Building Your Own Serverless Platform: Deploying Firecracker MicroVMs for a Custom FaaS on an Ubuntu VPS

Introduction to Self-Hosted Serverless Infrastructure

Function-as-a-Service (FaaS) and serverless computing have revolutionized modern application architecture by decoupling code execution from infrastructure management. However, relying solely on public cloud providers like AWS Lambda or Google Cloud Functions can lead to vendor lock-in, unpredictable scaling costs, and limited control over the underlying runtime environment. For enterprises and engineers seeking the agility of serverless combined with the control of private infrastructure, building a custom FaaS platform is an increasingly compelling strategy.

The primary challenge in building a multi-tenant FaaS platform lies in balancing isolation and performance. Traditional virtual machines (VMs) offer strong security boundaries but suffer from slow boot times and heavy resource overhead. Conversely, containers (like Docker) provide lightweight execution but share the host operating system kernel, introducing potential security vulnerabilities in multi-tenant environments. This is where AWS Firecracker bridges the gap, offering the security of traditional virtualization with the speed and footprint of containers.

Understanding AWS Firecracker and MicroVMs

Originally developed by Amazon Web Services to power AWS Lambda and AWS Fargate, Firecracker is an open-source virtualization technology purpose-built for creating and managing secure, multi-tenant containers and function-based services. Firecracker utilizes Linux’s Kernel-based Virtual Machine (KVM) to spin up minimalist virtual machines, known as MicroVMs, in a fraction of a second.

Key Benefits of Firecracker for FaaS

• Sub-Millisecond Boot Times: MicroVMs can launch in as little as 5 milliseconds, making them ideal for handling ephemeral, on-demand function executions without experiencing severe 'cold start' delays.
• Minimal Memory Footprint: A running Firecracker MicroVM can consume as little as 5 MB of RAM, allowing thousands of isolated functions to run concurrently on a single physical host or Virtual Private Server (VPS).
• Enhanced Security Isolation: Each MicroVM runs in its own guest kernel environment, isolated from the host and other MicroVMs by KVM. Firecracker further jails each process using cgroups, seccomp filters, and namespaces.

"Firecracker combines the security and isolation properties of traditional virtual machines with the speed and low resource overhead of containers."

Prerequisites and Environment Setup

Before deploying Firecracker, you must ensure that your Ubuntu VPS supports hardware virtualization. Because Firecracker relies on KVM, it cannot run on standard operating system-level virtualization platforms like OpenVZ; you will need a bare-metal server or a VPS that supports nested virtualization (such as KVM-based instances).

1. Verifying KVM Availability

Log into your Ubuntu VPS via SSH and execute the following commands to check if your CPU supports virtualization and if the KVM kernel modules are loaded properly:

# Check for hardware virtualization support
egrep -c '(vmx|svm)' /proc/cpuinfo

# Verify KVM installation
kvm-ok

If kvm-ok indicates that KVM acceleration can be used, your environment is ready. Next, ensure your current user has appropriate permissions to access the KVM device node:

sudo usermod -aG kvm $USER

2. Installing Dependencies

Update your system package repository and install the fundamental tools required for network configuration and process management:

sudo apt-get update && sudo apt-get install -y iproute2 bridge-utils iptables curl jq

Installing and Configuring Firecracker

Firecracker is distributed as a static binary. You can download the latest stable release directly from the official GitHub repository. For optimal security and compatibility, it is recommended to target the specific architecture of your VPS (typically x86_64 or aarch64).

1. Downloading the Binary

# Fetch the latest binary version
release_url=$(curl -s [https://api.github.com/repos/firecracker-microvm/firecracker/releases/latest](https://api.github.com/repos/firecracker-microvm/firecracker/releases/latest) | jq -r '.assets[] | select(.name | contains("x86_64")) | select(.name | test("firecracker-v[0-9]")) | .browser_download_url')
curl -L -o firecracker $release_url
chmod +x firecracker
sudo mv firecracker /usr/local/bin/

2. Preparing the Guest Kernel and Root Filesystem

Unlike a traditional hypervisor that boots a full operating system installer, Firecracker requires an uncompressed Linux kernel binary (vmlinux) and an ext4 file system image acting as the root drive (rootfs). Amazon provides pre-built, minimalist assets that are optimized for rapid booting.

# Download an uncompressed kernel image
curl -fsSL -o vmlinux [https://s3.amazonaws.com/spec.ccfc.min/firecracker-vmlinux/vmlinux-5.10.0](https://s3.amazonaws.com/spec.ccfc.min/firecracker-vmlinux/vmlinux-5.10.0)

# Download a minimalist Alpine Linux rootfs image
curl -fsSL -o rootfs.ext4 [https://s3.amazonaws.com/spec.ccfc.min/firecracker-ci/images/alpine3.17.rootfs.ext4](https://s3.amazonaws.com/spec.ccfc.min/firecracker-ci/images/alpine3.17.rootfs.ext4)

Architecting the Custom FaaS Runtime Loop

To transform these isolated MicroVMs into a functioning Cloud Functions platform, we must establish a control plane that orchestrates function execution. A complete FaaS architecture requires three essential components:

1. The API Gateway / Control Plane: A lightweight manager (often written in Go, Node.js, or Python) running on the host system that listens for incoming HTTP requests or event triggers.
2. The Firecracker Socket Manager: A sub-process controller that communicates with Firecracker’s REST API over an isolated Unix domain socket to configure and start the MicroVM.
3. The Function Wrapper: An agent embedded inside the guest rootfs.ext4 that waits for payload data, executes the target function code, and returns the output to the host.

Configuring a MicroVM via the REST API

Firecracker is controlled entirely by interacting with its local Unix socket. When an execution request is routed to your control plane, the manager initializes a Firecracker instance and executes a configuration script similar to the following:

# Start Firecracker process in the background bound to a socket
firecracker --api-sock /tmp/firecracker.socket &

# Set the guest kernel path
curl --unix-socket /tmp/firecracker.socket -X PUT 'http://localhost/boot-source' \
  -H 'Accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
    "kernel_image_path": "vmlinux",
    "boot_args": "console=ttyS0 reboot=k panic=1 pci=off"
  }'

# Attach the root filesystem
curl --unix-socket /tmp/firecracker.socket -X PUT 'http://localhost/drives/rootfs' \
  -H 'Accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
    "drive_id": "rootfs",
    "path_on_host": "rootfs.ext4",
    "is_root_device": true,
    "is_read_only": false
  }'

# Allocate hardware resources (1 vCPU, 128MB RAM)
curl --unix-socket /tmp/firecracker.socket -X PUT 'http://localhost/machine-config' \
  -H 'Accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
    "vcpu_count": 1,
    "mem_size_mib": 128
  }'

# Command the MicroVM to boot
curl --unix-socket /tmp/firecracker.socket -X PUT 'http://localhost/actions' \
  -H 'Accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
    "action_type": "InstanceStart"
  }'

Networking and Security Hardening

To run multiple concurrent tenant functions safely, network traffic must be structurally sandboxed. Bridged interfaces or TAP devices should be provisioned for each individual MicroVM, paired with restrictive iptables or nftables rules to prevent unauthorized cross-VM data exfiltration or access to the host private network.

Implementing Network Isolation via TAP Devices

For each MicroVM instance, create a dedicated TAP interface on the host Ubuntu server to handle isolated network communication:

# Create a TAP interface
sudo ip tuntap add dev tap0 mode tap
sudo ip addr add 172.16.0.1/24 dev tap0
sudo ip link set tap0 up

# Enable IP forwarding on the host
sudo sysctl -w net.ipv4.ip_forward=1

# Restrict cross-interface traffic via iptables
sudo iptables -A FORWARD -m conntrack --ctstate RELATED,ESTABLISHED -j ACCEPT
sudo iptables -A FORWARD -i tap0 -o eth0 -j ACCEPT

By ensuring that each function runs within its own micro-segmented subnet, you can confidently run untrusted code without exposing vital host configurations or administrative endpoints.

Production Considerations and Optimization Strategies

While the fundamentals of launching a single Firecracker MicroVM are straightforward, achieving true production-grade serverless scalability requires implementing strategic optimization policies:

• Snapshotting and Warm Pools: To bypass even the minimal cold start times of a fresh kernel boot, leverage Firecracker’s built-in snapshotting features. You can pause a pre-initialized MicroVM, save its memory state, and resume it instantly upon receiving an execution trigger.
• Automated Resource Garbage Collection: Ensure your orchestration layer monitors the lifecycle of each MicroVM. Once a function finishes executing, the control plane must systematically kill the process, unmount the drive images, and tear down the associated TAP interfaces to reclaim memory and CPU cycles.
• Storage Optimization via OverlayFS: Instead of copying massive rootfs.ext4 files for every single concurrent function execution, use OverlayFS or copy-on-write storage backends. This allows multiple MicroVMs to safely share a single read-only base rootfs image while redirecting ephemeral runtime modifications to a transient, disposable memory tier.

Conclusion

Deploying AWS Firecracker on a standard Ubuntu VPS offers a powerful, flexible mechanism for engineers looking to design a cost-efficient, secure, and private Function-as-a-Service architecture. By utilizing KVM-driven MicroVMs, you combine the strict isolation properties necessary for multi-tenant code execution with the rapid elasticity required by modern cloud native workflows. Armed with this configuration, you are well-positioned to take complete control of your serverless scaling paths, reduce infrastructure overhead, and eliminate external public cloud dependencies.