Applied Research
Despite the advantages to leveraging the Azure AI Marketplace for some use cases, there are many scenarios in which performing Fine-Tuning, Deep Learning and MLops on your local hardware is preferable to performing the same in the cloud. In my experience, this often includes one or more of the following: Now, my prediction is that…
Read More “Deploying Locally Trained LLM & ML Assets to Azure” »
In the previous article (The Big Data SIEM: Ingestion Layer with Azure) we establish a baseline of principles with which to ingest data at the multiple petabyte per day scale. Though many aspects align to lessons learned in review of Azure’s Well Architected Framework(WAF), we include our recommendations for API client calls, data transformations, team…
In our previous article (The Big Data SIEM), we opened the series with a tongue and cheek scenario, a detailed use-case and general overview of the basic four layers to the big-data SIEM as we (Tyson Barber and Tyler G.) like to frame them in the minds of decision makers on these types of projects….
You’ve just gotten into the office on a Monday and your CISO has pulled you into a meeting. The board has decided you’re moving your SIEM off of Splunk (Elastic, Rapid7, etc.) to save money…
A case study and recommended Azure cloud architecture, designed to enrich data and train machine learning models with industrial IoT production data.
A case study and simple hybrid (public/private) cloud architecture, designed to join Azure capabilities with on-premises computing clusters.
Resources, tools and advice with the benefit of hindsight having recently passed the AZ-104.
$ whoami: A general, high-level overview of the career, goals and direction of the author.
