Business Cloud 9

The company, already known for real-time operational intelligence systems, has just announced the general availability of Splunk Storm, a SaaS Cloud service aimed at organisations that develop and run applications in the public cloud, using services such as Amazon Web Services (AWS), Heroku, Google App Engine, Rackspace, and others.

 

It allows users to diagnose and troubleshoot application problems and gain rapid visibility and insight into cloud-based applications and mix the results with those generated by Splunk Enterprise working with on-premise and Cloud applications today. The Storm version provides developers with an easy-to-use, subscription version of the same software. It runs as a fully managed, multi-tenant service on AWS and dynamically provisions all the resources needed to store and analyse data.

 

It offers all the classic SaaS benefits of monthly, pay-as-you-go pricing, payable by credit card, no installation or maintenance of hardware or software, and the ability to scale storage up or down as needed, on demand, using a simple slider.

 

Using this model, the company is targeting a new generation of developers and organisations who require on-demand services. The Cloud gives developers a fast route to market for new, innovative applications. People developing and running applications in the Cloud can now get the visibility and insights they are used to getting with Splunk software for applications running in their own environments.

 

The key features in Splunk Storm include the ability to store machine data from any source, indexing and storing the data in real-time from any source, format, platform, or Cloud provider without needing custom parsers or connectors. It also allows users to use the Splunk search language to search real-time and historical machine data, filter events, correlate information across various data types, link transactions across multiple application components, and trend critical operational parameters.

 

Users can extract the precise information they require and generate reports dynamically and iteratively. They can also collaborate and share projects with others to generate cross-functional views of the data.