Database Benchmarking and Stress Testing
An Evidence-Based Approach to Decisions on Architecture and Technology
Produktform: Buch / Einband - flex.(Paperback)
Provide evidence-based answers that can be measured and relied upon by your business. Database administrators will be able to make sound architectural decisions in a fast-changing landscape of virtualized servers and container-based solutions based on the empirical method presented in this book for answering “what if” questions about database performance.Today’s database administrators face numerous questions such as: As an administrator, do you know the answers or even how to test the assumptions?
introduces you to database benchmarking using industry-standard test suites such as the TCP series of benchmarks, which are the same benchmarks that vendors rely upon. You’ll learn to run these industry-standard benchmarks and collect results to use in answering questions about the performance impact of architectural changes, technology changes, and even down to the brand of database software. You’ll learn to measure performance and predict the specific impact of changes to your environment. You’ll know the limitations of the benchmarks and the crucial difference between benchmarking and workload capture/reply.
This book teaches you how to create empirical evidence in support of business and technology decisions. It’s about not guessing when you should be measuring. Empirical testing is scientific testing that delivers measurable results. Begin with a hypothesis about the impact of a possible architecture or technology change. Then run the appropriate benchmarks to gather data and predict whether the change you’re exploring will be beneficial, and by what order of magnitude. Stop guessing. Start measuring. Let show the way.
Database administrators and professionals responsible for advising on architectural decisions such as whether to use cloud-based services, whether to consolidate and containerize, and who must make recommendations on storage or any other technology that impacts database performance
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