Here are five troubleshooting situations that can occur with Amazon Redshift:

1. Slow query performance: This can happen due to inefficient query design, lack of proper indexing, or insufficient resources allocated to the cluster. To troubleshoot, you can use the Redshift query optimizer, analyze query execution plans, and consider adding appropriate indexes or increasing cluster resources.

2. Disk space issues: If your Redshift cluster runs out of disk space, it can lead to query failures and performance degradation. To resolve this, you can consider resizing the cluster, deleting unused tables or data, or enabling automatic vacuum and analyze operations to reclaim space.

3. Connection problems: Users may experience issues connecting to the Redshift cluster due to network connectivity problems, incorrect security group configurations, or invalid user credentials. Troubleshooting steps include verifying network settings, checking security group rules, and ensuring that user credentials are correct.

4. Data load failures: When loading data into Redshift, you may encounter errors due to data incompatibility, incorrect file formats, or issues with the data itself. To troubleshoot, review the load error logs, ensure that the data is in a supported format, and validate the data integrity before attempting to load it again.

5. Concurrency and queuing issues: If there are too many concurrent queries or long-running queries, it can lead to high queue wait times and poor performance. To mitigate this, you can use Redshift workload management (WLM) to prioritize and allocate resources to different query queues based on their importance and adjust the concurrency settings accordingly.

Remember to regularly monitor Redshift metrics, enable logging, and use Amazon Redshift Advisor for automated recommendations on optimizing your cluster's performance and troubleshooting issues.