Abstract: Examples disclosed herein relate to triggering a high availability feature in response to detecting impairment of client experience. Examples include detecting, based on content of interactions between at least one application component and a client, a threshold impairment of an experience of the client in relation to the at least one application component. Examples also include triggering a high availability feature for the at least one application component in response to detecting the threshold impairment.

Abstract: A common action flow for an application is identified by processing session data maintained for a plurality of users to identify a plurality of action flows. Each action flow represents a series of actions taken by one of the users navigating the application's user interface during a session. A data structure is generated from the plurality of action flows. That data structure is indicative of a plurality of candidate sub-flows. The data structure is analyzed to identify a selected one of the candidate sub-flows repeated in multiple ones of the plurality of action flows. That identified sub-flow is the common action flow. Data representative of the identified common action flow can then be communicated.

Abstract: In one implementation, a system can include a tenant engine to maintain a plurality of tenant profiles with access to a first set of metrics of a plurality of metrics based on authorization via a certificate, a metrics engine to maintain a plurality of metrics derived from instrumentation of a plurality of applications, and a report engine to provide the first set of metrics in response to a report request when the report request is from a user associated with a first tenant profile of the plurality of tenant profiles and the first tenant profile is authorized to access the first set of metrics based on the certificate associated with a private key used to sign a first application of the plurality of applications.

Abstract: Example embodiments relate to monitoring application flow of an application responsive to receiving a monitoring mode upon launch of a session of the application. In this manner, the embodiments disclosed herein enable monitoring an application on a first computing device based on a first received monitoring mode and monitoring the same application on a second computing device based on a second received monitoring mode.

Abstract: A non-transitory machine-readable storage medium encoded with instructions executable by a processing resource of a computing device to access network traffic exchanged with a web server application. The storage medium also identifies, in the accessed network traffic, an analysis reporting message of a client system and extracts, from the analysis reporting message, information representing a client system analysis of at least one prior transaction between the client system and a proxy server associated with the web server application. The information representing the client system analysis can comprise information describing an experience of the client system, including an indication of an amount of time to perform at least one prior transaction between the client system and the proxy server.

Abstract: Packets from a first network entity to a second network entity are received. A maximal size of packets from the second network entity to the first network entity is determined based on information in the received packets.

Abstract: According to an example, a Trie is formed from URLs and nodes of the Trie are assigned a weight. A node is selected based on its weight and child nodes of the selected node merged together. A URL classification is output based on a path in the Trie.

Abstract: Methods, systems, and computer-readable and executable instructions are provided for simulating real user issues in support environments. Simulating real user issues in support environments can include providing stored data related to a real user issue associated with an application to a support device having the ability to modify the application, the stored data can include network traffic associated with a user device in a live environment and inputs provided via the user device. Simulating real user issues in support environments can include causing the support device to simulate the real user issue using the stored data.

Abstract: A common action flow for an application is identified by processing session data maintained for a plurality of users to identify a plurality of action flows. Each action flow represents a series of actions taken by one of the users navigating the application's user interface during a session. A data structure is generated from the plurality of action flows. That data structure is indicative of a plurality of candidate sub-flows. The data structure is analyzed to identify a selected one of the candidate sub-flows repeated in multiple ones of the plurality of action flows. That identified sub-flow is the common action flow. Data representative of the identified common action flow can then be communicated.

Abstract: In one implementation, a system can include a tenant engine to maintain a plurality of tenant profiles with access to a first set of metrics of a plurality of metrics based on authorization via a certificate, a metrics engine to maintain a plurality of metrics derived from instrumentation of a plurality of applications, and a report engine to provide the first set of metrics in response to a report request when the report request is from a user associated with a first tenant profile of the plurality of tenant profiles and the first tenant profile is authorized to access the first set of metrics based on the certificate associated with a private key used to sign a first application of the plurality of applications.

Abstract: A common action flow for an application is identified by processing session data maintained for a plurality of users to identify a plurality of action flows. Each action flow represents a series of actions taken by one of the users navigating the application's user interface during a session. A data structure is generated from the plurality of action flows. That data structure is indicative of a plurality of candidate sub-flows. The data structure is analyzed to identify a selected one of the candidate sub-flows repeated in multiple ones of the plurality of action flows. That identified sub-flow is the common action flow. Data representative of the identified common action flow can then be communicated.

Abstract: Packets from a first network entity to a second network entity are received. A maximal size of packets from the second network entity to the first network entity is determined based on information in the received packets.

Abstract: Packets from a first network entity to a second network entity are received. A maximal size of packets from the second network entity to the first network entity is determined based on information in the received packets.

Abstract: Example embodiments relate to monitoring application flow of an application responsive to receiving a monitoring mode upon launch of a session of the application. In this manner, the embodiments disclosed herein enable monitoring an application on a first computing device based on a first received monitoring mode and monitoring the same application on a second computing device based on a second received monitoring mode.

Abstract: A method for discovering an operating system of a remote machine includes monitoring network communications to detect a plurality of data packets that were generated by the remote machine. The contents of each detected data packet are read so as to extract a packet signature of each detected data packet. Each packet signature is compared with at least one signature of a database of signatures in order to determine a similarity between each packet signature and the signature from the database. A confidence level for at least one candidate operating system is calculated based on the determined similarities. A candidate operating system is selected based on the confidence level for that operating system. Relating computer program product and data processing system are also disclosed.

Abstract: According to an example, a Trie is formed from URLs and nodes of the Trie are assigned a weight. A node is selected based on its weight and child nodes of the selected node merged together. A URL classification is output based on a path in the Trie.

Abstract: Examples disclosed herein relate to identifying an analysis reporting message in network traffic. Examples include accessing network traffic exchanged with a web server application and identifying, in the network traffic, an analysis reporting message. In examples described herein, the analysis reporting message may include information representing a client system analysis of at least one prior transaction of the client system.

Abstract: Examples disclosed herein relate to determining the type of a network tier. Examples include determining that a target network tier is a forwarding type network tier if a protocol of communications between the target network tier and a source network resource is the same as a protocol of communications between the target network tier and a backend network tier. Examples further include comparing select content of communications between the target and backend network tiers to select content of communications between the target network tier and the source networking resource, if the protocols are the same.

Abstract: A technique includes using a network sniffer to acquire at least one measurement of network activity associated with an application component, where the application component is a candidate to be migrated to a cloud. The technique further includes, based at least in part on the measurement(s), determining at least one cost factor associated with the application component being provided by the cloud.

Abstract: A common action flow for an application is identified by processing session data maintained for a plurality of users to identify a plurality of action flows. Each action flow represents a series of actions taken by one of the users navigating the application's user interface during a session. A data structure is generated from the plurality of action flows. That data structure is indicative of a plurality of candidate sub-flows. The data structure is analyzed to identify a selected one of the candidate sub-flows repeated in multiple ones of the plurality of action flows. That identified sub-flow is the common action flow. Data representative of the identified common action flow can then be communicated.