![]() ![]() We will also collect new stages (filters) and tools from the iObserve project. Our future plans aim to improve build quality, release cycle and delivery of packages. In the process, we also upgrade the documentation to reflect the current state of Kieker. Therefore, we are moving the Kieker documentation to our wiki pages. While this was a practical approach in the past, it is not fitting for today. Kieker comes with a tutorial and usage guide in PDF. Furthermore, these changes will enable us to create releases faster and provide better support for releases in the long run. One effect of this migration are the aforementioned tool packages. Therefore, we slowly migrate to a more canonical layout for the Kieker project. However, many special constructs from the ant file had to be ported to gradle and do not fit typical modern Java gradle project layouts and workflows. The Kieker build system was based on an growing ant file in the past. Therefore, most tools can receive data from any reader implemented in Kieker, e.g., binary TCP (compressed or uncompressed), via REST API and from files in different formats. As this can be cumbersome to maintain this adaptive feature in an ever growing number of tools, we collected such functionality in the Kieker tool library, reducing the implementation cost. ![]() This requires that tools can adapt their pipe-and-filter configuration at startup time. Especially when it comes to reading, receiving or writing monitoring logs or other information. The tools in Kieker are highly configurable. Dot-Pic File Converter Helper script to process output files from the Trace Analysis Tool.Trace Analysis - GUI a graphical UI to control the Trace Analysis Tool.and stores them in a joint log file or repeats them to another node. Collector – Kieker Data Bridge allows to receive monitoring data from different source including TCP/binary, HTTP/JSON, files etc.Log Replayer allows to replay logs to feed them into analysis services, like iObserve and ExplorViz.Convert Logging Timestamps converts timestamps into local time.Trace Analysis Tool allows to analyze call traces through applications.Documentation to the tools is available on our wiki. As our efforts will progress, more tools will be available separately. To support this need, we now produce specific packages for tools which can be found here. However, nowadays Kieker is used in more research and commercial projects and people want to have packages for specific tasks. This had the advantage to present especially students with an easy way to get all what they need in one download. In the past Kieker produced one large distribution package containing all tools, libraries, probes, and setups. In case you are in a rush, all the new features can be found in the current Kieker snapshot and will be part of Kieker 1.15. As these additions are numerous, we will present only a brief overview in this article and add new posts to provide more details to certain new additions. In this article, we will introduce the new stages and tools which originated in iObserve or where first used by iObserve, as the key user for the addition. Therefore, users of Kieker tooling do no longer need to download the complete Kieker package and extract the tools they need. Furthermore, we updated the build process to create ready to use packages for these tools. In this process, we created new tools and ported older Kieker tools to TeeTime. In the iObserve project, we heavily relied on TeeTime and the new Kieker stages (filter) implemented and ported to work with TeeTime. In recent years we started to use the new pipe-and-filter framework TeeTime for the analysis and tool part which reduces the amount of configuration and implementation code necessary to create your own combination of analyses. The Kieker monitoring framework and toolset comprises different monitoring probes utilizing different probe introduction mechanisms for Java and other languages, a wide variety of analysis stages to receive, read and analyze monitoring data, and tools to support handling data and creating analyses based on monitoring data. ![]()
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