Hi all, I am initiating a significant revitalization of the official rsyslog Docker image project. This long-term effort aims to establish a robust and easily manageable rsyslog presence within containerized environments, particularly within microservice architectures. I have now done the initial commits, which are now visible to the world-at-large :-)
Our initial focus is on solidifying the foundational technology. We are leveraging Ubuntu LTS and the Adiscon PPA for consistent, up-to-date rsyslog versions. A key design principle is layered images with extensive runtime configurability. As you know, traditionally, rsyslog configuration has presented a steep learning curve. Our new approach seeks to mitigate this by providing pre-validated configurations for common use cases. These can be activated and tuned simply by setting environment variables, effectively transforming rsyslog into a more plug-and-play component. As a concrete example of this design philosophy, consider the 'rsyslog-dockerlogs' container. This variant directly interfaces with the Docker API (using imdocker), enabling native log collection from containers and enrichment with relevant Docker metadata. This functionality, often requested but historically challenging for users to implement and configure manually, is now automatically available for default scenarios with minimal environment variable adjustments. We acknowledge the existence of a small number of community-driven rsyslog Docker images. While some of these are high-quality, they tend to be use-case specific. Our objective is to provide a broader, officially supported solution that addresses diverse logging needs. Along this way, enhancements to rsyslog itself will be made. For example, I am right now in the process of adding a Prometheus metrics scraping point, implemented via imhttp. I already merged a PR to enable impstats to use Prometheus format in addition to the other formats supported. This project is currently in an active development and testing phase. Consequently, configurations and output formats should be considered subject to change as we refine and streamline the system. Your technical expertise is critical during this period. We encourage early adopters to deploy and test these images. We are also exploring integrations with data analysis tools such as Grafana, to provide a comprehensive, resource-efficient monitoring solution for small and medium-sized organizations. Please provide feedback and report any observations directly via issues on our GitHub repository: https://github.com/rsyslog/rsyslog-docker/issues As usual, your contributions will directly influence the stability and feature set of future releases. As a side-note: I am currently considering the best ways to integrate AI technology for better code quality, doc and broader reach. I did so for several months, but recent advancements in AI boosted the quality. I'll probably announce some changes like support files for AI agents within the next time. I case you see something upcoming on git, you now know at least why this is ;-) Thanks again to everyone. I hope this will be a well-perceived effort. It took all of us in the rsyslog core time quite some time to iron out the initial hurdles, but now we have a plan. Rainer _______________________________________________ rsyslog mailing list https://lists.adiscon.net/mailman/listinfo/rsyslog http://www.rsyslog.com/professional-services/ What's up with rsyslog? Follow https://twitter.com/rgerhards NOTE WELL: This is a PUBLIC mailing list, posts are ARCHIVED by a myriad of sites beyond our control. PLEASE UNSUBSCRIBE and DO NOT POST if you DON'T LIKE THAT.
