International Business Machines Corporation

Jin Shan Li

Rui Liu

Peng Hui Jiang

Yang Yang

Huai Long Zhang

Peng Peng Wang

Yue Wang

Ming Lei Zhang

Gang Tang

Yi Liu

Yun Ma

Xiong Zhao

Jian Wen

Yuan Yuan Jia

Shuang Men

Li Wei Wang

Shao Mei Ji

An indication to remove one or more data in a time series database is received. A metadata index associated with the time series database is updated to indicate a soft removal of each data of the one or more data. A data hole index associated with the time series database is updated to indicate a data hole at a location of each data of the one or more data in the time series database. Responsive to an input/output rate for the time series database being below a threshold, the data hole of each data of the one or more data is optimized.

Data holes in a time series database

A query string for an encrypted database storing a plurality of encrypted data records is received from a requestor. The query string is segmented to obtain at least one word. The at least one word is encrypted with the irreversible encryption algorithm to obtain at least one encrypted word. At least one first encrypted item with a co-occurrence weight higher than a preset threshold based on the at least one encrypted word and a co-occurrence statistics model is acquired. The co-occurrence statistics model is built to provide co-occurrence weights, each indicating a probability that the at least one encrypted word appears in a first encrypted data item of the plurality of encrypted data records. At least one second encrypted data item corresponding to the at least one first encrypted data item is acquired from the plurality of encrypted data records.

Data query against an encrypted database

In an approach, a processor creates a local first Pod API object in a first lower Kubernetes cluster based on a first Pod API object in an upper Kubernetes cluster, where: the local first Pod API object includes internal and external network descriptions for a Pod described in the local first Pod API object, and the upper cluster manages the first and second lower Kubernetes cluster. A processor adds an annotation for the Pod to the local first Pod API object and the first Pod API object. A processor creates a local endpoint API object in the first lower cluster based on an endpoint API object in the upper cluster and annotations of Pods in the upper cluster. A processor redirects the first request to the endpoint of the second Pod described in the local endpoint API object.

Service access across Kubernetes clusters

Managing real-time monitoring alerts is provided. An alert is generated for one or more metrics exceeding corresponding defined metric threshold values. A root cause dependency table showing relationships between alerts is retrieved. It is determined whether current real-time metrics are needed from one or more monitoring agents that correspond to dependent alerts not triggered in an alert chain of the generated alert based on information in the root cause dependency table. In response to determining that the current real-time metrics are needed from the one or more monitoring agents that correspond to the dependent alerts not triggered in the alert chain of the generated alert based on the information in the root cause dependency table, the current real-time metrics are requested from the one or more monitoring agents that correspond to the dependent alerts not triggered in the alert chain.

Real-time monitoring alert chaining, root cause analysis, and optimization

Growing community of inventors

Beijing, China

Jin Shan Li