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| Product Overview |
|---|
The IBM Quad-Ports 16Gbps Fibre Channel PCI Express Network Adapter offers four high-speed Fibre Channel connections designed for Flex System environments. It fits into servers needing reliable and fast SAN connectivity, making it a practical choice for data centers aiming to optimize storage networking and support demanding workloads. |
| General Information | |
|---|---|
| Brand | IBM |
| Part Number | 00Y5637 |
| Technical Information | |
|---|---|
| Protocol | Fibre Channel (FC) |
| Data Rate | 16Gbps |
| Port Count | 4-Port (Quad) |
| Bus Interface | PCIe 3.0 x8 |
| Generation | Gen 5 |
| Connector Type | SFP+ (LC) |
| Network Topology | Point-to-Point, Switched Fabric (N-Port) |
| Advanced Features & Compatibility | |
|---|---|
| Management Features | NPIV Support, Boot from SAN, Selective LUN Masking, Full Fabric Support, Diagnostics (D_Port) |
| OS Compatibility | Windows Server 2019, Windows Server 2022, VMware ESXi 7.x, VMware ESXi 8.x, RHEL 8, RHEL 9, SLES 15, Solaris, AIX |
| Physical Characteristics | |
|---|---|
| Weight | 3.00 |
| Condition | Refurbished |
| Miscellaneous | |
|---|---|
| Compliance Standards | WEEE, RoHS, CE, FCC, UL, TUV, cULus |
| Product Description |
|---|
This IBM Quad-Ports 16Gbps Fibre Channel Network Adapter is built for robust storage networking, delivering four high-speed 16Gbps ports. It is commonly used in enterprise data centers to connect Flex System servers directly to SANs, enabling efficient storage management and data transfer. Often found in environments that demand reliable and fast storage connectivity, this adapter benefits IT professionals managing virtualized infrastructure or large-scale storage setups. Its design supports streamlined integration and improved throughput for storage-intensive applications. Key Features
This adapter is typically deployed in enterprise SAN environments, where high availability and performance are critical. It plays a key role in maintaining fast access to storage resources, helping organizations manage large data workloads with fewer bottlenecks and increased reliability. |