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Un-Broken Logging
the foundation of software operability
Operability.io conference #OIO15
Friday 25th September 2015
Matthew Skelton
Skelton Thatcher Consulting
@matthewpskelton
The way we use logging is (often) broken
How to make our logging more awesome
Why we should care
Matthew Skelton
@matthewpskelton
#OIO15
@Operability
#operability
WhoOwnsMyOperability.com
confession:
I am a big fan of logging
exceptional situations
edge cases
metrics
analytics
‘audits’
…
@evanphx
execution trace
BAD STUFF
Logging is often unloved
1. Discontinuous
2. Errors only, or arbitrary
3. ‘Bolted on’
4. No aggregation & search
5. Specify severity up front
GOOD STUFF
How to make logging awesome
1. Continuous event IDs
2. Transaction tracing
3. Log aggregation & search tools
4. Design for logging
5. Decoupled severity
reduce time-to-detect
increase team engagement
increase configurability
enhance DevOps collaboration
#operability
Background
Autonomous weather station
MRI brain scan imaging
Oil well monitoring
Web-scale systems
logging makes things work
(event sourcing)
(structured logging)
(CQRS)
How is logging usually broken?
Logging is often unloved
1. Discontinuous
2. Errors only, or arbitrary
3. ‘Bolted on’
4. No aggregation & search
5. Specify severity up front
using logging mainly for errors
inconsistent use of logging
logging slows down the
software
logging ‘pollutes’ my precious
domain model
logging is just for those weird
Ops people
logging assumed to be free
($0) to implement
no budget for aggregating logs
across machines
log aggregation happens only
in Production
logs not available to Devs
fights over log severity levels
poor time synchronisation
Some history, with pirates
weather, course, sightings,
latitude, longitude, …
(even when quiet)
JohnHarrison
Why log?
verification
traceability
accountability
charting the waters
- June 13th – Pirates!!!!
- Weds – Sharks!!!
- 19th Jun –BIGGER sharks!!!!
How to make logging awesome
How to make logging awesome
1. Continuous event IDs
2. Transaction tracing
3. Log aggregation & search tools
4. Design for logging
5. Decoupled severity
Storage I/O
Worker Job
Queue
Upload
Continuous event IDs
How many distinct event
types (state transitions) in
your application?
represent distinct states
enum
Human-readable sets:
unique values, sparse, immutable
C#, Java, Python, node
(Ruby, PHP, …)
public enum EventID
{
// Badly-initialised logging data
NotSet = 0,
// An unrecognised event has occurred
UnexpectedError = 10000,
ApplicationStarted = 20000,
ApplicationShutdownNoticeReceived = 20001,
PageGenerationStarted = 30000,
PageGenerationCompleted = 30001,
MessageQueued = 40000,
MessagePeeked = 40001,
BasketItemAdded = 60001,
BasketItemRemoved = 60002,
CreditCardDetailsSubmitted = 70001,
// ...
}
Technical
Domain
public enum EventID
{
// Badly-initialised logging data
NotSet = 0,
// An unrecognised event has occurred
UnexpectedError = 10000,
ApplicationStarted = 20000,
ApplicationShutdownNoticeReceived = 20001,
PageGenerationStarted = 30000,
PageGenerationCompleted = 30001,
MessageQueued = 40000,
MessagePeeked = 40001,
BasketItemAdded = 60001,
BasketItemRemoved = 60002,
CreditCardDetailsSubmitted = 70001,
// ...
}
BasketItemAdded = 60001
BasketItemAdded = 60001
BasketItemRemoved = 60002
BasketItemAdded = 60001
BasketItemRemoved = 60002
represent distinct states
OrderSvc_BasketItemAdded
Monolith to microservices:
debugger does not have the full view
Even with remote debugger, it’s
boring to attach and detach
Storage I/O
Worker Job
Queue
Upload
Transaction tracing
‘Unique-ish’ identifier for each request
Passed through downstream layers
Unique-ish ID
What about APM?
APM gives us application insight
BUT
How much do we learn?
Is APM available on the Dev box?
It’s not just ‘an Ops problem’!
Helps us to understand how the
software really works
Small overhead is worth it
Configurable severity levels
Which log level is right?
DEBUG, INFO, WARNING,
ERROR, CRITICAL
Log level should *not* be fixed at
compile or build time!
Tune log levels
Tune log levels
Tune log levels
{
"eventmappings": {
"events": {
"event": [ {
"id": "CacheServiceStarted",
"severity": { "level": "Information" }
}, {
"id": "PageCachePurged",
"severity": { "level": "Debug" },
"state": { "enabled": false }
}, {
"id": "DatabaseConnectionTimeOut",
"severity": { "level": "Error" }
} ]
}
}
}
Tune severity levels of specific
event IDs
Event tracing
Use enumerations (or closest thing)
Technical and Domain event types
Distributed systems: debuggers less useful
Trace calls with ‘unique-enough’ handles
Tune log levels via config
Log aggregation & search tools
Design for log aggregation
develop the software using log
aggregation as a first-class thing
stories for testing logging
BasketItemAdded
grep BasketItem
logging is (‘just’) another
system component
NTP
Dev and Ops collaboration*
* and testers too!
Where?
auditing
compliance
pre-emptive fault diagnosis
performance
metrics
…
Recap
Logging is often unloved
1. Discontinuous
2. Errors only, or arbitrary
3. ‘Bolted on’
4. No aggregation & search
5. Specify severity up front
How to make logging awesome
1. Continuous event IDs
2. Transaction tracing
3. Log aggregation & search tools
4. Design for logging
5. Decoupled severity
logging makes things work
“There is no thought behind
aspect-oriented programming”
MINDFUL LOGGING (?!)
database transaction logs
‘Structured Logging’
TW: “Adopt” (May 2015)
https://www.thoughtworks.com/radar/techniques/structured-logging
http://gregoryszorc.com/
.NET: http://serilog.net/
Java: https://github.com/fluent/fluent-logger-java
sanity
More
Ditch the Debugger and Use Log
Analysis Instead
Matthew Skelton
https://blog.logentries.com/2015/07/ditch-
the-debugger-and-use-log-analysis-instead/
More
Using Log Aggregation Across
Dev & Ops: The Pricing Advantage
Rob Thatcher
https://blog.logentries.com/2015/08/using-
log-aggregation-across-dev-ops-the-pricing-
advantage/
Evan Phoenix (@evanphx)
youtube.com/watch?v=Z-JskKlIBOA
Books
operabilitybook.comoperationalfeatures.com
Thank you
http://skeltonthatcher.com/
enquiries@skeltonthatcher.com
@SkeltonThatcher
+44 (0)20 8242 4103
@matthewpskelton

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