#distributed-systems

#distributed-systems

Data deletion in distributed systems presents challenges that extend far beyond simple database operations. Engineers face a fundamental dilemma: the fear of accidentally destroying critical information keeps teams cautious, yet failing to delete data can expose them to legal risks under regulations like GDPR, increase storage costs, and erode customer trust. "Deletion can't be an afterthought," the presenters emphasized. A major driver of Netflix's platform is managing testing data generated by frequent end-to-end production tests.

Airbnb has developed Impulse, an internal load testing framework designed to improve the reliability and performance of its microservices. The tool enables distributed, large-scale testing and allows engineering teams to run self-service, context-aware load tests integrated with CI pipelines. By simulating production-like traffic and interactions, Impulse helps engineers identify bottlenecks and errors before changes reach production. According to the Airbnb engineering team, Impulse is already in use in several customer support backend services and is under review for broader adoption.

In modern, distributed systems, that work is harder than ever. Services depend on other services, deployments happen constantly, and small failures ripple into larger ones. While teams scramble to piece things together, customers are already feeling the impact, and the business is losing money by the minute. For years, the industry used $5,600 per minute as the average cost of an outage as was suggested by Gartner in 2014.

I'm going to be talking about something very basic, which is almost like the fundamental ideas that I think that every developer should know if they're unfortunate enough to have to work on a distributed system, which is probably most of you. The reason I've written this talk is because I'm working on a book, which is designed as like, you've been dropped onto a project where somebody ill-advisedly made the choice to use microservices, which is always a terrible idea.

Pinterest engineers successfully debugged a rare failure during their move to Kubernetes, emphasizing the challenges of cloud-native migrations and the need for effective debugging.

At the heart of .NET Aspire is its dashboard, which gives you many of the necessary observability and management tools for your code. You can launch and debug applications, and at the same time watch their performance and behavior along with external resources running in containers.

Memory leaks are silent killers in distributed systems, gradually consuming memory until performance degrades significantly and services crash.

Agentic AI has become a priority with enterprises everywhere as a new model that can potentially replace enterprise software as we understand it today. With today's announcement, we're making it easy for customers to build their distributed systems, including agentic AI systems, without having to commit to the Akka Platform.

LittleHorse is an open-source platform for orchestrating distributed systems, effectively tackling state management and microservice coordination challenges for developers.