Systems | Development | Analytics | API | Testing

In partnership with Tumult Labs, BigQuery differential privacy can help to anonymize data, and will integrate with BigQuery data clean rooms.

As an application development leader, you’ll want to continuously improve your team's processes and outcomes. The cloud marketplace has become a popular way for enterprises to buy software, but with the increasing amount of sensitive data being processed, stored, and transmitted in the cloud, security has become a critical concern for both cloud service providers and their customers.

Although the severity of the risks can vary, it’s nevertheless crucial for your development process to reduce risk as much as possible.

As fraud continues to grow in prevalence, SecOps teams are increasingly investing in fraud prevention capabilities to protect themselves and their customers. One approach that’s proved reliable is the use of log analytics and telemetry data for fraud prevention. By collecting and analyzing data from various sources, including server logs, network traffic, and user behavior, enterprise SecOps teams can identify patterns and anomalies in real time that may indicate fraudulent activity.

There are many factors to keep in mind when thinking about how to keep systems and applications secure. First and foremost is the actual environment where the application is deployed. The environment consists of the Operating System (OS), libraries included with the OS, and software that runs in the background. In a perfect world, an application would have very few or zero dependencies on the environment, thereby eliminating the need to keep dependencies up to date.

In software development, shift left is a practice that helps developers find vulnerabilities and coding errors earlier in the software development process. Shift-left security is an efficient approach that focuses on security and helps address any security issues in code long before the software is released. Here, we provide an overview of what is shift-left security and offer guidance on how a static analyzer can help you uncover security vulnerabilities early in the SDLC.

Many of us now take our daily digital experiences for granted, whether it’s making a purchase, taking an exercise class, playing a game, or checking our bank accounts. Moreover, the lines between the physical and digital worlds have become increasingly blurred, and few people think twice about using mobile tickets to attend an event or checking a digital watch to track a workout. However, security has not kept pace with the demands of today’s digital ecosystems.

In our previous Countly Digest, we delved into the top concern of product managers and analysts: tracking user behaviour. It is a crucial aspect of product analytics, as it enables companies to understand user behaviour and preferences, leading to better product development and increased revenue. ‍

In the world of Node.js, application development, speed, flexibility, and scalability are critical for modern software development. However, the risk of vulnerabilities and security breaches looms with the increasing reliance on open-source Node packages. NCM (NodeSource Certified Modules) is the next-generation security solution that empowers Node.js developers to safeguard their applications easily and confidently.