Vmware, Inc.

Nicira, Inc.

Hailing Xu

Liang Cui

Ying Jian He

Dongping Chen

Jian Lan

Jianjun Shen

Uday Suresh Masurekar

Mani Kancherla

Weiqing Wu

Aravind Srinivasan

Shudong Zhou

Todd Sabin

Yan Qi

Xi Zeng

Juntao Liu

Prachi Dalvi

Shuting Ma

K Antion Shiban

Howie Xu

Ying He

An example method of propagating fault domain topology information in a distributed container orchestration system includes: receiving, at control plane software executing in a data center, the fault domain topology, which includes tags for a protection group and fault domains for remote sites in communication with the data center; deploying, by a master server of the distributed container orchestration system that executes in the data center, a node pool comprising virtual machines (VMs) executing in servers of the remote sites, the VMs being nodes of the distributed container orchestration system in which containers execute; determining, by a controller of the master server, relationships among the VMs, the servers, the protection group, and the fault domains based on state of resources maintained by the master server; and providing, by the controller, labels to the servers for associating the tags of the protection group and the fault domains to the VMs.

Propagating fault domain topology to nodes in a distributed container orchestration system

Embodiments described herein relate to managing firewall rules. Embodiments include identifying a plurality of firewall rules for request handling. Embodiments include determining a deny count for each given firewall rule of the plurality of firewall rules based on a number of requests flagged on account of the given firewall rule. Embodiments include determining an anomaly score for each given firewall rule of the plurality of firewall rules indicating a severity of attacks the given firewall rule protects against. Embodiments include determining an urgency measure for each given firewall rule of the plurality of firewall rules based on the deny count for the given firewall rule and the anomaly score for the given firewall rule. Embodiments include determining an update to at least one firewall rule of the plurality of firewall rules based on the urgency measure for each given firewall rule of the plurality of firewall rules.

Managing firewall rules based on triggering statistics

The disclosure herein describes a system for providing distributed global server load balancing (GSLB) over resources across multiple data centers. The system includes a directory group comprising one or more directory nodes and a plurality of GSLB nodes registered to the directory group. A respective GSLB node is configured to provide GSLB services over a respective portion of the resources. A directory node includes a domain name system (DNS) query-receiving module configured to receive a DNS query from a client, a node-selecting module configured to select from the plurality of GSLB nodes a first GSLB node based at least on the DNS query, and a DNS query-responding module configured to respond to the DNS query to the client using an address of the selected first GSLB node, thereby facilitating the selected first GSLB node in performing GSLB while resolving the DNS query.

Distributed global load-balancing system for software-defined data centers

A method includes indexing data and/or metadata in online virtual machines (VMs), offline VMs, virtual applications, and/or snapshots thereof on one or more host server(s) in a virtualization environment through a search architecture in the virtualization environment. The online VMs are VMs that are powered on, and the offline VMs are VMs that are powered off. The method also includes maintaining a database of the indexed data and/or metadata in the online VMs, the offline VMs, the virtual applications, and/or the snapshots thereof to enable a comprehensive search result to a search query through the search architecture. The database is associated with the search architecture.

Comprehensive, relevant, and dynamic data searching in a virtualization environment

Embodiments monitor application performance metrics representing the performance of a software application executed by one or more host computing devices. Based on the application of rules to the application performance metrics, an elasticity action, such as a power-on action, a power-off action, a deploy action, and/or a destroy action, is determined. The elasticity action is transmitted to one or more target hosts, which perform the elasticity action. The target host may be selected based on host performance metrics. Further, a load balancing service may accommodate the addition of a new software application instance to a cluster and/or the removal of an existing software application instance from the cluster.

Elastic allocation of computing resources to software applications

Growing community of inventors

Peking, China

Hailing Xu