Imagine needing to make an urgent phone call from the office, but when you look around, you realize all the phones are in use. With no alternative form of communication your only course of action is to file a ticket with IT and wait for a phone to come available, so you can make your call.
While this scenario is certainly farfetched, something similar happens every day in enterprises that don’t properly allocate the necessary hardware to business-critical applications. The ability to deliver employees what they need to get their job done, when they need it, is essential for companies who want to be agile and stay ahead of the competition. And it’s one of the reasons organizations are looking to the cloud.
In significant numbers enterprise companies – including Adecco, Airbnb, GoPro, Nielsen, and others – are running Cloudera Enterprise on public cloud infrastructure. In addition to driving increased agility, our customers often opt to deploy in the cloud for the following reasons:
- Reduce the cost associated with purchasing, configuring, and maintaining on-premises hardware required to run big data applications
- Increase the ability for data engineers and data analysts to respond to business problems through self-service provisioning
- Meet strategic objectives to “move to the cloud” to reduce a company’s owned data center footprint.
Today at Strata+Hadoop World in New York, Cloudera announced enhancements to its core platform, Cloudera Enterprise, and Cloudera Director to make it easier for customers to deploy and manage the lifecycle of production-grade Hadoop in the cloud across any cloud service. With the latest releases, Cloudera users can run big data workloads on AWS, Google Cloud Platform, and Microsoft Azure using pre-built templates that make deploying, scaling, and terminating clusters fast and easy.
Other new features that are helping customers achieve additional levels of agility and self-service include:
- Cloud-native infrastructure support for Apache Impala (incubating) to enable high-performance SQL analytics and BI workloads on the data in Amazon S3 without having to move that data to another location. Check out our recent Impala on S3 benchmarks here
- Automated billing and metering on a per-hour, per-node basis to help customers lower TCO and take advantage of cluster transience.
Our aim is as it has always been. To deliver a consistent, secure, high-performance experience to our customers, wherever they choose to deploy – in the cloud, on-prem or in a hybrid environment.
For example, Novantas, a leader in financial services analytics has developed an analytical model for its retail banking customers that maps things like shopping behavior, rate sensitivity, and retention period. These models help banks better predict which of their customers are likely to be profitable. The company is using Cloudera Enterprise with Apache Spark to process thousands of business metrics with sub-second response time. Most of this customer data lives in AWS.
However, because Novantas deals in the highly regulated banking industry, they find many of their customers would prefer that their data remain on premises. That’s why Cloudera’s ability to provide data processing and analytics in hybrid environments is so important.
We’re going to be talking about cloud a lot this week, starting off with a keynote Wednesday morning from Mike Olson. If you’re interested in hybrid cloud, I suggest checking out the Hadoop World livestream Thursday morning for a keynote from James Powell, CTO at Nielsen, who will talk about running Cloudera Enterprise in a multi-cloud architecture to move faster and manage risk.