When it comes to DevOps, the less time you have to spend searching for information, the better. That’s where the importance of enterprise-scale monitoring comes in.

You need a system that provides access to all of your Key Performance Indicators (KPIs). In real time and presented in views that are meaningful in your datacenters and clouds. 

Beyond these requirements, there are 4 noticeable usability concerns for enterprise-scale monitoring:

1. How do I keep track of my KPIs? 

Keeping track of all of the monitoring data across applications is a non-trivial concern. At the end of the day, making sense of these metrics is a complex task. Chances are, you really don’t have time for that. At the same time, you don’t want to limit your visibility to any of the data, so that you can make decisions that are maximally informed.

2. How do I prevent downtime?

Let’s get real. You have a business to run and you need to have technology that won’t go down. Periods of downtime can have devastating business impact, so you need eyes and ears (real or virtual) on the status of your many applications at all times.

3. What level of investment should I dedicate?

Until recently, reliable monitoring has been expensive. Proprietary solutions predominate, but a new generation of open source tools is making investment in monitoring a simple matter of trading off infrastructure cost against resiliency.

4. How do I make sense of all of the data?

As you know, a huge amount of data is produced in the normal course of enterprise operations. The information explosion leads to these questions: How do you choose what to monitor and how do you synthesize monitoring into a meaningful view? With gigabytes of metrics coursing through your systems, coalescing the right bits into useful views is a first-class concern. Especially for the people who consume these data in the middle of the night. In case of an unexpected failure, having go-to views can mean quick analysis. This allows faster resolution, which has a real business impact.

The good news is that all of these concerns don’t have to concern you anymore.


Collect, Store, Manage Your Data Successfully with XAP

With time series database technology and modern visualization tools, you can collect, store, manage, and visualizeall of your data according to the constraints and requirements defined by business.

In our case, GigaSpaces’ XAP applications are built atop a distributed platform. This means that correspondent metrics data can be viewed in a number of different ways: By host, by datacenters or application context.

XAP Premium emits metrics for applications, platform components and underlying infrastructure. Most common performance metrics are built into the product. But it gets better yet, as you can implement custom reporters for KPIs and have operational visibility in real time.

XAP Premium integrates seamlessly with proprietary and open source tools.

Enterprise-Scale Monitoring

Hope you found this post helpful. In our next post I will show you how XAP is designed to integrate with a variety of open source tools, like InfluxDB and Grafana, to optimize monitoring and management of enterprise-grade applications.

Stay tuned!

Feel free to download XAP Premium Edition and see if it works for you.

Have any questions for us? We’d love to hear about your experience with XAP12 Premium in the comments or via email: getxap@gigaspaces.com

4 Major Usability Concerns for Enterprise-Scale Monitoring
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Jason Nerothin
Senior Technical Account Manager @ GigaSpaces
Jason is a Senior Technical Account Manager at GigaSpaces. With over 10 years of industry experience as a consultant, senior solutions architect, and software engineer, Jason's expertise is leveraged by the largest enterprises for architecture planning & review and project life-cycle planning.
Jason holds a computer science degree from the University of Eastern Michigan. He's all about real-time analytics, distributed compute, and all things Scala. Prior to joining GigaSpaces, Jason held positions at Pharmacy OnceSource and the Roche-Nimblegen.

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