Root cause of DNS deadlock (2026-03-18, 2026-04-12): node-bootstrap
DaemonSet overwrote /etc/resolv.conf with ONLY nameserver 10.32.0.10
(cluster DNS). When nodes rebuild, CoreDNS can't pull its image because
containerd resolves via 10.32.0.10 which requires CoreDNS to be running.
Fix: resolv.conf now has DUAL nameservers:
nameserver 10.32.0.10 # primary: cluster DNS
nameserver 169.254.169.254 # fallback: Scaleway metadata DNS
Containerd tries kube-dns first (fast, resolves .svc.cluster.local),
falls back to VPC resolver when kube-dns is unreachable. Breaks the
chicken-and-egg permanently.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Root cause: weight tensors packed sequentially in the flat params buffer
had non-aligned start offsets when preceding tensors had odd element counts
(e.g. bias of 51 atoms = 204 bytes, 204 % 16 = 12). cublasLtMatmul with
CUBLAS_COMPUTE_32F_FAST_TF32 requires 16-byte aligned buffer pointers.
Fix: pad each tensor to 4-element boundary (16 bytes) in both
f32_weight_ptrs_from_base (pointer computation) and compute_total_params
(buffer allocation). Added align4() and padded_byte_offset() helpers,
fixed shrink_perturb skip range and bottleneck gradient offset.
Switched compute type: CUBLAS_COMPUTE_32F → CUBLAS_COMPUTE_32F_FAST_TF32
(forward + backward). Explicit TF32 tensor core path, required by cuBLAS
13.0 on H100 SM90.
Deleted dead bf16_weight_ptrs function.
19/19 smoke tests pass on RTX 3050.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Argo requires task output parameters to flow through DAG arguments →
template inputs, not direct {{tasks.X.outputs}} in container args.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- iqn_lambda restored to 0.25 (was 0.0 for NaN isolation)
- STEP_DIAG per-step logging removed (was temporary)
- FOXHUNT_GRAD_DIAG env var removed from Argo template
IQN NaN root cause fixed in 8cbabcef5 (f32-as-bf16 type mismatch).
Ready for H100 baseline deployment.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Temporary diagnostic: logs per-stage gradient norms (pre-clip, post-clip,
post-IQN, final) to identify where H100 gradient collapse occurs.
Remove after root cause is found.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Per-mount readOnly: true is still set on hyperopt/train/evaluate steps.
Only the precompute step gets write access to generate fxcache.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
PVC is ReadWriteOnce — can't mount on compile node (different pool).
Precompute step now:
- runs on GPU node (same as training, shares PVC mount)
- depends on fetch-binary (gets binary from GitLab to /workspace/)
- copies binary to /data/bin/ on PVC for future use
- skips if cache already exists (data unchanged)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- precompute_features early-exits if {cache_key}.fxcache already exists
(cache key = SHA256 of filenames + sizes, only changes when data changes)
- compile-and-train copies binaries to PVC /data/bin/ after compile
- precompute step added to compile-and-train DAG (runs after compile,
before training, parallel with GPU warmup)
- precompute template reads binary from PVC (no GitLab download)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Was relying on stale binary at /data/bin/precompute_features on PVC.
Now downloads latest from GitLab Package Registry (uploaded by
compile-and-train). Falls back to PVC binary if download fails.
Also added precompute_features to compile-and-train examples list.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
cuda-nvcc-12-4 + cuda-cudart-dev-12-4 (~400MB) added to the CPU builder.
Reverts compile-and-deploy back to ci-builder-cpu (was briefly switched
to full ci-builder which is 6GB+ and unnecessary).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
cudarc build.rs requires nvcc to precompile CUDA kernels to .cubin files.
The ci-builder-cpu image doesn't have the CUDA toolkit installed.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Previously appended /${SYMBOL} to data-dir AND passed --symbol, causing
double nesting. Now data-dir stays as-is and --symbol handles filtering
via collect_dbn_files_filtered.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Rust tracing with JSON subscriber in a container without TTY uses
fully-buffered stdout — logs only flush on buffer full or process exit.
This made H100 training appear stuck for 28+ minutes with no output.
stdbuf -oL forces line buffering so epoch logs appear immediately.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Epoch duration self-balances: bigger GPU → bigger auto-scaled batch →
fewer steps per epoch. The manual cap created 7 different values
(0, 8, 64, 100, 200, 300, 2000) across configs/tests/examples, making
behavior inconsistent between environments.
Removed from: DQNHyperparameters, training profiles (smoketest,
localdev, production), CLI args, Argo templates, hyperopt adapter,
all test overrides, supervised example.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
precompute passes data-dir/SYMBOL to match how train_baseline_rl
calls load_all_bars(data_dir, symbol). compile-and-train gets
FOXHUNT_FEATURE_CACHE_DIR env var and --epochs fix.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Reuses compile-training, gpu-warmup, fetch-binary templates from
compile-and-train. Own train step runs train_baseline_rl directly
with --epochs, FOXHUNT_FEATURE_CACHE_DIR, and fxcache validation.
No hyperopt — pure baseline with default params.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- DAG: compile (ci-compile-cpu) + gpu-warmup → train (H100)
- Compiles from source targeting compute cap 90
- fxcache REQUIRED — fails if no .fxcache found
- Error chains printed with {:#} for full cause visibility
- Uses cargo-target-pvc for compile cache + sccache
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Dedicated workflow for baseline RL training without hyperopt.
Runs train_baseline_rl binary on GPU node with fxcache.
Fetches pre-compiled binary from MinIO, falls back to PVC.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
All pods with app.kubernetes.io/part-of=foxhunt get base infra
access. Fixes MinIO log archival timeout for precompute-features
and databento-download workflows. Component-specific policies
still add extra rules (GitLab SSH, external HTTPS, etc.).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Previous 32Gi OOM'd with 148GB of MBP-10 data (61M snapshots ≈ 15GB
in memory + trades + OHLCV). ci-compile-cpu node has 64GB.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Adds feature-cache-dir parameter (default: /data/feature-cache) so
the training binary can load pre-computed .fxcache files.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
All downloads now use the Rust download_baseline binary via the
Argo WorkflowTemplate (databento-download).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
500m/512Mi request fits alongside existing platform workloads.
Download is I/O-bound, not CPU-bound.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Remove runAsUser:1000 so apt-get install ca-certificates works.
Fix double-nested ES.FUT path (output-dir is the schema root, not ES.FUT subdir).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
