Ca, Inc.

Martin Tali

Ramesh Mani

Marco Gagliardi

Karmjit Singh

A customer-facing overhead management tool reduces the task of feature configuration to adjusting a scale representing relative feature availability. Features are configured by adjusting a graphical control element presented on a graphical user interface to activate or deactivate features based on relative weights and priorities associated with the features. Weights and priorities are stored within a configuration file underlying the control element and indicate an approximate order in which features will be deactivated upon 'dialing down' the available features. The control element facilitates application resource management for the customer, as the customer may configure features to reduce overhead without knowledge of the underlying feature priorities and weights or relative overhead each feature incurs when activated. Customers may override the automatic feature adjustment by manually activating features which have been deactivated following a lowering of the value on the control element.

Managing monitoring feature overhead

In various embodiments, a method of automatically identifying back-end components of a processing system may be performed. The method may include logging socket communications as a plurality of stack traces. The method may further include filtering the plurality of stack traces to identify a transaction from a particular thread, where the transaction includes a write stack trace and a read stack trace. The method may further include identifying, based on an examination of common stack elements between the write stack trace and the read stack trace, a candidate software component as a back-end component that is communicating with an external software component.

Identifying back-end components based on stack traces

Techniques are disclosed herein for monitoring a software application. The software application may run on servers in a cloud environment. Remote packet capture may be used to capture packets at the servers and forward them over a network to a manager node. However, the forwarding of the packets could potentially impact the software application itself by, for example, overloading the network. This may especially be the case during times of spikes in network traffic. Resource conditions, such as network conditions, may be monitored to minimize the impact by reducing the amount of data packets forwarded, which allows the monitored application to operate normally under traffic spikes. Also, a tunnel protocol having low overhead may be used to reduce the impact of monitoring.

Low impact passive monitoring of application performance

A technique for monitoring software which efficiently communicates transaction trace data, including static and dynamic data, from an agent to a manager is disclosed. A tree data structure describes transactions as a sequence of transaction elements. Each branch may correspond to one type of transaction. The nodes along a branch may be associated with components of monitored software that are invoked to perform the transaction. A provisional branch may be constructed when an agent is unable to initially identify the transaction. Transaction data may be stored in association with the nodes in the provisional branch during the monitoring. After information needed to identify the transaction becomes available to the agent, the provisional branch is updated. The transaction data is reported in response to determining the branch in the tree data structure that matches the provisional branch.

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Foster City, CA, United States of America

Martin Tali