Dynatrace
DECEMBER 8, 2021
You may be using serverless functions like AWS Lambda , Azure Functions , or Google Cloud Functions, or a container management service, such as Kubernetes. In contrast to modern software architecture, which uses distributed microservices, organizations historically structured their applications in a pattern known as “monolithic.”
O'Reilly
FEBRUARY 18, 2020
Software architecture, infrastructure, and operations are each changing rapidly. The shift to cloud native design is transforming both software architecture and infrastructure and operations. Also: infrastructure and operations is trending up, while DevOps is trending down. Coincidence?
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O'Reilly
MAY 19, 2020
O’Reilly Learning > We wanted to discover what our readers were doing with cloud, microservices, and other critical infrastructure and operations technologies. AWS is far and away the cloud leader, followed by Azure (at more than half of share) and Google Cloud. All told, we received 1,283 responses. .
Strategic Tech
JULY 21, 2020
Architecture modernisation tools and techniques for each phase (these lists are not exhaustive) Business Strategy Alignment Software architecture is the significant technical decisions that have business consequences. This means a software architecture should be purposely designed for the most favourable business consequences.
O'Reilly
NOVEMBER 12, 2019
Respondents who have implemented serverless made custom tooling the top tool choice—implying that vendors’ tools may not fully address what organizations need to deploy and manage a serverless infrastructure. A related point: the rise of the serverless paradigm coincides with what we’ve referred to elsewhere as “ Next Architecture.”
cdemi
FEBRUARY 20, 2017
Rapid Development - You can quickly deploy a function without having to worry about infrastructure resources and growth. Whether you choose Azure Functions or AWS Lambda, you cannot easily switch to another. Azure Functions don't have this restriction, but on AWS Lambda, functions are not allowed to run for longer than 5 minutes.
The Netflix TechBlog
DECEMBER 3, 2019
About two years ago, we, at our newly formed Machine Learning Infrastructure team started asking our data scientists a question: “What is the hardest thing for you as a data scientist at Netflix?” Our job as a Machine Learning Infrastructure team would therefore not be mainly about enabling new technical feats.
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