With ten years industry experience, Amy Arambulo Negrette builds APIs for enterprise clients for a cloud consulting firm and leads a team of other Cloud Software Engineers.
ServerlessConf: Managing your Serverless Servers
The backbone of serverless architecture is using Functions as a Service to handle your logic needs. This is done by spinning up containers to run these functions on demand. For many use cases, this would be enough. Other times, you would need to manage small configurations such as time outs and memory. More often, a developer needs to use third-party libraries or a company built and maintained library. For small changes, the timeout and memory can be adjusted through configuration settings with the cloud provider such as AWS Lambda or Google Cloud Functions. To import third-party or other pre-built libraries, cloud providers will accept deployment packages that can be uploaded with a zip file or other deployment procedure after building the package locally. AWS has also introduced Layers as a way of having a standard way of deploying libraries to already existing runtimes. In more complicated scenarios, such as an IT Department requirement that any runtime be ‘blessed’ or maintaining a golden archive of runtimes, a combination of OpenWhisk and Docker Blackbox can allow you to choose your own runtime. This talk will go over all of these options, how to choose which is the best for your particular use case, and how to implement them.
For traditional application engineers with a few years under their belt, technology trends like Serverless come and go. It’s hard to get excited if you’ve already lost time and energy to a trend that never got adopted. This talk will go over common arguments and open a path to Serverless Adoption.
Serverless ETLs Three Ways
ETLs are a staple in application development and data engineering, and AWS offers multiple solutions depending on your need. In this session, you walk through a developer experience evolving an ETL with changing customer requirements. Beginning with a bare-bones, single Lambda function, the experience grows into a more sophisticated single-read ETL solution, and finally an upgrade to Amazon Athena for a more intuitive batch solution that doesn’t destroy your source with use. Each solution is serverless but inherently different in design and intent, and you’ll learn the advantages and failings of each.