Systems | Development | Analytics | API | Testing

Memory leaks happen when a program fails to release memory it no longer needs, and can be a big issue for developers and system administrators alike, as the gradual depletion of available memory often makes for complex troubleshooting and debugging. Given how the consequences of a memory leak can range from decreased system performance to outright crashes, it’s crucial to isolate the root cause of the leak quickly and efficiently.

Testing without any direction is the same as navigating without a map. It is disorganized, full of errors, weak outcomes, and fraught with risks. This is where test strategy comes into play, for the clarity of the pathway, robust structure of tests, and alignment of the project’s goals. Have a read about how test planning could prove to be a game changer for your organizations.

AI has come as a game-changer in plenty of industries, with OpenAI’s GPT series setting the pace in natural language processing and decision-making abilities. The latest edition, GPT-4, promises even more powerful features, like enhanced accuracy, enlarged context window, and improved performance for grape tasks. However, before the adoption of this avant-garde technology, it is necessary to understand how much GPT-4 costs.

Static sentiment analysis is a groundbreaking theoretical approach that could reshape the software development process. Here we explain what is static sentiment analysis and how it has the potential to understand developer intent. Read along or jump ahead to the section that interests you most.

The API Waterfall is a sequentially and methodically defined approach for managing data flows and integration of services in software development. Aligned to the traditional waterfall methodology, the architectural model essentially targets a step-wise flow of events where each stage depends on the completion of the previous step.

In k8s world every resource created via controller. Like there are inbuilt controllers for pods, deployments , replica set etc. So basically, Controllers are nothing but a control loop that continuously monitor the state of the cluster and take actions to bring the cluster into the desired state. The resources have a spec that provides the desired state. The controller checks the current states.

Observability refers to understanding a system’s internal state by examining its external outputs, like logs, metrics, and traces. Borrowed from control theory, it’s the ability to infer what’s happening inside a system without direct access. To visualize observability, consider the human body. We don’t need to open it up to understand its internal state. By measuring external signals like body temperature, heart rate, or blood pressure, we can infer what’s happening inside.