Effective Multi-Tenant Distributed Systems

Chapter 9. Conclusion: Performance Challenges and Solutions for Effective Multi-Tenant Distributed Systems

Organizations now have access to more data than ever before from an increasing number of sources, and big data has fundamentally changed the way all of that information is managed. The promise of big data is the ability to make sense of the many data sources by using real-time and ad hoc analysis to derive time-critical business insights, enabling organizations to become smarter about their customers, operations, and overall business. As volumes of business data increase, organizations are rapidly adopting distributed systems to store, manage, process, and serve big data for use in analytics, business intelligence, and decision support.

Beyond the world of big data, the use of distributed systems for other kinds of applications has also grown dramatically over the past several decades. Just a few examples include physics simulations for automobile and aircraft design, computer graphics rendering, and climate simulation.

Unfortunately, fundamental performance limitations of distributed systems can prevent organizations from achieving the predictability and reliability needed to realize the promise of large-scale distributed applications in production, especially in multi-tenant and mixed-workload environments. The need to have predictable performance is more critical than ever before, because for most businesses, information is the competitive edge needed to survive in today’s ...