Serverless
Serverless computing is a cloud-computing execution model in which the cloud provider dynamically manages the allocation of machine resources. Pricing is based on the actual amount of resources consumed by an application, rather than on pre-purchased units of capacity. It is a form of utility computing.
Serverless computing still requires servers, hence it's a misnomer. The name "serverless computing" is used because the server management and capacity planning decisions are completely hidden from the developer or operator. Serverless code can be used in conjunction with code deployed in traditional styles, such as microservices. Alternatively, applications can be written to be purely serverless and use no provisioned servers at all.
Source: https://en.wikipedia.org/wiki/Serverless_computing
Position on the Adoption Curve
Presentations about Serverless
The State of Serverless Computing
Building and Operating a Serverless Data Pipeline
The Not-So-Straightforward Road From Microservices to Serverless
Serverless - What to Know and How to Prepare
Knative Workshop
Knative Workshop
Serverless: JavaScript's Journey to the Edge (Workers)
Interviews
Building and Operating a Serverless Data Pipeline
What is the focus of your work these days?
I'm the lead of the data platform team at Intent. Intent is a data science company that helps commerce sites maximize the value for each person who visits their site. Our main product is an ad network that runs on travel sites. On the data platform team we oversee our data pipeline, that collects data from ad servers and various other sources, the processing of that data and storage of that data to a data lake. We also oversee data warehouses, and aggregation jobs that compute summaries of that data; making it available to various analysts and other business users. Our team is also responsible for automated reporting solutions for our publishers and advertisers.
What is the motivation for your talk?
To talk about our experiences at Intent building out our serverless data platform. Going from our legacy platform to this new data platform. Some of the wins that we experienced with that and also some of those pain points that we had during that transition. I also think that Serverless is becoming a bit of a buzzword so I think it’s worth clarifying what serverless is, and some of the benefits and tradeoffs.
