Example implementations relate to consensus protocols in a stretched network. According to an example, a distributed system includes continuously monitoring network performance and/or network latency among a cluster of a plurality of nodes in a distributed computer system. Leadership priority for each node is set based at least in part on the monitored network performance or network latency. Each node has a vote weight based at least in part on the leadership priority of the node. Each node's vote is biased by the node's vote weight. The node having a number of biased votes higher than a maximum possible number of votes biased by respective vote weights received by any other node in the cluster is selected as a leader node.

Techniques are provided for managing resources among clusters of computing devices in a computing system. Resource reassignment message are generated for indicating that servers are reassigned and in response to resource compute loads exceed or fall below certain thresholds. Techniques also include establishing communications with the reassigned servers to assign compute loads without physically relocating the servers from one cluster to another cluster.

Example implementations relate to a role-based autoscaling approach for scaling of nodes of a stateful application in a large scale virtual data processing (LSVDP) environment. Information is received regarding a role performed by the nodes of a virtual cluster of an LSVDP environment on which a stateful application is or will be deployed. Role-based autoscaling policies are maintained defining conditions under which the roles are to be scaled. A policy for a first role upon which a second role is dependent specifies a condition for scaling out the first role by a first step and a second step by which the second role is to be scaled out in tandem. When load information for the first role meets the condition, nodes in the virtual cluster that perform the first role are increased by the first step and nodes that perform the second role are increased by the second step.

The subject technology selects a particular zone among multiple zones based on a target skew to meet a global balancing of cluster instances. The subject technology deploys a particular type of cluster instance to the particular zone. The subject technology, for each zone from the multiple zones, determines a respective number of cluster instances. The subject technology identifies a second particular type of cluster instance to remove based on a total number of the second particular type of cluster instance in the multiple zones and a second total number of the particular type of cluster instance in the multiple zones. The subject technology removes the second particular type of cluster instance from a second particular zone to meet the global balancing of cluster instances in the multiple zones.

A gateway performs silent authentication refreshes with an identity management platform in order to extend the expiration of a cookie provided to an endpoint that accesses network applications through the gateway.

A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include compiling cost data for at least one node and revenue data for at least one pod. The operations may include calculating a resource value of a node of the at least one node with the cost data and quantifying a priority value of a pod of the at least one pod with the revenue data. The operations may include pairing the priority value of the pod with the resource value of the node and assigning the pod to the node.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating customized recommendations for environmentally-conscious cloud computing frameworks for replacing computing resources of existing datacenters. One of the methods involves receiving, through a user interface presented on a display of a computing device, data regarding a user's existing datacenter deployment and the user's preferences for the new cloud computing framework, generating one or more recommendations for environmentally-conscious cloud computing frameworks based on the received data, and presenting such recommendations through the user interface for the user's review and consideration.

A method for performing scheduling includes extracting information from at least one log file for an application. The method also includes determining an allocation of cloud resources for the application based on the information from the log file(s).

Some embodiments provide a novel method for deploying containerized applications. The method of some embodiments deploys a data collecting agent on a machine that operates on a host computer and executes a set of one or more workload applications. From this agent, the method receives data regarding consumption of a set of resources allocated to the machine by the set of workload applications. The method assesses excess capacity of the set of resources for use to execute a set of one or more containers, and then deploys the set of one or more containers on the machine to execute one or more containerized applications. In some embodiments, the set of workload applications are legacy workloads deployed on the machine before the installation of the data collecting agent. By deploying one or more containers on the machine, the method of some embodiments maximizes the usages of the machine, which was previously deployed to execute legacy non-containerized workloads.

A node management method, a node management apparatus, a cluster node manager, a non-transitory computer-readable storage medium and a network function virtualization system are disclosed. The node management method may include: receiving node life cycle management information (S11); performing life cycle management on a node according to the node life cycle management information, where the node life cycle management includes at least one of node creation, node scaling and node release (S12).