aws-lambda-managed-instances

What this skill does

# AWS Lambda Managed Instances (LMI)

Run Lambda functions on current-generation EC2 instances in your account while AWS manages provisioning, patching, scaling, routing, and load balancing. Combines Lambda's developer experience with EC2's pricing and hardware options.

For standard Lambda development, see [aws-lambda skill](../aws-lambda/). For SAM/CDK deployment, see [aws-serverless-deployment skill](../aws-serverless-deployment/).

## When to Load Reference Files

- **Cost comparison**, **pricing analysis**, **Lambda vs LMI cost**, **Savings Plans**, or **Reserved Instances** -> see [references/cost-comparison.md](references/cost-comparison.md)
- **Instance types**, **memory sizing**, **vCPU ratios**, **scaling tuning**, or **capacity provider config** -> see [references/configuration-guide.md](references/configuration-guide.md)
- **Thread safety**, **concurrency model**, **code review checklist**, **Powertools compatibility**, or **multi-concurrency readiness** -> see [references/thread-safety.md](references/thread-safety.md)
- **Before/after code examples**, **runtime-specific migration** (Node.js, Python, Java, .NET), or **connection pooling** -> see [references/migration-patterns.md](references/migration-patterns.md)
- **IAM roles**, **VPC setup**, **CLI commands**, **SAM template**, or **CDK example** -> see [references/infrastructure-setup.md](references/infrastructure-setup.md) and [scripts/setup-lmi.sh](scripts/setup-lmi.sh)
- **Errors**, **throttling**, **debugging**, or **stuck deployments** -> see [references/troubleshooting.md](references/troubleshooting.md)

## Quick Decision: Is LMI Right for This Workload?

| Signal         | LMI is a strong fit                                                                     | Standard Lambda is better                              |
| -------------- | --------------------------------------------------------------------------------------- | ------------------------------------------------------ |
| Traffic        | Steady, predictable, 50M+ req/mo                                                        | Bursty, unpredictable, long idle                       |
| Cost           | Duration-heavy spend at scale                                                           | Low or sporadic invocations                            |
| Cold starts    | Unacceptable (LMI eliminates for provisioned capacity; scale-out may have brief delays) | Tolerable or mitigated by SnapStart                    |
| Compute        | Latest CPUs, specific families, high network bandwidth                                  | Standard Lambda memory/CPU sufficient                  |
| Isolation      | Dedicated EC2 instances in your account, full VPC control                               | Shared Firecracker micro-VMs acceptable                |
| Scale-to-zero  | Not needed (execution environments always running)                                      | Required (pay nothing when idle)                       |
| Code readiness | Thread-safe (Node.js/Java/.NET) or any Python code                                      | Non-thread-safe Node.js/Java/.NET, expensive to change |

## Instructions

### Step 1: Assess the Workload

Gather these signals before recommending:

1. **Traffic pattern**: Steady vs bursty? Requests per second?
2. **Current costs**: Monthly Lambda spend? Existing Savings Plans?
3. **Runtime**: Node.js, Java, .NET, or Python?
4. **Memory/CPU**: How much memory? CPU-bound or I/O-bound?
5. **Execution duration**: Average and P99?
6. **Concurrency readiness**: Thread safety (Node.js/Java/.NET)? Shared `/tmp` paths? Per-invocation DB connections?
7. **VPC**: Already in a VPC? Private resource access needed?

### Step 2: Build the Cost Comparison

REQUIRED: Present a cost comparison before recommending LMI. Compare at minimum:

| Scenario         | When it wins                |
| ---------------- | --------------------------- |
| Lambda on-demand | Low volume, bursty traffic  |
| LMI on-demand    | High volume, steady traffic |

Rule of thumb: LMI becomes cost-competitive when your Lambda spend exceeds ~$1,000/month with steady traffic.

For discount analysis (Savings Plans, Reserved Instances), refer users to the [AWS Pricing Calculator](https://calculator.aws/) and [references/cost-comparison.md](references/cost-comparison.md) for formulas and worked examples. Discount recommendations require workload-specific forecasting beyond this skill's scope.

### Step 3: Configure the Deployment

**Instance families** (~450 types): C-series (compute, .xlarge+), M-series (general, .large+), R-series (memory, .large+). ARM (Graviton) for best price-performance.

**Memory-to-vCPU ratios**: 2:1 (compute), 4:1 (general, default), 8:1 (memory). Min 2 GB, max 32 GB.

**Multi-concurrency defaults/vCPU**: Node.js 64, Java 32, .NET 32, Python 16.

**Scaling**: MinExecutionEnvironments (default 3), MaxVCpuCount (default 400), TargetResourceUtilization.

See [references/configuration-guide.md](references/configuration-guide.md) for decision trees and detailed tuning.

### Step 4: Migrate the Code

Review code for concurrency safety. LMI runs multiple invocations concurrently per execution environment, but the model differs by runtime:

- **Python**: Process-based isolation — globals are NOT shared. No thread-safety changes needed. Focus on `/tmp` conflicts and memory sizing (per-process × concurrency).
- **Node.js**: Worker threads — globals shared within a worker. Requires async safety. Callback handlers not supported on Node.js 22.
- **Java/.NET**: OS threads/Tasks — handler shared across threads. Requires full thread safety.

**Common issues (all runtimes)**: shared `/tmp` paths, per-invocation DB connections.
**Thread-safety issues (Node.js/Java/.NET only)**: mutable globals, non-thread-safe libs.

See [references/thread-safety.md](references/thread-safety.md) for the review checklist and [references/migration-patterns.md](references/migration-patterns.md) for runtime-specific before/after code.

### Step 5: Set Up Infrastructure

1. Create two IAM roles: execution role (for the function) and operator role (for capacity provider EC2 management)
2. Configure VPC with subnets across multiple AZs (recommended 3+ for resiliency)
3. Create capacity provider with VPC config and scaling limits
4. Create or update function with capacity provider attachment
5. Publish a version (triggers instance provisioning)

See [references/infrastructure-setup.md](references/infrastructure-setup.md) for CLI commands and SAM templates.

### Step 6: Validate and Cut Over

1. Deploy to a non-production environment first
2. Monitor CloudWatch: CPU utilization, memory, concurrency, throttle rate
3. Gradual traffic shift with weighted aliases (10% → 50% → 100%)
4. Compare costs after 1-2 weeks of production data
5. Decommission standard Lambda once stable

## Best Practices

### Configuration

- Do: Start with 4:1 ratio and runtime default concurrency
- Do: Use ARM (Graviton) unless x86 dependencies exist
- Do: Let Lambda choose instance types unless specific hardware needed
- Do: Set MaxVCpuCount to control cost ceiling
- Don't: Set MinExecutionEnvironments below 3 in production (reduces multi-AZ coverage). Non-prod environments can use 1 as the minimum.
- Don't: Over-restrict instance types (lowers availability)

### Migration

- Do: Start with I/O-heavy functions (benefit most from multi-concurrency; CPU-bound functions compete for same CPU)
- Do: Review code for concurrency safety before attaching to capacity provider (thread safety for Node.js/Java/.NET; `/tmp` and memory for Python)
- Do: Use weighted aliases for gradual traffic shift
- Do: Include request IDs in all log statements
- Do: Initialize DB pools and SDK clients outside the handler
- Do: Estimate total `/tmp` usage under max concurrency
- Don't: Write to hardcoded `/tmp` paths without request-unique naming
- Don't: Skip cost comparison — LMI is not always cheaper

### Operations

- Do: Set CloudW