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Prerequisites and resources

Technical prerequisites:

  • Kubernetes: v1.24+ (recommended 1.26–1.30)
  • Cluster access: kubectl configured with a valid context
  • Helm 3.x
  • Container registry (if you build/push your own image)
  • HDFS reachable from Kubernetes worker nodes (open NameNode/DataNode ports)

HDFS prerequisites:

  • HDFS URL (e.g., hdfs://namenode:8020)
  • Dedicated HDFS service user (e.g., hdfs_csi) with appropriate ACL/permissions on target paths
  • Quota/ACL policy aligned with your isolation requirements
  • Kerberos environment if your HDFS is secured: a service principal and a keytab are required for this CSI driver

Minimum resources per driver pod:

  • CPU: 100m–250m (controller), 50m–200m (node)
  • Memory: 128Mi–512Mi depending on load/logging
  • Ephemeral storage: 100Mi+ (logs, sidecars)

Network requirements and bandwidth recommendations:

  • Stable, low-latency connectivity between K8s nodes and NameNode/DataNodes
  • DNS resolution for NameNode(s)
  • Open HDFS ports (commonly 8020/9000 for NameNode RPC; DataNode ports often 50010/50075/50475, depending on your distro)
  • Throughput: at least 1 Gbps end-to-end for general-purpose workloads; 10 Gbps or higher recommended for data-intensive jobs
  • Follow Hadoop client best practices: avoid excessive small files, batch I/O when possible, tune io.file.buffer.size, and size client thread pools appropriately for your workload

Storage and functionality notes:

  • The driver exposes HDFS as a filesystem for workloads. It does not provide POSIX guarantees beyond HDFS semantics. Validate app compatibility (append semantics, file-level atomicity, rename patterns).

External components:

  • Required CSI sidecars (deployed with the chart)
  • Optional: centralized logging (ELK/OpenSearch), metrics (Prometheus)

Capabilities and limitations:

  • Snapshots/clones: depend on your HDFS policies; not natively managed by the driver
  • Volume expansion: logically supported via parameters; verify against your HDFS governance and quotas