Abstract: A workflow resource manager receives a request to execute a workflow in a cloud computing environment. The workflow resource manager determines that a first set of cloud computing resource requirements associated with the first set of operations for the workflow is satisfied by available cloud computing resources, and responsive to determining that a second set of cloud computing resource requirements associated with a subsequent set of operations for the workflow is not satisfied by the available cloud computing resources, rejects the request to execute the workflow.

Abstract: A processing device can make use of an Artificial Intelligence (AI) model to make projections about resource usage based on data from external sources. The processing device can then adjust cloud-based resources accordingly. The cluster resource allocation can be adjusted as examples, by increasing, decreasing, or maintaining a number of nodes allocated to a cluster, by increasing, decreasing, or maintaining the number of pods assigned to an application or a container running in a cluster, or by increasing, decreasing, or maintaining central processing unit (CPU) resource, memory, disk storage, or a replication factor assigned to a pod.

Abstract: A processing device can make use of an Artificial Intelligence (AI) model to make projections about resource usage based on data from external sources. The processing device can then adjust cloud-based resources accordingly. The cluster resource allocation can be adjusted as examples, by increasing, decreasing, or maintaining a number of nodes allocated to a cluster, by increasing, decreasing, or maintaining the number of pods assigned to an application or a container running in a cluster, or by increasing, decreasing, or maintaining central processing unit (CPU) resource, memory, disk storage, or a replication factor assigned to a pod.

Abstract: A workflow resource manager receives a request to execute a workflow in a cloud computing environment. The workflow resource manager determines that a first set of cloud computing resource requirements associated with the first set of operations for the workflow is satisfied by available cloud computing resources, and responsive to determining that a second set of cloud computing resource requirements associated with a subsequent set of operations for the workflow is not satisfied by the available cloud computing resources, rejects the request to execute the workflow.

Abstract: A processing device can make use of an Artificial Intelligence (AI) model to make projections about resource usage based on data from external sources. The processing device can then adjust cloud-based resources accordingly. The cluster resource allocation can be adjusted as examples, by increasing, decreasing, or maintaining a number of nodes allocated to a cluster, by increasing, decreasing, or maintaining the number of pods assigned to an application or a container running in a cluster, or by increasing, decreasing, or maintaining central processing unit (CPU) resource, memory, disk storage, or a replication factor assigned to a pod.

Abstract: A workflow resource manager receives a request to execute a workflow in a cloud computing environment, where the workflow comprises a first set of operations and a second set of operations, and where the first set of operations precedes the second set of operations in the workflow. The workflow resource manager determines a set of cloud computing resource requirements associated with the second set of operations, determines whether the set of cloud computing resource requirements associated with the second set of operations is satisfied by available cloud computing resources, and responsive to determining that the set of cloud computing resource requirements associated with the second set of operations is not satisfied by the available cloud computing resources, rejects the request to execute the workflow.

Abstract: A workflow resource manager receives a request to execute a workflow in a cloud computing environment, where the workflow comprises a first set of operations and a second set of operations, and where the first set of operations precedes the second set of operations in the workflow. The workflow resource manager determines a set of cloud computing resource requirements associated with the second set of operations, determines whether the set of cloud computing resource requirements associated with the second set of operations is satisfied by available cloud computing resources, and responsive to determining that the set of cloud computing resource requirements associated with the second set of operations is not satisfied by the available cloud computing resources, rejects the request to execute the workflow.

Abstract: A processing device can make use of an Artificial Intelligence (AI) model to make projections about resource usage based on data from external sources. The processing device can then adjust cloud-based resources accordingly. The cluster resource allocation can be adjusted as examples, by increasing, decreasing, or maintaining a number of nodes allocated to a cluster, by increasing, decreasing, or maintaining the number of pods assigned to an application or a container running in a cluster, or by increasing, decreasing, or maintaining central processing unit (CPU) resource, memory, disk storage, or a replication factor assigned to a pod.

Abstract: A wireless camera (102) is configured to removeably connect to a complementary camera (101) and includes machine-readable software instructions configured to communicate with the complementary camera to determine a designated role (e.g., “master” or “slave”). The software instructions are capable of performing, when the designated role is “master,” the steps of: capturing a first video frame; instructing the complementary camera (101) to capture a second video frame; receiving the second video frame from the complementary camera (101); combining the first frame and the second frame to create a combined frame associated with a stereoscopic image, and wirelessly transmitting the combined frame to a mobile device (140). When the designated role is “slave,” the wireless camera (102) is capable of performing the steps of: capturing a first video frame and sending the first video frame to the complementary camera (101).