ClearScale Blog

What’s the General Data Protection Regulation, known as GDPR, have to do with the cloud? The answer: a lot. Personal data — any data that can identify a person — is increasingly making its way into the cloud. For example, organizations are using IoT - connected devices, AI and RFID technologies to collect, use and integrate personal information into products and are storing and processing that data in the cloud. GDPR provides updated legislation throughout the EU to protect that personal

Pharmaceutical research is data-intensive. It takes tremendous computational power to parse and analyze the requisite giant chunks of data. The cloud delivers that power and helps accelerate research processes and, ultimately, research findings. That’s why one pharmaceutical company was using some “off the shelf” CloudFormation templates to create its own powerful informatics environment on the AWS cloud. However, the company determined that it needed assistance in optimizing that environment. A key driver was its use of a set of

It’s one thing to create a platform to support software development. But it requires special expertise to build out one that specifically employs AWS best practices and meets rigorous compliance requirements. The challenge is further intensified when the software development process relies on open source libraries to accelerate time-to-market. With open source libraries come open source vulnerabilities. The Assignment When a life sciences organization requested ClearScale’s assistance in creating infrastructure for a new software project, the ClearScale team

In the world of software development, the use of a feature branch workflow is a good thing. The idea is that all feature development takes place in a dedicated branch instead of the master branch. Among the benefits: multiple developers can work on a particular feature without disturbing the main codebase. That was how a ClearScale customer was handling new feature development for the software underlying one of its key products. However, the process required dynamically and automatically launching an

Machine learning-enabled medical image analysis. Prosthetics customized for individual patient comfort and performance courtesy of 3-D printing. Context-aware, real-time communication platforms. Virtual Reality (VR) tools that enable medical students to experience and learn from life-and-death scenarios in low-stakes environments. They’re among the numerous examples of technology pushing healthcare to new levels of efficiency and sophistication. In many cases, the technologies driving these innovations are cloud-based. That’s good and, in the minds of some healthcare organizations, not so good

It’s a common problem. You can’t seem to develop and deploy applications fast enough to meet your customers’ changing demands. By automating the processes involved, however, you can speed things up. You’re also able to scale up and down on the fly, reduce manual errors, improve the overall availability of the application and realize the cost benefits of on-demand compute. Sounds great, right? But as Tom Hanks’ character said in the movie, A League of Their Own

Research and development (R&D) at most companies is a collaborative process. It requires working with and analyzing large amounts of data, often by teams spread out across multiple geographies and time zones. In many cases, companies rely on enterprise resource planning (ERP) applications to help them integrate and visualize the entire R&D process from idea to production. It’s essential for both the data and applications to always be accessible, secure and free from corruption or

Across all industries, automation is radically transforming the way business is conducted. Time-consuming tasks that once required an army of human beings can now be completed via automation technology. Just some of its many benefits include cost savings, greater operational efficiency and the chance to move human capital to tasks better suited for human intelligence, such as problem-solving. Organizations that can find new ways of executing workflows through automation are poised to become leaner, faster and more intelligent. The Challenge

The Challenge A financial analytics company's data analysis application had proved highly successful, but that success was also a problem. With a growing number of isolated data centers generating constant data streams, it was increasingly difficult to efficiently gather, store and analyze all that data. The company knew a cloud-based big data analytics infrastructure would help, specifically a data ingestion pipeline that could aggregate data streams from individual data centers into a central cloud-based data storage. Among the challenges in

Big data has transformed the way companies conduct business. Through the careful analysis of large amounts of information, organizations can be empowered with modern decision-making capabilities that make it easier to draw conclusions and carry out actions based on accurate, relevant, and up-to-date data. Companies that embrace big data gain access to tools that can significantly reduce the cost of doing business. Using big data to help an organization lower costs requires a detailed understanding of how, when, and where