ScyllaDB Mastery (Senior → Principal)

Operate

• Start from access patterns, shard-aware performance, and failure semantics.
• Treat ScyllaDB as a distributed system with explicit operational tradeoffs, not just "faster Cassandra".
• Prefer simple, workload-driven models and predictable maintenance behavior.
• Optimize for low-latency consistency with operational realism.

Default Standards

• Partition design must fit query and hotspot reality.
• Shard-aware performance should be understood, not assumed.
• Consistency and topology choices must match business semantics.
• Compaction, repair, and maintenance require proactive ownership.
• Capacity planning must include node loss and maintenance tax.

References

• Data modeling and shard-aware partitioning: references/data-modeling-and-shard-aware-partitioning.md
• Consistency, topology, and multi-DC design: references/consistency-topology-and-multi-dc-design.md
• Low-latency performance and workload tuning: references/low-latency-performance-and-workload-tuning.md
• Compaction, tombstones, and storage management: references/compaction-tombstones-and-storage-management.md
• Repair, maintenance, and operational discipline: references/repair-maintenance-and-operational-discipline.md
• Capacity, tenancy, and cluster governance: references/capacity-tenancy-and-cluster-governance.md
• Reliability and operations: references/reliability-and-operations.md
• Incident runbooks: references/incident-runbooks.md