Logging In

Log service for centralized logging. This is Elastic Stack, Slack, Graylog, and other similar products. To handle large amounts of data, you need a logging stack with a powerful parser / visualizer. Part of the infrastructure can be one of these services and each host in the environment is configured to forward log files on behalf of each service. It tracks the definition of the ID and enables the location of all logs in all micro services that process a single external request. The idea here is to generate a unique ID for each external request entering the micro service and pass that ID to the internal micro service call processing the request. Therefore, by searching a single tracking ID, you can find all micro service calls generated by a single external access.

A new log file is created daily and audit logging and client user activity are enabled. The audit log file is named according to the structure is_auditYYYMMDD.log. For example, is_audit20091231.log. The _is prefix is ​​due to the audit log file being generated by the Image Server service. In addition to managing application log files, all log files are checked for integrity every 24 hours. Consistency checking is performed by the system's log checking service. The result of the consistency check is automatically written to a file named according to the LogCheck_YYYYMMDD.log structure such as LogCheck_20091231.log. As with the log file itself, the log check file is in the corresponding All Users folder of your operating system by default.

Look now, they should be in / var / log. A file called nginx_something.log. In the console, enter "wc - l / var / log / nginx _*. Log". What number did you get? This is the number of times the engineer visited since the last log update. Depending on the amount, maybe you have something unique! If you read a file line by line, you can also tell if the user is desktop or mobile, which page has the most traffic. Get numbers from Google Docs or allow engineers to browse databases. There should be something like "customer" or "user". No matter what, no matter what, we just learned something the competitors do not know.