An example developer tools system provided by a messaging system includes a software development kit (SKD) engagement monitor that permits capturing app open events in third party resources (e.g., third party apps) that use the developer tools system. The SKD engagement monitor is configured to operate in a manner that preserves privacy of the third party developers and avoids conveying to the messaging system backend environment personally identifiable information (PII) about the third party resource usage.

An example developer tools system provided by a messaging system includes a software development kit (SKD) engagement monitor that permits capturing app open events in third party resources (e.g., third party apps) that use the developer tools system. The SKD engagement monitor is configured to operate in a manner that preserves privacy of the third party developers and avoids conveying to the messaging system backend environment personally identifiable information (PII) about the third party resource usage.

In some embodiments, a real-time event is detected and context is determined based on the real-time event. An application model is fetched based on the context and meta-data associated with the real-time event, the application model referencing a micro-function and including pre-condition and post-condition descriptors. A graph is constructed based on the micro-function. The micro-function is transformed into micro-capabilities by determining a computing resource for execution of a micro-capability by matching pre-conditions and post-conditions of the micro-capability, and enabling execution and configuration of the micro-capability on the computing resource by providing access in a target environment to an API capable of calling the micro-capability to configure and execute the micro-capability. A request is received from the target environment to execute and configure the micro-capability on the computing resource. The micro-capability is executed and configured on the computing resource, and an output of the micro-capability is provided to the target environment.

In some embodiments, a real-time event is detected and context is determined based on the real-time event. An application model is fetched based on the context and meta-data associated with the real-time event, the application model referencing a micro-function and including pre-condition and post-condition descriptors. A graph is constructed based on the micro-function. The micro-function is transformed into micro-capabilities by determining a computing resource for execution of a micro-capability by matching pre-conditions and post-conditions of the micro-capability, and enabling execution and configuration of the micro-capability on the computing resource by providing access in a target environment to an API capable of calling the micro-capability to configure and execute the micro-capability. A request is received from the target environment to execute and configure the micro-capability on the computing resource. The micro-capability is executed and configured on the computing resource, and an output of the micro-capability is provided to the target environment.

Techniques for monitoring enterprise networks with endpoint agents are disclosed. In some embodiments, a system, process, and/or computer program product for monitoring enterprise networks with endpoint agents includes deploying a plurality of endpoint agents to a plurality of endpoint devices; collecting test results from each of the plurality of endpoint agents, wherein the test results are based on tests executed on each of the plurality of endpoint devices for monitoring network activity; and generating a graphical visualization of an application delivery state for one or more application delivery layers based on the test results, generating an alert based on the test results, or generating a report based on the test results.

A method of traffic reduction in a mesh computing system (400), the mesh computing system (400) comprising hosts located on edge nodes of the mesh computing system (400) and a central registry located outside the mesh computing system (400), the central registry holding the images. The method comprises, at a first host located at a first edge node, receiving (920) a request from a client for an image, sending (930) a request for the image to at least one other host of the mesh computing system (400). When the first host receives (940) notification that at least a second host holds the image, the first host downloads (960) the image from the second host to the first host. The first host creates (970) a container from the image. A host at a node (636; 700) and a mesh computing system (400) are also provided.

A method of traffic reduction in a mesh computing system (400), the mesh computing system (400) comprising hosts located on edge nodes of the mesh computing system (400) and a central registry located outside the mesh computing system (400), the central registry holding the images. The method comprises, at a first host located at a first edge node, receiving (920) a request from a client for an image, sending (930) a request for the image to at least one other host of the mesh computing system (400). When the first host receives (940) notification that at least a second host holds the image, the first host downloads (960) the image from the second host to the first host. The first host creates (970) a container from the image. A host at a node (636; 700) and a mesh computing system (400) are also provided.

The disclosure herein describes managing multiple clusters within a container environment using a control cluster. The control cluster includes a single deployment model that manages deployment of cluster components to a plurality of clusters at the cluster level. Changes or updates made to one cluster are automatically propagated to other clusters in the same environment, reducing system update time across clusters. The control cluster aggregates and/or stores monitoring data for the plurality of clusters creating a centralized data store for metrics data, log data and other systems data. The monitoring data and/or alerts are displayed on a unified dashboard via a user interface. The unified dashboard creates a single representation of clusters and monitor data in a single location providing system health data and unified alerts notifying a user as to issues detected across multiple clusters.

The disclosure herein describes managing multiple clusters within a container environment using a control cluster. The control cluster includes a single deployment model that manages deployment of cluster components to a plurality of clusters at the cluster level. Changes or updates made to one cluster are automatically propagated to other clusters in the same environment, reducing system update time across clusters. The control cluster aggregates and/or stores monitoring data for the plurality of clusters creating a centralized data store for metrics data, log data and other systems data. The monitoring data and/or alerts are displayed on a unified dashboard via a user interface. The unified dashboard creates a single representation of clusters and monitor data in a single location providing system health data and unified alerts notifying a user as to issues detected across multiple clusters.

Disclosed herein are embodiments of methods, devices and systems for device fingerprinting and automatic and dynamic software deployment to one or more endpoints on a computer network. The device fingerprinting systems and devices herein are configured to operate with limited data without sitting between network devices and the internet, without monitoring all network traffic, and without limited or no active scanning. The embodiments herein may passively collect information as distributed peers and may perform very limited active scans. In some embodiments, the information is used as an input to a custom hierarchical learning model to fingerprint devices on a network by identifying attributes of the devices such as the operating system family, operating system version, and device role. In some embodiments, a dynamic deployer selection process may be utilized to simply and efficiently deploy software. Some embodiments herein involve end-to-end encryption of credentials in a deployment process.