3 ms·
For our company we are in 2 phases. In the cloud, it's 'hair on fire'. MLOps is a hot space. For on-premises, MLOps is basically download MLFlow and Kubeflow an
by jamesblonde 3y ago
For our company we are in 2 phases.
In the cloud, it's 'hair on fire'. MLOps is a hot space.
For on-premises, MLOps is basically download MLFlow and Kubeflow and you think you're sorted. So it's the 'hard fact' segment.
- richardw 3y agoNot on premises who are regulated and might have enterprise requirements. If you need eg role based access control you can’t use on prem MLFlow etc. So you could niche down to customers who don’t know this yet. Smaller banks, insurers etc. Edit: we went through this. Started putzing around with open source things on prem on Openshift. Ended up on Databricks for a variety of reasons. The impact on the business to be wiring up lots of new widgets, maintaining them, training, ability to switch to new components when required. Lean team, so turn Databricks on and secure it properly, exclude PI where possible, sort out ETL and CICD etc, profit. Delegate MLOps stack innovation to the vendor and focus on our own job.
- deleted 3y ago[deleted]
- jamesblonde 3y agoThat's a typical journey we see for on-premises prospects.
- phillipcarter 3y agoYep, this journey is exactly the kind of thing I run into when I get prospects who want our product (observability) to be on-prem. What they actually want is assurances around data storage, retention, and controls; and a "throat to choke" to cover their asses in case something goes wrong. At least in this domain, very few people who need Observability actually need things to be on-prem as well.