Abstract: Provided herein are methods of treating cancer by administering to a subject having cancer an antibody, or functional fragment or functional variant thereof, that specifically binds programmed cell death protein 1 (PD1); and a fusion protein that comprises a targeting moiety and an immunomodulatory moiety, wherein: i) said targeting moiety specifically binds epidermal growth factor receptor (EGFR); and (ii) said immunomodulatory moiety comprises an amino acid sequence of the extracellular domain of transforming growth factor-beta receptor II (TGF?RII).

Abstract: A tool may provide a real-time analysis of potential bottlenecks while threads wait on locks held by other threads. For each job currently operating on the server instance, the tool may access a list of threads and retrieve call stacks associated with those threads. The call stacks may then be analyzed to identify threads that are holding a lock, along with any corresponding threads that are waiting on the lock. The locks may be held on memory resources or any other type of computing resource. These bottlenecks may be identified and an adjustment of the configuration of the server instance may be triggered in response that is configured to reduce the likelihood that these types of bottlenecks may occur in the future.

Abstract: Threads and kernels across multiple server instances may maintain static connections to a database during operation. To apply a patch or other upgrade to the database, a notification may be sent to the database system that causes the database system to redirect new incoming connection requests for the database to a backup database. A second notification may also be sent to each of the server instances where threads maintain active connections to the database. These threads may be allowed to finish executing a current job, then when entering the idle state these threads may be directed to refresh their connections. This refresh operation may be redirected to the backup database. The patch may be applied after all connections have been switched to the backup database. This process switches static connections to the backup database as quickly as possible without interrupting existing thread operations.

Abstract: Techniques for deploying a server stack having a cross-server dependency are disclosed. A deployment engine initiates a deployment process for a server stack. The deployment engine provisions servers of one server type (“requisite servers”). The deployment engine attempts to provision servers of another server type (“dependent servers”). The deployment engine executes a test that requires the dependent servers to invoke a service executed by the requisite servers. Based on the test results, the deployment engine determines that an operational requirement of the dependent servers is not satisfied. The deployment engine modifies a configuration for the requisite servers to satisfy the operational requirement of the dependent servers. The deployment engine re-provisions the requisite servers using the modified configuration. The deployment engine completes the deployment process for the server stack.

Abstract: Threads and kernels across multiple server instances may maintain static connections to a database during operation. To apply a patch or other upgrade to the database, a notification may be sent to the database system that causes the database system to redirect new incoming connection requests for the database to a backup database. A second notification may also be sent to each of the server instances where threads maintain active connections to the database. These threads may be allowed to finish executing a current job, then when entering the idle state these threads may be directed to refresh their connections. This refresh operation may be redirected to the backup database. The patch may be applied after all connections have been switched to the backup database. This process switches static connections to the backup database as quickly as possible without interrupting existing thread operations.

Abstract: Threads and kernels across multiple server instances may maintain static connections to a database during operation. To apply a patch or other upgrade to the database, a notification may be sent to the database system that causes the database system to redirect new incoming connection requests for the database to a backup database. A second notification may also be sent to each of the server instances where threads maintain active connections to the database. These threads may be allowed to finish executing a current job, then when entering the idle state these threads may be directed to refresh their connections. This refresh operation may be redirected to the backup database. The patch may be applied after all connections have been switched to the backup database. This process switches static connections to the backup database as quickly as possible without interrupting existing thread operations.

Abstract: A tool may provide a real-time analysis of potential bottlenecks while threads wait on locks held by other threads. For each job currently operating on the server instance, the tool may access a list of threads and retrieve call stacks associated with those threads. The call stacks may then be analyzed to identify threads that are holding a lock, along with any corresponding threads that are waiting on the lock. The locks may be held on memory resources or any other type of computing resource. These bottlenecks may be identified and an adjustment of the configuration of the server instance may be triggered in response that is configured to reduce the likelihood that these types of bottlenecks may occur in the future.

Abstract: Operations include diagnosing performance hotspots with minimal performance impact. A system selectively extracts a subset of in-memory application data, for failure analysis, based on application metadata associated with an application. The selective data extraction may be used to generate succinct reports that are customized to explore the specific vulnerabilities of each particular application. Application metadata identifies application data attributes for value extraction. The application metadata may identify, for example, a client attribute which indicates the client which requested the execution of a failed operation (or execution of an operation with a failed sub-function). The application metadata may identify a particular function, associated with an operation, that is to be analyzed in case of operation failure. The application metadata may identify a thread-local variable of a thread, executing an operation, that is to be analyzed in case of operation failure.

Abstract: Operations include diagnosing performance hotspots with minimal performance impact. A system selectively extracts a subset of in-memory application data, for failure analysis, based on application metadata associated with an application. The selective data extraction may be used to generate succinct reports that are customized to explore the specific vulnerabilities of each particular application. Application metadata identifies application data attributes for value extraction. The application metadata may identify, for example, a client attribute which indicates the client which requested the execution of a failed operation (or execution of an operation with a failed sub-function). The application metadata may identify a particular function, associated with an operation, that is to be analyzed in case of operation failure. The application metadata may identify a thread-local variable of a thread, executing an operation, that is to be analyzed in case of operation failure.

Abstract: Techniques for deploying a server stack having a cross-server dependency are disclosed. A deployment engine initiates a deployment process for a server stack. The deployment engine provisions servers of one server type (“requisite servers”). The deployment engine attempts to provision servers of another server type (“dependent servers”). The deployment engine executes a test that requires the dependent servers to invoke a service executed by the requisite servers. Based on the test results, the deployment engine determines that an operational requirement of the dependent servers is not satisfied. The deployment engine modifies a configuration for the requisite servers to satisfy the operational requirement of the dependent servers. The deployment engine re-provisions the requisite servers using the modified configuration. The deployment engine completes the deployment process for the server stack.

Abstract: Disclosed are methods and apparatuses for reducing the number of database calls when transferring data from a database to a server. One embodiment provides an approach for utilizing staging tables to collate and transform core data and related data in the database before transferring the data to the server, so that the number of database calls used may be reduced.

Abstract: Operations include diagnosing performance hotspots with minimal performance impact. A system selectively extracts a subset of in-memory application data, for failure analysis, based on application metadata associated with an application. The selective data extraction may be used to generate succinct reports that are customized to explore the specific vulnerabilities of each particular application. Application metadata identifies application data attributes for value extraction. The application metadata may identify, for example, a client attribute which indicates the client which requested the execution of a failed operation (or execution of an operation with a failed sub-function). The application metadata may identify a particular function, associated with an operation, that is to be analyzed in case of operation failure. The application metadata may identify a thread-local variable of a thread, executing an operation, that is to be analyzed in case of operation failure.

Abstract: Techniques for deploying a server stack having a cross-server dependency are disclosed. A deployment engine initiates a deployment process for a server stack. The deployment engine provisions servers of one server type (“requisite servers”). The deployment engine attempts to provision servers of another server type (“dependent servers”). The deployment engine executes a test that requires the dependent servers to invoke a service executed by the requisite servers. Based on the test results, the deployment engine determines that an operational requirement of the dependent servers is not satisfied. The deployment engine modifies a configuration for the requisite servers to satisfy the operational requirement of the dependent servers. The deployment engine re-provisions the requisite servers using the modified configuration. The deployment engine completes the deployment process for the server stack.

Abstract: A method, system, and computer program product for dynamically building a database query by combining a static query clause with a user-specified filter. A method commences upon receiving a user-specified query filter from a user interface, then reformatting the user-specified query filter from a first query filter representation (e.g., clicks or text from the user interface) into a second query filter representation (e.g., into XML or into a database connectivity format, or into an SQL format, or into any native format). Subsequent steps combine the second query filter representation with a predefined database query (e.g., from an enterprise application) to form a dynamically-generated database language query. The filter is specified at a user interface, and the predefined database query is specified by an application.

Abstract: Techniques for tracking function usage in an enterprise system are provided. The techniques include executing a set of processes in one or more applications on one or more computer systems. Next, a set of threads in each process is used to track, in a hash table stored in memory on a computer system, calls to a set of functions by the process. A thread in the process is then used to update a data store containing usage data for the process with the tracked calls in the hash table.

Abstract: Operations include diagnosing performance hotspots with minimal performance impact. A system selectively extracts a subset of in-memory application data, for failure analysis, based on application metadata associated with an application. The selective data extraction may be used to generate succinct reports that are customized to explore the specific vulnerabilities of each particular application. Application metadata identifies application data attributes for value extraction. The application metadata may identify, for example, a client attribute which indicates the client which requested the execution of a failed operation (or execution of an operation with a failed sub-function). The application metadata may identify a particular function, associated with an operation, that is to be analyzed in case of operation failure. The application metadata may identify a thread-local variable of a thread, executing an operation, that is to be analyzed in case of operation failure.

Abstract: Techniques for deploying a server stack having a cross-server dependency are disclosed. A deployment engine initiates a deployment process for a server stack. The deployment engine provisions servers of one server type (“requisite servers”). The deployment engine attempts to provision servers of another server type (“dependent servers”). The deployment engine executes a test that requires the dependent servers to invoke a service executed by the requisite servers. Based on the test results, the deployment engine determines that an operational requirement of the dependent servers is not satisfied. The deployment engine modifies a configuration for the requisite servers to satisfy the operational requirement of the dependent servers. The deployment engine re-provisions the requisite servers using the modified configuration. The deployment engine completes the deployment process for the server stack.

Abstract: Operations include diagnosing performance hotspots with minimal performance impact. A system selectively extracts a subset of in-memory application data, for failure analysis, based on application metadata associated with an application. The selective data extraction may be used to generate succinct reports that are customized to explore the specific vulnerabilities of each particular application. Application metadata identifies application data attributes for value extraction. The application metadata may identify, for example, a client attribute which indicates the client which requested the execution of a failed operation (or execution of an operation with a failed sub-function). The application metadata may identify a particular function, associated with an operation, that is to be analyzed in case of operation failure. The application metadata may identify a thread-local variable of a thread, executing an operation, that is to be analyzed in case of operation failure.

Abstract: Techniques for deploying a server stack having a cross-server dependency are disclosed. A deployment engine initiates a deployment process for a server stack. The deployment engine provisions servers of one server type (“requisite servers”). The deployment engine attempts to provision servers of another server type (“dependent servers”). The deployment engine executes a test that requires the dependent servers to invoke a service executed by the requisite servers. Based on the test results, the deployment engine determines that an operational requirement of the dependent servers is not satisfied. The deployment engine modifies a configuration for the requisite servers to satisfy the operational requirement of the dependent servers. The deployment engine re-provisions the requisite servers using the modified configuration. The deployment engine completes the deployment process for the server stack.

Abstract: Techniques for tracking function usage in an enterprise system are provided. The techniques include executing a set of processes in one or more applications on one or more computer systems. Next, a set of threads in each process is used to track, in a hash table stored in memory on a computer system, calls to a set of functions by the process. A thread in the process is then used to update a data store containing usage data for the process with the tracked calls in the hash table.