Question: I need a solution that can guarantee safe and consistent state across distributed services, can you suggest something?

If you're looking for a way to ensure safe and consistent state across distributed services, Temporal could be the answer. It's an open-source durable execution platform that can ensure applications and services complete their work even when something goes wrong. Temporal supports several programming languages and offers durable execution, event-driven architecture, SAGA and distributed transactions, state machines, batch processing and scheduled jobs. It also offers a cost-effective serverless option with Temporal Cloud, which runs in 11+ regions and can be deployed in a variety of ways.

Another top contender is Honeycomb, an observability platform that helps teams quickly pinpoint the source of problems in distributed services. With features like distributed tracing, smart data sampling, and debuggable Service Level Objectives, Honeycomb lets you capture and analyze logs and metrics data so you can deploy with confidence and resolve incidents fast. The platform integrates with Slack and supports OpenTelemetry, so it's adaptable and scalable for large teams without incurring more costs.

For secure and efficient secrets management, check out Akeyless. This cloud-native SaaS platform uses Distributed Fragments Cryptography (DFC) to create encryption keys as distributed fragments in the cloud. Akeyless features automated credential rotation, just-in-time credentials and secure remote access. It integrates with many tools and platforms, so it's a good option for ensuring secure access to critical applications and services.

Also worth a look is Edge Delta, which offers automated observability, monitoring services and guidance on root-cause analysis through AI-driven data analysis. With flexible pipelines for data ingest and AI/ML anomaly detection, Edge Delta lets teams monitor and troubleshoot complex systems. Its distributed architecture and scalable log data querying abilities make it useful for petabyte-scale data management and monitoring.