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Graph/transient-peak-ram-killed-by-limits

Pattern

Resource Limits Breakbacks

transient-peak-ram-killed-by-limits

System memory constraints (peak RAM during dequantization or cgroup limits during CPU offload) cause processes to be killed before work can complete, even when swap is added, because the runtime’s transient allocations exceed the enforced limit.

Node Details

Public graph metadata

Updated6/27/2026

Connections

30 linked nodes

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.

KeyError: 1 — after increasing the partition count from 1 to 2 for the snuba-commit-log topic. Tension: I sometimes saw timeout errors and thought I could fix them by increasing the partition count.

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 ).

valgrind: Linux is required for this software. Tension: I would like to perform memory checking for both macos and windows. Outcome: Process completed with exit code 1.

I could start a process (using Python multiprocessing) - and kill it to cancel the download — potentially big files from S3. Tension: that would probably leave large chunks already in memory but not saved to the file "lost".

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.

Buffer slice []byte{} appends in amortized time, causing slower downloads and higher memory use

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.

Buffer overflow cannot be demonstrated reliably

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

stack layout and register allocation are subject to a great amount of optimization — An attempt to interfere this process nondeterministically. Tension: benchmarks will become useless. Outcome: nondeterministic performance.

java.lang.OutOfMemoryError: Java heap space — When running the app in the dev environment (Gradle based), the app is running without any problem. If I build a jlink image of this app. Tension: I know about "Xmx" option, but this is not the solution. Outcome: the same line will throw.

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.

108 consecutive 429s in ~90 minutes — A Node.js rate limit proxy sitting between agents and the Anthropic API tracked token usage and budget calibration entirely in memory. Tension: The proxy thought it had 100% budget remaining when the Anthropic-side window was actually exhausted.

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.

Heap buffer overflow in GRUB2's PNG image loader — when processing crafted 16-bit grayscale PNG images without alpha. Tension: grub_png_convert_image() advances destination pointer by 4 bytes per pixel for 16-bit gray images, but the destination bitmap is allocated as RGB_888 (3 bytes/pixel). Outcome: causing heap OOB write of width*height bytes past the bitmap buffer.

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

strcpy with unchecked length on stack buffer in sunrpc/clnt_gen.c:62 — When the protocol is 'unix', the function copies a user-controlled hostname parameter directly into a 108-byte fixed-size buffer (sun_path). Tension: Hostnames longer than 108 bytes cause the strcpy() to overflow the buffer and corrupt adjacent stack memory, potentially allowing code execution.

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

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

429s from OpenAI (RPM limit exceeded) — We have ~200 autonomous agents hitting our internal API gateway. Tension: Cascading retries amplifying the load. Outcome: P99 latency spikes to 30+ seconds.

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.

An ETL pipeline slowed from 19s/pair to 40-47s/pair — after one "resilience hardening" commit changed three perf-relevant knobs at once. Tension: TWO commits 15 minutes apart each claimed to be "the actual cause" of the SAME slowdown, with no measurement between them. Outcome: the file documented a policy it did not implement, and nobody could tell whether the regression had returned.

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