Architectural Invariant Design: eBPF TC In-Kernel Pod Drainage Rerouting Invariant
eBPF TC In-Kernel Pod Drainage Rerouting Invariant defines an industrial-grade behavioral standard for devops engineering. Enforces deterministic in-kernel TCP packet rerouting using eBPF Traffic Control (TC) ingress/egress programs during Kubernetes pod terminations and rolling node drains. Eliminates race conditions between endpoint deregistration and conntrack teardown by rewriting L3/L4 headers and socket metadata before packets hit network namespace boundaries. Modern software architectures require strict adherence to deterministic patterns to guarantee high availability, maintainability, and zero security vulnerabilities.
Hazard Analysis: What Breaks Without This Rule
The following failure modes have been cataloged from hundreds of hours of production code reviews where AI assistants produced non-compliant implementations:
| Failure Mode | AI Symptom (The Anti-Pattern) | Severity | Production Impact & Remedy |
|---|---|---|---|
| AI Hallucination & Deprecation Drift | Relying on Userspace Iptables/IPVS Sync Latency During Pod Eviction Causing RST Injections and Dropped In-Flight Packets | Critical | Violating this industrial standard introduces regression bugs, security risks, and unexpected runtime failures in production. Enforce explicit behavioral system directives across all AI coding assistants in your repository. |
| Silent Architecture Inconsistency | AI assistants produce mixed paradigms across files, creating fragmented codebase conventions. | Medium | Increases cognitive load during code reviews and leads to maintenance debt across engineering teams. Pin project conventions in .cursor/rules, CLAUDE.md, and AGENTS.md so all team agents follow identical guardrails. |
Step-by-Step Production Directives
Each rule constraint below is injected into the AI agent's system prompt to establish deterministic boundaries:
Engineers MUST ALWAYS attach eBPF programs to the Traffic Control (`clsact` / `SCHED_CLS`) hook rather than standard XDP when TCP connection state tracking and L4 checksum recalculation across veth pairs are required.
Engineers MUST ALWAYS attach eBPF programs to the Traffic Control (`clsact` / `SCHED_CLS`) hook rather than standard XDP when TCP connection state tracking and L4 checksum recalculation across veth pairs are required.
Engineers MUST NOT rely on userspace kube-proxy or endpointslices controllers to handle in-flight connections during node drainage, as the propagation latency (100ms - 2s) directly causes packet drops.
Engineers MUST NOT rely on userspace kube-proxy or endpointslices controllers to handle in-flight connections during node drainage, as the propagation latency (100ms - 2s) directly causes packet drops.
Code MUST update eBPF BPF_MAP_TYPE_HASH connection tracking tables atomically using BPF_EXIST flags before signaling SIGTERM to terminating containers.
Code MUST update eBPF BPF_MAP_TYPE_HASH connection tracking tables atomically using BPF_EXIST flags before signaling SIGTERM to terminating containers.
Services MUST inspect `BPF_F_INGRESS` and recalculate IP and TCP checksums incrementally via `bpf_l4_csum_replace` and `bpf_l3_csum_replace` when mutating destination IP and MAC addresses in packet headers.
Services MUST inspect `BPF_F_INGRESS` and recalculate IP and TCP checksums incrementally via `bpf_l4_csum_replace` and `bpf_l3_csum_replace` when mutating destination IP and MAC addresses in packet headers.
Components NEVER issue a direct `TC_ACT_SHOT` on packets belonging to established flows (`TCP_ESTABLISHED`) mapped to a draining endpoint
Components NEVER issue a direct `TC_ACT_SHOT` on packets belonging to established flows (`TCP_ESTABLISHED`) mapped to a draining endpoint; they must route to alternative healthy pod endpoints in the fallback array or gracefully forward with updated conntrack markers.
Frequently Asked Technical Questions
Common questions developers face when configuring AI coding assistants for this stack:
Q:Why is eBPF TC In-Kernel Pod Drainage Rerouting Invariant critical for AI coding assistants?
Enforces deterministic in-kernel TCP packet rerouting using eBPF Traffic Control (TC) ingress/egress programs during Kubernetes pod terminations and rolling node drains. Eliminates race conditions between endpoint deregistration and conntrack teardown by rewriting L3/L4 headers and socket metadata before packets hit network namespace boundaries. Without explicit behavioral boundaries, AI coding assistants (Cursor, Claude Code, Windsurf, Codex) rely on training data averages, which frequently produce deprecated, inefficient, or vulnerable code patterns.
Q:How does adopting this rule prevent AI hallucinations?
This rule explicitly declares what the AI must avoid (Relying on Userspace Iptables/IPVS Sync Latency During Pod Eviction Causing RST Injections and Dropped In-Flight Packets) and prescribes verified positive examples. Grounding the LLM with negative and positive pairs eliminates guesswork.
Q:Which AI coding environments are supported?
This specification is multi-platform compatible: Cursor (.cursor/rules/*.mdc & .cursorrules), Anthropic Claude Code (CLAUDE.md), Windsurf (.windsurfrules), Codex / Cline (AGENTS.md), and GitHub Copilot (.github/copilot-instructions.md).
Q:Can I combine this rule with other technology stacks?
Yes. Use the Interactive Stack Builder or download an Agent Pack to merge this rule with other frontend, backend, database, security, and DevOps rules without syntax collision.