International Business Machines Corporation

Ryan Kirk Cradick

John Matthew Santosuosso

Michael J Branson

Brandon William Schulz

Zachary Adam Garbow

Jason Allan Nikolai

Michael D Pfeifer

Eric L Barsness

Adam Thomas Stallman

Cory J Kleinheksel

Daniel Beuch

James E Carey

Alexander Cook

Jim C Chen

Kevin Glynn Paterson

Peter Andrew Nicholls

Andrew Lawrence Frenkiel

Victor Dogaru

Ryan Pendergast

Daniel Leonard Hiebert

John A Riendeau

Gabriela Jacques Da Silva

Paul Gerver

David Borrillo

John Sebastian Warren

Derek Lee Bromenshenkel

Suresh Guduru

Emuejevoke Jane-Frances Sanomi-Fleming

Michael K Branson

Connie M Cradick

R Eric Morter

Timothy D Zosel

Gabriela Jacques De Silva

Encryption key management for containerized applications is provided. An application container receives a request, directed to a wrapped data encryption key (WDEK), and it is determined whether a local cache associated with the application container stores a mapping of the WDEK to an unwrapped data encryption key (DEK). In response to a cache miss, a shared list, that stores entries corresponding to WDEKs to be synchronized among a plurality of local encryption key caches of a set of application containers, is accessed to determine a set of WDEKs that are missing from the local cache. A key management service provides the WDEKs and corresponding DEKs for the set of WDEKs. The shared list data structure and the local encryption key cache are updated based on the WDEKs and DEKs obtained from the key management service, to thereby synchronize the local encryption key cache with the shared list data structure.

Key management cache synchronization

An example computer-implemented method for mirroring memory in a disaggregated memory clustered environment is provided. The method includes assigning, by a hypervisor, a disaggregated memory to a virtual machine comprising a remote disaggregated memory, the virtual machine being one node of a cluster of the disaggregated memory clustered environment. The method further includes allocating, by a disaggregated memory manager, a mirrored memory for the remote disaggregated memory to mirror the remote disaggregated memory on an alternate node of the cluster of the disaggregated memory clustered environment. The method further includes responsive to a memory access occurring, maintaining, by the disaggregated memory manager, the mirrored memory. The method further includes, responsive to detecting a memory allocation adjustment, modifying, by the disaggregated memory manager, memory usage across the cluster. The method further includes, responsive to detecting a failure resulting in loss of access to the remote disaggregated memory, implementing a corrective action.

Mirrored disaggregated memory in a clustered environment

A stream of tuples is processed by a stream application. The stream application includes a plurality of processing elements that operate on one or more compute nodes, each processing element includes one or more stream operators. One or more databases that are capable of communicating with the stream application are monitored during the processing of the stream of tuples. A potential performance condition of a first database of the one or more databases is detected based on the monitoring. An output adjustment is performed, in response to the potential performance condition.

Datastore aware streams computing

Information indicating a source of electric current can be transmitted alongside or within the electric current itself, enabling downstream recipients to identify a source of their electricity. The information may be embedded directly into the electric current, such as by adding a modulated carrier signal to an alternating current before transmitting the current to a downstream recipient.

Identification and selection of the source of electric power

Information indicating a source of electric current can be received alongside or detected within the electric current itself, enabling recipients to identify a source of their electricity. The information may be determined based on analysis of the received electric current, such as by detecting a modulated carrier signal embedded within a received alternating current.

An embodiment includes analyzing data associated with an original flow graph comprising a plurality of operators of a stream computing application, including identifying a secure network connection between a first operator and a second operator that uses encryption. The embodiment fuses the first operator with the second operator such that a first logical function of the first operator is combined with a second logical function of the second operator. The embodiment then generates a modified flow graph as a modification of the original flow graph that combines the first operator and the second operator and lacks encryption between the first operator and the second operator.

Using fusion to reduce encryption in streaming applications

An embodiment includes determining, in response to receiving data at a source node for transmission as streaming data on a network, whether a characteristic of the data indicates that an attribute of the data includes sensitive information. The embodiment also includes calculating, responsive to determining that the attribute includes sensitive information, an entropy value for the attribute. The embodiment also includes determining, responsive to the calculating of the entropy value, a likelihood that the attribute is encrypted by comparing the entropy value to a threshold value. The embodiment also includes generating a parameter value for a cryptographic parameter for the attribute.

Selective encryption of streaming data

Provided is a method for disabling encryption of data in motion in response to an event. The method includes a service processing data. The service may process the data while in a public mode, in which the service is configured to encrypt data in motion. The method further comprises detecting an event that triggers the service to go into a protected mode. The method further comprises isolating the service from one or more public systems in response to detecting the event. The method further comprises deactivating encryption of data in motion, and processing the data without encrypting the data while in motion.

Selective encryption of data in motion

An embodiment includes monitoring a distributed computing application at runtime for occurrence of a condition, where the condition includes occurrence of a degradation condition on a processing element (PE). The embodiment also includes starting a provisional PE on a second node at runtime while maintaining runtime operation of the PE. The embodiment compares operation of the PE to operation of the provisional PE based on a performance metric associated with the computing resource. The embodiment connects the provisional PE to replace the stream of tuples from the PE to a downstream PE with a stream of tuples from the provisional PE to the downstream PE.

Dynamic replacement of degrading processing elements in streaming applications

A computer-implemented method includes exchanging device data, associated with a first participating user device, with the one or more second participating user devices; receiving audio data associated with a voice command; exchanging the audio data with the one or more second participating user devices; identifying, by the first participating user device, a voice command based on exchanging the audio data; determining which one of the first participating user device or the one or more second participating user devices should respond to the voice command based on details of the voice command and the exchanging the device data; responding to the voice command based on determining that the first participating user device should respond to the voice command; and signaling a particular second participating user device to respond to the voice command based on determining that the particular second participating user device should respond to the voice command.

Coordinating the execution of a voice command across multiple connected devices

Managing a streaming environment of an operator graph by performing corrective actions based on a threshold of changes in state being reached. An operator graph includes states of information stored within a memory of a first processing element configured to process a set of tuples. The memory of the first processing element is monitored. A change in the information from a first state to a second state is identified, based on the monitoring. The change from the first state to the second state is recorded. A determination is made if the change from the first state to the second state has caused a threshold of changes between the states of the information to be reached. A corrective action is performed that modifies a configuration of the operator graph in response to the threshold of changes between the states of the information being reached.

Monitoring states of processing elements

A stream of tuples to be processed by a plurality processing elements executing on two or more compute nodes is received. Each compute node stores one or more of the processing elements having one or more stream operators. It is determined whether an overhead parameter associated with a first streams service located at a first stream operator is outside of a first overhead criterion. The first streams service is ended at the first stream operator and a second streams service is instantiated at a second stream operator when the overhead parameter associated with the first streams service is outside of the first overhead criterion. The second stream operator is different from the first stream operator. The method may include determining whether the first streams service samples a first data attribute of tuples or measures performance.

Placement of services in stream computing applications

Techniques are described for eliminating backpressure in a distributed system by changing the rate data flows through a processing element. Backpressure occurs when data throughput in a processing element begins to decrease, for example, if new processing elements are added to the operating chart or if the distributed system is required to process more data. Indicators of backpressure (current or future) may be monitored. Once current backpressure or potential backpressure is identified, the operator graph or data rates may be altered to alleviate the backpressure. For example, a processing element may reduce the data rates it sends to processing elements that are downstream in the operator graph, or processing elements and/or data paths may be eliminated. In one embodiment, processing elements and associate data paths may be prioritized so that more important execution paths are maintained.

Dynamic reduction of stream backpressure

Streamlining a stream computing environment by distributing tuple attributes to associated operators in the environment involves receiving a stream of tuples for processing by one or more stream operators. A tuple in the stream of tuples is analyzed to identify one or more data attributes required by the one or more stream operators during processing. Each of the identified attributes is distributed to particular operators that require the identified attribute.

Streamlining tuple processing by delivering tuple attributes to associated operators

Adjusting a computing environment for processing a data stream involves identifying one or more dummy tuples in the data stream processed by the computing environment. Propagation of the identified dummy tuples to be processed through a plurality of operators in the computing environment is controlled in order to control adjustment of the computing environment. The computing environment is adjusted based on the processing of the propagated dummy tuples.

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Oronoco, MN, United States of America

Ryan Kirk Cradick