International Business Machines Corporation

Ying Mo

Yue Chen

Guangya Liu

Yue Wang

Paul R Bastide

Fang Lu

Rui Liu

Alaa Abou Mahmoud

Zhi Li

Nan Chen

Hu Wang

Qing Yu

Ju Ling Liu

Peng Li

Hai Hui Wang

Xiang Zhen Gan

Xiaoli Duan

Xing Tian

Lei Ren

Guanqin Zhang

Gui Ying Jin

Ya Xiao

Yan Wei Li

Hou Fang Zhao

Wu Di

Hui Guang Liu

Yao Chen

A method, system, and computer program product that are configured to: create a resource dependency graph that defines dependencies between resources created in an installation of a cloud native application, wherein the resource dependency graph includes a respective time range of each respective one of the resources; for each respective one of the resources, determine a condition of the respective one of the resources based on the respective time range of the respective one of the resources, a success condition of the respective one of the resources, and one or more failure conditions of the respective one of the resources; and create a cause analysis resource that includes the determined condition of each respective one of the resources.

Anomaly detection during cloud application installation

Described are techniques for providing a ready status for network connections to remote services. The techniques include monitoring network connectivity between a server and a plurality of remote services, where the server exposes the plurality of remote services to at least one application, and the server and the at least one application are hosted on a cluster of nodes managed by a container orchestration system. The techniques further include assigning to the server, based on the network connectivity between the server and the remote service, a ready status for each remote service in the plurality of remote services exposed by the server to the at least one application, where the ready status indicates a readiness of the server to provide network connections between the remote service and the at least one application.

Indicating ready statuses for network connections to remote services

A container image is deployed, at runtime, on a node within a computing environment. The deploying includes downloading, at runtime, container image content from multiple sites. The downloading includes obtaining a core image of the container image from one or more image registries and updating a local image store with the core image, and obtaining one or more add-ons of the container image from one or more add-on registries and updating a local add-on store with the one or more add-ons. The deployed container image is executed on the node.

Deployment of container images with separate add-ons

In several aspects for generation of high quality synthetic observability data for computing systems, traces and logs from a system are collected as a seed dataset. Multiple conditional variational autoencoder (VAE) models are trained using the seed dataset for learning association between the traces and the logs. Synthetic traces and logs are generated using the multiple CVAE models while retaining the association between the traces and the logs for the synthetic traces and logs.

Generating massive high quality synthetic observability data

An embodiment maps identifying information of a remote registry into a database within a local inventory at a local registry hub. An embodiment selects at least one remote registry from an index maintained in the local inventory in accordance with a policy received at a scheduler from an external client of the local registry hub. An embodiment selects a locally stored image in accordance with a policy received from an external client of the local registry hub. An embodiment uploads replicas of the selected image via one or more registry agents, each registry agent transmitting to its corresponding remote registry, transmitting constituent layers of the replica across multiple remote registries simultaneously such that a subset of the layers constituting the image are uploaded to each remote registry. An embodiment stores metadata for the uploaded image in a cache within a local metadata store.

Multiple distributed private registry management

A user's interactions with an application may be recalled for a user upon the user's return to an application. Interactions including a point of gaze and input interactions by a user within an application may be recorded. A user may become distracted, no longer interacting with the application, and this can be detected. In response, a segment of the recorded interactions can be saved. This segment can determined based on a time period prior to the detection that the user is distracted. When the user's interaction returns to the application, this can be detected, and the saved segment of interactions can be replayed to the user.

Application specific interaction based replays

Growing community of inventors

Beijing, China

Ying Mo