Question: Can you recommend a system that makes it easy to build scalable distributed systems and handle errors and state propagation?

If you need a system that makes it easy to build distributed systems that scale and that handle error and state propagation, Temporal is a great choice. It's an open-source durable execution platform that guarantees your applications and services complete even when there are failures. Temporal supports durable execution, event-driven architecture, SAGA and distributed transactions, state machines, batch processing, and scheduled jobs, and it's written in multiple programming languages. It also offers a fully managed serverless option called Temporal Cloud, which is available in 11+ regions and costs $25 for 1,000,000 actions.

Another interesting platform is Honeycomb, an observability platform that lets teams quickly identify the source of problems in distributed services. It offers distributed tracing, smart data sampling, debuggable Service Level Objectives (SLOs), and integration with Slack for better triage. Honeycomb's pricing is based on event volume, so it's economical for teams of any size.

For AI workloads, Anyscale is a strong platform for building, deploying and scaling AI workloads. It includes workload scheduling, cloud flexibility, smart instance management and heterogeneous node control, all built on the open-source Ray framework. Anyscale also offers cost savings on spot instances and integrates well with popular IDEs and Git.

Last, SingleStore is a real-time data platform for intelligent applications that need high-throughput streaming data ingestion and millisecond query performance. It combines transactional and analytical data in a single engine with support for multiple data models, which makes it a good fit for generative AI and real-time analytics. Pricing is based on usage with a free tier and competitive enterprise plans.