Log Collection¶
Guance has comprehensive log collection capabilities, mainly divided into host log collection and K8S container log collection. The installation methods of DataKit for both are different, and the log collection methods are also different. The collected log data is centralized in Guance for unified storage, search and analysis, helping us quickly identify and resolve issues.
This article mainly introduces how to collect logs in host environment.
Preconditions¶
You can also login to Guance, In Integrations > DataKit and select "Linux", "Windows" and "MacOS" according to the host system, and get the DataKit installation instructions and installation steps.
Log collection¶
After the DataKit installation is completed, you can log collect various log data from system logs and application logs such as Nginx, Redis, Docker and ES by turning on standard log collection or custom log collection.
Go to the conf.d/log directory under the DataKit installation directory, copy logging.conf.sample and name it logging.conf for configuration. After the configuration is completed, restarting DataKit will take effect. Refer to Host Log Collection for details.
warning
When configuring the log collector, you need to turn on the Pipeline function of the log and extract the fields of log time time and log level status:
time: the time when the log is generated. If the time field is not extracted or parsing this field fails, the current system time is used by default.status: The level of the log. If the status field is not extracted, the default is to set stats to unknown.
See Pipeline Configuration and Use for more details.
After the log collector is configured, restart the DataKit, and the log data can be uniformly reported to the guance workspace.
Log Data Storage¶
Once the configuration of the log collector is completed, restart DataKit, and the log data will be uniformly reported to the Guance workspace.
- For users with a large amount of log data, you can use log index or log blacklist to save data storage costs;
- For users who need long-term log storage, you can use data forward to save log data.