Microsoft Technology Licensing, LLC

Linkedin Corporation

Haricharan K Ramachandra

Badrinath K Sridharan

John W Nicol

Zhenyun Zhuang

Cuong Huu Tran

Ritesh Maheshwari

Nicholas P Baggott

Sergiy Zhuk

Arman H Boehm

Anant Rao

Tao Feng

Jui Ting Weng

Man Wai Ip

The disclosed embodiments provide a system for detecting and managing memory inefficiency in a software program. During operation, the system obtains a first snapshot of a heap for a software program, wherein the first snapshot includes a first set of objects stored in the heap at a first time. Next, the system applies a compression technique to the first snapshot to obtain a first set of inefficiency metrics for the first set of objects, wherein each inefficiency metric in the first set of inefficiency metrics represents a memory inefficiency of an object in the heap at the first time. The system then outputs the first set of inefficiency metrics with additional attributes of the first set of objects to improve identification of the memory inefficiency in the software program.

Compression-based detection of memory inefficiency in software programs

A system, apparatus, and methods are provided for managing on-demand profiling of one or more instances of a software application executing on a plurality of machines within one or more data centers. During operation, the system executes the one or more instances of the software application on the plurality of machines. Next, the system publishes, to a command channel, a command message that comprises a profiling request, wherein the profiling request specifies a subset of the machines. The system then receives, via a data channel, one or more data messages from the subset of the machines, wherein the data messages comprise data gathered by the subset of the machines in response to receiving the command message. Next, the system then evaluates the performance of the software application by aggregating and processing the data messages. Responsive to detecting an anomaly in the performance, the system then executes one or more remedies.

On-demand profiling based on event streaming architecture

The disclosed embodiments provide a system for processing data. During operation, the system obtains an attribute of a stack trace of a software program. Next, the system uses the attribute to select an address-translation instance from a set of address-translation instances for processing the stack trace. The system then provides the stack trace to the selected address-translation instance for use in translating a set of memory addresses in the stack trace into a set of symbols of instructions stored at the memory addresses.

Efficient address-to-symbol translation of stack traces in software programs

The disclosed embodiments provide a system for detecting and managing inefficiency in external services. During operation, the system obtains a snapshot of a data stream transmitted over an external service from a computer system at a first time. Next, the system applies a compression technique to the snapshot to obtain a set of inefficiency metrics for a set of data elements in the snapshot. The system then outputs the set of inefficiency metrics with additional attributes of the data stream to improve identification of inefficiency in the data stream.

Compression-based detection of inefficiency in external services

The disclosed embodiments provide a system for detecting and managing inefficiency in local storage. During operation, the system obtains a first snapshot of data in local storage of a computer system, wherein the first snapshot comprises a first set of data elements in the local storage at a first time. Next, the system applies a compression technique to the first snapshot to obtain a first set of inefficiency metrics for the first set of data elements. The system then outputs the first set of inefficiency metrics with additional attributes of the data to improve management of inefficiency in the data.

Compression-based detection of inefficiency in local storage

The disclosed embodiments provide a system for analyzing data from a monitored system. During operation, the system identifies a difference between a performance of an application and a service-level agreement (SLA) of the application. Next, the system determines a correlation between the performance of the application and a disk input/output (I/O) performance of a data storage device used by the application. When the correlation exceeds a threshold, the system outputs a recommendation to migrate the application between the data storage device and a different type of data storage device.

Performance-based migration among data storage devices

A system, method, and apparatus are provided for performing a transparent hybrid data storage scheme in which data are stored as blocks distributed among one or more flash-based storage devices (e.g., solid state drives) and one or more magnetic storage devices (e.g., magnetic disk drives). Files larger than a given size (e.g., 1 MB) are segmented into blocks of that size and stored on one or more devices; blocks of one file may be stored on devices of different types. Periodically, a utility function calculates utility values for each of some or all stored blocks based on frequency of access to the block, frequency of access of a particular type (e.g., random, sequential), a preference regarding where to store the block or the corresponding file, and/or other factors. Blocks having the highest utility values are subject to migration between devices of different types and/or the same type (e.g., for load-balancing).

Transparent hybrid data storage

In order to prevent data thrashing and the resulting performance degradation, a computer system may maintain an application-layer cache space to more effectively use physical memory and, thus, significantly improve an application-memory hit ratio and reduce disk input-output operations. In particular, the computer system may maintain a managed memory cache that is separate from a page cache. The managed memory cache may be managed according to predefined caching rules that are separate from the caching rules in the operating system that are used to manage the page cache, and these caching rules may be application-aware. Subsequently, when data for an application is accessed, the computer system may prefetch the data and associated information from disk and store the information in the managed memory cache based on data correlations associated with the application.

Growing community of inventors

Fremont, CA, United States of America

Haricharan K Ramachandra