Except then you're stuck with a $15K server, and you had to spend all 15K up front. What happens when a component prematurely fails? Better buy two. What about the person-hours you spend with ISPs, CoLo provider, etc? You want network redundancy? Big ISP bills.

Yes, cost per compute measurable (memory, CPU, etc) is higher in the cloud. But what's never mentioned when people complain about the cloud being expensive:

a) ISP and CoLo costs

b) Redundancy/Multiple AZs

c) Backups

d) Failure recovery/cutover

e) Support

f) Monitoring/Health statistics

g) The other goodies that come along with being in the cloud(Lambda, CloudFront, Route53, SQS, etc)

I feel like we're at a point where people should have to justify why they are running their own data centers vs. having to justify why they're running in the cloud. There's obviously many very good reasons to do either, or both, but if you don't already have a data center, you better have some damn good reasons for starting one up.

That $15,000 server is leased across 36 months becoming an OpEx expenditure. On the accounting side this is no different than AWS. So let's say you buy two for failover.

A) Colo is $50-150/U with blended top tier bandwidth, 99th% billing and usually includes remote hands time.

B) Even with 100% redundancy you're still ahead by $3000/month. Please understand Amazon offers absolutely no redundancy built in and nodes go down regularly. It is up to you as a developer to build redundancy around the tools they offer.

C) Amazon doesn't take backups for you. You have to pay for this either way.

D) Again Amazon doesn't handle this for you. You have to pay either way. Buying an exact replica of the hardware I've mentioned and cololocating it elsewhere still puts you ahead by $3000/month.

E) What support do you need? Dell offers same day or even 4 hour parts replacement with the appropriate warranty service. Most Colos offer remote hands for free up to a certain hourly.

F) Lots of ways to handle this. You can use IPMI, built in OS tools, etc. There isn't much exclusive to AWS you can't easily replicate elsewhere.

G) I never said not to use Amazon for anything. In fact you should be building your applications for scaleability INTO the cloud. This is part of the idea behind the whole microservices movement.

  > Except then you're stuck with a $15K server, and you had to spend all 15K up front

I think you missed the part where the parent said "lease it at $400/month (OpEx)"

Cloud doesn't automatically come with that stuff - you need to set up your own failovers, backups and monitoring. Also you still need to administer those servers.

Also, tying yourself exclusively to AWS services is not a good long term strategy because then you have vendor lock-in that's worse than being stuck with some old hardware.

If you don't need the scaling abilities of cloud, then it just doesn't justify the added expense because no matter what you say, you still need people to manage systems.

Yes you do need to know your shit. But that's true for all kinds of products and services any business buys. Someone has to understand the deep weeds Health Insurance at any company (in the USA).

You left out the paying multiple people >$10k/month that can replace a hardware failure immediately (and somehow with 0 downtime), the redundant hardware, etc.

Oh, preachin' to the choir with that : my company's SaaS service is deployed across 10 or so tin boxes that I personally screwed together from Supermicro parts; humming in a faceless DC in Santa Clara with a backhoe sat in the far corner of the parking lot..

What I mean is : if you make a list of "shit that's wrong with my crafted good selling business", "how the servers are made" wouldn't be in the top 10 things to worry about. The fact that they're arguing that said servers should be sourced in a very cost-inefficient way makes it even more odd.

Consider for example this : http://www.zdnet.com/article/snapchat-spending-2-billion-ove... which, other than here, nobody seemed to question as strange.

On the other hand, a reserved m4.Large instance is $45/month. After a year of that, you're just $550 into hosting, barely enough to select and order the case and power supply for your server. It would be 30 years before you paid the cost of that Dell, so unless you actually need that power and your time is free, it's easier to let this be a tiny fraction of Amazon's expenses and workload than a big part of yours.

The $15,000 Dell being discussed is equivalent to a m4.16xlarge with 64 threads and 256 gigs of RAM. The m4.large you're referencing at $45/mo only has 2 CPUs and 8 gigs of RAM.

Not all instances are the same. You can't run a database on an m4.large, not any database you plan on running queries on.

So you need that m4.16xlarge to handle the load, and honestly, there's no single instance available on Amazon that I've found that can come anywhere near the performance of physical hardware when it comes to handling database loads. Right now I am running ten r4.16xlarge instances to do the job of two Dell R710s, at considerably reduced performance even still.

I guess our use cases are just different. Mind sharing some examples of your use case that demands that much compute power?

I do run a database on my server (which isn't even a Large) for an e-commerce site. It fits handily in half a gig of ram. The hundreds of products we offer have associated images, but we just store the filenames in the database and they load from disk (or, more likely, Cloudflare cache). Honestly, it could be a static site but the database is a convenient way to edit the content and control the presentation.

You have 640 CPUs running at multiple gigahertz and trillions of bytes of RAM. What kind of workload requires that insane amount of compute power?

We have billions of rows of data and very complicated CTEs doing joins on a dozen tables matching based on GEOS radius data, and it's the primary query for our application. We're running PostgreSQL 9.5 and need to have all the data in memory for the fastest results.

Part of the problem is that the network disk that EC2 provides as EBS is 100x slower than local disk, so keeping all the indexes and data in memory is the only way to replicate physical hardware performance.

If anyone knows of a better EC2 setup for PostgreSQL, I'm all ears.

> Part of the problem is that the network disk that EC2 provides as EBS is 100x slower than local disk, so keeping all the indexes and data in memory is the only way to replicate physical hardware performance.

> If anyone knows of a better EC2 setup for PostgreSQL, I'm all ears.

Have a proper replication & archiving setup, and use instance storage. If you have configured streaming replication to 1-2 other servers, and archive your WAL to s3 (using wal-e or such), you're already above EBS's guarantees (99.9% durability IIRC?).

Instance storage is much more limited and is heavily tied to the specific instance types you pick.

Indeed. I didn't want to say it's a panacea, just that you can sometimes get a lot better performance for your money. E.g. larger i3's both have decent IO performance and sizes.

Still doesn't even remotely compete with what you can get with "normal" hardware.

This is why I claim a hybrid model is the way to go. Your baseline/mean load should be on redundant dedicated hardware with spill-over into a cloud provider.

> For example: A dedicated m4.16xLarge EC2 instance in AWS is $3987/month. You could build that same server for $15,000 through Dell, lease it at $400/month (OpEx), and colo it with a 1GB/s connection for $150/month.

If this is all you see when it comes getting servers or working with Cloud servers/services, then you don't know what you are talking about.

You don't build for one massive single server, you build for a bunch of small ones that spin up and down as needed. It's micro services or you are wasting your time and money.