Abstract: A method and apparatus for autonomous container management configuration changes to container clusters during runtime and autonomous configuration-based release orchestration. A release manager manages a staggered feature release that includes staggers, stagger order, and container clusters included in each stagger. A logging service manages logs generated by the container clusters and/or app containers. An update service determines container management configuration changes based on analysis of data provided by the logging service. A shared engine attempts to implement instructions provided by the release manager and the update service at different times. The release manager receives an indication of success or failure of the attempted deployment of the feature release to the current stagger. The release manager, responsive to the indication of success or failure, determines to perform one of a plurality of actions, including attempting to deploy the feature release to the next stagger, and rolling back.

Abstract: A method and apparatus for autonomous container management configuration changes to container clusters during runtime and autonomous configuration-based release orchestration. A release manager manages a staggered feature release that includes staggers, stagger order, and container clusters included in each stagger. A logging service manages logs generated by the container clusters and/or app containers. An update service determines container management configuration changes based on analysis of data provided by the logging service. A shared engine attempts to implement instructions provided by the release manager and the update service at different times. The release manager receives an indication of success or failure of the attempted deployment of the feature release to the current stagger. The release manager, responsive to the indication of success or failure, determines to perform one of a plurality of actions, including attempting to deploy the feature release to the next stagger, and rolling back.

Abstract: A method and apparatus for autonomous release orchestration that supports staggered releases across a plurality of container clusters. A representation of a risk level for a current release is obtained. Based on the risk level, a set of one or more attributes of a stagger configuration is determined. An attempt to deploy the current release to the plurality of container clusters in accordance with the stagger configuration is caused.

Abstract: A method and apparatus for autonomous configuration-based release orchestration that supports staggered feature releases across a plurality of container clusters. A release seeking goal is obtained. An unprocessed stagger is selected as a current stagger based on a stagger order. The current stagger is processed by attempting to cause a deployment of the feature release to the container clusters in the current stagger, receiving an indication of success or failure of the attempted deployment, and determining whether to roll back the current stagger based on the indication. A determination is made whether the release seeking goal can still be met. If the release seeking goal can no longer be met, a release level rollback is caused, and otherwise the selecting, processing, and determining is repeated for the next unprocessed stagger based on the stagger order.

Abstract: A method and apparatus for autonomous configuration-based release orchestration. A first engine obtains stagger configuration data that includes an indication of container clusters in each stagger and a stagger order, selects a current stagger based on the order, and attempts to deploy the feature release to the current stagger by causing an app config update to be sent to a second engine within each container cluster of the current stagger, and receives an indication of success or failure of the attempted deployment of the feature release to the current stagger. Responsive to the indication of success or failure, the first engine performs one of a plurality of actions that include attempting to deploy the feature release to a next one of the staggers according to the order responsive to the indication indicating success, and causing a roll back of the current stagger responsive to the indication indicating failure.

Abstract: Embodiments of the present disclosure relate to detecting and mitigating errors associated with software pull requests such as software deployment packages. The embodiments include identifying a failure of a pull request, identifying a system error associated with the failure, determining a failure mitigation process based on the failure and the system error, and executing the failure mitigation process to resolve the failure. The errors can be classified as system errors, user errors or planned downtime. The failure mitigation process can include generating an alert associated with the identified system error, updating a status of the pull request, re-evaluating the failure after a predetermined period of time, and retrying deployment of the pull request using an exponential retry process.

Abstract: Among other things, embodiments of the present disclosure relate to detecting and mitigating errors associated with software pull requests (PRs). Other embodiments may be described or claimed.

Abstract: System and methods are described for distributing artifacts in a cloud computing environment. Processing includes receiving an artifact at an upstream computing system in a network of computing systems, the artifact including a file of a continuous integration (CI) process, dividing the artifact into chunks, storing the chunks into a shared storage of the upstream computing system accessible by downstream computing systems of the network, determining downstream computing systems in the network to receive the artifact, receiving a request from one of the downstream computing systems for a chunk of the artifact; and providing the chunk to the downstream computing system from the shared storage.

Abstract: System and methods are described for distributing artifacts in a cloud computing environment. Processing includes receiving an artifact at an upstream computing system in a network of computing systems, the artifact including a file of a continuous integration (CI) process, dividing the artifact into chunks, storing the chunks into a shared storage of the upstream computing system accessible by downstream computing systems of the network, determining downstream computing systems in the network to receive the artifact, receiving a request from one of the downstream computing systems for a chunk of the artifact; and providing the chunk to the downstream computing system from the shared storage.