Example techniques for adaptive time window-based log message deduplication are described. In an example, message values are obtained from received log messages. Further, the number of log messages received in a time window having a message value is counted. A log message from which the message value is obtained and the counted number are transmitted upon expiry of the time window. A length of a time window in which a subsequent counting of log messages is to be performed is determined based on various parameters.

A cloud network is a complex environment in which hundreds and thousands of users or entities can each host, create, modify, and develop multiple virtual machines. Each virtual machine can have complex behavior unknown to the provider or maintainer of the cloud. Technologies disclosed include methods, systems, and apparatuses to monitor the complex environment to detect network anomalies using machine learning techniques. In addition, techniques to modify and adapt to user feedback are provided allowing the developed models to be tuned for specific use cases, virtual machine types, and users.

Methods for managing a communication session in a communication network are disclosed. For example, a method includes detecting, by a first endpoint comprising at least one processor, an error condition associated with the communication session, sending, by the first endpoint, a notification of the error condition to a second endpoint that is using a transport layer session and receiving, by the first endpoint, a communication from the second endpoint, proposing a response to the error condition. Another method includes receiving, by a first endpoint comprising at least one processor, a notification of an error condition associated with the communication session, selecting, by the first endpoint, a response to the error condition, and sending, by the first endpoint, a communication to a second endpoint that is using a transport layer session, proposing a response to the error condition.

A method and corresponding system for implementing Virtual Network Function (VNF) performance monitoring is provided. The method includes that: an Element Management (EM) receives a threshold policy of a VNF performance monitoring threshold sent by a Network Management (NM) or an Operation Support System (OSS); the EM acquires related information about virtual resources after the VNF is scaled up/down; and the EM sets a new performance monitoring threshold for the VNF according to the threshold policy and the related information about virtual resources after the VNF is scaled up/down, and the performance monitoring threshold includes at least one of a scale up/down threshold and a performance warning threshold.

In various examples, a system identifies a first issue object associated with the alert by making a first set of determinations, based on an alert of an active issue of a system resource. Additionally, the system can determine whether the active issue associated with the first issue object can be automatically corrected by one or more self-healing processes, based on the first issue object. Moreover, the system can implement the one or more self-healing processes, based on determining that the active issue associated with the first issue object can be automatically corrected by one or more self-healing processes.

In various examples, a system identifies a first issue object associated with the alert by making a first set of determinations, based on an alert of an active issue of a system resource. Additionally, the system can determine whether the active issue associated with the first issue object can be automatically corrected by one or more self-healing processes, based on the first issue object. Moreover, the system can implement the one or more self-healing processes, based on determining that the active issue associated with the first issue object can be automatically corrected by one or more self-healing processes.

To improve the reliability of nodes that are utilized by a cloud computing provider, information about the entire lifecycle of nodes can be collected and used to predict when nodes are likely to experience failures based at least in part on early lifecycle errors. In one aspect, a plurality of failure issues experienced by a plurality of production nodes in a cloud computing system during a pre-production phase can be identified. A subset of the plurality of failure issues can be selected based at least in part on correlation with service outages for the plurality of production nodes during a production phase. A comparison can be performed between the subset of the plurality of failure issues and a set of failure issues experienced by a pre-production node during the pre-production phase. A risk score for the pre-production node can be calculated based at least in part on the comparison.

To improve the reliability of nodes that are utilized by a cloud computing provider, information about the entire lifecycle of nodes can be collected and used to predict when nodes are likely to experience failures based at least in part on early lifecycle errors. In one aspect, a plurality of failure issues experienced by a plurality of production nodes in a cloud computing system during a pre-production phase can be identified. A subset of the plurality of failure issues can be selected based at least in part on correlation with service outages for the plurality of production nodes during a production phase. A comparison can be performed between the subset of the plurality of failure issues and a set of failure issues experienced by a pre-production node during the pre-production phase. A risk score for the pre-production node can be calculated based at least in part on the comparison.

A classification based notification system is disclosed which performs operations that include: accessing user profile data associated with a user account associated with a client device, the user profile data including a list of user connections; designating a notification type to a portion of the list of user connections, the notification type corresponding to an alert attribute; receiving a notification from a user connection from among the portion of the list of user connections at the client device; and presenting an alert based on the alert attribute that corresponds with the notification type associated with the portion of the list of user connections at the client device.

A classification based notification system is disclosed which performs operations that include: accessing user profile data associated with a user account associated with a client device, the user profile data including a list of user connections; designating a notification type to a portion of the list of user connections, the notification type corresponding to an alert attribute; receiving a notification from a user connection from among the portion of the list of user connections at the client device; and presenting an alert based on the alert attribute that corresponds with the notification type associated with the portion of the list of user connections at the client device.