Modern data is continuous, diverse, and ever accelerating

How companies such as athenahealth can transform legacy data into insights.

Application development in the big data space has changed rapidly over the past decade, driven by three factors: the need for continuous availability, the richness of diverse data processing pipelines, and the pressure for accelerated development. Here we look at each of these factors and how they combine to require new environments for data processing. We also look at how one company, athenahealth, is adjusting its legacy systems, for billing, scheduling, and treatment for health care providers, to accommodate these trends, using the Mesosphere DC/OS platform.

Continuous availability: Data is always on

This is a world where people could be working or visiting your site at three in the morning, and if it's unavailable or slow you'll be hearing complaints. Failure recovery and scaling are both critical capabilities. These used to be handled separately: failure recovery revolved around heartbeats and redundant resources, whereas scaling was an element of long-term planning by IT management. But the two capabilities are now handled through the same kinds of operations. This makes sense, because they both require monitoring and resource management.

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