Remove Database Remove DevOps Remove Software Engineering Remove Training
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Cloudy with a high chance of DBMS: a 10-year prediction for enterprise-grade ML

The Morning Paper

Many of the software engineering discipline and controls need to be brought over into an ML context. The following chart breaks down features in three main areas: training and auditing, serving and deployment, and data management, across six systems. But model inference migrating into the DBMS is a bolder prediction.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. Can’t we just fold it into existing DevOps best practices?

DevOps 138
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USENIX LISA 2018: CFP Now Open

Brendan Gregg

Today's LISA attracts attendees working on all sizes of production systems, and its attendees include sysadmins, systems engineers, SREs, DevOps engineers, software engineers, IT managers, security engineers, network administrators, researchers, students, and more. Hope to see you in Nashville!

DevOps 43
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USENIX LISA 2018: CFP Now Open

Brendan Gregg

Today's LISA attracts attendees working on all sizes of production systems, and its attendees include sysadmins, systems engineers, SREs, DevOps engineers, software engineers, IT managers, security engineers, network administrators, researchers, students, and more. Hope to see you in Nashville!

DevOps 40
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Microservices Adoption in 2020

O'Reilly

Software engineers comprise the survey audience’s single largest cluster, over one quarter (27%) of respondents (Figure 1). software and systems architects, technical leads—architects represent almost 28% of the sample. Use of a Central, Managed Database. Respondent Demographics. Figure 1: Respondent roles.

Database 135