Abstract: An adaptive idle detection method determines whether software defined data centers (SDDCs) in a hyperconverged infrastructure (HCI) environment are idle. Idleness may be quantified via a coefficient of variation (CV) against resource usage, so as to adapt the idle detection method to SDDCs with different hardware specifications and workloads. Management overhead may also be filtered out by the idle detection method, and the idle detection method may use idleness scores to further reduce overhead.

Abstract: An example system including a first top-of-rack (ToR) switch, and a second ToR switch, the second ToR switch is to receive a network packet from a first host, the network packet to include a destination address of a second host, and after a failure of a physical network interface card (pNIC) at the second host eliminates a first link between the second host and the second ToR switch, send the network packet to the first ToR switch via an inter-switch link between the first and second ToR switches to cause the first ToR switch to forward the network packet to the second host via a second link between the first ToR switch and the second host.

Abstract: The current document is directed to efficient, distributed-search methods and subsystems within distributed computer systems, including computer systems distributed over multiple sets of geographically distributed data centers, each comprising multiple discrete computer systems, such as multi-processor servers. In one implementation, the distributed-search methods and subsystems are implemented locally within participating entities as well as within one or more distributed-search engines. Each search is directed, by a participant, to identify attribute-associated entities within, provided by, connected to, or otherwise accessible to a distributed computing system having attribute values specified or indicated by the search query. Certain attribute values are continuously collected and centrally stored by the one or more centralized distributed-search engines while other attribute values are obtained through information requests distributed among participating entities.

Abstract: The current document is directed to methods and systems that automatically generate training data for machine-learning-based components used by a metric-data processing-and-analysis component of a distributed computer system, a subsystem within a distributed computer system, or a standalone metric-data processing-and-analysis system. The training data sets are labeled using categorical KPI values. The machine-learning-based components are applied to metric data both for predicting anomalous operational behaviors and problems within the distributed computer system and for determination of potential causes of anomalous operational behaviors and problems within the distributed computer system. Training of machine-learning-based components is carried out concurrently and asynchronously with respect to other metric-data collection, aggregation, processing, storage, and analysis tasks.

Abstract: Disclosed are various approaches for authenticating a user through a voice assistant device and creating an association between the device and a user account. The request is associated with a network or federated service. The user can use a client device, such as a smartphone, to initiate an authentication flow. A passphrase is provided to the client device can captured by the client device and a voice assistant device. Audio captured by the client device and voice assistant device can be sent to an assistant connection service. The passphrase and an audio signature calculated from the audio can be validated. An association between the user account and the voice assistant device can then be created.

Abstract: The disclosure provides an approach for processing communications between connected data centers. Embodiments include receiving, at a first gateway of a first data center from a second gateway of a second data center, one or more policies associated with traffic attributes. Embodiments include programming priority routes between the first gateway and the second gateway over a virtual private network (VPN) tunnel based on the one or more policies, wherein each of the priority routes is associated with a traffic attribute of the traffic attributes. Embodiments include providing the one or more policies to a central controller of the first data center and programming, by the central controller, one or more tables associated with a centrally-managed virtual switch based on the one or more policies. Embodiments include updating a database associated with each of a plurality of hosts based on the programming of the one or more tables.

Abstract: Techniques for decoupling compute and storage resources in a hyper-converged infrastructure (HCI) are provided. In one set of embodiments, a control plane of the HCI deployment can provision a host from a host platform of an infrastructure on which the HCI deployment is implemented and can provision one or more storage volumes from a storage platform of the infrastructure, where the storage platform runs on physical server resources in the infrastructure that are separate from the host platform. The control plane can then cause the one or more storage volumes to be network-attached to the host in a manner that enables a hypervisor of the host to make the one or more storage volumes available, as part of a virtual storage pool, to one or more virtual machines in the HCI deployment for data storage.

Abstract: The current document is directed to methods and systems that automatically identify log/event-message traces and computational-entity transactions within collections and/or streams of log/event messages. Automated identification of log/event-message traces provides the basis for automated interpretation, by automated computer-system administration-and-the management subsystems, of the information represented by collections and/or streams of log/event messages. Disclosed approaches to automatically identifying log/event-message traces and computational-entity involve identifying log/event-message types, generating time-series-like log/event-message-type occurrence signals from log/event-message collections and/or streams, and computing cross correlations between pairs of log/event-message-type occurrence signals.

Abstract: Some embodiments of the invention provide a method for deploying network elements for a set of machines in a set of one or more datacenters. The datacenter set is part of one availability zone in some embodiments. The method receives intent-based API (Application Programming Interface) requests, and parses these API requests to identify a set of network elements to connect and/or perform services for the set of machines. In some embodiments, the API is a hierarchical document that can specify multiple different compute and/or network elements at different levels of compute and/or network element hierarchy. The method performs automated processes to define a virtual private cloud (VPC) to connect the set of machines to a logical network that segregates the set of machines from other machines in the datacenter set. In some embodiments, the set of machines include virtual machines and containers, the VPC is defined with a supervisor cluster namespace, and the API requests are provided as YAML files.

Abstract: In some embodiments, a method receives a packet at an instance of a distributed firewall associated with one of a plurality of workloads running on a hypervisor. Each of the plurality of workloads has an associated instance of the distributed firewall. An index table is accessed for the workload where the index table includes a set of references to a set of rules in a rules table. Each workload in the plurality of workloads is associated with an index table that references rules that are applicable to each respective workload. The method then accesses at least one rule in a set of rules associated with the set of references from the rules table and compares one or more attributes for the packet to information stored for the at least one rule in the set of rules to determine a rule in the set of rules to apply to the packet.

Abstract: An example method of providing a common volume (cVol) datastore for virtual machines (VMs) managed by a hypervisor in a virtualized computing system is described. The method includes: mounting, by the hypervisor, a network file system share of a common volume (cVol), the cVol stored in shared storage of the virtualized computing system, the network file system share storing metadata for the VMs; creating a file system for the cVol datastore backed by the network file system share; routing file operations targeting the metadata to the file system for the cVol datastore; and routing file operations targeting virtual disks of the VMs to an object storage pool of the cVol based on descriptors in the metadata that point to objects backing the virtual disks.

Abstract: In one example, a computing node includes a metric dependency graph knowledge base to store a data structure representing a relationship between a plurality of metrics. Further, the computing node may include a processor and a memory having a metric recommendation unit. The metric recommendation unit may determine a first metric of a monitored computing-instance while a user interacts with a GUI of a monitoring application. Further, the metric recommendation unit may retrieve the data structure corresponding to the first metric. The data structure may include the first metric and a plurality of dependent metrics associated with the first metric. Further, the metric recommendation unit may apply a machine learning model on the data structure to determine a second metric from the plurality of dependent metrics. Furthermore, the metric recommendation unit may output the second metric related to the first metric on the GUI.

Abstract: Some embodiments of the invention provide a method of detecting and remediating anomalies in an SD-WAN implemented by multiple forwarding elements (FEs) located at multiple sites connected by the SD-WAN. The method receives, from the multiple FEs, multiple sets of flow data associated with application traffic that traverses the multiple FEs. The method uses a first set of machine-trained processes to analyze the multiple sets of flow data in order to identify at least one anomaly associated with at least one particular FE in the multiple FEs. The method uses a second set of machine-trained processes to identify at least one remedial action for remediating the identified anomaly. The method implements the identified remedial action by directing an SD-WAN controller deployed in the SD-WAN to implement the identified remedial action.

Abstract: The disclosure describes growing a data cache using a background hash bucket growth process. A first memory portion is allocated to the data buffer of the data cache and a second memory portion is allocated to the metadata buffer of the data cache based on the cache growth instruction. The quantity of hash buckets in the hash bucket buffer is increased and the background hash bucket growth process is initiated, wherein the process is configured to rehash hash bucket entries of the hash bucket buffer in the increased quantity of hash buckets. A data entry is stored in the data buffer using the allocated first memory portion of the data cache and metadata associated with the data entry is stored using the allocated second memory portion of the metadata buffer, wherein a hash bucket entry associated with the data entry is stored in the increased quantity of hash buckets.

Abstract: A method comprising instantiating virtual routers (VRs) at each of a set of nodes that form a network. Each VR is coupled to the network and to a tenant of the node. The network comprises virtual links in an overlay network provisioned over an underlay network including servers of a public network. The method comprises configuring at least one VR to include a feedback control system comprising at least one objective function that characterizes the network. The method comprises configuring the VR to receive link state data of a set of virtual links of the virtual links, and control routing of a tenant traffic flow of each tenant according to a best route of the network determined by the at least one objective function using the link state data.

Abstract: Automated computer-implemented methods and systems for resolving performance problems with objects executing in a data center are described. The automated methods use machine learning to obtain rules defining relationships between probabilities of event types of in log messages and performance problems identified by a key performance indictor (“KPI”) of the object. When a KPI violates a corresponding threshold, the rules are used to evaluate run time log messages that describe the probable root cause of the performance problem. An alert identifying the KPI threshold violation, and the log messages are displayed in a graphical user interface of an electronic display device.

Abstract: The current document is directed to an improved communications protocol that encompasses XOR-based forward error correction and that uses dynamic check-packet graphs that provide for efficient recovery of packets for which transmission has failed. During the past 20 years, XOR-based forward-error-correction (“FEC”) communications protocols have been developed to provide reliable multi-packet message transmission with relatively low latencies and computational complexity. These XOR-based FEC communications protocols, however, are associated with a significant amount of redundant-data transmission to achieve reliable multi-packet message transmission. The currently disclosed XOR-based FEC communications protocol employs dynamic, sparse check-packet graphs that provide for receiver-side packet recovery with significantly less redundant-data transmission.

Abstract: TPM attestation for soft reboots is described herein. One embodiment includes instructions to receive a request to perform a soft reboot of a computing device executing an existing OS instance and having a TPM, and perform a soft reboot process on the computing device responsive to receiving the request. The soft reboot process can include loading a new kernel and boot modules associated with a new OS instance into a memory of the computing device, measuring the boot modules into PCRs of the TPM, generating entries in an event log of the TPM corresponding to the boot modules and the new kernel, exporting the event log and a metadata file associated with the existing OS instance to storage, importing the event log from storage to the new kernel, copying the metadata file from storage to a server, and storing a new metadata file created from manifests of the new OS instance at the server.

Abstract: A method for provisioning images to deploy containerized workloads in a virtualized environment can include bringing up a containerized workload in a virtualized computing environment responsive to receiving a request to run a containerized workload in the virtualized computing environment. Bringing up the containerized workload can include creating a VMDK that includes a container image in shared storage of an image registry responsive to authenticating with the image registry, attaching the VMDK to a virtual computing instance, responsive to receiving a request, made by a container running in the VCI, for a file of the container image in the attached VMDK, retrieving the file from the shared storage, and bringing up the containerized workload using the file.

Abstract: An example method of handling, at a hypervisor on a host in a virtualized computing system, a write input/output (IO) operation to a file on a storage device having a virtual machine file system (VMFS) is described. The method includes: generating logical transactions for the write IO operation having updates to metadata of the VMFS for the file; estimating, for the logical transactions, common space reservations for those of the updates to common fields in the metadata for the file; estimating, for the logical transactions, exclusive space reservations for those of the updates to exclusive fields in the metadata for the file; batching the logical transactions into a physical transaction, which includes a single reservation of space in a journal of the VMFS based on the common space reservations and a reservations of space in the journal for each of the exclusive space reservations, respectively.