Do you really need a hyperscaler?

AWS is built for enormous scale, and it prices, bills and documents accordingly. If you are running a handful of applications for a few dozen people, you end up paying for that scale twice: once on the invoice, and again in the hours somebody spends navigating a service catalog of several hundred entries in order to do something straightforward.

For a lot of smaller workloads, a smaller provider is simply the better answer.

The case for a smaller provider

DigitalOcean starts at a few dollars a month for a usable virtual machine. More importantly, the price you are quoted is close to the price you pay. Hyperscaler billing is not predictable in that way, not with egress charges and per-request pricing spread across a dozen interlocking services.

The second advantage is operational. The control panel is small enough to hold in your head. Spinning up a server, attaching storage, configuring networking, deploying an application: each is a short task rather than a project. That saves time directly. It also cuts the misconfigurations that come from working in an interface nobody fully understands.

None of this is an argument that AWS is bad. Where you need a specific managed service, a genuine global footprint, or compliance features only a hyperscaler provides, that is what it is for, and we work in AWS for exactly those cases. The argument here is narrower: most organizations adopt it by default rather than by decision, and then pay for capabilities they never touch.

Where a hyperscaler is still the right call

Be honest about this before you commit either way. AWS earns its keep when you need deep managed services such as large-scale managed databases, data warehousing or specialized analytics; when regulatory or contractual requirements name a specific provider or certification; when you need a genuine multi-region presence; or when you are already invested enough in the surrounding tooling that leaving would cost more than staying.

What we do

Fries Consulting Services provides cloud consulting for non-profits, schools, and small businesses:

• Provider selection. An honest assessment of what your workloads actually need, whether that is AWS, a smaller provider, on-premises hardware or some combination. No reseller relationship steers the answer.
• Configuration and hardening. Networking, firewall rules, backups, access control and monitoring, all set up correctly from the start rather than retrofitted later.
• Cost review. Finding what you are paying for and not using, then right-sizing what remains.
• Scaling. Infrastructure that grows without a rebuild, defined in code so growth is a reviewed change rather than an improvisation.
• GPU droplets. DigitalOcean’s NVIDIA GPU instances for AI and machine learning workloads, at a fraction of the effort of arranging equivalent capacity on a hyperscaler.

If moving off a cloud provider entirely turns out to be the better answer, we will say so. Our write-up on building a private cloud with Proxmox and Ceph works the hardware costs through against equivalent AWS compute.

If this sounds like something that interests you, please feel free to reach out at the contact form to see how Fries Consulting Services can help with your cloud consulting needs.