AWS / Cloud Platforms

AWS Lambda Runtime Exited with signal: killed (OOMKill) — Max Memory Used Matches Memory Size

Lambda function hits memory ceiling, gets killed instantly with SIGKILL rather than graceful timeout; CloudWatch shows Max Memory Used equaling Memory Size — developer needs to find actual peak usage and set proper buffer Includes evidence for AWS troubleshooting demand.

Source-backed Last updated June 2, 2026 3 sources Needs local verification

Category: Cloud Platforms
Error signature: Runtime exited with error: signal: killed — Max Memory Used matches Memory Size allocation exactly
Quick fix: Compare the failing environment with a known working setup, then change one configuration value at a time.
Updated: June 2, 2026
Verification status: Source-backed
Evidence: 3 public source URLs

Before you change production

This page includes public source URLs in the imported troubleshooting record. Compare those references with your version and environment before applying changes.

Reproduce the smallest failing action and save non-secret logs before changing configuration.
Check versions for AWS, related SDKs, package managers, CI runners, and hosting providers.
Change one setting or dependency at a time, then rerun the same failing command or request.
Avoid destructive commands, credential rotation, billing changes, or security relaxations without a rollback plan.

What this error means

Runtime exited with error: signal: killed — Max Memory Used matches Memory Size allocation exactly is a AWS failure pattern reported for developers trying to lambda function hits memory ceiling, gets killed instantly with sigkill rather than graceful timeout; cloudwatch shows max memory used equaling memory size — developer needs to find actual peak usage and set proper buffer. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

OneUptime guide (Feb 2026) details the Out-of-Memory error in Lambda where increasing memory not only allocates more RAM but proportionally increases CPU cores (at 1.8GB gets full vCPU, at 10GB gets 6 vCPUs). Dash0 guide covers timeout best practices. Re:Post shows real case: pandas reading S3 CSV at 128MB causing both OOM and timeout. Terraform/SAM config examples available. Category: Cloud Platforms per mapping.

Common causes

OneUptime guide (Feb 2026) details the Out-of-Memory error in Lambda where increasing memory not only allocates more RAM but proportionally increases CPU cores (at 1.8GB gets full vCPU, at 10GB gets 6 vCPUs). Dash0 guide covers timeout best practices. Re:Post shows real case: pandas reading S3 CSV at 128MB causing both OOM and timeout. Terraform/SAM config examples available. Category: Cloud Platforms per mapping.

Quick fixes

Confirm the exact error signature matches Runtime exited with error: signal: killed — Max Memory Used matches Memory Size allocation exactly.
Check the AWS account, local tool state, and provider configuration involved in the failing workflow.
Compare the failing environment with a known working setup, then change one configuration value at a time.

Platform/tool-specific checks

Verify the command, editor, extension, or API client that produced the error.
Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
Avoid deleting credentials, local model data, or project settings until the failing scope is clear.

Step-by-step troubleshooting

Capture the exact error message and the command, editor action, or request that triggered it.
Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
Review the source evidence below and compare it with your environment.
Apply one change at a time and rerun the smallest failing action.
Keep the working fix documented for the team or deployment environment.

How to prevent it

Keep provider/tool configuration documented.
Record non-secret diagnostics such as tool version, provider name, model name, and command path.
Add a lightweight check before CI or production workflows depend on the tool.

Diagnostic flow for this page

Match Runtime exited with error: signal: killed — Max Memory Used matches Memory Size allocation exactly exactly before applying the quick fix.
Compare the failing environment with AWS versions, account scope, provider settings, and deployment context.
Check the listed common causes in order, starting with the cause that best matches your logs.
Use the evidence status below to decide whether to confirm against public sources or official documentation.
Apply one reversible change, rerun the smallest failing action, and keep rollback notes.

FAQ

What does Runtime exited with error: signal: killed — Max Memory Used matches Memory Size allocation exactly mean in AWS?

Runtime exited with error: signal: killed — Max Memory Used matches Memory Size allocation exactly indicates the workflow described by "AWS Lambda Runtime Exited with signal: killed (OOMKill) — Max Memory Used Matches Memory Size" failed in a Cloud Platforms context. Start by confirming the exact signature and the component that emitted it.

What should I check first for Runtime exited with error: signal: killed — Max Memory Used matches Memory Size allocation exactly?

Check whether this cause matches your environment: OneUptime guide (Feb 2026) details the Out-of-Memory error in Lambda where increasing memory not only allocates more RAM but proportionally increases CPU cores (at 1.8GB gets full vCPU, at 10GB gets 6 vCPUs). Dash0 guide covers timeout best practices. Re:Post shows real case: pandas reading S3 CSV at 128MB causing both OOM and timeout. Terraform/SAM config examples available. Category: Cloud Platforms per mapping.

Is the Runtime exited with error: signal: killed — Max Memory Used matches Memory Size allocation exactly guidance source-backed?

The "AWS Lambda Runtime Exited with signal: killed (OOMKill) — Max Memory Used Matches Memory Size" page is labeled source-backed. It has 3 public source URLs from oneuptime.com, dash0.com, repost.aws, so use that evidence status when deciding how much additional verification you need.

When should I avoid the quick fix for Runtime exited with error: signal: killed — Max Memory Used matches Memory Size allocation exactly?

For "AWS Lambda Runtime Exited with signal: killed (OOMKill) — Max Memory Used Matches Memory Size", avoid applying "Compare the failing environment with a known working setup, then change one configuration value at a time." when the error text differs, the affected version or provider is different, or the change would touch credentials, billing, DNS, production deploy settings, or irreversible data.

What should I collect before debugging Runtime exited with error: signal: killed — Max Memory Used matches Memory Size allocation exactly?

For "AWS Lambda Runtime Exited with signal: killed (OOMKill) — Max Memory Used Matches Memory Size", collect the failing AWS command or request, non-secret configuration, versions, timestamps, request IDs when available, and the smallest reproduction that still triggers the signature.