Nutanix, Inc.

Devrev, Inc.

Jan Olderdissen

Binny Sher Gill

Miao Cui

Rajiv Mirani

Nikhil Bhatia

Sragdhara Datta Chaudhuri

Manoj Sudheendra

Viswanathan Vaidyanathan

Brian Finn

Nimar Singh Arora

Aroosh Sohi

Anindya Misra

Raghu Prasad Rapole

Viraj Sapre

Ken Chen

Toms Varghese

Vidhi Taneja

Jaspal Singh Dhillon

Brian Byrne

Thomas Jason Hill

Mengyang Li

Jerome Joseph

Shane Chu

Yj Yang

Steven Poitras

Bhavana Thudi

Manoj Agarwal

Examples of systems are described herein which may dynamically allocate compute resources to recovery clusters. Accordingly, a recovery site may utilize fewer compute resources in maintaining recovery clusters for multiple associate clusters, while ensuring that, during use, compute resources are allocated to a particular cluster. This may reduce and/or avoid vulnerabilities arising from a use of shared resources in a virtualized and/or cloud environment.

Dynamic allocation of compute resources at a recovery site

Disclosed is an improved approach to process data and events from disparate ecosystems pertaining to products. An approach is provided to automatically cluster events from various ecosystems into noteworthy incidents and to correlate them with entities extracted from each system. Incidents are correlated between ecosystems to classify the type of incidents and to give a coherent converged picture of the event streams coming from the various ecosystems. Noteworthy incidents are automatically converted into tickets and their severity is ascertained from the associated incidents. Tickets that reference underlying defects with the product or service are converted into issues.

Method and system for integrated analysis of data from multiple source environments

Examples described herein includes initialization of a computing node cluster. An example method providing a query request from an initialization application/service of a computing node for a default configuration management server identifier via a network, and receiving, from a network management server, an internet protocol address associated with the default configuration management server identifier. The example method further includes providing a configuration request from the computing node to the internet protocol address requesting configuration information, and receiving the configuration information at the computing node from a configuration management server associated with the internet protocol address.

Apparatuses and methods for zero touch computing node initialization

Examples of systems described herein may include virtualized computing environments having one or more upgrade management agents. An upgrade management agent may detect current versions of multiple components in a computing system, including at least one software component and at least one firmware component, obtain a group of updates based on the current versions of the multiple components, and schedule installation of the group of updates including grouping together installation of selected ones of the group of updates for a particular computing node of the computing system, wherein the selected ones each utilize a particular state change of the computing node during the installation. The schedule may also be selected to accommodate dependencies between multiple components which are resolved by the upgrade management agent to obtain the schedule.

Scheduling upgrades in distributed computing systems

Examples of systems and methods are described for selecting firmware versions of multiple components for a distributed computing system (e.g., a cluster). Multiple selection interfaces may be presented to a user who may select at least one firmware version of at least one component. Based on the user selection(s), a service manager may evaluate firmware component dependencies and identify compatible firmware versions of other components for installation. In this manner, a set of firmware versions may be installed and/or upgraded which may be different than a current set of versions and/or a set of versions recommended in a wholly automated manner.

Service managers and firmware version selections in distributed computing systems

Systems and method for expanding a cluster with nodes before an upgrade so that the cluster can handle a failover event during an upgrade and still continue operating. The system and method includes receiving, at a processor, a signal indicating a cluster is about to commence an upgrade; computing, by the processor, a first number of nodes; adding, by the processor, the first number of nodes from a network to the cluster before the upgrade is performed on the cluster; receiving, at the processor, a signal indicating the cluster finished the upgrade; and removing a second number of nodes that is no greater than the first number of nodes from the cluster after the processor receives the signal indicating the upgrade is complete.

System and method for the dynamic expansion of a cluster with co nodes before upgrade

Examples described herein may include virtualized environments having multiple computing nodes accessing a storage pool. User interfaces are described which may allow a user to enter one or more IP address generation formula for various components of computing nodes. Examples of system described herein may evaluate the IP address generation formula(s) to generate a set of IP addresses that may be assigned to computing nodes in the system. This may advantageously allow for systematic and efficient assigning of IP addresses across large numbers of computing nodes.

Virtual computing systems including IP address assignment using expression evaluation

Examples of systems described herein include resource management processes which may dedicate a portion of resources (e.g. memory) to serve as a dedicated leadership resource pool, accessible to only those instances of services which are designated as having a leadership role. In some examples, if sufficient resources are not available in the dedicated leadership resource pool, an instance of a service running on that computing node may decline to serve in the leadership role. Accordingly, memory and allocation of leaders may be better controlled across the distributed system in some examples.

Computing resource management using dedicated leadership pool

Growing community of inventors

Herrenberg, Germany

Jan Olderdissen