Redpanda is a modern, distributed platform designed for streaming data with a focus on maintaining data integrity and availability even under high-throughput conditions. The deployment choices for a Redpanda cluster significantly impact both performance and availability, particularly in business-critical environments where failures must be anticipated and mitigated. The text explores several deployment patterns for high availability (HA) and disaster recovery, such as clustered, multi-availability-zone, multi-region, and multi-cluster deployments, each offering different trade-offs between latency, resilience, and complexity. Key considerations include understanding failure scenarios, replica synchronization, rack awareness, partition leadership, producer acknowledgment, and partition rebalancing, all of which contribute to maintaining system availability. Additionally, the document emphasizes the importance of using remote storage over local storage in containerized environments and having a robust disaster recovery plan, supported by Redpanda's tiered storage architecture for data backup and recovery. The article is the first in a series on HA deployments, promising further exploration of these topics in future posts, while encouraging engagement with the Redpanda Community for further discussion and insights.