The 5 Best Methods for Drawing Insight out of Machine Data

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Infrastructure Monitoring

Infrastructure monitoring provides information about individual servers and how they are handling the load of application and requests. The data includes CPU and memory usage, load, disk I/O, and memory I/O aggregated for the system or displayed individually by process.

Data is either captured by an agent installed on each server or a service connects to machines via SNMP and then data is sent to a centralized location for visualization.

Why is this important? Understanding how your infrastructure performs allows the engineering team to proactively address issues, set alerts, and assess how to scale the environment and optimize performance.

The pursuit of data-driven decision making has put tracking, logging and monitoring at the forefront of the minds of product, sales and marketing teams. Engineers are generally familiar with gathering and tracking data to maintain and optimize infrastructure and application performance. However, with the power of data, other business groups are clamoring for the latest tools and instrumentation. Quite often the expense of implementation is undersold as merely placing a tag on a site or adding a library, and doesn’t take into account the additional expense of tracking unique aspects of the application. To complicate matters, there is usually quite a bit of confusion on the types of data being captured by the tools a company already has in place.

In this slideshow, Thomas Overton, from the Sumo Logic Developer Community, offers the five best methods for gaining insight from machine data.

 

Related Topics : IBM Looks to Redefine Industry Standard Servers, APC, Brocade, Citrix Systems, Data Center

 
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