Keeping big data initiatives on schedule and under budget while delivering value is a challenge. To rise to this challenge, you need a holistic view of their entire big data stack, as well as visibility into capacity management and automatic optimization.
Having a holistic picture unearths usage patterns, peak computing demand, resource requirements, resource allocation, storage utilization, and processor requirements. Unhindered access to all this information gives users the ability to derive actionable insights and take decisive action, ultimately impacting both optimization and ROI.
With classic APM solutions, all you see are the application and its performance data. You don’t have visibility over other essential components such as the number of resources consumed by your infrastructure. A slight miscalculation on resources can result in overprovisioning and misallocation, which can cost you money.
When you aim for success for all your big data initiatives, you need to view the problem holistically. You have to look beyond your application. A holistic view means you’re looking at your application and also what its effect on the shared source, your cluster.
To create that holistic picture, you must integrate big data, application metrics, and platform metrics. Doing this will help you understand performance and see how each element interacts with the other. You achieve a comprehensive and detailed view into what is occurring on the application and the platform. Once you have this, you receive timely notifications, alerts, and useful recommendations or resource usage and tuning.
In this report, we discuss the three keys to big data performance management. Understanding what each key represents is critical to the success of your big data projects. After reading this report, you’ll understand what three things you need to take your organization to the next level. Download your copy of The Three Keys to Big Data Performance Management to discover how you can make big data work for you and your business.