Matt Asay
Contributor
Matt Asay runs evangelism at MongoDB. Previously. Asay was a Principal at Amazon Web Services and Head of Developer Ecosystem for Adobe. Prior to Adobe, Asay held a range of roles at open source companies: VP of business development, marketing, and community at MongoDB; VP of business development at real-time analytics company Nodeable (acquired by Appcelerator); VP of business development and interim CEO at mobile HTML5 start-up Strobe (acquired by Facebook); COO at Canonical, the Ubuntu Linux company; and head of the Americas at Alfresco, a content management startup. Asay is an emeritus board member of the Open Source Initiative (OSI) and holds a J.D. from Stanford, where he focused on open source and other IP licensing issues.
Google gets boring
Joining the ranks of the predictable, dependable software companies, Google Cloud focuses its strategy on broader enterprise issues.
The best way to go ‘all in’ on cloud
Banks are finally realizing that cloud offers a lot of benefits they can’t replicate in their own data centers. But lock-in with one vendor has its own risks.
Where AI has made real progress
Better data infrastructure has provided a big boost to AI’s growth, but some things still require a human.
Don’t rush to machine learning
A simpler approach—good data, SQL queries, if/then statements—often gets the job done.
GitLab’s S-1 points to an integrated devops future
GitLab prepares to go public, offering a way for devops, security, IT, and business teams to collaborate on software development.
The future of Rust
The Rustacean Principles are more than feel-good ideas. They are a key part of why developers keep giving Rust the crown.
Open source is selfish
Companies don't support open source for purely altruistic reasons. They expect a return on their investment.
What you don’t know about working with AWS
You’ll get further by understanding what a company values and what makes its employees tick.
How cloud services get built today
Taking a great open source project and building it into a product people will pay for require skills in development and operations.
The long, long reigns of popular databases
Database popularity rises and falls over decades, not years. The databases that developers are interested in trying today may permeate the enterprises of the future.
Data science needs drudges
Quality data science outputs depend on quality inputs. Data cleansing and preparing may not be exciting work, but it’s critical.
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