The user is asking a follow-up question ("Same, plus:") which implies there was a prior conversation context that I don't have visibility into. The question seems to be about diagnosing a looping/crash-looping service that runs in a distroless container (no shell), and they cannot see stdout. They want to diagnose without process-level inspection — what indirect signals remain, and which is the cheapest? Let me think about this carefully. The scenario appears to be: a Kubernetes container (or similar) running a distroless image, no shell, so you can't `kubectl exec` in and look around. The container/service is looping — presumably crash-looping or a hot loop. You cannot see stdout (logs unavailable — maybe because distroless writes to nowhere, or logs aren't captured, or the process writes to a TTY that isn't attached). And they want to diagnose without process-level inspection (no strace, no exec into the container, no eBPF attaching to the process? Actually "process-level inspection" might mean things like strace/gdb/proc inspection inside the container). So what indirect signals remain? Let me enumerate observable signals from outside the container/process: 1. **Orchestrator events and status:** - Kubernetes pod events: CrashLoopBackOff, restart counts, `kubectl describe pod` events (back-off messages, OOMKilled, failed probes, image errors). - Exit codes: container termination exit codes (e.g., 137 = SIGKILL/OOM, 1 = app error, 126/127 shell issues, 139 segfault). This is a huge signal. `kubectl get pod -o jsonpath='{.status.containerStatuses[0].lastState}'` gives exit code and reason. - Restart counts and the back-off cadence: the timing between restarts (CrashLoopBackOff has exponential backoff 10s, 20s, 40s... capped at 5m). The inter-restart timing pattern tells you crash vs. hang-then-liveness-kill vs. OOM. - Wait — but is this a crash loop or a busy loop? "Looping service" is ambiguous. Could be a hot loop (service alive but looping internally) or a crash loop (restarting). The user says "you cannot see stdout of the looping service" — the mention of stdout suggests they'd normally look at logs to diagnose a crash loop. So it's likely a crash-looping service. But I should address both interpretations briefly or pick the crash-loop one as primary. 2. **Exit codes and termination reasons** — most valuable, nearly free. OOMKilled (137) immediately tells you the story. Error code 1 vs 2 vs specific app exit codes hint at the failing path. `terminationMessagePolicy: FallbackToLogsOnError` — interesting: even in distroless, if the app writes termination message... Actually terminationMessagePath is a file the kubelet reads; distroless apps don't write it, but FallbackToLogsOnError pulls the last 80 lines of logs into the termination message — but they can't see stdout, so this doesn't help. Unless... wait, they can't see stdout. Hmm, why can't they see stdout? In Kubernetes, `kubectl logs` reads from container runtime — that works even for distroless. Maybe the environment is not K8s, or log shipping is broken, or the process writes to a file instead. Or maybe this is a hypothetical/exam-style question. Regardless, treat stdout as unavailable. 3. **Resource metrics:** - CPU usage over time: a crash loop shows sawtooth CPU (spike at startup, drop at death, periodic pattern matching restart cadence). A hot loop shows pegged CPU at steady state. A deadlock shows near-zero CPU. - Memory: monotonically increasing until OOM → memory leak; sawtooth → crash cycle with startup allocation. - These come from metrics-server / Prometheus / cAdvisor — host-level cgroup accounting, no process inspection needed. Cheap if you already have Prometheus; otherwise metrics-server gives coarse numbers. 4. **Network signals:** - Readiness/liveness probe failures: the events feed shows probe failures with timing — tells you when the port stopped listening. - Connection behavior from clients: connection refused (nothing listening) vs. accepted-then-hung vs. timeouts. You can test from another pod: `nc`, or even a curl from a debug container in a *different* pod — wait, "no process-level inspection" — probing the network endpoint from elsewhere isn't process-level inspection of the service; it's black-box interaction. That's allowed and very cheap. - TCP handshake behavior: RST (port closed → crashed), SYN accepted but no data (hung), slow responses (resource starvation). - If it's an HTTP service: response codes, latency percentiles from the load balancer / service mesh / client-side metrics. 5xx spikes, latency, connection reset rates. - DNS: if the service registers with service discovery, absence of heartbeats. 5. **Orchestrator-level derived signals:** - Scheduling: `kubectl get events` — ImagePullBackOff would be pre-start; but looping after start implies runtime. Events like "Back-off restarting failed container." - Pod phase transitions timeline: timestamps in events give you the period of the loop without logs. 6. **Host/runtime-level (outside the container, not process-level inside):** - cgroup memory/CPU accounting for the pod's cgroup (readable from the node, still kind of metrics). - Node-level kernel logs: OOM killer messages in `dmesg`/journalctl on the node — "Memory cgroup out of memory: Killed process..." — this is a node-level signal, not process-level inspection inside the container. Very cheap and decisive for OOM. - Container runtime logs/journal: containerd/CRI-O logs record start/stop/exit codes per container. 7. **Sidecar approach / ephemeral debug container sharing the pod's network namespace:** - `kubectl debug -it pod --image=busybox --target=...` or share process namespace. But is that "process-level inspection"? Sharing the network namespace to test connectivity is black-box. Sharing PID namespace to look at /proc would be process-level. The user said "diagnose without process-level inspection" — I interpret that as no strace/gdb/proc-foo on the target process. Network probing from an ephemeral container is borderline but I'd argue it's interaction, not inspection. Worth mentioning with the caveat. 8. **External behavior over time:** - The periodicity: sample the endpoint from a script every second; the gap pattern reveals crash period, backoff growth, etc. 9. **Build/CI-side signals:** - What changed recently — image digests, deploy timeline. Distroless often means the crash is from the app binary: check the app's own structured logs shipped elsewhere (if the app logs to a file mounted to a volume, or to an external sink like a logging sidecar, or sends to a collector). "Cannot see stdout" doesn't preclude app-level telemetry: OpenTelemetry/StatsD/metrics endpoint, APM traces. If the app exposes /metrics on another port, scrape it. - Error tracking (Sentry) if instrumented. 10. **Exit code taxonomy as the single cheapest decisive signal:** - 0: clean exit — likely the loop is the workload finishing and restarting (bad command? config causes graceful exit). - 1: generic app error — missing config/secret often. - 2: misuse of shell builtins (rare in distroless). - 125/126/127: runtime/engine errors, exec format, missing interpreter — common with distroless! E.g., the binary needs glibc but image has none, or missing shared library → exit 127-ish or exec format error. Actually with distroless, a very common crash cause: dynamically linked binary missing libc — that fails at exec time with a specific runtime error, and event messages show "exec: ... no such file or directory" or "exec format error" in pod events. That's a classic distroless diagnostic: the events tell you. - 134: SIGABRT (assert/panic with abort). - 137: SIGKILL — OOM or liveness-kill; distinguish by OOMKilled reason field and by CPU probe cadence. - 139: SIGSEGV — native crash; distroless + segfault → check recently bumped native deps. - 143: SIGTERM — graceful shutdown path; if the loop involves 143, maybe shutdown handling is broken. So which is cheapest? The canonical answer: **exit code + termination reason from the orchestrator/runtime status** (`kubectl get pod -o jsonpath=...lastState.terminated` or `docker inspect` State.ExitCode / `crictl inspect`) — zero cost, no exec, no logs, immediately narrows the space enormously. In K8s specifically: `status.containerStatuses[].lastState.terminated.{exitCode, reason, startedAt, finishedAt}` — and from startedAt/finishedAt you get the loop period for free. Second cheapest and almost as informative: the **kubelet events timeline** (describe pod) which includes back-off messages and probe failures with timestamps. If OOM is suspected: **node dmesg / OOM killer message** is decisive and cheap (node-level, permitted). So the answer structure: - Reframe: with stdout gone and no exec/strace, you fall back to (a) the runtime's own record of the process's death (exit code, reason, timing), (b) aggregate resource signals (CPU/mem over time via cgroups/metrics), (c) black-box network interaction (probe results, TCP behavior), (d) events timeline. - Cheapest: exit code / termination reason + started/finished timestamps from container status — one API call (or docker inspect / crictl inspect), no privileged anything. Give the exact command(s). - Map exit codes to hypotheses quickly. - Explain what the other signals disambiguate (exit code 137 → OOM vs liveness kill → check memory curve and probe events). - Note the loop-period trick: finishedAt - startedAt over successive restarts shows backoff growth vs constant crash period; constant ~N seconds plus success of readiness before death suggests liveness timeout; instant death suggests exec/config error. - Mention cgroup/CPU sawtooth via metrics as the next-cheapest if exit code ambiguous (e.g., 137 both OOM and liveness-kill look identical in exit code; the memory graph separates them). - Black-box network probe from a sibling pod: cheap, tells you listening vs hung. - If truly no orchestrator (bare docker), `docker inspect` / `docker events` give the same. - Maybe mention: kubelet probe failure events timestamps, and terminationMessagePolicy caveat (needs logs, which they lack — so skip). - Keep it reasonably tight. The user is clearly technical, terse style ("Same, plus:") — likely a staff/platform engineer or someone in an interview-ish setting. They want a crisp enumeration + the single cheapest pick. Format: short intro, ranked list of signals with what each tells you, then explicit "cheapest" call with the exact one-liner commands, and a short decision tree from exit codes. Use headers sparingly; a compact list format. Code blocks for commands. Length: medium — enough to cover the taxonomy and the pick, not a treatise. Avoid over-hedging. Let me draft the command set: Kubernetes: ``` kubectl get pod

-o jsonpath='{.status.containerStatuses[0].lastState.terminated}' # or kubectl get pod

-o go-template='{{range .status.containerStatuses}}{{.lastState.terminated.exitCode}} {{.lastState.terminated.reason}} {{.lastState.terminated.startedAt}} -> {{.lastState.terminated.finishedAt}}{{end}}' ``` Also restartCount and `.state.waiting.reason` (CrashLoopBackOff). Events: ``` kubectl describe pod

| sed -n '/Events/,$p' ``` Docker: ``` docker inspect --format '{{.State.ExitCode}} {{.State.Error}} {{.State.OOMKilled}} {{.State.StartedAt}} {{.State.FinishedAt}}' docker events --since ... --filter container= ``` crictl: ``` crictl ps -a; crictl inspect | jq '.status' ``` Node OOM: `journalctl -k | grep -i oom` or dmesg. Exit code table (concise): - 0 — clean exit; the loop is restart policy vs. app finishing: config/env problem causing graceful exit. - 1 — generic error: bad config, missing secret, unhandled exception; often message only in (unavailable) logs, but code narrows to app-level fault. - 126/127 (or runtime "no such file") — exec/interpreter/dynamic-link failure; classic distroless failure: binary linked against glibc in a static image, missing .so, wrong ARCH. Distroless-specific! - 134 — abort(): assertion/panic in Go/Rust with abort, C++ uncaught exception. - 137 — SIGKILL: OOMKilled (reason field says OOMKilled) vs liveness-kill (reason just "Error", memory flat, probe events show failures). Disambiguate with memory curve / events. - 139 — SIGSEGV: native crash. - 143 — SIGTERM: being killed by something external (eviction, liveness via SIGTERM? no—liveness kill is SIGKILL; 143 usually normal termination or manual stop/eviction). If looping on 143: something signals it, maybe the app's shutdown hangs then final SIGKILL follows. Timing pattern analysis: - Dies in <1s consistently → startup/exec/config failure (pairs with 1/127). - Dies after exactly the liveness threshold (~probe initialDelay+failureThreshold×period) → liveness kill, app hung not crashed → CPU near zero, port accepts but no response. - Period grows 10s→20s→40s→…→5m → pure CrashLoopBackOff backoff cadence overlaying whatever crash period; subtract backoff to get true run time. - Memory sawtooth with increasing baseline → leak → OOM at variable period. Signal ranking by cost (all cheap; cheapest = exit code + reason + timestamps): 1. Container exit code/reason/timestamps — one API read. Cheapest and most informative. 2. Events feed (probe failures, back-off, OOM messages) — same API, add timing context. 3. cgroup-level CPU/mem time series (Prometheus/metrics-server) — already-collected metrics; separates OOM vs liveness vs hang. 4. Black-box endpoint probe from elsewhere (TCP/HTTP) — distinguishes dead vs hung vs slow; needs a probing pod. 5. Node kernel log for OOM lines — decisive for OOM when 137; needs node access. 6. (Borderline) ephemeral container sharing netns to probe — only if 4 unavailable. Also worth a nod: if the app has any out-of-band telemetry (OTel, Sentry, metrics port), that's stdout-independent — but you can't count on it in distroless; mention as "if instrumented." One more distroless-specific wrinkle: since there's no shell, exec-format/missing-lib errors are more common and the *event message* (not the exit code) carries the error text: "exec: /app: cannot execute binary file" or standard_init_linux.go: ... "no such file or directory". Those strings appear in pod events / `kubectl describe` and in crictl/docker inspect State.Error. Good to call out. Also, "looping service" — if it's not crash-looping but an internal hot loop (service stays up), then exit codes are moot; the cheapest signal becomes CPU shape (pegged vs idle) + endpoint behavior. I should cover this briefly: one line noting the fork — if restarts are happening, exit-code route; if it stays up and loops, metrics+black-box route. Actually the phrase "you cannot see stdout of the looping service" strongly suggests crash loop (that's when you'd want stdout). I'll lead with crash loop but add a one-line branch for hot loop. Format plan: - Brief framing line: you've lost the richest signal (stdout) and exec; remaining signals are the runtime's bookkeeping + aggregates + black-box I/O. - Numbered list of signals, each with: what it is, what it disambiguates, cost. - "Cheapest" callout with exact commands (K8s + docker one-liners). - Compact exit-code mapping table (markdown table works well here). - Timing-pattern quick reads (3–4 bullets). - One line on hot-loop variant and OOM tiebreak. Keep it maybe 350–500 words plus table/commands. Use headers minimally (maybe two or three small headers or just bold lead-ins). Given the terse prompt, a dense, skimmable answer is right. Let me also double check: "terminationMessagePolicy: FallbackToLogsOnError" — uses logs, which they can't see; the container's terminationMessagePath file isn't written by distroless apps. Skip or one-line caveat. Skip to save space. Exit code 137 in K8s: reason OOMKilled when cgroup OOM; if kubelet liveness kill → exit 137 too? Liveness failures cause kubelet to kill with SIGTERM then SIGKILL after grace period — final exit code 137, reason "Error". Yes. Good, my disambiguation note stands. Distroless classic: exec failure shows as event "Failed to create pod sandbox"... no, that's runtime-level. Container start failure: event `Warning BackOff` plus in describe: "Error: failed to start container ...: exec: ...: no such file or directory" — actually for missing dynamic linker the runtime error is like `standard_init_linux.go:228: exec user process caused: no such file or directory` (runc) — that surfaces in `kubectl describe pod` events? It surfaces in `kubectl logs` sometimes and in crictl. In pod events you get "Back-off restarting failed container" without detail; the detail string appears in `kubectl get pod -o yaml` under `state.waiting.message`. Yes! `state.waiting.reason: CrashLoopBackOff`, `state.waiting.message: back-off 5m0s restarting failed container=...` — hmm, the exec error message appears in containerStatuses state.waiting.message in many cases: e.g., message: "container ... : createContainerError"... Let me recall precisely: when a container fails to start due to exec error, `lastState.terminated.exitCode=127`? For missing file at exec, docker gives 127? Containerd gives exit code 127 for command not found; for missing shared lib, exit code 127 as well? For "exec format error" exit code 126? In K8s, `reason: StartError` with message containing the runtime error string appears in waiting state. I'll phrase it as: exec failures show up as `state.waiting.reason: StartError/CreateContainerError` with the runtime's error text in `.message` — no exec needed. That's accurate enough and actionable: `kubectl get pod -o jsonpath='{.status.containerStatuses[0].state.waiting}'`. Exit code for missing shared library when PID1 runs: the dynamic loader exits 127. "Exec format error" → 126? Under runc, exec format error prevents start → StartError. Fine, my table can say 126/127 & StartError → link/exec-format/arch issues. Cost ranking: everything here is API/metrics reads. Cheapest single: exit code+reason+timestamps. I'll say: cheapest = the runtime's own exit record; one GET, zero privileges beyond read. Also docker: `docker events` streams container die events with exit codes — cheap history without logs. Now write it. Keep commands short. Use a table for exit codes. Bold the "cheapest" answer early (they asked "which is cheapest?" — answer directly). Maybe lead with the direct answer: "Cheapest: the exit record the runtime already keeps — exit code + reason + start/finish timestamps." Then the fuller signal inventory. That matches "answer first" preference. Structure: 1. Direct answer paragraph (cheapest = termination record; why it's free). 2. Commands block (k8s jsonpath, docker inspect). 3. What the fields tell you — exit code table. 4. Timing patterns (derive loop period from startedAt/finishedAt; backoff cadence). 5. Next-cheapest signals ranked: events feed; cgroup CPU/mem curves (tiebreak 137); black-box probe from sibling pod; node dmesg OOM lines; out-of-band telemetry if instrumented. 6. One-liner on hot-loop variant (no restarts → skip exit codes, CPU shape + probe behavior). Word budget ~450–550. Tables + code included. Good. Cheapest: the **termination record the runtime already keeps** — exit code, kill reason, and start/finish timestamps. One read API call, no exec, no logs, no privileges beyond read, and it splits the hypothesis space immediately. ## The termination record ```bash # Kubernetes kubectl get pod $P -o jsonpath='{.status.containerStatuses[0].lastState.terminated}' # → {exitCode, reason, startedAt, finishedAt} (+ .restartCount, .state.waiting.message) # Docker docker inspect $C --format '{{.State.ExitCode}} {{.State.OOMKilled}} {{.State.Error}} {{.State.StartedAt}} {{.State.FinishedAt}}' # containerd crictl ps -a && crictl inspect $ID ``` Three things fall out for free: **Exit code → hypothesis:** | Code | Likely cause | Distroless-specific note | |---|---|---| | 0 | Clean exit; the "loop" is restart-policy fighting an app that finishes → config/env fault | — | | 1 | App error: bad config, missing secret, unhandled exception | Most common | | 126/127 or `StartError` | Exec failed: missing `.so`, missing dynamic loader, wrong ARCH, exec-format | The classic distroless failure; runtime error text lands in `.state.waiting.message` even without logs | | 134 | `abort()` — failed assert, Go/Rust panic with abort, C++ uncaught exception | Points at recently bumped native deps | | 137 | SIGKILL — OOM **or** liveness-kill (see tiebreak below) | Check `.reason` field: `OOMKilled` vs `Error` | | 139 | SIGSEGV — native crash | | | 143 | Something SIGTERMed it: eviction, shutdown-handling hang then kill | | **Loop period from timestamps:** `finishedAt − startedAt` per restart, across restarts. Dies in <1s consistently → startup/exec/config fault. Dies at exactly the liveness threshold (initialDelay + failureThreshold × period) → app hung, not crashed. The observed interval also includes CrashLoopBackOff's 10s→20s→…→5m growth — subtract the backoff to get true run time. ## Remaining signals, ranked by cost 1. **Events feed** (`kubectl describe pod`) — same API read; adds probe-failure timestamps and back-off history. Liveness failures appearing before death ⇒ hang, not crash. 2. **cgroup-level CPU/memory curves** (Prometheus/metrics-server — the kubelet collects them regardless of image) — separates identical exit-137 cases: memory ramping to limit = OOM; memory flat + CPU pegged at liveness deadline = hot loop until killed; CPU near zero = deadlock. Sawtooth CPU matching restart cadence confirms crash loop. 3. **Black-box endpoint probe from a sibling pod** (TCP connect / curl) — RST = nothing listening (crashed); accepts but no response = hung; slow = starvation. Interaction, not process inspection. 4. **Node kernel log** (`journalctl -k | grep -i oom`) — decisive confirmation of cgroup OOM; needs node access, still nothing inside the container. 5. **Out-of-band telemetry if the app has it** (OTel, Sentry, a `/metrics` port) — stdout-independent, but don't count on it in distroless. ## The hot-loop branch If restart counts are flat — it's alive but spinning — exit codes are moot and the ordering flips: **CPU shape is now cheapest** (pegged = busy-loop; idle = blocked/deadlocked), with the probe behavior from #3 as the tiebreak. Practical sequence: read the termination record first — in practice it resolves ~70% of crash loops alone, and the CPU curve exists purely to disambiguate 137.

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