Given that traditional apps log to files on a local disk, when migrated to an elastic multi-instance model, logging can become unmanageable. This cloud anti-pattern must be remediate in any cloud migration effort. Apprenda attaches to traditional application logging models to reroute local, on-disk logging and stream writing to a cloud scale logging aggregator service that’s complete with cross instance log searching, contextual tagging, and log pruning. For example, Apprenda instruments into Tomcat’s logging to be able to capture Tomcat’s outputs (e.g. stdout/stderr), as well as to be able to modify Tomcat’s logging levels (together with a listener that picks up log override updates when they happen globally on the platform). Apprenda also detects usage of common logging abstractions (e.g. log4j in Java and log4net in .NET) and replaces configured appenders to route files to the on-platform cloud logging system and/or forward logs to other cloud scale logging stacks such as ELK or AWS’ cloud watch. This remediates the logging anti-pattern that would otherwise significantly increase migration friction of traditionally architected applications, while also enhancing the cloud debugging experience by providing an aggregate, multi-instance log management system
Apprenda’s Logging System allows developers to log messages easily and efficiently, even on a distributed network of servers. Complete with log levels, filtering, and notifications, the Logging System provides an out of the box way to handle most application logging needs.