> I'm curious how many engineers per year this costs to maintain
The end of the article has this:
> Consider custom infrastructure when you have both: sufficient scale for meaningful cost savings, and specific constraints that enable a simple solution. The engineering effort to build and maintain your system must be less than the infrastructure costs it eliminates. In our case, specific requirements (ephemeral storage, loss tolerance, S3 fallback) let us build something simple enough that maintenance costs stay low. Without both factors, stick with managed services.
And I am curious how many engineer years it requires to port code to cloud services and deal with multiple issues you cannot even debug due to not having root privileges in the cloud.
Without cloud, saving a file is as simple as "with open(...) as f: f.write(data)" + adding a record to DB. And no weird network issues to debug.
> as simple as "with open(...) as f: f.write(data)"
Save where?
With what redundancy?
With what access policies?
With what backup strategy?
With what network topology?
With what storage equipment and file system and HVAC system and...
Without on-prem, saving a file is as simple as s3.put_object() !
>> Without cloud, saving a file is as simple as "with open(...) as f: f.write(data)" + adding a record to DB.
> Save where? With what redundancy? With what access policies? With what backup strategy? With what network topology? With what storage equipment and file system and HVAC system and...
Most of these concerns can be addressed with ZFS[0] provided by FreeBSD systems hosted in triple-A data centers.
> Save where? With what redundancy? With what access policies? With what backup strategy? With what network topology? With what storage equipment and file system and HVAC system and...
Wow that's a lot to learn before using s3... I wonder how much it costs in salaries.
> With what network topology?
You don't need to care about this when using SSDs/HDDs.
> With what access policies?
Whichever is defined in your code, no restrictions unlike in S3. No need to study complicated AWS documentation and navigate through multiple consoles (this also costs you salaries by the way). No risk of leaking files due to misconfigured cloud services.
> With what backup strategy?
Automatically backed up with rest of your server data, no need to spend time on this.
>> No risk of leaking files due to misconfigured cloud services.
> One misconfigured .htaccess file for example, could result in leaking files.
I don't think you are making a compelling case here, since both scenarios result in an undesirable exposure. Unless your point is both cloud services and local file systems can be equally exploited?
It sounds like you’re not at the scale where cloud storage is obviously useful. By the time you definitely need S3/GCS you have problems making sure files are accessible everywhere. “Grep” is a ludicrous proposition against large blob stores
I inherited an S3 bucket where hundreds of thousands of files were written to the bucket root. Every filename was just a uuid. ls might work after waiting to page though to get every file. To grep you would need to download 5 TB.
It's probably going to be dog slow. I dealt with HDDs where just iterating through all files and directories takes hours, and network storage is going to be even slower at this scale.
You can't ever definitively answer most of those questions on someone else's cloud. You just take Amazons word for whatever number of nines they claim it has.
Bro were you off grid last week. Your questions equally apply to AWS, you just magically handwave away all those questions as if AWS/GCP/Azure outages aren’t a thing.
> Without cloud, saving a file is as simple as "with open(...) as f: f.write(data)" + adding a record to DB. And no weird network issues to debug.
There may be some additional features that S3 has over a direct filesystem write to a SSD in your closet. The people paying for cloud spend are paying for those features.
Ah that is where logging and traceability comes in! But not to worry, the cloud has excellent tools for that! The fact that logging and tracing will become half your cloud cost, oh well let's just sweep that under the rug.
What I notice, that large companies use their own private cloud and datacenters. At their scale, it is cheaper to have their own storage. As a side business, they also sell cloud services themselves. And small companies probably don't have that much data to justify paying for a cloud instead of buying several SSDs/HDDs or creating SMB share on their Windows server.
