Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: The present invention provides for multidimensional automated database administration, such that, multiple database scripts can be deployed and executed across multiple database servers and the multiple databases stored therein. In addition, the present invention manages the sequence/order in which the scripts are automatically deployed/executed and provides for automated tracking of execution results including error tracking on a per script basis. Additionally, the invention can be deployed in a distributed network allowing for cross domain connectivity to the database servers for the purpose of executing the database scripts without requiring deployment of server-side script deployment agents.

Abstract: An apparatus stores a schedule indicating when a job is scheduled to execute. The apparatus receives a request to execute a first job and determines from the schedule that a second job is scheduled to execute during the execution of the first job. The apparatus estimates a first amount of memory to be consumed by the first job and a second amount of memory to be consumed by the second job, and determines whether a sum of the first amount and the second amount exceeds an amount of free memory. The apparatus determines a table that the first job accesses, and determines whether the table is accessed by the second job. The apparatus communicates a message indicating a period of time to wait before executing the first job if the sum exceeds the amount of free memory or if the table is accessed during by the second job.

Abstract: 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.

Abstract: 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.