International Business Machines Corporation

Kyndryl, Inc.

Vishal Anand

Rajneesh Kumar

Vijay S Patil

Amit Patra

Sahadev Dey

Manish Satyapal Gupta

Suryanarayana K Rao

Ramesh Chandra Pathak

Venkateswara Reddy Madduri

Santanu Bandyopadhyay

Ravi Kothari

A system and method for multiple parameter based composite rule data validation includes receiving a request to validate target data of a target object based on constituent parameters, identifying the data type of the target data, suggesting validation rules based on the data type of the target object, generating a set of composite validation queries, identifying at least one composite validation query in the set of composite validation queries corresponding to the constituent parameters and values, validating the target data of the target object against the at least one composite validation query, and returning a validation result for the target data.

Multiple parameter based composite rule data validation

A method for validating data in a hybrid cloud model that includes providing a validation layer in the brokerage module of the hybrid architecture. The validation layer is separate from an applications layer of the hybrid architecture. The method includes sending target object values to a centralized brokerage layer composite query generator (BLCQG) component of the validation layer from an application needing validation of target data time. The method continues with generating a composite validation rule set with the brokerage layer composite query generator (BLCQG) component based on the parameters of the target object values. The method further includes validating the target data item of the target object values with the composite validation rule in the validation rules validator (VRV) component; and sending the target data item that has been validated to the application.

Multiple parameter based composite rule wise data validation in cloud hybrid model

An approach is provided for monitoring disk utilization at an object level. At a first time a first size of an object in a System i computing platform is determined by calling an application programming interface (API). At a second time a second size of the object is determined by calling the API. A difference between the first and second sizes is determined. The difference is determined to be greater than a threshold. Based on the difference exceeding the threshold, an alert is sent indicating growth at the object level rather than at an auxiliary storage pool level. The API is called to obtain the sizes of libraries in the System i computing platform. Differences between the sizes of the libraries at a user-entered start date and the current time are determined and presented. A report including the differences is generated and sent.

Disk utilization analysis

An approach is provided for monitoring disk utilization at an object level. At a first time a first size of an object in a System i computing platform is determined by calling an application programming interface (API). At a second time a second size of the object is determined by calling the API. A difference between the first and second sizes is determined. The difference is determined to be greater than a threshold. Based on the difference exceeding the threshold, an alert is sent indicating growth at the object level rather than at an auxiliary storage pool level. The API is called to obtain the sizes of objects in an integrated file system in the System i computing platform. Differences between the sizes of the objects at a user-entered start date and the current time are determined and presented. A report including the differences is generated and sent.

An approach is provided for monitoring disk utilization at an object level. At a first time a first size of an object (i.e., integrated file system or library) in a System i computing platform is determined. At a second time a second size of the object is determined. A difference between the first and second sizes is determined. The difference is determined to be greater than a threshold. Based on the difference exceeding the threshold, an alert is sent indicating growth at the object level rather than at an auxiliary storage pool level. Sizes of System i libraries are monitored at multiple dates and stored in a repository. Sizes of the libraries at user-entered start and end dates are retrieved from the repository. Differences between the sizes of the libraries at the start and end dates are determined and presented.

A method and apparatus for implementing a storage optimization process is provided. The method includes identifying a file for storage on a storage device. The storage device determines that the file comprises a file size that exceeds multiple physical disk blocks of the storage device by a fractional value. The file is divided into a first portion and a second portion. The first portion comprises a file size such that the first portion fits entirely within a first single block of the storage device. The second portion comprises a size such that the second portion exceeds a size of a second single block of the storage device by the fractional value. The first portion is stored within the first single block. The second portion is compressed such that a resulting compressed file fits entirely within the second single block.

Storage device optimization

An approach is provided for monitoring disk utilization at an object level. At a first time a first size of an object in a System i computing platform is determined by calling an application programming interface (API). The object is an integrated file system object or a library that includes other objects in the System i platform. At a second time a second size of the object is determined by calling the API. A difference between the first and second sizes is determined. The difference is determined to be greater than a threshold. Based on the difference exceeding the threshold, an alert is sent. The alert indicates the object had a growth in size that exceeds the threshold and indicates the growth at a level of the object, which is different from a growth at a level of an auxiliary storage pool in the System i platform.

A resource requirements method and system is provided. The method includes identifying dependencies and calculating a utilization value for a source server. The source server is mapped to an application and a source infrastructure is compared to a target infrastructure. Deficiencies and differences associated with the target infrastructure are determined and dependency requirements for fulfillment in the target infrastructure are generated. The utilization value is compared to a resource capability of the target server and resource requirements for fulfillment on the target server are generated.

Server virtualization

Techniques for automatically documenting activity data in connection with execution of a ticket are provided. The techniques include receiving activity data in connection with execution of a ticket, processing the activity data to generate an output, and appending the processed activity data output to the ticket for ticket enrichment. Techniques for identifying a wrong choice of resolution code in connection with a ticket are also provided. The techniques include analyzing one or more previous tickets to determine a category in which a ticket belongs, determining whether a user-defined code is in variance with a system-suggested code, and sending an alert to a system administrator if the user-defined code is different than the system-suggested code.

Automatic documentation of ticket execution

A system and method of employing a facade to intercept change action commands to be carried out on a target IT endpoint resource. The intercepted commands are compared to information on a corresponding change ticket and any differences, along with the information such as target history, are used to compute a risk assessment of the risk in allowing the intercepted change action commands to be executed. Where the risk exceeds a predetermined threshold, the intercepted change action commands may be modified or eventually aborted.

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Bihar, India

Vishal Anand