博科SAN网络管理最佳实践全览

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博科SAN网络最佳实践指南-原厂版是博科公司为数据中心管理员精心编撰的一份高级指导手册，主要关注于如何有效地配置、监控和管理Brocade光纤通道存储区域网络（SAN）基础设施。这份21页的文档旨在解决数据中心管理员在SAN管理中的挑战，提供实用的策略和建议，确保高效、稳定和安全的网络环境。 **主要内容概述：** 1. **介绍**：给出了指南的目的和背景，帮助读者了解为何遵循这些最佳实践对于数据中心运营至关重要。 2. **受众和范围**：明确了目标读者——经验丰富的数据中心管理员，以及指南覆盖的具体内容，如Brocade工具集的使用。 3. **Brocade工具集**：强调了博科提供的工具在SAN管理中的核心角色，包括用于主动配置和维护的工具。 4. **企业数据中心的演变**：简述了数据中心发展历史，以便理解当前SAN网络环境的需求和变迁。 5. **SAN管理员的困境与解决方案**：分析了管理员可能面临的常见问题，如性能瓶颈、配置复杂性等，并提出相应的解决策略。 6. ** Fabric Configuration**：详细解释了全局参数设置的重要性，针对Condor 28 Gbps平台的特殊考虑，以及如何避免或识别潜在的性能瓶颈。 7. **Bottleneck Detection and Edge Hold Time**：讲解如何通过监测边缘节点的延迟和保持时间来诊断网络瓶颈，提高性能优化效率。 8. **Debug LogLevel Settings**：推荐正确的日志级别设置，以优化故障诊断和性能跟踪。 9. **Brocade Fabric Watch**：介绍了博科的实时监控工具，有助于实时监控和预警网络异常情况。 10. **Zoning**：阐述了 zoning 的基本原则和高级考虑，包括最佳的 zoning 推荐，确保数据隔离和安全性。 11. **Advanced Zoning Considerations**：深入探讨了针对特定场景和需求的 zoning 深度配置技巧。 12. **Firmware Management**：强调了定期更新 firmware 对于维持网络性能和安全的重要性，以及推荐的升级策略。 13. **Routing Policies**：区分了基于端口的路由、基于交换机的路由和动态负载共享策略，确保流量优化。 14. **Lossless Dynamic Load Sharing & In-Order Delivery (IOD)**：讲解如何利用先进的负载均衡技术来提升服务质量，确保数据一致性。 15. **Fabric Diagnostics**：提供了诊断工具和技术，帮助管理员快速定位和修复设备性能问题。 16. **Device Latency & Faulty Media**：讨论了如何通过诊断设备延迟和检测故障介质来维护网络健康。 17. **Data Collection for Support**：指导如何收集和整理支持所需的网络数据，便于快速解决问题。 18. **附录A**：可能包含详细的示例、脚本和参考资料，为深入学习和实施提供补充内容。博科SAN网络最佳实践指南-原厂版是一份实用的参考文档，涵盖了数据中心SAN管理员在日常管理和优化过程中所需的关键知识和技能，旨在帮助管理员建立和维护高效、稳定的Brocade SAN网络环境。

SAN Administration BEST PRACTICES

Brocade SAN Administration Best Practices – Support Perspective 5 of 21

The result of all this change is the appearance of increasing issues with application performance that seem to be

associated with storage performance in some way but that cannot be sufficiently identified so that corrective action

can be taken.

SAN ADMINISTRATOR DILEMMA

When application performance problems become obvious, the SAN complex is frequently blamed. SAN

administrators usually have no metrics that might point to some other component in the infrastructure.

Frequently, the result is very long delays before the culprit or culprits are identified and measures are taken to

address the problem. The impact of such outages range from an inconvenience to a massive outage, where mission-

critical application availability is compromised and the enterprise is seriously affected. The experience is never a

positive one.

Brocade recognized the need for improved monitoring and problem determination aids and started a series of

initiatives to address the problem of relevant performance and problem determination metrics in the fabric.

Bottleneck detection is one of the first deliverables of this work. Bottleneck detection is designed to positively

identify bottlenecks in the fabric.

Two types of bottlenecks are detected:

• Bandwidth-based bottlenecks are determined by high link utilization. These are called congestion

bottlenecks. Congestion bottlenecks are relatively easy to detect and, in effect, can be detected by

other Brocade products such as Brocade Fabric Watch. Bottleneck detection provides an alternative

mechanism and more information about the congestion.

• Device latency-based bottlenecks, called latency bottlenecks are much more difficult to detect. This is

the primary focus of bottleneck detection, and the focus of much of the remainder of this section.

Latency detection is frame-based and identifies buffer credit problems. One of the major strength of Fibre Channel is

that it creates lossless connections by implementing a flow control scheme based on buffer credits. The

disadvantage of such an approach is that the number of available buffers is limited and may eventually be totally

consumed.

The temporary unavailability of buffer credits creates a temporary bottleneck. The longer the credits are unavailable,

the more serious the bottleneck. Whereas temporary credit unavailability is expected in normal Fibre Channel

operation, the longer durations are of most concern.

Long periods without buffer credits are typically manifested as performance problems and are usually the result of

device latencies. Exceptional situations cause fabric back pressure that can extend all the way across the fabric and

back. Excessive back pressure can create serious problems in an operational SAN.

Chronic back pressure can exacerbate the effect of hardware failures and misbehaving devices and can also

contribute to serious operational issues, as the existence of existing bottlenecks increases the probability of a

failure.

There are several common sources of high latencies:

• Storage ports (targets) often produce latencies that can slow down applications, because they do not

deliver data at the rate expected by the host platform. Even well-architected storage array performance

can deteriorate over time. For example, LUN provisioning policies such as allocating too many LUNs

behind a given port can contribute to poor performance of the storage, if the control processor in the

array cannot deliver data from all the LUNs quickly enough to satisfy read requests. The overhead of

dealing with a very large number of LUNs may cause slow delivery.

• Hosts (initiators) may also produce significant latencies by requesting more data than they are capable

of processing in a timely manner.

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