网站运维（影印版）

foreword
preface
1 web operations: the career
　theo schlossnagle
　why does web operations have it tough?
　from apprentice to master
　conclusion
2 how picnik uses cloud computing: lessons learned
　justin huff
　where the cloud fits (and why!)
　where the cloud doesn’t fit (for picnik)
　conclusion
3 infrastructure and application metrics
　john aiispaw, with matt massie
　time resolution and retention concerns
　locality of metrics collection and storage
　layers of metrics
　providing context for anomaly detection and alerts
　log lines are metrics, too
　correlation with change management and incident timelines
　making metrics available to your alerting mechanisms
　using metrics to guide load-feedback mechanisms
　a metrics collection system, illustrated: ganglia
　conclusion
4 continuous deployment
　eric ries
　small batches mean faster feedback
　small batches mean problems are instantly localized
　small batches reduce risk
　small batches reduce overhead
　the quality defenders’ lament
　getting started
　continuous deployment is for mission-critical
　applications
　conclusion
5 infrastructure as code
　adam jacob
　service-oriented architecture
　conclusion
6 monitoring
　patrick debois
　story: “the start of a journey”
　step 1: understand what you are monitoring
　step 2: understand normal behavior
　step 3: be prepared and learn
　conclusion
7 how complex systems fail
　john aiispaw and richard cook
　how complex systems fail
　further reading
8 community management and web operations
　heather champ and john aiispaw
9 dealing with unexpected traffic spikes
　brian moon
　how it all started
　alarms abound
　putting out the fire
　surviving the weekend
　preparing for the future
　cdn to the rescue
　proxy servers
　corralling the stampede
　streamlining the codebase
　how do we know it works?
　the real test
　lessons learned
　improvements since then
10 dev and cps collaboration and cooperation
　paul hammond
　deployment
　shared, open infrastructure
　trust
　on-call developers
　avoiding blame
　conclusion
11 how your visitors feel: user-facing metrics
　alistair croll and sean power
　why collect user-facing metrics?
　what makes a site slow?
　measuring delay
　building an sla
　visitor outcomes: analytics
　other metrics marketing cares about
　how user experience affects web cps
　the future of web monitoring
　conclusion
12 relational database strategy and tactics for the web
　baron schwartz
　requirements for web databases
　how typical web databases grow
　the yearning for a cluster
　database strategy
　database tactics
　conclusion
13 how to make failure beautiful: the art and science ofpostmortems
　jake loomis
　the worst postmortem
　what is a postmortem?
　when to conduct a postmortem
　who to invite to a postmortem
　running a postmortem
　postmortem follow-up
　conclusion
14 storage
　anoop nagwani
　data asset inventory
　data protection
　capacity planning
　storage sizing
　operations
　conclusion
15 nonrelational databases
　eric florenzano
　nosql database overview
　some systems in detail
　conclusion
16 agile infrastructure
　andrew clay sharer
　agile infrastructure
　so, what’s the problem?
　communities of interest and practice
　trading zones and apologies
　conclusion
17 things that go bump in the night (and how to sleep throughthem)
　mike christian
　definitions
　how many 9s?
　impact duration versus incident duration
　datacenter footprint
　gradual failures
　trust nobody
　failover testing
　monitoring and history of patterns
　getting a good night’s sleep
contributors
index