Abstract: Generation of multi-stage container images using Artificial Intelligence (AI) is provided and includes retrieving a first input that includes a set of instructions associated with an application. A set of build stages is generated based on the first input and a first set of errors associated with a first subset of instructions of the set of instructions are identified. The first subset of instructions is associated with a first build stage of the set of build stages. An AI model is applied to the first set of errors and the first set of errors is resolved based on the application of the AI model to the first set of errors. Based on the resolution of the first set of errors a first portion of a container image is generated and outputted.

Abstract: Generation of a compliance graph includes receiving a deployment input associated with a set of workload resources. Compliance data associated with the set of workload resources is retrieved. The compliance graph associated with the set of workload resources is generated based on the retrieved compliance data. A plurality of vulnerabilities associated with a plurality of workload resources is monitored. The plurality of workload resources includes the set of workload resources. A set of vulnerabilities are identified from the plurality of vulnerabilities. A set of vulnerability metrics associated with the set of vulnerabilities are determined. The compliance graph is updated based on the set of vulnerability metrics.

Abstract: Controlling resource access requests in a containerized platform includes receiving a request to access a resource associated with a containerized platform. A set of authorization plugins is determined based on the request. A request relay model is applied to the request. The request is transmitted to each authorization plugin of the set of authorization plugins based on the application of the request relay model to the request. A response of a set of responses is determined based on the transmission of the request to an authorization plugin of the set of authorization plugins. A response analyzer model is applied to the set of responses. The access to the resource associated with the containerized platform is controlled based on a set of security levels and the application of the response analyzer model to the set of responses.

Abstract: Horizontal pod autoscaling based on real-time request rate includes detecting a trigger associated with the scaling of a set of pods. A count of a set of real-time requests accessing a service of an application based on the trigger is determined. A health ratio value is obtained for each pod of the set of pods. An available request handling capacity is determined for each pod of the set of pods based on the trigger. An empirical coefficient value is determined based on a set of metrics associated with the set of pods. A scaling coefficient is calculated based on the count of the set of real-time requests, the health ratio value, the available request handling capacity value, and the empirical coefficient value. The set of pods is modified based on the scaling coefficient and an instantiation of the modified set of pods is controlled.

Abstract: Computer implemented methods, systems, and computer program products include program code executing on a processor(s) (in the confidential computing environment), obtaining, from an untrusted computing resource, via a secure channel between the confidential computing environment and the untrusted computing resource, a debugging command in a command request packet. The processor(s) analyzes the packet to determine a security level for the debugging command and a security level for the confidential computing environment, wherein the analyzing comprises comparing a quantitative value of the security level for the debugging command to a quantitative value of the security level for the confidential computing environment. The processor(s) generates a command reply packet, wherein contents of the command reply packet and based on the comparing. The processor(s) transmits the command reply packet to the untrusted computing resource via the secure channel.

Abstract: Updating a first base layer of at least one operational container includes detecting a trigger to update the first base layer of the at least one operational container. A system imports the at least one operational container in a replacement memory of at least one containerization system based on the detection of the trigger. The system imports a second base layer of the at least one operational container in the replacement memory based on the importation of the at least one operational container in the replacement memory. The system associates the second base layer with a container filesystem of the at least one operational container based on the importation of the second base layer in the replacement memory. The system updates the first base layer with the second base layer based on the association of the second base layer.

Abstract: The present invention relates to a high-speed protocol conversion device and a parallel processing unit for industrial heterogeneous networks, and belongs to the technical field of industrial Internet. The device comprises a queue transceiver unit, a protocol conversion unit, a parallel processing unit and an SDN management interface unit; uses a wireless module to receive and transmit data of an industrial wireless network; and uses a network card to receive and transmit data of an industrial wired network and data of an IPv6 backbone network.

Abstract: Controlling update of instruction sets based on identifiers includes retrieving a first identifier associated with a first instruction set. The first instruction set is deployed within an application hosted on one of a cloud platform or an electronic device. A second identifier associated with a second instruction set is retrieved. The second instruction set is hosted on the cloud platform. The first identifier and the second identifier are analyzed. It is determined that the first identifier is different from the second identifier. The second instruction set is retrieved from cloud platform based on the determination that the first identifier is different from the second identifier. The application is updated based on the retrieved second instruction set. The update of the application corresponds to a replacement of the first instruction set within the application with the second instruction set. Further, the updated application is outputted.

Abstract: A method, system, and computer program product configured to perform operations including: identifying sensitive variables marked with a confidential computing sensitive tag within a compiled microservice code; identifying unmarked variables related to the sensitive variables within the compiled microservice code; tagging the unmarked variables related to the sensitive variables with a sensitive attribute; generating debugging information entries comprising the sensitive variables and the sensitive attribute tag of the tagged unmarked variables; generating a protect flag in a debugging reply packet based on the debugging information entries; and denying data access to downstream debugger clients based on the protect flag.

Abstract: In the present application, a tunnel oxide layer is deposited by means of a combination of PECVD and PEALD. A thin oxide layer with a thickness of 0.1 nm to 0.5 nm is pre-deposited by means of PECVD. In a subsequent PEALD process, the thin oxide layer chemically passivates a surface of a substrate, and then the PEALD process is configured to uniformly deposit a tunnel oxide layer on the basis of the oxide layer. The basic principle of such growth mode is atomic layer deposition.

Abstract: Management of compute resources for containers includes obtaining first usage data associated with at least one container and obtaining a set of threshold parameters. A system compares the first usage data with the set of threshold parameters. The system detects a first anomaly associated with a usage of the one or more compute resources by the at least one container. The system also determines a first set of allocation parameters associated with the at least one container. The system also generates a first allocation command for allocating the one or more compute resources to the at least one container.

Abstract: A computer-implemented method includes receiving a request from a user, the request being one of a first request to push an image layer of a container from a local graph to an image repository or a second request to pull an image layer of a container image from the image repository to the local graph. The method further includes identifying permissions associated with the user and determining whether the permissions associated with the user authorize the user to perform an action associated with the request. The method further includes, responsive to determining that the permissions associated with the user authorize the user to perform the action associated with the request, performing the action, the action being one of pushing the image layer of the container from the local graph to the image repository or pulling the image layer of the container image from the image repository to the local graph.

Abstract: An image layer of a container image deployed as a container on a local resource is identified as having a patch in error. The image layer is marked, at an image repository, as having the patch in error. It is determined that one or more image layers of the container have a dependency on the image layer having the patch in error. The one or more image layers that have the dependency are indicated at the image repository. Recovery of the container is initiated, and the recovery is based on at least one of the marking or the indicating. To recover the container, selected image layers are to be pulled from the image repository. The image layer marked as having the patch in error and the one or more image layers indicated as having the dependency on the image layer are to be omitted from being pulled.

Abstract: Container dependency management is provided. The container dependency management includes identifying a software service process file for a container at runtime, comparing the software service process file to a dependency management file for the container to identify one or more unreferenced dependencies, deleting the one or more unreferenced dependencies from the container, and in response to identifying a run error related to a first deleted dependency of the one or more unreferenced dependencies, rolling back deletion of the first deleted dependency.

Abstract: World foundation models (WFMs) are trained to process video frames (observations) and a text prompt (perturbation) to generate output video corresponding to future observations based on the video frames and text prompt. Training WFMs requires a large amount of high-quality video training data with diverse content and action that is consistent with the physical world. The WFMs are trained to generate output video while maintaining three-dimensional consistency and physics accuracy. An image data curation pipeline is implemented that may be scaled to process large quantities of video data to produce a high-quality video training dataset.

Abstract: An image layer of a container image deployed as a container is identified as having a patch in error. The image layer is marked, at an image repository, as having the patch in error. It is determined that one or more image layers have a dependency on the image layer. The dependency for a particular image layer is one type selected from multiple types including a direct dependency and an indirect dependency. The one or more image layers that have the dependency are indicated at the image repository. Recovery of the container is initiated, and the recovery is based on at least one of the marking or the indicating. To recover the container, selected image layers are to be pulled from the image repository. The image layer marked as having the patch in error and the one or more image layers are to be omitted from being pulled.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: performing natural language processing to process a text string of a user, wherein the text string specifies characteristics of a container image to be built; processing, with use of natural language processing, instances of text-based data that describe respective ones of a plurality of container images stored within a container image repository; selecting, in dependence on a result of the performing natural language processing, and the processing, a base image from the plurality of container images; and presenting prompting data to the user that prompts building of a new container image, wherein the prompting data references the base image.

Abstract: Embodiments of the present disclosure provide a solution for multimodal data processing. A method comprises: obtaining image data and text data; and extracting a target visual feature of image data and a target textual feature of text data using a feature extraction model. The feature extraction model comprises alternatively deployed cross-modal encoding parts and visual encoding parts. The extracting comprises: performing, using a first cross-modal encoding part of the feature extraction model, cross-modal feature encoding on a first intermediate visual feature of the image data and a first intermediate textual feature of the text data, to obtain a second intermediate visual feature and a second intermediate textual feature; performing, using a first visual encoding part of the feature extraction model, visual modal feature encoding on the second intermediate visual feature, to obtain a third intermediate visual feature.

Abstract: A computer-implemented method for debugging microservices within a Trusted Execution Environment (TEE). The TEE receives a debugging script and its corresponding digital signature. The debugging script is digitally signed by a private key to create the digital signature. The TEE verifies the authenticity and integrity of the debugging script by using a public key to validate the digital signature. The TEE executes the debugging script to perform debugging operations on the microservices and generates debugging results. The TEE encrypts the debugging results using the public key and transmits the encrypted debugging results to a logging service for storage.

Abstract: A supramolecule compound, a two-dimensional rare earth oxysalt, and a preparation method therefor are provided. By utilizing a series of ?-conjugated planar supramolecule compounds as synthesis templates, a variety of novel two-dimensional rare earth oxysalts can be produced. By carefully fine-tuning the properties of the supramolecule compound template, along with the types of oxoanion and organic amine, it is possible to effectively and precisely obtain two-dimensional rare earth oxysalts with diverse structures. This template-based synthesis strategy, leveraging supramolecule compounds, is highly versatile and applicable to all rare earth elements. It enables the preparation of two-dimensional rare earth oxysalts with uniform structures, containing either a single rare earth element or multiple elements, and allows for precise control over the material's properties.