Big Data Performance and Capacity Planning

Your business can’t afford slow application performance or downtime. But with ever-growing big data workloads and constraints on infrastructure or cloud spend, keeping applications running optimally and meeting SLAs is a challenge. High volumes of data and large-scale distributed computing architectures ratchet up the pressure to improve operational efficiencies. Without the ability to predict future needs and plan, your IT environment risks performance bottlenecks and outages. Capacity management and planning can help you better understand your performance needs for today and provide a plan for growth.

Capacity planning is the process of evaluating your current and future big data infrastructure needs and developing a strategy to provide the best performance while accounting for growth. Successful capacity management and planning help ensure you can meet your SLAs, deliver applications on time and within your IT budget, and continue to offer the capability the business needs to grow. Predictive analysis helps you know when you will no longer be able to meet service levels, how to prepare for future workloads, and determine the most cost-effective configuration for your IT environment.

CPU, memory, and storage metrics provide performance numbers on how your applications and workloads are running today. Utilization trends help you better understand what resources are in demand and determine what growth you can factor in for the future. Dashboards can provide a visual representation of utilization rates for your resources. These tools can also help you think through “what if” scenarios.

Getting an understanding of what business initiatives are driving the current usage and how changes in your business impact your applications and workloads gives you a more holistic approach to decision making. Taking these business views into account will allow you to optimize your utilization for current resources and eliminate potential waste. Incorporating a wider view of the business and growth also enables you to stay ahead of organizational expansion.

Poor application load times, response, and outages can have serious consequences for your business as well as the IT team. Calculating the ROI for your big data infrastructure can provide much-needed data for the executive team to help them make IT decisions. Furthermore, quantifying the true cost of an outage or outages for big data applications, in terms of lost revenue or customer opportunities, helps organizations understand their big data applications and their workloads’ contribution towards business success.

Reducing the Runaway Costs of a Hybrid Big Data Architecture – e-Book

Using Capacity Optimizer with Platform Spotlight, you can:

• Analyze and optimize the relationship between your big data workloads and infrastructure.

• Precisely determine your existing needs, in the cloud or on-premises.

• Accurately model and forecast future requirements.

• Reduce business risk.

• Gain better control over infrastructure spend.

Learn more about Pepperdata Platform Spotlight and Capacity Optimizer performance management solutions.