Juniper Networks, Inc.

Cisco Technology, Inc.

Aniruddh S Dikhit

Joseph LaSalle White

Khanh Vinh Nguyen

Naveen Kumar Tyagi

Bojesha Nagaraja

Abhilash Sreedharan Nair Mannathanil

Techniques for orchestrating a workflow for configuring a computer networking environment or other complex workflows are described. A Directed Acyclic Graph (DAG) that defines a plurality of tasks to be executed to complete the workflow and a plurality of orders between the tasks is received. Embodiments generate a State-Machine Neural Network (SNN) based on the received DAG, by generating a plurality of SNN neurons for the SNN, based on the plurality of tasks within the received DAG and generating a plurality of SNN connections for the SNN, connecting pairs of SNN neurons within the plurality of SNN neurons, based on the plurality of connections within the received DAG. The SNN is executed to orchestrate the workflow by sending and receiving signals to and from the SNN neurons.

Network automation and orchestration using state-machine neural networks

Embodiments herein describe a retroactive tracer that retroactively generates traces using data stored in local caches. Rather than continually generating and collecting tracing data in a distributed system (which may requires massive amounts of storage and bandwidth), the embodiments herein store tracing data in local caches corresponding to nodes in the distributed system (e.g., a service, application, virtual machine, server, network device, etc.). When an error is detected when executing a task, the retroactive tracer can broadcast a request that the nodes send any trace data they may have corresponding to that task. The tracer can then retroactively generate the trace from the collected trace data. In contrast, if a task completes without an error, the nodes delete the trace data from their local caches (i.e., the trace data is not collected by the retroactive tracer).

Retroactive tracing in a distributed system

A method includes receiving a signal indicative of a value of a data point associated with a compute device at a first time. The value of the data point includes a data point category that is correlated with a fault category. The compute device is operatively coupled to a record module having a protected mode and an unprotected mode. A signal is received indicative of a value of the data point at a second time, after the first time. When a characteristic of a change in the value of the data point at the first time to value of the data point at the second time crosses a threshold in a first direction, a signal is sent to the record module indicative of an instruction to record data associated with the compute device in the protected mode to define a protected data set.

Methods and apparatus for improved fault analysis

In some embodiments, a method includes storing a set of data point values. Each data point value from the set of data point values is associated with a compute device from a set of compute devices that are included in a data center. The method also includes receiving a selection indicative of a region of the data center. A portion of the set of compute devices is disposed within the region of the data center. The method further includes sending a signal to display a topological map that includes a set of indicators. Each indicator from the set of indicators is associated with a compute device from the portion of the set of compute devices. A characteristic of an indicator from the set of indicators is based on a data point value of a respective compute device.

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San Jose, CA, United States of America

Aniruddh S Dikhit