Python has staked its claim as the most popular programming language among developers worldwide. Accessible via Windows, Linux, and Mac, it’s intuitive and easy to read, and its use of maths lends itself perfectly to Python for finance and data analysis.

There is a common painful workflow with many observability solutions. Each data type is separated into its own user interface, creating a disjointed workflow that increases cognitive load and slows down Mean Time to Diagnose (MTTD). At Coralogix, we aim to give our customers the maximum possible insights for the minimum possible effort. We’ve expanded our APM features (see documentation) to provide deep, contextual insights into applications – but we’ve done something different.

AWS recently introduced a new Lambda Telemetry API giving users the ability to collect logs, metrics, and traces for analysis in AWS services like Cloudwatch or a third-party observability platform like Coralogix. It allows for a simplified and holistic collection of observability data by providing Lambda extensions access to additional events and information related to the Lambda platform.

Distributed tracing is the ability to follow a request through a software system from beginning to end. While that may sound trivial, a single request can easily spawn multiple child requests to different microservices with modern distributed architectures. These, in turn, trigger further sub-requests, resulting in a complex web of transactions to service a single originating request.

The world of computer games is vast, ranging from single-player agility games and logic puzzles with simple 2D animations to the stunning graphics in 3D rendered massive multiplayer online role-playing games like the Lost Ark. Wanting to design and build your own games is a common motivator for learning to code while building a portfolio of work is an essential step for breaking into the gaming industry.