Error Containment and Recovery Policies: Debug Playbook

Debug playbook

Debug Playbook for Error Containment and Recovery Policies focuses on Blast radius of injected faults, mean time to recovery, and service availability during RAS events. The purpose is to turn memory observations into mechanism-backed actions with explicit owners and release-safe validation.

PCIe/CXL debug should narrow from broad symptom to one dominant mechanism. Avoid mixed-knob sweeps that produce accidental wins without causal confidence.

1. Freeze workload seed, firmware image, timing profile, and thermal setup.

2. Find first failing transition in command timeline.

3. Classify mechanism: locality loss, legality pressure, queue policy, margin drift, or RAS behavior.

4. Build focused reproducer for top hypothesis.

5. Apply minimal reversible fix and define rollback gate.

6. Re-run full performance + reliability matrix.

Debug decision tree

ROOT CAUSE TREE - Error Containment and Recovery Policies

symptom: Blast radius of injected faults, mean time to recovery, and service availability during RAS events
  |-- LTSSM / PHY margin
  |-- credit / ordering stall
  |-- coherency / HDM config
  |-- RAS / poison handling
  |-- enumeration / resource conflict

Review memo template

PCIe/CXL REVIEW MEMO - Error Handling and RAS / Error Containment and Recovery Policies

1. Symptom
   - Watched metric: Blast radius of injected faults, mean time to recovery, and service availability during RAS events
   - Failing traffic slice: <workload/phase/class>
   - First failing transition: <LTSSM/credit/ordering/coherency/RAS>
   - Revision tags: <firmware/controller/timing/board/package>

2. Mechanism hypothesis
   - Primary mechanism: RAS policies define whether to reset a function, retrain a link, or failover a workload. Containment boundaries span PCIe hierarchy, CXL regions, and VM/device assignment models.
   - Competing hypotheses: <mapping, scheduling, PHY margin, SI/PI, reliability policy>
   - Missing evidence: <command trace, queue snapshot, lane margins, CE/UE logs>

3. Proposed action
   - Smallest reversible change: <policy/register/firmware/flow>
   - Expected movement: <p99 latency, effective bandwidth, stability>
   - Regression risk: fairness, thermal drift, training robustness, field reliability

4. Signoff
   - Re-run artifact: RAS policy matrix, fault injection report, and recovery playbook
   - Required owners: reliability owner, platform architect, firmware owner, SRE owner
   - Final decision: ship, bounded rollout, rollback, or escalate

PCIe/CXL deep dive

RAS closure maps AER, poison, and surprise-down events to bounded containment and recovery actions.

Concept diagram

RAS ESCALATION

detect -> classify -> contain -> recover -> validate

Metric graph

RAS EVENT MIX

correctable trend   ███████
uncorrectable       ██
surprise-down       █

Reports and artifacts

• AER register dump

• poison injection log

• surprise-down timeline

• containment action record

Mini case study

Masked correctable errors accumulated until a surprise-down during peak traffic forced unplanned failover.

Debug branches

• Separate CE trend from UE containment paths

• Validate poison handling end-to-end

• Test surprise-down drain and driver recovery

Senior review question

Ask: which latency, bandwidth, and reliability evidence proves this PCIe/CXL topic is closed under real traffic?

Key takeaways

• Always tie controller and PHY counter shifts to application latency and throughput outcomes.

• Lock firmware timing profile, thermal condition, and DIMM state before comparing PCIe/CXL captures.

Common pitfalls

• Chasing peak bandwidth while ignoring p99 latency and fairness tails.

• Changing timing guardbands without separating SI noise from scheduling issues.

• Declaring closure without reliability gates, fault injection, and regression replay.

Principal PCIe/CXL review addendum

Error Containment and Recovery Policies should be read as an end-to-end memory behavior, not as a single block definition. A production PCIe/CXL subsystem reflects interactions between array physics, command legality, scheduler policy, PHY margin, and reliability controls before software experiences final latency or bandwidth.

RAS policies define whether to reset a function, retrain a link, or failover a workload. Containment boundaries span PCIe hierarchy, CXL regions, and VM/device assignment models. PCIe/CXL inefficiency is multiplicative: one extra ACTIVATE, one unnecessary turnaround, one weak lane margin, or one refresh collision repeated across billions of accesses can dominate product tail latency and power.

Use Blast radius of injected faults, mean time to recovery, and service availability during RAS events as the opening signal, not the conclusion. A metric move only becomes actionable when paired with workload context, command traces, training telemetry, and evidence artifacts such as RAS policy matrix, fault injection report, and recovery playbook.

RAS policies translate PCIe/CXL errors into bounded blast radius and predictable recovery. Senior review quality comes from proving a complete chain: request pattern -> memory-state transition -> bottleneck mechanism -> smallest owner fix -> regression-safe validation.

Review discipline should enforce a single causal chain: traffic pattern -> command-level behavior -> array/PHY effect -> measured product impact. That chain prevents tuning folklore from replacing evidence.