Logs have been used for a long time in many areas to record important events. In shipping, logs are kept to help the crew to navigate when GPS, radio or radar fail. Logs are used also in marine inquiries, similar to an airplane black box, registering weather conditions, ports docked at, significant incidents and distance traveled with respect to a given start position.

We know you’re not member of ship crew, but the logs used in programming and operating systems are VERY similar, obviously, because our logs are based on the shipping logs!

There are two main purposes for logs in our area - debugging, similar to the logs used to help the ship crew, and audit, that are used in investigation processes. We will focus on the first type of log.

But why logging?

Logging, in opinion, is one of the most powerful tools we developers have got in our tool belts.

It allows you know exactly the execution flow of your application and can be used even in production environment. Unit testing allows you only to know that the feature you developed does what it needs to do (if you developed your test the right way, of course), logging shows how it is doing, thus, it’s a indispensable tool to discover problems in your code.

By logging errors (and sending you notifications by email or SMS), you can start solving critical problems without anyone notify you (despite we know users are terribly fast to communicate these issues).

What should you log?

Simple, you should log everything you judge as important! No one, unless you know, what it is important for your application. To help you identify what is important, let’s take a look at some log entries I took from my dmesg:

[    0.755157] PM: Hibernation image not present or could not be loaded.
[    0.755848] Freeing unused kernel memory: 1336K (ffffffff81d20000 - ffffffff81e6e000)
[    0.755849] Write protecting the kernel read-only data: 12288k
[    9.544173] Adding 3905532k swap on /dev/sda2.  Priority:-1 extents:1 across:3905532k FS
[    9.552651] IPv6: ADDRCONF(NETDEV_UP): eth0: link is not ready
[    0.205464] pci 0000:00:1c.0: PME# supported from D0 D3hot D3cold
[    0.205704] pci 0000:00:1c.3: System wakeup disabled by ACPI

None of the above log entries are error messages, they are useful information obtained and logged in specific events, such as turning the computer on, enabling/disabling network adapters, plugging storage devices and so on. Services such as the Apache Httpd, for example, log every request and its context data (we will see that later) as well as errors, like restarting the server with an invalid virtual host, and events as starting, stopping and restarting the server. All these log entries can be used by system administrators to possibly find a problem.

Severity levels

There are eight severity levels for logs, as described in RFC 5424 and, implemented by most of logging frameworks:

Debug: It’s that one that helps you to find bugs, in which you log an event, such a condition evaluated to true and a variable value, for example, and are specially useful while developing the application.

Info: Allows you knowing your application’s execution flow. In this type, you usually log events, such a user registered, a user that logged the system, a payment refused and so on.

Notice: Similar as the previous one - used when normal but significant events occur in a system. In an event subscription website, for example, when an event gets closed or when it reaches its full capacity, could add a notice log entry.

Warning: These are used when something unusual happened in your system, it isn’t an error yet but it will become if an action is not taken in a near future. Using that event subscription website example, when the database system starts to return that its capacity to handle simultaneous connections are failing, it could be a good idea to log this as warning and obviously monitor your log entries to contact the database administrators when appropriate.

Up to this point you are able to add logs manually, placing the log framework calls in catch blocks or based on specific conditions. However, it’s really interesting if you use a kind of exception handler to deal with events starting from this log severity, so that you can handle certain exceptions, maybe logging them and showing a default error message, and deal with unexpected exceptions.

Error: Used when something definitely went wrong, such as runtime errors, BUT it doesn’t require immediate action.

Critical: Used when something critical happens (duh), such as a system component unavailable, for example.

Alert: Used for actions that must be taken immediately, waking you up on the middle of the night on your vacation, such as entire system down, database unavailable and so on.

Emergency: It’s used when the system gets unusable.

Sincerely, Emergency and Alert for me are the same. When the entire system is down, isn’t the system unusable, most of the times? Now it’s up to you decide at what severity level you want/need to stop… I particularly never used Alert and Emergency ones. When something really serious happens, such as a database unavailable, I add a critical log entry and, thus, send an e-mail message for the team, but that’s my need. If you want to send a SMS message for you no matter the time, go ahead if it’s you need/want… I don’t care unless the message is sent to me! :)

Notice that not all the logging frameworks follow these convention, some of them can add or remove severity levels, but the RFC 5424 is a good starting point to understand the severity levels. With this in mind, do not be afraid if you face a trace, off or fatal in logging framework documentations…

Context data

Context data is the information about you’re logging and not using them is almost the same as not logging at all! Consider for example the log entry below:

[    9.552651] IPv6: link is not ready

So you have a problem, is investigating your dmesg output and see that a link isn’t ready… This could help you if you knew the network interface!

Other example, this one closer to our lives while developers: you have an event subscription website and someone is having a problem when tries to subscribe in a specific event, which log entries you think would help the most?


[2016-06-30 12:40:05] [INFO] User registered
[2016-06-30 12:42:11] [INFO] User activated
[2016-06-30 12:45:03] [INFO] Event subscribed by user
[2016-06-30 12:46:32] [ERROR] Fail subscribing to event by user

Or these?

[2016-06-30 12:40:05] [INFO] User 'gabrieloliverio' registered
[2016-06-30 12:42:11] [INFO] User 'gabrieloliverio' activated
[2016-06-30 12:45:03] [INFO] Event 'Foo' subscribed by user 'gabrieloliverio'
[2016-06-30 12:46:32] [ERROR] Fail subscribing to event 'Bar' by user 'gabrieloliverio'

Now think in a log file with thousands of entries, with several users registering and subscribing to events simultaneously… You can take your own conclusions :)

Log handlers

Logging frameworks usually have something they call ‘handlers’, which are structures that allow you to handle log entries based on its severity level. This way, you can use a file handler to store logs with severity Info to Critical in your filesystem and an email handler, to send an email message to your team with log entries with Critical severity level, for example.

Most of the logging frameworks support a myriad of handlers that allow you send your log entries to other tools, such as Slack, NewRelic, Loggly and Graylog, as well as storing your entries in databases, like Redis and MongoDB, for example.

Using Graylog, LogStash or Loggly, for example, you can centralize all log files to, then, search and analyze entries to discover important information, such as monitoring and analyzing user activity and response times, to, perhaps, take some proactive approach ;)

I hope you enjoyed the subject, the article and, after your reading, you can use logging in your projects to enjoy its benefits. If you have something to say, correct or insult me perhaps, leave a message below, OK?