Five Key Areas to Consider When Implementing Real-Time Processing - Slide 5

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One of the most important underlying metrics of service performance is latency: the time delay experienced between a request and response at every layer of infrastructure. If a service randomly reads and/or writes data to support its response, storage IO is frequently the largest contributor to latency. Compute and network tiers under heavy load can spend the majority of their time waiting on storage IO. The next generation of enterprise-class solid-state storage provides a new level of performance for low-level IO operations, taking individual reads and writes from 10s and 100s of milliseconds to 100s of microseconds, an order of magnitude higher performance. This can be the difference between an end-user experience going from 10 seconds of wait time to 1 second or less. Some solid-state storage can support consistent performance of read-write operations regardless of sequential or random IO. This is especially important when many users are interacting with the system concurrently.

Any number of business models have been built around the exchange of data on daily, weekly and monthly intervals, but scheduling processes to produce results in the future can be a significant barrier to today’s computing, mobile, Web and application needs with the increased connectivity of businesses and consumers.

Examples include real-time access to inventory, order management, services and data assets within your business. Successfully managing real-time processing enables partners to better integrate offerings and third-party developers to create mobile apps, expanding business reach.

There are many opportunities to better leverage existing data assets and services in a larger ecosystem by providing real-time access through APIs. A great example of this vision is Netflix, which provided a real-time API for its consumer accounts and content. It has been so successful that it is working on the next version. Today Netflix serves more than a billion requests per day, with peak loads of over 20k requests per second.

Storage IO performance is critical to scale these real-time services while keeping your level of service consistent. Your storage architecture can impact the performance of these services both operationally as well as capture and report service usage for analytics and optimization.

Now is the time to leverage business assets — data, services, etc. — as real-time services. In doing so, you will find new business opportunities, provided you have infrastructure that can scale up and out for the large data demands of today and tomorrow.

Scott Metzger, vice president for corporate development at Violin Memory, has identified five key areas to consider when implementing and scaling real-time processing systems and services.

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