Today we continue discussing the best practice from storage engineering:
436) Event monitoring software can accelerate software development and test cycles. Event monitoring data is usually machine data generated by the IT systems. Such data can enable real-time searches to gain insights into user experience. Dashboards with charts can then help analyze the data. This data can be accessed over TCP, UDP and HTTP. Data can also be warehoused for analysis. Issues that frequently recur can be documented and searched more quickly with the availability of such data leading to faster debugging and problem solving.
437) Data is available to be collected, indexed, searched and reported. Applications can target specific interests such as security or correlations for building rules and alerts. Data is also varied such as from network, from applications, and from enterprise infrastructure. Powerful querying increases the usability of such data.
438) Queries for such key valued data can be written using PIG commands such as load/read, store/write, foreach/iterate, filter/predicate, group-cogroup, collect, join, order, distinct, union, split, stream, dump and limit.
439) Some of the differentiators of such software include the ability to have one platform, fast return on investment, ability to use different data collectors, use non-traditional flat file data stores, ability to create and modify existing reports, ability to create baselines and study changes, programmability to retrieve information as appropriate and ability to include compliance, security, fraud detection etc
440) Early warning notifications, running rules engine, detecting trends are some of the features that enhance not only popular use cases by providing feedback of deployed software but also increase customer satisfaction as changes are incremental
436) Event monitoring software can accelerate software development and test cycles. Event monitoring data is usually machine data generated by the IT systems. Such data can enable real-time searches to gain insights into user experience. Dashboards with charts can then help analyze the data. This data can be accessed over TCP, UDP and HTTP. Data can also be warehoused for analysis. Issues that frequently recur can be documented and searched more quickly with the availability of such data leading to faster debugging and problem solving.
437) Data is available to be collected, indexed, searched and reported. Applications can target specific interests such as security or correlations for building rules and alerts. Data is also varied such as from network, from applications, and from enterprise infrastructure. Powerful querying increases the usability of such data.
438) Queries for such key valued data can be written using PIG commands such as load/read, store/write, foreach/iterate, filter/predicate, group-cogroup, collect, join, order, distinct, union, split, stream, dump and limit.
439) Some of the differentiators of such software include the ability to have one platform, fast return on investment, ability to use different data collectors, use non-traditional flat file data stores, ability to create and modify existing reports, ability to create baselines and study changes, programmability to retrieve information as appropriate and ability to include compliance, security, fraud detection etc
440) Early warning notifications, running rules engine, detecting trends are some of the features that enhance not only popular use cases by providing feedback of deployed software but also increase customer satisfaction as changes are incremental
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