How to implement a robust caching strategy for a microservices architecture?
We're building a microservices platform and need to implement caching across multiple services. Looking for best practices and common pitfalls to avoid. Architecture: 5 microservices (user, product, order, payment, notification) Redis as primary cache Need cache invalidation strategies Must handle cache warming and cold starts What patterns have worked well for you in production?
What are the best algorithms for sorting large datasets in production?
I'm working on a data processing pipeline that handles millions of records daily. Currently using quicksort, but I'm wondering if there are better alternatives for production environments. Current Setup: Dataset size: 2-5 million records Memory constraints: 8GB available Performance requirement: Data type: Mixed (strings, numbers, dates) I've considered merge sort for stability, but the memory overhead concerns me. Any production experience with this?