---
id: aws-cdk-lambda-layer-kubectl-v35
version: "2.2.2"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# aws-cdk.lambda-layer-kubectl-v35 — A Lambda Layer that contains kubectl v1.35

License: permissive · Maintenance: active · Downloads: 81.6K/mo

## What it is and what it does

This package is an AWS CDK construct that bundles kubectl v1.35.2 and Helm v4.1.3 into a Lambda Layer, making those command-line tools available to Lambda functions. When added to a Lambda function via CDK, it stages kubectl at `/opt/kubectl/kubectl` and helm at `/opt/helm/helm` within the function's execution environment. It is designed for infrastructure-as-code workflows where you define AWS resources in Python using the AWS CDK framework.

The package is a thin wrapper around pre-built binaries; it does not compile or build kubectl or Helm itself. It is most useful when your Lambda functions need to interact with Kubernetes clusters or manage Helm charts—for example, triggering deployments, querying cluster state, or applying manifests. The layer approach avoids bundling these tools into every function's deployment package, reducing code size and enabling reuse across multiple functions.

Use it for:

- Add kubectl and helm to Lambda functions that manage or query Kubernetes clusters from AWS infrastructure.
- Automate Helm chart deployments triggered by Lambda events without packaging tools in each function.
- Build CDK-based infrastructure that provisions Lambda functions with pre-configured Kubernetes CLI access.
- Enable Lambda-based CI/CD pipelines to apply Kubernetes manifests or run kubectl commands against EKS clusters.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides a Lambda Layer packaging kubectl v1.35.2 and Helm v4.1.3 for use in AWS Lambda functions running Python.

Yes, if you are using AWS CDK to define Lambda functions that need kubectl or Helm access. The package has low install friction, active maintenance, no known vulnerabilities, and a permissive license. Install only if you are already in a CDK-based workflow; it adds no value outside that context.

## Install

pip install aws-cdk-lambda-layer-kubectl-v35
uv add aws-cdk-lambda-layer-kubectl-v35
poetry add aws-cdk-lambda-layer-kubectl-v35

## Installing aws-cdk.lambda-layer-kubectl-v35

Before you install: Low install friction with a pure-Python wheel. Active maintenance as of 2026-08-12 with recent releases; depends on stable AWS CDK ecosystem libraries (aws-cdk-lib, constructs, jsii).

License in practice: Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most production environments.

Quickstart:

from aws_cdk.lambda_layer_kubectl_v35 import KubectlV35Layer
import aws_cdk.aws_lambda as lambda_

kubectl = KubectlV35Layer(self, "KubectlLayer")
fn.add_layers(kubectl)

Requires Python 3.9 or later; intended for use within AWS CDK infrastructure-as-code projects, not standalone scripts.

Verify before relying:

- Whether the layer size and cold-start overhead are acceptable for latency-sensitive Lambda workloads.
- Compatibility with Lambda runtimes other than Python (e.g., Node.js functions that need kubectl access).

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 81.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

lambda layer kubectl, aws cdk kubernetes tools, helm in lambda, kubectl lambda layer, aws cdk lambda deployment, kubernetes cli lambda, helm deployment automation, aws-cdk, kubernetes, lambda-layer

[View on SkillFed](https://skillfed.io/packages/aws-cdk-lambda-layer-kubectl-v35) · [View on PyPI](https://pypi.org/project/aws-cdk-lambda-layer-kubectl-v35/)