When I moved from business to business (B2B) to analytics earlier this year, the first thing that struck me was the one major common aspect between the two domains: the need for data transformation. Both B2B and analytics need to transform data to make it conform to certain specifications. The raw input data is never close to the final format that they can use.
Application-level disaster recovery is not the solution for every scenario, but it can be a valid, cost effective and less complex alternative.
In this post, I describe the benefits of a pattern-based approach and share an example from Zend Technologies, an IBM Business Partner.
IBM is bringing social, mobile and cloud together with IBM SmartCloud mobile applications for iPhone, iPad, and BlackBerry devices.
Earlier this year, IBM released its IBM PureSystems family of products. There are two products in this family: IBM PureFlex System and IBM PureApplication System. In very simple terms, the PureSystems family can be thought of as cloud capabilities on a rack.
Service-oriented architecture (SOA) has been a major concept in the evolution of information technology. There have been a lot of discussions and hype around it over the past decade. The hype has shifted to cloud computing, but the principles of SOA are still vitally important. The service orientation is fundamental for most paradigms of cloud computing.
Note: Over the next two weeks, we’ll be posting one blog per day from our top 10 “greatest hits” from Thoughts on Cloud since we launched in September. This post was originally published on Nov. 7.
The major providers in the cloud space, such as Amazon, Rackspace, and IBM, include resiliency mechanisms that ensure data is not lost in the case of an infrastructure outage, at least to satisfy the levels of business continuity established in their service level agreements (SLAs). Some cloud providers also offer services that give users the ability to create private images, and snapshots of the instances and storage they provisioned for added safety from data loss. However, none of these prevent database outages.