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In computing, data is information that has been translated into a form that is efficient for movement or processing. Relative to today’s computers and transmission media, data is information converted into binary digital form. It… Continue reading
The adoption of highly scriptable cloud-based technologies, along with the emergence of continuous integration (CI) and continuous deployment (CD) tools, has created an environment in which every operations process should be
scriptable and all manual processes targeted for database automation. Organizations with a DevOps approach to application lifecycle management should automate every process imaginable, but they often hit a wall when they reach the persistence layer. Emerging technologies have the potential to make that limitation disappear.
“Database release automation is a real problem,” Datical CTO Robert Reeves says. “You’ve got lots of great ways of automating the application and provisioning servers. But we are still asking DBAs [database administrators] to just work faster, work harder, as they do manual updates.”
So, why can’t we take the lessons we learned from Agile or the progress DevOps has made and apply them to the persistence layer?
“Because of state,” Reeves explains. Unlike applications, a database can’t simply be deleted and recreated on the fly as though you were deploying and undeploying a microservice packaged in a Docker container. “You can’t just zap it.” Continue reading
Big data systems, for some companies, aren’t just platforms for new types of data processing and analytics applications — they’re the driving force behind entirely new business strategies.
Organizations hungry for more revenue are using Hadoop and other big data technologies to break their existing business molds and pursue new strategies and product offerings.
That’s the case at iPass Inc., which is using a big data environment to fuel a strategic shift from pay-for-use Wi-Fi access to tools for managing and optimizing mobile connectivity for corporate users. Introduced in late 2015, the company’s iPass SmartConnect software includes algorithms that identify Wi-Fi access points and rank them on performance so mobile users can connect to the fastest and most reliable hotspots available. That marks a big change from when iPass gave users a static list of hotspots.
And it wouldn’t be possible without the underlying data management platform built around the Spark processing engine, said Tomasz Magdanski, director of big data and analytics at iPass. “We do need the big data architecture, 100%,” he explained. “There’s no way we could crunch all this data in real time and do all the ranking and measurements without it.” Continue reading