Advanced Vector Extensions (AVX) and MongoDB
As part of routine homelab maintenance, I investigated upgrading containers that run MongoDB and ran into AVX-related compatibility issues.
Well, this wasn't anything routine, as I quickly learned quite a bit about MongoDB's requirements. Specifically, the Advanced Vector Extensions instructions set, or AVX for short.
What is AVX?
AVX is a family of CPU instruction-set extensions that provide SIMD (Single Instruction, Multiple Data) vector operations. AVX exposes wider vector registers and instructions for floating-point and integer math, which allows the CPU to process multiple values in parallel with a single instruction. That makes workloads compression, cryptography, and numeric computation much faster when developers choose to compile their code to take advantage.
In short, AVX is a hardware feature implemented in the processor microarchitecture; software only uses it if the compiler and runtime explicitly enable and emit AVX instructions. There are multiple generations (AVX, AVX2, AVX-512) with increasing register width and capabilities.
With that technical jargon out of the way, let's focus back on to MongoDB's requirements.
What does MongoDB require and why?
Modern MongoDB binaries are frequently built and optimized using modern compiler toolchains that may emit vectorized instructions when available. If a MongoDB binary is compiled with AVX-enabled optimizations, attempting to run it on a CPU that does not support AVX can cause immediate failures (such as illegal-instruction errors) or force slower fallback code paths where the binary provides them. From my limited experience, new versions of MongoDB from the last couple years prefer to just break with immediate failures.
Functionally, AVX not only affects binary compatibility but also performance characteristics. When AVX is present, you often see improved throughput and lower CPU time for the same workload. I've never benchmarked or ran significant workloads to notice, but a quick search can easily provide those enlightening details (should you choose to go down that rabbit hole).
Checking CPU Flags
Okay, so the latest and greatest MongoDB requires AVX and will immediately fail if it's missing for the CPU. Thankfully, there is an easy way to check for this beforehand (on Linux anyways!).
For Linux, the simplest checks are lscpu and examining flags in /proc/cpuinfo:
lscpu | grep -i avx
grep -m1 '^flags' /proc/cpuinfo
Look for tokens like avx, avx2 (and related tokens such as fma or sse4_2) in the flags string. Those tokens indicate the CPU advertises support for the corresponding instruction sets.
Inside a container, the visible CPU flags are generally the host's flags. You can probe them from a short-lived container as well:
# Docker:
docker run --rm --privileged alpine:3.23 grep -m1 '^flags' /proc/cpuinfo
# Podman:
podman run --rm --privileged alpine:3.23 grep -m1 '^flags' /proc/cpuinfo
# Kubernetes
kubectl run -it --rm test-pod --image=alpine --restart=Never -- sh
grep -m1 '^flags' /proc/cpuinfo
exit
For Windows, you'll have to use the Sysinternals coreinfo utility (coreinfo -f) to enumerate supported instruction sets, or check from WSL if available.
For cloud VMs it is best to consult the provider's VM SKU documentation, as many public cloud providers list the CPU generation and whether the instance exposes AVX/AVX2. If not, then you'll need to review things for yourself.
In either case (Linux/Windows/Cloud), I have found the following list helpful. This assumes you know your CPU model/family: - QEMU / KVM CPU model configuration.
Confirming CPU flags was never on my bingo card until now. It is important for both a compatibility check (will the binary/software run) and an operational one (are you getting expected performance).
Note that some hypervisor configurations or nested virtualization setups can hide or alter exposed CPU features. This was the case for my Proxmox VE servers. I was still using the type x86-64-v2-AES default for my VMs, which does not include the AVX relevant flags. I'll detail those fixes for another post, so stay tuned!
Mitigations if AVX is missing
If you find a host without AVX support, practical mitigations include:
- Selecting a different VM or host SKU whose CPUs advertise AVX/AVX2.
- Selecting a different CPU type for your VM that advertises AVX/AVX2.
- Building MongoDB from source with conservative compiler flags that avoid AVX, producing a compatible binary for older CPUs. (Not something I recommend)
- Using an earlier MongoDB binary that targets older instruction sets (weighing security/support implications, also not recommended).
- Running MongoDB on managed services (e.g., Atlas) or on dedicated nodes provisioned with compatible CPUs.
General Recommendations
So in addition to other system admin duties I perform on my homelab, I now have a few other items to build out and add to my routine:
- Use or add a pre-install check that inspects CPU flags on each VM, container, or node intended to run MongoDB to catch incompatibilities early.
- If using Kubernetes, look into having a label for nodes with a capability marker (for example
cpu.avx=true) and use node selectors/affinity for MongoDB pods so they only schedule onto compatible hosts. - Ensure CI and test runners either match the minimum CPU feature set of production or build multiple artifacts targeting different instruction sets.
That last one is more of a check on sanity to keep me viewing things as production vs testing. Because let's be honest, nothing in my homelab is technically production, even though I rely on it. It's all just under development, all the time!
However, these steps reduce surprise failures and let you take advantage of vectorized performance when the software developers make it available.