| Foreword I |
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xvii | |
| Foreword II |
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xix | |
| Preface |
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xxiii | |
| 1 How SRE Relates to DevOps |
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1 | (16) |
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2 | (2) |
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2 | (1) |
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3 | (1) |
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3 | (1) |
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Tooling and Culture Are Interrelated |
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4 | (1) |
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4 | (1) |
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4 | (4) |
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Operations Is a Software Problem |
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5 | (1) |
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Manage by Service Level Objectives (SLOs) |
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5 | (1) |
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5 | (1) |
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Automate This Year's Job Away |
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6 | (1) |
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Move Fast by Reducing the Cost of Failure |
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6 | (1) |
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Share Ownership with Developers |
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7 | (1) |
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Use the Same Tooling, Regardless of Function or Job Title |
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7 | (1) |
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8 | (1) |
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Organizational Context and Fostering Successful Adoption |
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9 | (8) |
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Narrow, Rigid Incentives Narrow Your Success |
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10 | (1) |
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It's Better to Fix It Yourself; Don't Blame Someone Else |
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10 | (1) |
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Consider Reliability Work as a Specialized Role |
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11 | (1) |
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When Can Substitute for Whether |
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12 | (1) |
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Strive for Parity of Esteem: Career and Financial |
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12 | (5) |
| Part I. Foundations |
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17 | (26) |
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17 | (1) |
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18 | (5) |
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Reliability Targets and Error Budgets |
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19 | (1) |
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What to Measure: Using SLIs |
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20 | (3) |
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23 | (6) |
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Moving from SLI Specification to SLI Implementation |
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25 | (1) |
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26 | (2) |
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Using the SLIs to Calculate Starter SLOs |
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28 | (1) |
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Choosing an Appropriate Time Window |
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29 | (1) |
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Getting Stakeholder Agreement |
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30 | (4) |
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Establishing an Error Budget Policy |
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31 | (1) |
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Documenting the SLO and Error Budget Policy |
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32 | (1) |
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33 | (1) |
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Continuous Improvement of SLO Targets |
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34 | (3) |
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Improving the Quality of Your SLO |
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35 | (2) |
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Decision Making Using SLOs and Error Budgets |
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37 | (1) |
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38 | (4) |
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39 | (1) |
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Grading Interaction Importance |
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39 | (1) |
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40 | (1) |
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Experimenting with Relaxing Your SLOs |
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41 | (1) |
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42 | (1) |
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3 SLO Engineering Case Studies |
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43 | (18) |
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43 | (6) |
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Why Did Evernote Adopt the SRE Model? |
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44 | (1) |
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Introduction of SLOs: A Journey in Progress |
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45 | (3) |
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Breaking Down the SLO Wall Between Customer and Cloud Provider |
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48 | (1) |
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49 | (1) |
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The Home Depot's SLO Story |
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49 | (11) |
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50 | (2) |
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52 | (2) |
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54 | (1) |
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Automating VALET Data Collection |
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55 | (2) |
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The Proliferation of SLOs |
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57 | (1) |
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Applying VALET to Batch Applications |
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57 | (1) |
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58 | (1) |
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58 | (1) |
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59 | (1) |
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60 | (1) |
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61 | (14) |
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Desirable Features of a Monitoring Strategy |
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62 | (2) |
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62 | (1) |
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62 | (1) |
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63 | (1) |
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64 | (1) |
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Sources of Monitoring Data |
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64 | (3) |
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65 | (2) |
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Managing Your Monitoring System |
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67 | (2) |
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Treat Your Configuration as Code |
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67 | (1) |
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68 | (1) |
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68 | (1) |
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69 | (3) |
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70 | (1) |
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70 | (1) |
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71 | (1) |
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72 | (1) |
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Implementing Purposeful Metrics |
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72 | (1) |
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72 | (1) |
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73 | (2) |
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75 | (18) |
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75 | (1) |
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Ways to Alert on Significant Events |
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76 | (10) |
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1 Target Error Rate SLO Threshold |
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76 | (2) |
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78 | (1) |
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3 Incrementing Alert Duration |
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79 | (1) |
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80 | (2) |
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5 Multiple Burn Rate Alerts |
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82 | (2) |
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6 Multiwindow, Multi-Burn-Rate Alerts |
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84 | (2) |
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Low-Traffic Services and Error Budget Alerting |
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86 | (3) |
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Generating Artificial Traffic |
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87 | (1) |
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87 | (1) |
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Making Service and Infrastructure Changes |
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87 | (1) |
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Lowering the SLO or Increasing the Window |
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88 | (1) |
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Extreme Availability Goals |
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89 | (1) |
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89 | (2) |
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91 | (2) |
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93 | (38) |
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94 | (2) |
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96 | (2) |
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98 | (3) |
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98 | (1) |
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99 | (1) |
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99 | (1) |
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99 | (1) |
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Cost Engineering and Capacity Planning |
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100 | (1) |
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Troubleshooting for Opaque Architectures |
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100 | (1) |
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Toil Management Strategies |
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101 | (5) |
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Identify and Measure Toil |
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101 | (1) |
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Engineer Toil Out of the System |
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101 | (1) |
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101 | (1) |
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102 | (1) |
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Start with Human-Backed Interfaces |
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102 | (1) |
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Provide Self-Service Methods |
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102 | (1) |
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Get Support from Management and Colleagues |
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103 | (1) |
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Promote Toil Reduction as a Feature |
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103 | (1) |
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Start Small and Then Improve |
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103 | (1) |
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103 | (1) |
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Assess Risk Within Automation |
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104 | (1) |
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104 | (1) |
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Use Open Source and Third-Party Tools |
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105 | (1) |
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105 | (1) |
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106 | (1) |
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Case Study 1: Reducing Toil in the Datacenter with Automation |
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107 | (14) |
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107 | (3) |
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110 | (1) |
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110 | (1) |
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Design First Effort: Saturn Line-Card Repair |
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110 | (1) |
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111 | (2) |
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Design Second Effort: Saturn Line-Card Repair Versus Jupiter Line-Card Repair |
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113 | (1) |
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114 | (4) |
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118 | (3) |
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Case Study 2: Decommissioning Filer-Backed Home Directories |
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121 | (1) |
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121 | (1) |
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121 | (1) |
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122 | (1) |
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Design and Implementation |
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123 | (1) |
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124 | (3) |
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127 | (2) |
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129 | (2) |
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131 | (16) |
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131 | (2) |
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Simplicity Is End-to-End, and SREs Are Good for That |
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133 | (2) |
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Case Study 1 End-to-End API Simplicity |
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134 | (1) |
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Case Study 2 Project Lifecycle Complexity |
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134 | (1) |
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135 | (6) |
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Case Study 3 Simplification of the Display Ads Spiderweb |
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137 | (2) |
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Case Study 4 Running Hundreds of Microservices on a Shared Platform |
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139 | (1) |
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Case Study 5 pDNS No Longer Depends on Itself |
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140 | (1) |
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141 | (6) |
| Part II. Practices |
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147 | (28) |
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Recap of "Being On-Call"
Chapter of First SRE Book |
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148 | (1) |
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Example On-Call Setups Within Google and Outside Google |
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149 | (7) |
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Google: Forming a New Team |
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149 | (4) |
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Evernote: Finding Our Feet in the Cloud |
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153 | (3) |
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Practical Implementation Details |
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156 | (17) |
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156 | (11) |
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167 | (4) |
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171 | (2) |
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173 | (2) |
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175 | (20) |
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Incident Management at Google |
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176 | (1) |
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176 | (1) |
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Main Roles in Incident Response |
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177 | (1) |
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177 | (14) |
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Case Study 1 Software Bug-The Lights Are On but No One's (Google) Home |
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177 | (3) |
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Case Study 2 Service Fault-Cache Me If You Can |
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180 | (5) |
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Case Study 3 Power Outage-Lightning Never Strikes Twice...Until It Does |
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185 | (3) |
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Case Study 4 Incident Response at PagerDuty |
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188 | (3) |
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Putting Best Practices into Practice |
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191 | (3) |
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Incident Response Training |
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191 | (1) |
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192 | (1) |
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193 | (1) |
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194 | (1) |
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10 Postmortem Culture: Learning from Failure |
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195 | (30) |
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196 | (1) |
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197 | (6) |
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Why Is This Postmortem Bad? |
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199 | (4) |
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203 | (11) |
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Why Is This Postmortem Better? |
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212 | (2) |
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Organizational Incentives |
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214 | (6) |
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Model and Enforce Blameless Behavior |
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214 | (1) |
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Reward Postmortem Outcomes |
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215 | (2) |
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217 | (1) |
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Respond to Postmortem Culture Failures |
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218 | (2) |
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220 | (3) |
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220 | (1) |
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221 | (2) |
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223 | (2) |
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225 | (20) |
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Google Cloud Load Balancing |
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225 | (11) |
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226 | (1) |
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227 | (2) |
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Global Software Load Balancer |
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229 | (1) |
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229 | (1) |
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230 | (1) |
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231 | (1) |
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Case Study 1: Pokemon GO on GCLB |
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231 | (5) |
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236 | (3) |
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Handling Unhealthy Machines |
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236 | (1) |
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Working with Stateful Systems |
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237 | (1) |
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Configuring Conservatively |
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237 | (1) |
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238 | (1) |
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Including Kill Switches and Manual Overrides |
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238 | (1) |
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Avoiding Overloading Backends |
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238 | (1) |
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Avoiding Traffic Imbalance |
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239 | (1) |
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Combining Strategies to Manage Load |
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239 | (4) |
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Case Study 2: When Load Shedding Attacks |
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240 | (3) |
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243 | (2) |
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12 Introducing Non-Abstract Large System Design |
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245 | (18) |
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245 | (1) |
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246 | (1) |
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246 | (14) |
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246 | (1) |
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247 | (1) |
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248 | (3) |
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251 | (9) |
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260 | (3) |
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13 Data Processing Pipelines |
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263 | (38) |
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264 | (4) |
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Event Processing/Data Transformation to Order or Structure Data |
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264 | (1) |
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265 | (1) |
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265 | (3) |
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268 | (9) |
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Define and Measure. Service Level Objectives |
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268 | (2) |
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Plan for Dependency Failure |
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270 | (1) |
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Create and Maintain Pipeline Documentation |
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271 | (1) |
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Map Your Development Lifecycle |
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272 | (3) |
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Reduce Hotspotting and Workload Patterns |
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275 | (1) |
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Implement Autoscaling and Resource Planning |
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276 | (1) |
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Adhere to Access Control and Security Policies |
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277 | (1) |
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277 | (1) |
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Pipeline Requirements and Design |
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277 | (7) |
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What Features Do You Need? |
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278 | (1) |
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Idempotent and Two-Phase Mutations |
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279 | (1) |
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280 | (1) |
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280 | (1) |
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Pipeline Production Readiness |
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281 | (3) |
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Pipeline Failures: Prevention and Response |
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284 | (3) |
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284 | (2) |
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286 | (1) |
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287 | (12) |
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288 | (1) |
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Event Delivery System Design and Architecture |
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289 | (1) |
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Event Delivery System Operation |
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290 | (3) |
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Customer Integration and Support |
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293 | (5) |
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298 | (1) |
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299 | (2) |
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14 Configuration Design and Best Practices |
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301 | (14) |
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301 | (2) |
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Configuration and Reliability |
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302 | (1) |
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Separating Philosophy and Mechanics |
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303 | (1) |
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303 | (5) |
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Configuration Asks Users Questions |
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305 | (1) |
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Questions Should Be Close to User Goals |
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305 | (1) |
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Mandatory and Optional Questions |
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306 | (2) |
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308 | (1) |
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Mechanics of Configuration |
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308 | (5) |
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Separate Configuration and Resulting Data |
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308 | (2) |
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310 | (2) |
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Ownership and Change Tracking |
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312 | (1) |
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Safe Configuration Change Application |
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312 | (1) |
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313 | (2) |
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15 Configuration Specifics |
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315 | (20) |
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Configuration-Induced Toil |
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315 | (1) |
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Reducing Configuration-Induced Toil |
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316 | (1) |
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Critical Properties and Pitfalls of Configuration Systems |
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317 | (3) |
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Pitfall 1 Failing to Recognize Configuration as a Programming Language Problem |
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317 | (1) |
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Pitfall 2 Designing Accidental or Ad Hoc Language Features |
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318 | (1) |
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Pitfall 3 Building Too Much Domain-Specific Optimization |
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318 | (1) |
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Pitfall 4 Interleaving "Configuration Evaluation" with "Side Effects" |
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319 | (1) |
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Pitfall 5 Using an Existing General-Purpose Scripting Language Like Python, Ruby, or Lua |
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319 | (1) |
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Integrating a Configuration Language |
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320 | (2) |
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Generating Config in Specific Formats |
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320 | (1) |
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Driving Multiple Applications |
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321 | (1) |
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Integrating an Existing Application: Kubernetes |
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322 | (4) |
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322 | (1) |
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Example Kubernetes Config |
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322 | (1) |
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Integrating the Configuration Language |
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323 | (3) |
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Integrating Custom Applications (In-House Software) |
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326 | (3) |
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Effectively Operating a Configuration System |
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329 | (2) |
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329 | (1) |
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330 | (1) |
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330 | (1) |
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330 | (1) |
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When to Evaluate Configuration |
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331 | (2) |
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Very Early: Checking in the JSON |
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331 | (1) |
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Middle of the Road: Evaluate at Build Time |
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332 | (1) |
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Late: Evaluate at Runtime |
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332 | (1) |
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Guarding Against Abusive Configuration |
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333 | (1) |
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334 | (1) |
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335 | (20) |
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Release Engineering Principles |
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336 | (1) |
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Balancing Release Velocity and Reliability |
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337 | (1) |
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338 | (1) |
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Release Engineering and Canarying |
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338 | (2) |
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Requirements of a Canary Process |
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339 | (1) |
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339 | (1) |
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A Roll Forward Deployment Versus a Simple Canary Deployment |
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340 | (2) |
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342 | (3) |
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Minimizing Risk to SLOB and the Error Budget |
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343 | (1) |
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Choosing a Canary Population and Duration |
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343 | (2) |
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Selecting and Evaluating Metrics |
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345 | (3) |
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Metrics Should Indicate Problems |
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345 | (1) |
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Metrics Should Be Representative and Attributable |
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346 | (1) |
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Before/After Evaluation Is Risky |
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347 | (1) |
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Use a Gradual Canary for Better Metric Selection |
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347 | (1) |
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Dependencies and Isolation |
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348 | (1) |
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Canarying in Noninteractive Systems |
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348 | (1) |
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Requirements on Monitoring Data |
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349 | (1) |
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350 | (1) |
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350 | (1) |
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Artificial Load Generation |
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350 | (1) |
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351 | (1) |
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351 | (4) |
| Part III. Processes |
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17 Identifying and Recovering from Overload |
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355 | (16) |
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356 | (2) |
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Case Study 1: Work Overload When Half a Team Leaves |
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358 | (2) |
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358 | (1) |
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358 | (1) |
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359 | (1) |
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359 | (1) |
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360 | (1) |
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Case Study 2: Perceived Overload After Organizational and Workload Changes |
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360 | (6) |
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360 | (1) |
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361 | (1) |
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362 | (1) |
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363 | (2) |
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365 | (1) |
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365 | (1) |
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Strategies for Mitigating Overload |
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366 | (3) |
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Recognizing the Symptoms of Overload |
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366 | (1) |
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Reducing Overload and Restoring Team Health |
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367 | (2) |
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369 | (2) |
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371 | (20) |
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372 | (3) |
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Phase 1 Architecture and Design |
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372 | (1) |
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Phase 2 Active Development |
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373 | (1) |
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Phase 3 Limited Availability |
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373 | (1) |
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Phase 4 General Availability |
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374 | (1) |
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374 | (1) |
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374 | (1) |
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374 | (1) |
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Setting Up the Relationship |
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375 | (5) |
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Communicating Business and Production Priorities |
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375 | (1) |
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375 | (1) |
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375 | (4) |
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379 | (1) |
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379 | (1) |
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Sustaining an Effective Ongoing Relationship |
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380 | (2) |
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Investing Time in Working Better Together |
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380 | (1) |
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Maintaining an Open Line of Communication |
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380 | (1) |
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Performing Regular Service Reviews |
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381 | (1) |
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Reassessing When Ground Rules Start to Slip |
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381 | (1) |
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Adjusting Priorities According to Your SLOs and Error Budget |
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381 | (1) |
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Handling Mistakes Appropriately |
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382 | (1) |
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Scaling SRE to Larger Environments |
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382 | (3) |
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Supporting Multiple Services with a Single SRE Team |
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382 | (1) |
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Structuring a Multiple SRE Team Environment |
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383 | (1) |
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Adapting SRE Team Structures to Changing Circumstances |
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384 | (1) |
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Running Cohesive Distributed SRE Teams |
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384 | (1) |
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385 | (4) |
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385 | (2) |
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Case Study 2: Data Analysis Pipeline |
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387 | (2) |
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389 | (2) |
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19 SRE: Reaching Beyond Your Walls |
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391 | (8) |
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Truths We Hold to Be Self-Evident |
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391 | (3) |
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Reliability Is the Most Important Feature |
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392 | (1) |
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Your Users, Not Your Monitoring, Decide Your Reliability |
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392 | (1) |
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If You Run a Platform, Then Reliability Is a Partnership |
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392 | (1) |
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Everything Important Eventually Becomes a Platform |
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393 | (1) |
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When Your Customers Have a Hard Time, You Have to Slow Down |
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393 | (1) |
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You Will Need to Practice SRE with Your Customers |
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393 | (1) |
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How to: SRE with Your Customers |
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394 | (4) |
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Step 1 SLOs and SLIs Are How You Speak |
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394 | (1) |
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Step 2 Audit the Monitoring and Build Shared Dashboards |
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395 | (1) |
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Step 3 Measure and Renegotiate |
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396 | (1) |
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Step 4 Design Reviews and Risk Analysis |
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396 | (1) |
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Step 5 Practice, Practice, Practice |
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397 | (1) |
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Be Thoughtful and Disciplined |
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397 | (1) |
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398 | (1) |
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399 | (24) |
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SRE Practices Without SREs |
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399 | (1) |
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400 | (3) |
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400 | (1) |
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401 | (1) |
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Bootstrapping Your First SRE |
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402 | (1) |
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403 | (1) |
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403 | (10) |
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404 | (1) |
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405 | (3) |
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408 | (3) |
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411 | (2) |
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413 | (5) |
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413 | (1) |
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414 | (1) |
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415 | (3) |
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Suggested Practices for Running Many Teams |
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418 | (4) |
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419 | (1) |
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419 | (1) |
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419 | (1) |
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419 | (1) |
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420 | (1) |
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420 | (1) |
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Launch Coordination Engineering Teams |
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421 | (1) |
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421 | (1) |
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421 | (1) |
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422 | (1) |
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21 Organizational Change Management in SRE |
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423 | (18) |
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423 | (1) |
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Introduction to Change Management |
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424 | (3) |
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Lewin's Three-Stage Model |
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424 | (1) |
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424 | (1) |
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Kotter's Eight-Step Process for Leading Change |
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425 | (1) |
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425 | (1) |
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426 | (1) |
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426 | (1) |
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How These Theories Apply to SRE |
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427 | (1) |
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Case Study 1: Scaling Waze-From Ad Hoc to Planned Change |
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427 | (5) |
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427 | (1) |
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The Messaging Queue: Replacing a System While Maintaining Reliability |
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427 | (2) |
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The Next Cycle of Change: Improving the Deployment Process |
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429 | (2) |
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431 | (1) |
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Case Study 2: Common Tooling Adoption in SRE |
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432 | (7) |
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432 | (1) |
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433 | (1) |
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434 | (1) |
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434 | (2) |
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Implementation: Monitoring |
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436 | (1) |
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436 | (3) |
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439 | (2) |
| Conclusion |
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441 | (14) |
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445 | (4) |
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B Example Error Budget Policy |
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449 | (4) |
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C Results of Postmortem Analysis |
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|
453 | (2) |
| Index |
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455 | |
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