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 of postmortems
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 through them）
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
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