Bank of America Corporation

Anant Bondalapati Sharma

Rakesh Shah

Badelal Rameshwar Prasad Yadav

Sasidhar Purushothaman

Sandeep Kumar Chauhan

Rohit Kumar Jain

Thangaraju Nachimuthu

Sivasankar Sivasalam

Deepak Ranjan Mishra

Surinder Kumar

Rama Krishna Venkata Gandi

A separate, central server operating in a system including one or more database server machines and a graphical user interface displayed on a user's computer is disclosed and provides a technological improvement. In one example, computer-readable instructions are stored in computer memory on this shutdown control server. A user, such as a database administrator, may access the shutdown control server to initiate the shutdown, reboot, and/or restart of database services on one or more separate database servers. At least one advantage of such an arrangement is that the shutdown control server provides plug-and-play capabilities that may allow one or more database servers of one or more different database types to concurrently connect to the shutdown control server.

Database shutdown and restart stability optimizer

An apparatus includes a memory and a processor. The processor collects from a database server, statistics indicating a performance of the server. The processor applies to the statistics, a machine learning algorithm configured to identify, based in part on the statistics, one or more issues affecting the performance of the database server. Applying the machine learning algorithm includes applying to the statistics, a regression algorithm trained to identify one or more candidate issues. Applying the machine learning algorithm also includes applying to the one or more candidate issues, a classification algorithm trained to classify each candidate issue as an issue of the one or more issues or a false positive. The processor additionally generates a script that, when executed, remediates the candidate issues of the one or more candidate issues classified by the classification algorithm as the issues of the one or more issues. The processor further executes the script.

Self-learning database issue remediation tool

In one embodiment, a system for cloud network stability includes a cloud network, a cloud instrument monitor, and a cloud network stability server. The cloud network includes a plurality of components. The cloud instrument monitor includes one or more instruments. Each of the one or more instruments may monitor the plurality of components. The cloud network stability server may include an interface and a processor operably coupled to the interface. The interface may receive an identification of a performance anomaly in the cloud network. A predictive analyzer implemented by a processor may identify a plurality of operational parameters associated with the performance anomaly; detect one or more operational issues associated with the plurality of operational parameters; calculate a network component failure using the detected one or more operational issues; and determine a remediation solution to resolve the network component failure.

Cloud network stability

An apparatus includes a scanner and a cloud engine. The scanner determines that a first cloud environment is of a first type and that a second cloud environment is of a second type that is different from the first type. The cloud engine selects a first tool and a second tool. The cloud engine also sets a first parameter and a first configuration for the first tool and a second parameter and a second configuration for the second tool. The cloud engine further receives a first alert that a security vulnerability in the first cloud environment has been detected and a second alert that resource consumption in the second cloud environment has exceeded a threshold. The cloud engine communicates a first solution to resolve the security vulnerability in the first cloud environment and a second solution to lower resource consumption in the second cloud environment.

Cloud security tool

A disaster recovery tool includes a server monitoring engine, a configuration engine, a security engine, and a runtime engine. The server monitoring engine detects a production server and determines that a disaster recovery server should be created for the production server. The configuration engine compares database configuration files for the production server and the disaster recovery server and copies the database configuration file for the production server to the disaster recovery server. The security engine compares user logins and file sharing credentials of the production server and the disaster recovery server and copies the user login and file sharing credential of the production server to the disaster recovery server. The runtime engine compares database jobs and schedules of the production server and the disaster recovery server and copies the database job and schedule of the production server to the disaster recovery server.

Disaster recovery tool

A computer system monitors database servers to mitigate server availability risks. The plurality of servers may be proactively monitored to determine database status at each server before an alert is generated. An automated proactive process executes at a user's desktop to monitor database features over a plurality of database servers. Information about the server status is presented in a graphical user interface (GUI) format where status information for all of the database servers is presented in one integrated view in an automated manner. For example, the monitoring process reads a list of SQL instances and then connects to each listed SQL server to query the system catalogs of an SQL server engine. The monitoring process interprets the received information from the SQL servers and updates the GUI. The GUI may be color-coded to indicate the status state of individual SQL features for each monitored SQL server.

Growing community of inventors

Hyderabad Telangana, India

Anant Bondalapati Sharma