Download JAR files tagged by tracing with all dependencies

Enables custom instrumentation by providing an SDK to capture start and end times for your functions and include arbitrary data. While AppOptics provides superior out-of-the-box performance monitoring, using the SDK can allow for more detailed transaction reporting within AppOptics's user interface. For other information on our Java agent please visit http://docs.appoptics.com/kb/apm_tracing/java/. For SDK information please visit http://docs.appoptics.com/kb/apm_tracing/java/sdk/ .

composite REST app - this represents the baseline version that the Connect-Java repository uses for building microservice based REST apps. As they are all Jersey based, there is no real need for Spring or Guice. They always include Tracing, Prometheus, Health checks, Application Lifecycle, easy config injection, Bathe for application start with Service Loader initializers. We are focused on using JIB for Docker generation.

The AppOptics Java instrumentation agent jar file. This artifact provides a convenient way to download the agent jar from public Maven repository. Please take note that this should NOT be included as a part of the project dependencies. Rather, this artifact should be integrated into the build process by using extra step such as the "copy" goal of "maven-dependency-plugin". For more information, please refer to https://docs.appoptics.com/kb/apm_tracing/java/install/#getting-the-agent-jar

The IntelligentGraph SAIL offers an extended capability for embedded calculation support within any RDF graph. When enabled as an RDF4J SAIL, it offers calculation functionality as part of the RDF4J engine, on top of any RDF4J repository, using a variety of script engines including JavaScript, Jython, and Groovy. It preserves the SPARQL capability of RDF4J, but with additional capabilities for calculation debugging and tracing. IntelligentGraph includes the PathQL query language. Just as a spreadsheet cell calculation needs to access other cells, an IntelligentGraph calculation needs to access other nodes within the graph. Although full access to the underlying graph is available to any of the scripts, PathQL provides a succinct, and efficient method to access directly or indirectly related nodes. PathQL can either return just the contents of the referenced nodes, or the contents and the path to the referenced nodes. PathQL can also be used standalone to query the IntelligentGraph-enabled RDF database. This supplements, rather than replaces, SPARQL and GraphQL, as it provides graph-path querying rather than graph-pattern querying capabilities to any IntelligentGraph-enabled RDF database. The principles of IntelligentGraph are described here: https://inova8.com/bg_inova8.com/intelligent-graph-knowledge-graph-embedded-analysis/ The full PathQL syntax is described here: https://inova8.com/bg_inova8.com/pathpatternql-intelligently-finding-knowledge-as-a-path-through-a-maze-of-facts/ Using Jupyter as an IDE to IntelligentGraph and RDF4J, shown here: https://inova8.com/bg_inova8.com/intelligentgraph-getting-started/ IntelligentGraph source is here in GitHub: https://github.com/peterjohnlawrence/com.inova8.intelligentgraph IntelligentGraph Docker containers are available here: https://hub.docker.com/repository/docker/inova8/intelligentgraph