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IT Cost Optimization and ROI
IT Cost Optimization and ROI for Big Data Clusters
Improving performance, guaranteeing reliability, reducing cost, and achieving ROI is a critical priority for most data-driven companies, but it’s not easy. Managing performance on distributed systems is riddled with interdependencies and complexity.
IT cost optimization strategy gets confused with IT cost-cutting, but modern IT departments have moved beyond simple expense reduction to focus on optimizing the value of their big data analytics stack investment.
They understand that cost optimization isn’t a one-time action. They also know that when performance or reliability issues occur on the stack, those issues cannot typically be resolved by simply cutting expenses.
Get a Complete and Transparent View of Performance and Cost
Improving business efficiency by optimizing your big data analytics stack requires the metrics to understand everything happening on the cluster in real time and getting correlated visibility across big data applications and infrastructure for a complete and transparent view of performance and cost.
Unlike solutions that merely summarize static data, Pepperdata delivers complete system analytics on hundreds of real-time operational metrics continuously collected from applications as well as the infrastructure.This includes CPU, RAM, disk I/O, and network usage metrics on every job, task, user, host, workflow, and queue.
Simplify Troubleshooting and Reduce Time to Resolution
Complete system analytics should be viewable in a comprehensive, intuitive dashboard that provides a holistic view of cluster resources, system alerts, and dynamic recommendations for more effective troubleshooting, capacity planning, and IT chargeback reporting. This allows you to:
Diagnose problems quicker.
Automatically alert on critical conditions affecting system performance.
Get recommendations for rightsizing containers, queues, and other resources.
Leverage ML-driven resource management to recapture wasted capacity.