61. 46 Legacy Wednesday, August 21, 13
  62. 62. 46 Legacy 1. Cloud Instances != server Wednesday, August 21, 13
  63. 63. 46 Legacy 1. Cloud Instances != server 2. Plan to reduce mean time to recovery (MTTR) Wednesday, August 21, 13
  64. 64. 46 Legacy 1. Cloud Instances != server 2. Plan to reduce mean time to recovery (MTTR) 3. "We're HA, we're all good." -> Wrong. Wednesday, August 21, 13
  65. 65. 46 Legacy 1. Cloud Instances != server 2. Plan to reduce mean time to recovery (MTTR) 3. "We're HA, we're all good." -> Wrong. 4. Think about stateful vs stateless parts of your application and work piece by piece Wednesday, August 21, 13
  66. 66. 46 Legacy 1. Cloud Instances != server 2. Plan to reduce mean time to recovery (MTTR) 3. "We're HA, we're all good." -> Wrong. 4. Think about stateful vs stateless parts of your application and work piece by piece 5. Be creative about trade-offs:  many apps that run on more than one server have some type of common backend (NFS) Wednesday, August 21, 13
  67. 67. Thank You! Wednesday, August 21, 13
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