At Databox, we put our company values at the forefront of everything we do. Prioritizing customer impact is one of the values we focus on the most, so taking the time to really understand our customers is paramount and we employ multiple strategies, frameworks, and initiatives on a daily basis to achieve this. One of those strategies is our Customer Lifecycle Framework (CLF), which reflects our dedication to prioritizing the needs of our customers at every stage of their interaction with us.

In the modern IT stack, API gateways act as the first line of defense against attacks on backend services by enforcing authentication/authorization policies and validating and transforming requests. When backend services are protected with a token-based approach, client applications must obtain an access token to access the protected resource.

After getting our Konnect Data Planes vertically and horizontally scaled, with VPA and HPA, it's time to explore the Kubernete Node Autoscaler options. In this post, we start with the Cluster Autoscaler mechanism. (Part 4 in this series is dedicated to Karpenter.)

Today, Site Reliability Engineering (SRE) emerges as the key player in the fast-paced modern industries, where the demand for seamless software delivery collides with the need for reliability, maintaining this delicate equilibrium. It’s not merely a role; it’s a strategic position that safeguards system health while strategically mitigating the financial pitfalls associated with downtime.

According to a study by Stack Overflow, developers spend approximately 50% of their time debugging and fixing issues in their code. As a software engineer, I understand the problem first-hand. We pour our heart and soul into building applications, yet bugs persist despite our best efforts. While some are caught during compilation, others lurk undetected, potentially causing damage and financial woes. That’s why rigorous testing of applications becomes crucial before market launch.

Nearly every facet of society has felt the impact of AI since it burst into the mainstream in late 2022 with the public launch of ChatGPT. In 2024, the retail and consumer goods industry is expected to experience massive upheaval due to the proliferation of generative AI (gen AI) tools as well as changes in customer engagement and the general manner in which products are now sold.

It’s no secret that the expectations for public sector digital services have changed significantly over the past few years; services need to be rolled out fast to ensure usable and secure software that can help agencies deliver on their mission. These expectations can be met by combining DevSecOps with codeless automated software testing.

Testing software is like putting it through a series of challenges to make sure it’s tough enough for real-world use. Whether we’re testing each piece individually (unit testing) or how they all work together (integration testing), we need to be prepared for different situations. Sometimes, testing is tricky.There are times, when we need to isolate parts of our code from their dependencies.

In the dynamic landscape of software development, where agility and precision are paramount, testing reports emerge as a cornerstone for quality assurance, tracking progress, and fostering effective communication among stakeholders. Let's embark on a journey to explore the intricacies of testing reports, unraveling their significance, types, content, and the tools that can elevate your reporting game.

Financial services companies are leveraging data and machine learning to mitigate risks like fraud and cyber threats and to provide a modern customer experience. By following these measures, they are able to comply with regulations, optimize their trading and answer their customers’ needs. In today’s competitive digital world, these changes are essential for ensuring their relevance and efficiency.