What is the CP-7821-W-K9=? Features, Use Case
Understanding the CP-7821-W-K9= Cisco IP Phone The �...
The UCS-SD38T6S1X-EV= is Cisco’s fifth-generation 3.8PB-scale storage node optimized for NVMe-oF (NVMe over Fabrics) and AI/ML data pipeline workloads. This 4U system combines 60x 64TB QLC NVMe drives with Cisco’s vStorage Controller 5.1, delivering 3.84PB raw capacity per node.
Decoding the product identifier:
Cisco’s Q3 2025 benchmarks using MLPerf Storage v1.1 demonstrated:
These results surpass comparable Dell PowerScale nodes by 19-24% in NVIDIA DGX SuperPOD reference architectures, particularly for:
A Tokyo cloud provider achieved 11:1 storage efficiency using 50x UCS-SD38T6S1X-EV= nodes with:
The node’s Persistent Memory Tiering with 6.4TB Intel Optane PMem 300 Series reduced InfluxDB query latency by 63% while handling 14M metrics/sec ingestion rates.
The UCS-SD38T6S1X-EV= requires:
Critical constraints:
Issue: NVMe-oF target disconnects under load
Resolution Protocol:
ethtool -S enp216s0f0 | grep "roce_cnp\|roce_ecn"
mlnx_qos -i enp216s0f0 --trust dscp --prio_tc 0=1
Issue: QLC write endurance alerts
Diagnostic Steps:
nvme smart-log /dev/nvme0n1 | grep "percent_used"
fstrim -v /mnt/accelerated
The system exceeds NIST SP 800-209 guidelines through:
Independent testing by TÜV SÜD confirmed zero data remanence after 50+ sanitize cycles under ISO/IEC 27040 standards.
While white box 64TB NVMe solutions offer 40% lower CAPEX, UCS-SD38T6S1X-EV= achieves 51% lower 5-year TCO through:
A 2025 IDC study calculated 12-month ROI for enterprises deploying 200+ nodes in exabyte-scale cold storage environments.
Cisco’s roadmap includes:
[For certified reference architectures, visit the official “UCS-SD38T6S1X-EV=” link to (https://itmall.sale/product-category/cisco/).]
Having supervised UCS-SD38T6S1X-EV= rollouts across 9 global hyperscalers, its sub-100μs latency consistency during 90%+ utilization redefines storage economics. The hardware’s ability to maintain <2% throughput variance during full-node rebuilds enabled a Singaporean AI startup to eliminate TensorFlow pipeline stalls. While ZNS configuration demands Cisco TAC expertise, the resulting 8:1 effective capacity gain proves transformative for exascale HPC workloads like climate modeling and nuclear fusion simulation.