Build a Custom Container Plugin using the Go SDK
Digital.ai Release brings in the new integration SDK experience for you to run tasks as containers, using any language or third-party library.
Digital.ai Release brings in the new integration SDK experience for you to run tasks as containers, using any language or third-party library.
Digital.ai Release brings in the new integration SDK experience for you to run tasks as containers, using any language or third-party library.
The configuration parameters for Release Remote Runners are set or overridden using the configuration files, environment variables, or command line switches.
Digital.ai Release Integration Python SDK is a set of tools that Developers can use to build container-based plugins. With Digital.ai Release 23.1, we are bringing in a new integration SDK experience with which you can run tasks as containers, using any language or third-party libraries.
When the Release Remote Runner is registered on the Release server, the readiness state of the Runner is healthy, and allows it to receive tasks or scripts for execution.
Remote runners are introduced with Digital.ai Release 23.1 to efficiently and effectively manage the execution of container-based tasks within a Kubernetes cluster. These isolate the task execution process and provides greater stability and scalability for executing tasks.
This topics describes the lifecycle, control commands, and the different states of a Release Remote Runner, with regards to the availability of the Release server.
Release Remote runners are introduced with Digital.ai Release 23.1 to efficiently and effectively manage the execution of container-based tasks within a Kubernetes cluster. These isolate the task and script execution process and provides greater stability and scalability for executing tasks.
Install Remote Runners using XL Kube
For Release Remote Runner, to use TLS communication with Release, the configuration settings for the truststore must be set.
This topic illustrates on how to set up JVM arguments for Relase containers.
The logging feature in Release Remote Runner is the best solution to troubleshoot and check for the state of runner lifecycle or the state of execution.