Matt Asay
Contributor
Matt Asay runs partner marketing 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.
The uber-importance of docs
It doesn’t matter how great your software is if nobody understands how or why they should use it.
GitHub Copilot isn’t changing the future
AI-driven software development is great. But don’t lose sight of all the things it can’t do yet.
The real successes of AI
Despite the hype, especially around self-driving cars, AI is writing code, designing Google chip floor plans, and telling us how much to trust it.
How the cloud and big compute are remaking HPC
High-performance computing projects require massive quantities of compute resources. Pairing simulation and specialized hardware with the cloud powers the breakthroughs of the future.
Another day, another multi-billion IPO for open source
Investment in open source technologies and companies has been going strong for more than two decades. If anything, it keeps accelerating, along with the innovation.
The wrong way to think about cloud computing
Moving workloads in and out of the cloud isn’t really possible—or a good idea.
Excel, Python, and the future of data science
If the ubiquitous spreadsheet program is the gateway to data science, Python aims to be the next step.
Snowflake pushes back at… whom?
Making great efforts to tout its closed source software, Snowflake may be trying to convince an audience that doesn't really care.
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