Datatorrent, Inc.

Cisco Technology, Inc.

Cake Corporation

Yahoo! Inc.

Leapset, Inc.

Chetan Narsude

Amol J Kekre

Thomas Weise

Gaurav Gupta

Shadab Nazar

Pavan Mamillapalli

Phu D Hoang

Sundar Iyer

Azeem Suleman

Paul G Kelaita

Pasan Manisha Kulasooriya

James Boyd O'Connor

Pramod Immaneni

Jorn Wossner

Shanil Fernando

Kevin En-Kai Wu

Sadeesha Gamhewa

Navjyoti Sharma

David Yan

Navneet Yadav

John Thomas Monk

Jagdev Singh Tur

Chandni Singh

Ashwin Chandra Putta

Sravya Boggavarapu

Jose Delgado

Aspects of the technology provide solutions for determining a time period ('epoch') required to monitor or analyze a tenant network. Some implementations of the technology include a process for making automatic epoch determinations, which includes steps for identifying one or more network parameters for a tenant network, analyzing the tenant network using the network parameters to discover one or more configuration settings of the tenant network, and determining a first epoch for the tenant network, the first epoch corresponding with a period of time to complete analysis of the tenant network using the network parameters. In some aspects, the process can further include steps for generating a tenant profile for the tenant network, the tenant profile based on the network parameters, the first epoch, and the one or more configuration settings of the tenant network. Systems and machine-readable media are also provided.

Automatically determining an optimal amount of time for analyzing a distributed network environment

Aspects of the technology provide methods for simulating a failure in a tenant network. In some aspects, a monitoring appliance of the disclosed technology can be configured to carry out operations for receiving packets at a virtual device in the monitoring appliance, from a corresponding network device in the tenant network, and instantiating a firewall at the virtual device, wherein the firewall is configured to selectively block traffic routed from the network device to the virtual device in the monitoring appliance. The monitoring appliance can simulate failure of the network device by blocking traffic from the network device to the virtual device using the firewall, and analyze the tenant network to determine a predicted impact a failure of the network device would have on the tenant network. Systems and machine-readable media are also provided.

Controlled micro fault injection on a distributed appliance

Aspects of the technology provide methods for aggregating error log data between multiple devices in a network monitoring appliance. A method of the technology can include steps for identifying a plurality of operators running in a network monitoring appliance, instantiating a plurality of sensors, wherein each of the plurality of sensors is associated with a respective one of the plurality of operators, and wherein each sensor is configured to capture error log data of its corresponding operator. In some aspects, the method can further include steps for aggregating error log data from two or more of the plurality of sensors. Systems and machine-readable media are also provided.

Self diagnosing distributed appliance

Systems and methods for facilitating online to offline commerce are disclosed. In one embodiment, a system configured to receive a request to check-in a customer at a merchant facility is disclosed. The system receives a request to access real-time pre-sale transaction data associated with a first customer and transmits the real-time pre-sale transaction data associated with the first customer to a mobile client device. The request to check-in and the request to access the real-time pre-sale transaction data are transmitted by the first mobile client device. The system is configured to authenticate the request to check-in at the merchant facility, process the request to access the real-time pre-sale transaction data, and responsively access the real-time pre-sale transaction data associated with the first customer from a point of sale device located at the merchant facility.

Facilitating online to offline commerce

Systems, methods, and computer-readable media for aggregating and presenting network events in a network environment. In some embodiments, a system can maintain event correlation rules for aggregating \network events occurring in a network based on characteristics of previously occurring network events. Network events occurring in the specific network environment can be identified. The network events can be aggregated to form an aggregated network event using the event correlation rules maintained based on the characteristics of previously occurring network events. The aggregated network event can subsequently be presented to a user.

Network assurance event aggregator

Aspects of the technology provide systems and methods for interleaving a processing task in a network monitoring appliance. A process of the technology could include steps for identifying operators in the network monitoring appliance, wherein the operators are sequentially arranged to form a processing pipeline, determining an epoch for the processing pipeline, wherein the epoch corresponds with a time duration required for a processing task to traverse the pipeline, and determining a time window in which a supplemental processing task can be interleaved into the processing pipeline, wherein the time window is based on the epoch. Machine-readable media are also provided.

On-demand processing pipeline interleaved with temporal processing pipeline

Software for a distributed streaming platform receives a specification for a streaming application and converts the specification into a logical plan that includes a directed acyclic graph (DAG) with operators as nodes and streams as edges. The software translates the logical plan into a physical plan using any stream modes as specified and with one or more instances of the operators per any static partitioning. Then the software obtains a plurality of containers running on a networked cluster of servers. One slave executes in each container. The software assigns the instances to the slaves for execution according to an execution plan that depends at least in part on the physical plan and number of containers obtained. Each slave monitors throughput of the streaming windows through the instances in the container and other statistics related to service level and reports the results of the monitoring, which are used for dynamic adjustment.

Distributed streaming platform for real-time applications

Software receives a data stream for an application running on a distributed streaming platform over a networked cluster of servers. The software converts the data into a plurality of data tuples structured according to a schema. The software repeatedly emits a plurality of the data tuples as a streaming window, which is separated from other streaming windows by a leading control tuple associated with an ordinal identifier for the streaming window. The streaming window is a sequential sequence of tuples that is associated with a recovery policy. Then the software emits a checkpointing tuple after a plurality of streaming windows. The checkpointing tuple causes checkpointing of an instance of an operator for the application when the checkpointing tuple is received by the instance. Each of the operations is executed by one or more processors in real time or near real time rather than offline.

Checkpointing in distributed streaming platform for real-time applications

Software for a distributed streaming platform monitors a first operator instance in a container for an application running on a distributed streaming platform over a networked cluster of servers. The first operator instance includes an input port that receives streaming windows from an upstream instance and an output port that emits streaming windows to a downstream instance. And the monitoring includes determining a window identifier for a streaming window which the first operator instance is processing. The software reports results of the monitoring to a master and receives a dynamic adjustment from the master. The dynamic adjustment includes launching a second operator instance of the same operator in the container. The software resumes a flow of streaming windows into the input port and the output port according to first recovery policy for the first operator instance and a second recovery policy for the second operator instance.

Dynamic partitioning of instances in distributed streaming platform for real-time applications

Software for a distributed streaming platform receives an application. The application is structured as a directed acyclic graph (DAG) with instances of operators as nodes and streams as edges between nodes. Multiple instances of an operator access a shared database. The software receives a pre-defined hint associated with the application. The pre-defined hint sets a maximum period of time for local caching of a result from a query of the database by each of the multiple instances. The software launches the application by assigning the instances of operators to one or more containers provided by the streaming platform and initiating the streams. Each container is associated with a local cache. The software then receives a request from the application to make a dynamic adjustment that increases the maximum period of time for local caching of a result from a query of the database by each of the multiple instances.

Scalable local cache in distributed streaming platform for real-time applications

Software for a distributed streaming platform receives an application that runs on a streaming platform. The application is structured as a directed acyclic graph (DAG) with operators as nodes and streams as edges between nodes. The application includes an operator that receives a plurality of values, counts the values that are unique, and emits the unique values in a stream. The software partitions the operator into at least two partitioned instances. Then the software assigns a unique value emitting from a partitioned instance to one of a plurality of unifiers according to a pre-defined scheme. Each unifier creates a count of the unique values received by the unifier. Then the software transmits the counts from each of the unifiers to a downstream instance of an operator that aggregates the counts into a sum. And the software displays the sum in a graphical user interface (GUI).

Partitionable unifiers in distributed streaming platform for real-time applications

Software for a distributed streaming platform launches an application that runs on a streaming platform, in real time or near real time rather than offline. The application is structured as a directed acyclic graph (DAG) with instances of operators as nodes and streams as edges between nodes. The software receives an indication that a first instance of an operator is I/O bound. A stream connects the first instance of an operator to a second instance of another operator in a single container provided by the streaming platform. The software then transmits the indication to the application and receives a request to combine the first instance with the second instance into a single third instance of an operator. The software creates the third instance and re-initiates the stream using a recovery policy.

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Sunnyvale, CA, United States of America

Chetan Narsude