You are solving a design failure on a massive Hadoop cluster network that has an application with TCP incast behavior (also known as TCP Throughput collapse) affecting its many-to-one communications…

Question

Options

• AAvailability
• BBandwidth utilization
• CJitter values
• DBuffer utilization

• A
  5% (2)
• B
  8% (3)
• C
  16% (6)
• D
  71% (27)

Explanation

Buffer utilization is the critical metric because TCP incast occurs when dozens or hundreds of servers simultaneously flood a single last-hop switch port, overwhelming its buffer and causing packet drops that trigger TCP retransmissions and throughput collapse - monitoring buffer utilization directly reveals when this saturation is happening and whether your buffer tuning (e.g., increasing buffer size or enabling ECN) is effective.

Availability (A) is wrong because the network remains up during incast - the problem is severe performance degradation, not an outage, so availability metrics won't surface it.

Bandwidth utilization (B) is misleading here: incast paradoxically reduces aggregate throughput even when bandwidth appears underutilized, because TCP backs off after packet loss - high bandwidth utilization is not the cause or the symptom to chase.

Jitter (C) measures variation in packet delay, which is more relevant for real-time applications (VoIP, video) and doesn't pinpoint the buffer overflow root cause of incast collapse.

Memory tip: Think of incast as a "traffic jam at the on-ramp" - many lanes (servers) merging into one lane (switch port). The buffer is the ramp's holding capacity, so buffer utilization is the gauge that tells you whether the ramp is overflowing.

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