Model-based key performance indicator service for data analytics processing platforms

A method comprising:

• receiving input data from one or more data sources, the one or more data sources comprising a plurality of Internet of Things (IoT) sensors;
• identifying first and second distinct instances of a key performance indicator (KPI) management data model associated with respective first and second portions of the received input data;
• and
• performing particular first and second distinct KPI services on the respective first and second portions of the received input data in accordance with the respective first and second identified instances of the KPI management data model;
• wherein performing the particular first and second KPI services comprises:
• utilizing the first identified instance of the KPI management data model to extract one or more first metrics from the first portion of the received input data and to compute one or more first KPIs based at least in part on the one or more extracted first metrics;
• utilizing the second identified instance of the KPI management data model to extract one or more second metrics from the second portion of the received input data and to compute one or more second KPIs based at least in part on the one or more extracted second metrics;
• generating analytics output comprising the one or more computed first KPIs and the one or more computed second KPIs for the received input data;
• and
• automatically altering an allocation of one or more of network, storage and compute resources associated with the processing platform to obtain a particular configuration based at least in part on the analytics output;
• wherein automatically altering an allocation of one or more of network, storage and compute resources associated with the processing platform to obtain a particular configuration based at least in part on the analytics output comprises one or more of adjusting a number of running containers or virtual machines for one or more applications, migrating containers or virtual machines for one or more applications from one host device to another, and modifying an amount of compute, storage and network resources that are allocated to a given application;
• wherein the one or more extracted first metrics and the one or more extracted second metrics each comprise one or more of a resource utilization metric and an application metric;
• and
• wherein the method is implemented by a processing platform comprising a plurality of processing devices each comprising a processor coupled to a memory.

A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by a processing platform comprising a plurality of processing devices, each such processing device comprising a processor coupled to a memory, causes the processing platform:

• to receive input data from one or more data sources, the one or more data sources comprising a plurality of Internet of Things (IoT) sensors;
• to identify first and second distinct instances of a key performance indicator (KPI) management data model associated with respective first and second portions of the received input data;
• and
• to perform particular first and second distinct KPI services on the respective first and second portions of the received input data in accordance with the respective first and second identified instances of the KPI management data model;
• wherein performing the particular first and second KPI services comprises:
• utilizing the first identified instance of the KPI management data model to extract one or more first metrics from the first portion of the received input data and to compute one or more first KPIs based at least in part on the one or more extracted first metrics;
• utilizing the second identified instance of the KPI management data model to extract one or more second metrics from the second portion of the received input data and to compute one or more second KPIs based at least in part on the one or more extracted second metrics;
• generating analytics output comprising the one or more computed first KPIs and the one or more computed second KPIs for the received input data;
• and
• automatically altering an allocation of one or more of network, storage and compute resources associated with the processing platform to obtain a particular configuration based at least in part on the analytics output;
• wherein automatically altering an allocation of one or more of network, storage and compute resources associated with the processing platform to obtain a particular configuration based at least in part on the analytics output comprises one or more of adjusting a number of running containers or virtual machines for one or more applications, migrating containers or virtual machines for one or more applications from one host device to another, and modifying an amount of compute, storage and network resources that are allocated to a given application;
• and
• wherein the one or more extracted first metrics and the one or more extracted second metrics each comprise one or more of a resource utilization metric and an application metric.