Google Testing Blog: Optimal Logging

Optimal Logging

fredag, juni 14, 2013

by Anthony ValloneChanneling Goldilocks

Important startup configuration

Errors

Warnings

Changes to persistent data

Requests and responses between major system components

Significant state changes

User interactions

Calls with a known risk of failure

Waits on conditions that could take measurable time to satisfy

Periodic progress during long-running tasks

Significant branch points of logic and conditions that led to the branch

Summaries of processing steps or events from high level functions - Avoid logging every step of a complex process in low-level functions.

Function entry - Don’t log a function entry unless it is significant or logged at the debug level.

Data within a loop - Avoid logging from many iterations of a loop. It is OK to log from iterations of small loops or to log periodically from large loops.

Content of large messages or files - Truncate or summarize the data in some way that will be useful to debugging.

Benign errors - Errors that are not really errors can confuse the log reader. This sometimes happens when exception handling is part of successful execution flow.

Repetitive errors - Do not repetitively log the same or similar error. This can quickly fill a log and hide the actual cause. Frequency of error types is best handled by monitoring. Logs only need to capture detail for some of those errors.

There is More Than One Level

Debug - verbose and only useful while developing and/or debugging.

Info - the most popular level.

Warning - strange or unexpected states that are acceptable.

Error - something went wrong, but the process can recover.

Critical - the process cannot recover, and it will shutdown or restart.

Production - Every level is enabled except debug. If something goes wrong in production, the logs should reveal the cause.

Development & Debug - While developing new code or trying to reproduce a production issue, enable all levels.

Test Logs Are Important Too

Test execution environment

Initial state

Setup steps

Test case steps

Interactions with the system

Expected results

Actual results

Teardown steps

Conditional Verbosity With Temporary Log QueuesFailures and Flakiness Are OpportunitiesMight As Well Log Performance Data

Significant system calls

Network requests

CPU intensive operations

Connected device interactions

Transactions

Following the Trail Through Many Threads and ProcessesMonitoring and Logging Complement Each Other

10 kommentarer :

Unknown15. juni 2013 kl. 11:54:00 PDT
Lucid and enlightening. Thank you for this
SvarSlett
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Unknown17. juni 2013 kl. 05:34:00 PDT
Awesome information about logging. Thanks Anthony!
SvarSlett
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Unknown19. juli 2013 kl. 15:11:00 PDT
I'm gonna log this.
SvarSlett
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Anonym22. august 2013 kl. 06:43:00 PDT
Thanks!
SvarSlett
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Khaled Mosarof17. september 2013 kl. 03:19:00 PDT
Very informatics.
SvarSlett
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spccdt17. september 2013 kl. 04:34:00 PDT
Very helpful yet concise. Thanks!
SvarSlett
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Unknown21. september 2013 kl. 00:09:00 PDT
Very helpful for me，tks
SvarSlett
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Shanethatech2. oktober 2013 kl. 04:06:00 PDT
Thanks for publish.
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Anonym6. mai 2014 kl. 06:23:00 PDT
Hi folks,

we just open sourced our logging library which implements the Temporary Log Queues concept in this blog post:
https://github.com/egymgmbh/log-queue

Would be nice to get some feedback on that.

All the best,
Michael
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Unknown5. oktober 2020 kl. 01:15:00 PDT
Very helpful, thanks a lot. Why have you not sensitive user data like passwords as a bad thing to log?
SvarSlett
Svar

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Optimal Logging

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