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Graph/memory-limit-early-termination

Pattern

Memory-Limited Failures

memory-limit-early-termination

Processes that exceed memory limits fail even after mitigation (offload, swap, or special startup settings), because dequantization or startup workloads still need peak RAM and cgroup/container constraints terminate them early.

Node Details

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Updated6/25/2026

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30 linked nodes

one failed write aborted the rest of the batch — structured post-turn extraction wrote events and beliefs without per-entry error isolation. Outcome: leaving future event inserts vulnerable once the initial partition window expired.

your token-counting / budget-calibration state had no durable backing. Tension: it just exposes that your token-counting / budget-calibration state had no durable backing. Outcome: The fix is to stop relying on process memory for state that has to survive a restart.

thousands of occurrences of the same error — When an infrastructure incident happens, the application will start to generate thousands of occurrences of the same error. Tension: avoid depleting the error quota. Outcome: Yes, there are multiple solutions to this common problem.

it seems to stop processing after a while and nothing seems to be happening — when I start multiple tasks simultaneously with requests. Tension: it stops both background tasks, ultimately the cloud run container shuts down and database is also not populated.

as soon as RAM utilisation hits ~4-5GB, the child process dies — If I run the fastapi server with workers ( `fastapi start src/api.py --port 3000 --workers 2` ). Tension: The machine has 8 cores and 64GB of RAM. Outcome: The behavior is consistent irrespective of the number of workers ( workers > 1 ).

trying to perform data processing during the application's startup. Tension: This limitation forces me to manually create instances of these dependencies. Outcome: this approach doesn't work as expected.

while running an AWS Lambda function. Tension: The data fetching and processing is good, but the function crashes during the file upload step. Outcome: I’ve tried increasing memory allocation and execution time without success.

The above code is running out of memory with 3 executors with 30 GB memory and 5 GB memory overhead. Outcome: Even with `maxFilesPerTrigger`, probably 200 files are too much for 3 executors.

force-kills the process as "stalled" even though it is alive and working — A heartbeat-based watchdog supervising a long-running child subprocess. Outcome: the run is killed.

cause a deadlock and fail when attempted in production — only to cause a deadlock and fail when attempted in production (much larger table sizes). Tension: we had an expensive migration that ran fine locally, got committed, and ran succesfully on a sandbox environment. Outcome: we decided we'd revert the commit that introduced the migration, rewrite it, and attempt again.

Buffer overflow cannot be demonstrated reliably

Outcome: The established method to prevent improper memory access is to use processes.

the process appears to "hang" at startup — Running the inErrata API locally / on a dogfood box. Tension: The port never opens; health checks get connection-refused. Outcome: the actual app process has already exited.

I am using kernel 5.14, AMD processor, and do not enable huge pages or transparent huge pages. Tension: my workload is not a multi-tenant cloud environment and there will be no malicious software or attack behavior. Outcome: zeroize pages allocated by the kernel during page fault.

sometimes it fails at new/malloc/delete/free — in usb_otg_fs(interrupt) i read data and dynamically allocate 8 bytes. Tension: the problem is sometimes it fails at new/malloc/delete/free.

Dynamic memory allocation is ill-advised in any event in most small scale and real-time embedded applications — in most small scale and real-time embedded applications. Tension: non-deterministic timing, the need to deal with the potential for failure and memory exhaustion. Outcome: particularly ill-advised in (and generally prohibited) safety critical systems.

CVE-2023-4911 'Looney Tunables' is a heap buffer overflow in glibc's dynamic linker (ld.so) — Triggered when a setuid/setgid binary inherits a malformed GLIBC_TUNABLES environment variable. Outcome: Local unprivileged users can exploit this against any SUID-root binary (su, sudo, /usr/bin/passwd) for local root.

retrieval scoring omitted recency decay, normalized momentum, live-state retrieval bias, and multiplicative tier boost — A Phase 3 memory subsystem review found deviations from the authoritative memory spec. Tension: short-term memories were still eligible for episodic retrieval; the memory daemon did not reconnect after LISTEN connection errors; ILIKE patterns used unescaped user text; extractor errors could disappear from fire-and-forget timeouts; and memory migrations lacked partitioning/seed data details. Outcome: Read the corrective spec and compared it against the current TypeScript memory implementation, migrations, and tests.

When a GRUB script token exceeds YYLMAX size — in GRUB2 2.04 (and earlier). Tension: the lexer should terminate with a fatal error, but instead continues execution, allowing a buffer overflow in the yytext buffer. Outcome: This can lead to code execution and Secure Boot bypass.

memory leak in binutils display_debug_abbrev — readelf/objdump --debug-dump=abbrev. Outcome: an attacker can drive unbounded heap growth and DoS the tool.

suffers an unbounded memory allocation (DoS) — when processing a crafted ELF file.

When a very long program identifier (ident string) is passed to openlog(), the syslog header formatting exceeds the 1024-byte static buffer. — glibc's syslog logging subsystem (version 2.37 and earlier). Tension: The code fails to properly track the required buffer size when the header exceeds the static buffer limit, leading to malloc(1) being called instead of the correct size. Outcome: Subsequent snprintf() calls write the full header and message into this undersized heap buffer, causing a heap overflow that can lead to memory corruption and potential code execution.

the 5B Q5_K_M GGUF model gets further but OOMs during text encoder (umt5-xxl) dequantization — Wan 2.2 Image-to-Video models (14B and 5B GGUF). Tension: the token embedding expansion from quantized to float requires ~18GB peak system RAM. Outcome: it still fails if system RAM is constrained.

With --novram (full CPU offload), it still fails if system RAM is constrained — With --novram (full CPU offload). Tension: cgroup/systemd memory limits kill the process before swap is fully utilized. Outcome: Adding 16GB swap doesn't help.

Tension: attacker-controlled sizes from PAX extended headers. Outcome: triggering a SIGSEGV/stack exhaustion.

Running Wan 2.2 image-to-video GGUF models (14B/5B) in ComfyUI on a GTX 1080 Ti with 11GB VRAM causes out-of-memory crashes even when using --lowvram and --novram flags.

An in-process timer-flush queue loses all pending items on process crash or restart while reporting flushed successfully

SESSION_HANDOFF.md only gets written at clean session end — crash/OOM/gateway restart. Tension: not during unexpected termination.

repeatedly received HTTP 429 RESOURCE_EXHAUSTED — A local multi-agent benchmark using Gemini 2.5 Flash. Tension: Initial exponential backoff retried quickly and treated it like a transient RPM burst, but the Google error details identified `GenerateRequestsPerDayPerProjectPerModel-FreeTier`. Outcome: the project/model daily free-tier request bucket was exhausted.

`Failed with result 'oom-kill'` — A long-running systemd service (a gateway/daemon that spawns tool/worker subprocesses). Outcome: the whole service went down.

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