In The Lab: 128GB of RAM, 8 Cores, and Zero Cloud Bills: We Benchmarked Our Ryzen 3800X as a Dev Infrastructure Powerhouse

Everyone knows the drill by now. You spin up a handful of staging environments on AWS or Azure. Next thing you know, the monthly invoice drops and you are staring at a bill for a thousand euros. The worst part? That is before those sneaky egress charges hit you for every single image push or dependency pull. It gets expensive fast.

Curiosity finally got the better of us. We wanted to see exactly what a single, beefy bare metal server could handle if we tossed actual development workloads its way. So we grabbed an AMD Ryzen 7 3800X from our Frankfurt data center. We gave it 8 cores, 128GB of DDR4 memory, two solid state drives, and a completely unmetered gigabit pipe. After loading a fresh copy of Ubuntu, we put it through the wringer. We ran PostgreSQL databases, Docker staging stacks, Redis caches, CI/CD builds, and basic web serving.

We skipped the synthetic fluff. No cherry picked data either. Just real tools delivering real results.

This marks the first entry in our In The Lab series. The goal is simple. We benchmark our own hardware so you know exactly what the box can do before you spend a dime.

The Hardware

Look, this is a Zen 2 chip. It isn't the absolute newest silicon on the market today, and honestly, that is the whole point. Mature hardware gives you an incredible price point for infrastructure that needs to run around the clock. The 3800X easily hits 4.5 GHz boost clocks and handles instructions like a champ. When you pair that processing power with 128GB of RAM, you get a machine that punches way above its weight class. Finding a cloud VM with that much memory usually costs an absolute fortune. We also toss in gigabit connectivity and DDoS protection for free.

You can spin one of these up in Frankfurt, Amsterdam, or Miami. Pick whichever location sits closest to your users.

CPU Performance: The Foundation

Let's start with the baseline numbers. We fired up Geekbench 6 and sysbench. These scores give you a solid reference point to compare against your current cloud instances.

Having 8 cores and 16 threads gives you serious breathing room. You can confidently run a web server, a database, a caching layer, and several CI runners at the exact same time. They coexist beautifully without fighting for resources.

Storage: How Fast Can It Move Data?

Storage speed is everything. It impacts Docker layer builds and database commits heavily. To mimic actual usage, we ran fio using a blend of random and sequential I/O patterns.

Our test chassis holds two SSDs. We configured them in RAID-1 for some redundancy, but you could easily keep them separate to isolate your OS from your data. If you run heavy databases, you really only care about the random IOPS numbers. They are extremely solid here.

Network: Frankfurt at the Heart of Europe

We parked this server in our Frankfurt data center because it is arguably one of the most connected cities in Europe. But paper specs do not mean a thing until you measure the actual latency your team will feel. We sent pings out to major European ISPs to get the real story.

Latency to European ISPs

As the data shows, we hit sub-millisecond responses to Deutsche Telekom. Throughout the DACH region, latency remained in the single digits. Even reaching down into Southern Europe, it stayed well under 45ms. Your staging environments will feel incredibly responsive whether your team is sitting in Amsterdam or Athens. Webhooks fire instantly, and APIs answer right away. Developers working out of Madrid or Milan get a completely smooth experience.

Throughput to European Mirrors

Latency is only part of the puzzle. What about raw bandwidth? We verified the 1Gbps link by running iperf3 against mirrors located in Amsterdam and Frankfurt.

The connection completely saturates the link across Western Europe. You are getting the full gigabit you paid for. It does not matter if you are cloning massive repos or syncing database backups.

PostgreSQL: Real Database Performance

Databases are the heart of any staging environment. We installed PostgreSQL and cranked up the pressure using pgbench to see how the server handles real transactional patterns.

We used a test dataset of about 750MB. Because the server has 128GB of RAM, the entire dataset fit easily into memory. All I/O was perfectly cached. This is exactly what happens in the real world when your staging database is smaller than your available memory. You can stack multiple staging databases on this single server without them stepping on each other's toes.

Redis: In-Memory Speed for Your Cache Layer

Modern apps demand a caching layer. Redis handles everything from job queues to session storage. We tested the hardware using pipelined operations, since that is how your app will actually communicate with it.

Thanks to the massive 128GB RAM pool, Redis can hold enormous datasets. You do not have to shrink your cache size just to fit into a tiny 4GB cloud VM anymore. You can mirror your production cache behavior perfectly, which means way fewer surprises on deployment day.

Docker Staging Stacks: How Many Environments Can You Run?

This is the big question. We deployed a complete SaaS staging stack featuring Nginx, Redis, and PostgreSQL containers. After measuring the idle footprint, we calculated a realistic capacity based on active connections and cache data.

Every single environment gets its own isolated database and web server. You get zero contention between team members or pull requests. You can literally spin up a fresh environment for a new feature branch and delete it when the code merges. Even if your data requirements are heavy, you will run far more environments here than on a comparably priced cloud setup.

CI/CD Build Performance: Ship Faster

Developers hate waiting around for builds to finish. We tested this server as a self-hosted build machine using three real world CI/CD operations.

Having 8 cores and 128GB of RAM means you can run multiple runners in parallel easily. Think three or four concurrent builds happening without the CPU breaking a sweat. And since bandwidth is unmetered, downloading dependencies and pushing artifacts never adds to your monthly bill.

Web Serving: Nginx Out of the Box

This server handles traffic effortlessly. We tested Nginx using wrk with 50 concurrent connections sustained for thirty seconds. It served a realistic staging dashboard right over the public IP.

These numbers reflect actual server side processing capacity. We routed the traffic through the real network interface rather than using a loopback shortcut. The hardware has plenty of headroom left over for TLS termination and reverse proxying.

Why Netrouting? What You Get Beyond the Hardware

Anyone can rent you a processor. Here is what you actually get when you deploy with us.

What Should You Run on This?

Based on our benchmark runs, these are the use cases where this server delivers the best return on investment:

Honestly, this server is perfectly comfortable running production workloads. The benchmarks we ran reflect sustained real world loads. The economics are just incredibly compelling for teams trying to escape per-VM cloud pricing for their staging environments.

Methodology

We ran all these benchmarks on a freshly provisioned Ubuntu server over in our Frankfurt data center. No extra background services were running. We used industry standard tools like sysbench, fio, Geekbench 6, and pgbench. We used real Docker containers for the density testing and actual Docker builds for the CI/CD test. ISP latency was measured by pinging provider IPs across Germany, Switzerland, Italy, Spain, and France.

We actually put the full benchmark script on our GitHub. Feel free to grab it, run it on your own Netrouting server and compare notes.

— Netrouting Engineering · In The Lab Series · February 8, 2026 —