‘Enterprises are using cloud as a platform to store data and run Big Data analytics’

Amrita Premrajan| Informationweek

Today, customers are moving away from evaluating storage solutions in isolation, and are taking into consideration how easy or difficult it is to access this data from their compute solutions. Let us look at the classic situation where companies need to preserve petabytes of data, which they can’t afford to delete from a business perspective.

From an IT perspective since they’re dealing with large costs in durably preserving this content indefinitely, they need to figure out an extremely low cost option. This is one of the reasons that led us to invent and build Amazon Glacier, which is an extremely low-cost storage service that provides secure and durable storage for data archiving and backup.

In order to keep costs low, Amazon Glacier is optimized for data that is infrequently accessed and for which retrieval times of several hours are suitable. With Amazon Glacier, our customers can reliably store large amounts of data for as little as USD 0.01 per gigabyte per month, a significant savings compared to on-premises solutions.

However, Amazon Glacier is just a piece within an overall Big Data solution. When companies need to process their data, they also need access to high performance storage. Solutions like Amazon Elastic Block Store (EBS) and Amazon DynamoDB enable customers to provision storage on-demand with high, predictable performance. Amazon EBS provides block level storage volumes for use with Amazon Elastic Compute Cloud (Amazon EC2) instances.

For example, Splunk Inc. enables organizations to monitor, search, analyze, visualize and act on massive streams of real-time and historical machine data. Splunk uses Amazon EBS to deliver a service-based version of their data analytics software called Splunk Storm. This enables their customers companies to utilize Splunk to analyze their data without having to provision hardware.

Many of AWS’s customers run database applications that require a high and consistent level of IOPS (input/output operations per second) from their storage solutions. Last year, AWS launched EBS Provisioned IOPS volumes to further support these workloads. Customers can specify an IOPS rate when creating a Provisioned IOPS storage volume, and then Amazon EBS consistently delivers that specified level of IOPS to customers’ applications. Customers can use these volumes to consistently deliver thousands of IOPS to their applications running on Amazon EC2.

For customers with NoSQL workloads that require even higher performance, we offer Amazon DynamoDB, a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. Amazon DynamoDB is capable of exceeding hundreds of thousands of reads/writes per second.

Are enterprises across the globe actually evaluating cloud as a platform to do Big Data analytics and mine their enterprise data?

Enterprises are increasingly looking at cloud as a platform to store data and run Big Data analytics. We are seeing a number of successful companies use AWS to both store their data and leverage it to develop greater insights. This is a trend we see across verticals, whether it’s biotech, advertising, or e-commerce, where businesses are unearthing a number of innovative new ideas from mining their data.

At AWS, we’re focusing on innovating quickly to ensure our customers have a number of different storage options to flexibly manage and analyze their data, and that they have ready access to our various compute offerings.

For example, we enable customers to durably store their log data on our Amazon Simple Storage Service (Amazon S3), and then use our Amazon Elastic MapReduce service to easily analyze this data from Amazon EC2.

For example, Etsy, which runs a website that enables individuals to sell handmade, vintage items, uses Amazon S3 to durably store its HTTP server logs. They then take this enormous amount of data, and use Amazon Elastic MapReduce to analyze these logs over hundreds of machines.

Similarly, Yelp, best known for sharing in-depth reviews and insights on local businesses, uses Amazon S3 and Amazon Elastic MapReduce to store and mine logs for presenting review highlights, top searches, and advertisements on their website.

What is really driving this trend of enterprises contemplating cloud computing solutions, as compared to on-premise solutions?

Cloud computing levels the playing field, enabling companies with a great idea, but limited resources, to have access to the same storage and compute technologies. Customers are no longer tied to large capital investments in on-premises infrastructure, so they’re able to immediately benefit when we lower our prices (as opposed to being stuck with hardware for years).

This is one of the reasons we’ve seen strong growth across several verticals, including Internet businesses like Instagram, Netflix, Pinterest, and Dropbox who are all using the AWS platform. Many enterprises use services like Amazon S3 to increase their agility also where they use S3 without having to worry about managing for scale, and rapidly reduce their time-to-market. Because of this, we see a number of enterprise customers use AWS today, including Shell, Farmers Insurance, Nasdaq and Newsweek.

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