Abstract: Aspects of the disclosure are directed to methods, systems, and computer readable media for managing artificial intelligence and machine learning (“AI/ML”) datasets in cloud storage, especially for creating and controlling bookmarks or other references in cloud storage for a dataset selected for use for training ML models. Bookmarks are sets of object references that are used as a training data for the ML model. The bookmarks serve as a means for the ML platform to preserve a collection of objects in a cloud storage bucket. The bookmarks serve as references to objects in the buckets to preserve a dataset, instead of continuously replicating the objects selected for training. Bookmarks are used for grouping, providing access, and downloading objects in bulk. The ML platform can also grant buckets or bookmarks permission to make data accessible to specified entities.

Abstract: A distributed resource may be mapped into a virtual network, where the resource is distributed across a large number of nodes that are uniquely addressable within the distributed resource service's address space. The resource can be represented using a relatively small number of private VIP addresses within the virtual network, while still enabling access to all of the nodes that are uniquely addressable within the address space of the distributed resource service. A resource map may be created that relates the distributed resource service's address space to the virtual network's address space. The resource map may be used by a gateway that facilitates access to a distributed resource by clients. The resource map may also be used to translate packets that are sent from clients within a virtual network into the distributed resource service's address space.

Abstract: A distributed resource may be mapped into a virtual network, where the resource is distributed across a large number of nodes that are uniquely addressable within the distributed resource service's address space. The resource can be represented using a relatively small number of private VIP addresses within the virtual network, while still enabling access to all of the nodes that are uniquely addressable within the address space of the distributed resource service. A resource map may be created that relates the distributed resource service's address space to the virtual network's address space. The resource map may be used by a gateway that facilitates access to a distributed resource by clients. The resource map may also be used to translate packets that are sent from clients within a virtual network into the distributed resource service's address space.

Abstract: A distributed resource may be mapped into a virtual network, where the resource is distributed across a large number of nodes that are uniquely addressable within the distributed resource service's address space. The resource can be represented using a relatively small number of private VIP addresses within the virtual network, while still enabling access to all of the nodes that are uniquely addressable within the address space of the distributed resource service. A resource map may be created that relates the distributed resource service's address space to the virtual network's address space. The resource map may be used by a gateway that facilitates access to a distributed resource by clients. The resource map may also be used to translate packets that are sent from clients within a virtual network into the distributed resource service's address space.

Abstract: A distributed resource may be mapped into a virtual network, where the resource is distributed across a large number of nodes that are uniquely addressable within the distributed resource service's address space. The resource can be represented using a relatively small number of private VIP addresses within the virtual network, while still enabling access to all of the nodes that are uniquely addressable within the address space of the distributed resource service. A resource map may be created that relates the distributed resource service's address space to the virtual network's address space. The resource map may be used by a gateway that facilitates access to a distributed resource by clients. The resource map may also be used to translate packets that are sent from clients within a virtual network into the distributed resource service's address space.

Abstract: A distributed resource may be mapped into a virtual network, where the resource is distributed across a large number of nodes that are uniquely addressable within the distributed resource service's address space. The resource can be represented using a relatively small number of private VIP addresses within the virtual network, while still enabling access to all of the nodes that are uniquely addressable within the address space of the distributed resource service. A resource map may be created that relates the distributed resource service's address space to the virtual network's address space. The resource map may be used by a gateway that facilitates access to a distributed resource by clients. The resource map may also be used to translate packets that are sent from clients within a virtual network into the distributed resource service's address space.

Abstract: Techniques for allowing access to shared cloud resource using private network addresses are disclosed herein. In one embodiment, a connection packet representing a connection request to a shared cloud resource in the cloud computing system can be intercepted. In response, the connection packet can be encapsulated with data representing one or more of a VNET ID, a VNET source address, or a VNET destination address of a virtual network from which the connection packet is received. The encapsulated connection packet can then be forwarded to the shared cloud resource while retaining the data representing one or more of the VNET ID, the VNET source address, or the VNET destination address for access control at the shared cloud resource.

Abstract: Techniques for allowing access to shared cloud resource using private network addresses are disclosed herein. In one embodiment, a connection packet representing a connection request to a shared cloud resource in the cloud computing system can be intercepted. In response, the connection packet can be encapsulated with data representing one or more of a VNET ID, a VNET source address, or a VNET destination address of a virtual network from which the connection packet is received. The encapsulated connection packet can then be forwarded to the shared cloud resource while retaining the data representing one or more of the VNET ID, the VNET source address, or the VNET destination address for access control at the shared cloud resource.

Abstract: A system is provided and includes a processor and a non-transitory computer-readable medium configured to store instructions for execution by the processor. The instructions include: accessing a resource via a first machine in a cloud-based network, where the first machine is a virtual machine; converting at the first machine an IPv4 packet to a IPv6 packet; while converting the IPv4 packet, embedding metadata in the IPv6 packet, where the metadata includes information identifying the first machine or a virtual network of the first machine; and transmitting the IPv6 packet to a second machine to limit access to the resource based on the information identifying the the first machine or the virtual network of the first machine. The second machine limits access to the resource based on the information identifying the at least one of the first machine or the virtual network of the first machine.

Abstract: A population of devices provides telemetry data and receives software changes or updates. Event buckets for respective events are found. Event buckets have counts of event instances, where each event instance is an occurrence of a corresponding event reported as telemetry by a device. Records of the software changes are provided, each change record representing a software change on a corresponding device. The event buckets are analyzed to identify which indicate an anomaly. Based on the change records and the identified event buckets, correlations between the software changes and the identified event buckets are found.

Abstract: A population of devices provides telemetry data and receives software changes or updates. Event buckets for respective events are found. Event buckets have counts of event instances, where each event instance is an occurrence of a corresponding event reported as telemetry by a device. Records of the software changes are provided, each change record representing a software change on a corresponding device. The event buckets are analyzed to identify which indicate an anomaly. Based on the change records and the identified event buckets, correlations between the software changes and the identified event buckets are found.

Abstract: A population of devices provides telemetry data and receives software changes or updates. Event buckets for respective events are found. Event buckets have counts of event instances, where each event instance is an occurrence of a corresponding event reported as telemetry by a device. Records of the software changes are provided, each change record representing a software change on a corresponding device. The event buckets are analyzed to identify which indicate an anomaly. Based on the change records and the identified event buckets, correlations between the software changes and the identified event buckets are found.