Ask HN: Is your company sticking to on-premise servers? Why?

I always find it important to separate "cloud" into 2 categories:

1. IaaS - Which I mainly define as the raw programmable resources provided by "hypercloud" providers (AWS, GCP, Azure). Yes, it seems that using an IaaS provider with a VPC can provide many benefits over traditional on-prem data centers (racking & stacking, dual power supply, physical security, elasticity, programmability, locations etc).

2. SaaS - I lump all of the other applications by the hundreds of thousands of vendors into this category. I find it hard to trust these vendors the same way that I trust IaaS providers and am much more cautious of using these applications (vs OSS or "on-prem software" versions of these apps). They just don't have the same level of security controls in place as the largest IaaS providers can & do (plus the data is structured in a way that is more easily analyzed, consumed by prying eyes).

Small company here (30 total people, 8 in IT/software).

- unwillingness to seed control of the critical parts of our software infrastructure to a third party.

- given our small team size and our technical debt load we are not currently able to re-architect to make our software cloud-ready/resilient.

- true cost estimates feel daunting to calculate, whereas on-prem costs are fairly easy to calculate.

I wrote about it here:

https://aravindh.net/post/sysadmin/

> What form do these jobs have?

Mostly batch jobs written as bash scripts. Occasionally, some users run singularity containers. But, all through SLURM.

> How do you manage workloads?

SLURM

> How do you manage resources?

As a sysadmin, my inventory is via Ansible. All activity on servers happen via Ansible only.

> Do users have quota for compute and storage?

Yes, Users typically can run 72 cores, 512 GiB of mem at a time. Rest is queued until resources are released. Disk quota is only for home directories - 400GiB(enforced by ZFS refquota).

> Do you use GPUs? If so, how do you deal with malfunction?

No, weirdly our workloads(genetics and genomics) don’t fit the GPUs very well, as they are sparse matrix walks with wide precision floats. But, we plan to try for some other stuff soon.

> Is this a distributed processing?

No. Jobs run one node at a time.

> Are the machines heterogeneous?

Yes, inteL based servers all the way from Haswell to Cascade lake.

> What do you use for that cluster?

SLURM

> What if a job requires dependencies?

Taken care of by SLURM.

> Do you create a compute environment on the fly or do all jobs have the same dependencies and these don't change much?

I guess you mean the software libraries and tools that jobs use? If so, our central software repo is NFS mounted on all compute nodes. Users can install things they need if admin priv is not needed. If not either Singularity or email to me.

> How do you do data governance?

This is the painful and human oriented task. We lock down data transport to outside world, educate the users about data policies and then spend a lot of time looking at data flows with hope.

> Is the data read only? Do you have an API to fetch the data from the job code?

Sorry, I could not understand this question. Do you mean metadata about A job?

Unfortunately I don't have exact numbers, having never been responsible for the budget of those. This is only an estimation considering the pricing I see from the cloud providers, and the rates I know from my fellow contractors.

Besides, I'm not exactly trying to win a war here. Simply trying to know under which circumstances it is better to go for on-prem vs public cloud.

I was referring to the IaaS in this question.

As for the SaaS, I guess your mileage may vary. I trust some of them really make a point of securing your data :)