Systems | Development | Analytics | API | Testing

We are happy to announce the general availability of Kuma 0.7! This is very big release that includes countless improvements and updates, specifically when it comes to multi-zone deployments configuration and Kubernetes deployments. We strongly suggest to upgrade to this new version while paying attention to a few breaking changes that 0.7 introduces. For a complete list of features and updates, take a look at the full changelog.

Healthcare organizations like yours are riddled with mountains of data and document streams coming in each day. Whether it’s patient records, claims, denials, remits, or clinician credentials… the list goes on. All these items can quickly create chaos and confusion without proper organization protocols in place to handle this data deluge. When employees are tasked with manually handling inbound document management, there is the potential for a wide array of complications, including.

Medical devices have become increasingly complex as technology evolves, and the sheer number of these devices now being worn or implanted has grown exponentially over the past few years. There are currently over 500,000 different types of smart, connected medical devices in use that have the ability to collect, share, or store private patient data and protected health information (PHI)(1).

Coronavirus has impacted the travel industry, but as it adapts, there is one factor airlines have always worked hard to minimize: delayed flights. Arriving late or missing a connection can severely impact the customer experience, which is why airlines work hard to maintain high rates of on-time performance (OTP). To that end, pilots may have to use extra fuel to make up for a delayed departure or to reach a destination early, even if it means circling the airport before landing.

Kibana and the rest of the ELK stack (Elasticsearch, Kibana, Logstash) is great for parsing and visualizing API logs for a variety of use cases. As an open-source project, it’s free to get started (you need to still factor in any compute and storage cost which is not cheap for analytics).