Modern data analytics platforms such as Hadoop and Spark have become central to many Fortune 1000 businesses. As critical components for digital business success, they produce insights that can only be obtained by analyzing the massive amounts of data. The continued growth of these systems can mean that an enterprise may be running 100,000 applications a day on 1,000 nodes, and servicing over 2,000 users. Challenges at this massive scale include piecing together performance data from those applications and the infrastructure they are running on.
There’s no foreseeable end to the relentless growth of users and applications. So how do you address performance management problems and end the headache of constant manual tuning?
The answer: deploy a solution that automatically correlates both application and infrastructure performance data allowing you to be laser-focused in your efforts to improve performance. This solution must go beyond standard monitoring and provide real actionable insights.
Auto-Correlate Infrastructure and Application Performance Events
It’s much easier to resolve bottlenecks and failures when you have rich contextual information that traverses infrastructure and application performance.
Application performance management helps developers improve application and query performance within the context of cluster operations. This also supports better organizational alignment with IT Operations. Within today’s enterprise environment, it’s critical that the process is automated. Manual tuning is not an option.
With detailed application/workload metrics, IT Operations can quickly identify and troubleshoot infrastructure issues within such an environment, optimize related cluster resources, and quickly resolve performance problems. Streamlining this process is essential to successfully scaling analytics environments to meet the business’ needs.
Application and Infrastructure Correlation Requires a Holistic Approach
Gaining visibility across your distributed system means correlating and visualizing metrics to quickly pinpoint and resolve issues. This requires a holistic approach, one that looks at how your applications interact within the context of your big data infrastructure.
Pepperdata solutions provide that holistic strategy, allowing a view of your cluster resources and delivering context-aware application tuning recommendations. You get a unified operational view, real-time granular data, and historical references to optimize application performance and resource utilization.
The solutions also make it easy to quickly see whether an application, the infrastructure, or a combination of both are contributing to the latency of your workloads. A 360-degree view of all your performance data in one dashboard lets you g