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.

The gaming industry is an extensive software market segment, reaching over $225 billion US in 2022. This staggering number represents gaming software sales to users with high expectations of game releases. User acquisition takes up a large part of software budgets, with $14.5 billion US spending globally in 2021. User retention is critical to the success of any game, especially where monetization requires driving in-app purchases and ad revenue.

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.