First things first, check if services are properly registered in your service registry or load balancer, and ensure network policies are not blocking connections. Review configuration settings like timeouts, retries, and circuit breakers to make sure they are consistent across services. If you are using Kubernetes, confirm that service names, DNS settings, and namespaces align—small mismatches here can easily cause issues. Also, see if resource limits (CPU, memory) might be throttling responses under high load. Finally, monitor logs and metrics for patterns or spikes that could reveal deeper issues.

To troubleshoot microservice communication issues, verify service connectivity, check logs for errors, and monitor latency. Examine API requests and responses for mismatches, ensure consistent configurations, and confirm dependencies are operational. Use distributed tracing tools to map the request flow, identifying where breakdowns or delays happen.

- Confirm that communication between microservices is done via service, not through ingress (assuming you are using K8s); - Favor messaging; use a reactive approach; - Confirm that the parameters determining pod scaling are fine-tuned; - Finally, have centralized logs with correlation IDs for deeper analysis.

I'll keep it simple since a lot of people got very specific. First, check any logs, and if you cannot find a good log, make sure logging is enabled on each service. Check the permissions, often that will cause issues that will not log descriptively, and can easily be overlooked. Then, you will want to check load balancers, security groups, subnets, or vpcs to make sure the services are able to see each other. Additionally, make sure any runtime variables are pulling in properly with expected values, especially any credentials or secrets which may be needed.