Abstract: An improved technique involves providing application workload simulation capability via a centrally located synthetic data generation service to an external party. Along these lines, a client inputs a description of an application scenario into a web form which sends a request to a central server to generate a synthetic data simulation program. The central server extracts parameters values from the request corresponding to the application scenario and finds a model in a model database based on the parameter values. From the model, the central server derives a Java program that generates synthetic data for simulating the operation load of the application scenario described by the client, and sends the Java program to the client. The client is then able to generate synthetic data using the Java program on various configurations to determine which will successfully handle the synthetic data load continuously over a given period of time.

Abstract: An improved technique involves generating a predictive model for data storage system configuration management. A customer support center generates such a predictive model from detailed customer configuration and transaction history. For example, a population of customers submits transaction logs to the customer support center; such transaction logs provide details as to how the customers responded to various events. The population of customers may also submit data including various statistics such as load intensity, workload characteristics, data access patterns, data change patterns, and data fingerprints to the customer support center. The customer support center then performs an analysis on the data and, from the analysis, computes values of model parameters that define a predictive model. This predictive model is configured to take in a particular state of any data storage system and produce a configuration that optimizes performance of that data storage system.

Abstract: An improved technique involves consulting a predictive model to optimize a configuration of a data storage system. A customer at a data storage system requests a configuration optimization from a customer support center by sending values of input parameters to the customer support center. Such input parameters represent a current state of the data storage system, e.g., initial configuration. The customer support center then receives configuration parameters in response to inputting the input parameters into a predictive model running on a host computer. The customer uses the configuration parameters to define the configuration state in which the data storage system runs.

Abstract: An improved technique involves providing a decision procedure to determine whether an unsolved customer problem goes to a public problem-solving forum or internal support. For example, when a support center receives a customer problem and determines that the problem does not have a known solution, it assigns a severity weight to the problem based on a description of the problem. Along these lines, suppose that the call center receives a customer problem regarding excessive down time. When the call center places the problem into a “downtime” classification, the call center counts how many other unsolved “downtime” problems are awaiting solution. If there are not many similar problems awaiting solution, then the call center assigns a high severity level and assigns the task of solving the problem to a public forum, such as a crowdsourcing application.

Abstract: A method and system for use in supervising a data storage system is disclosed. The status of an operational feature in the data storage system is monitored. A human perceptible signal is outputted in response to monitoring the status of the operational feature in the data storage system. The data storage system outputs the human perceptible signal locally thereto indicating the current status of the operational feature in the data storage system.

Abstract: Software code sections can include at least one calling procedure (110) and a called procedure (140). The called procedure can include an interpreted code body (144). Execution of the interpreted code body can require the use of an associated interpreter. The software code sections can also include prologue (142) associated with the called procedure. The prologue can be invoked by the at least one calling procedure and can responsively actuate the interpreted code body causing programmatic actions defined within the interpreted code body to execute. Execution of the prologue does not require use of an interpreter. In one embodiment, the interpreted code body of the called procedure can execute upon a platform having an application binary interface (115). The prologue can actuate the interpreted code body according to specifications of the application binary interface.