S Aerni, S Ramanujam and J Vawdrey present approaches and open source tools for wrangling and modeling massive datasets, scaling Java applications for NLP on MPP through PL/Java and much more.
Hans Dockter discusses how to solve the challenges of standardization, dependency management, multi-language builds, and automatic build infrastructure provisioning.
Rick Hudson discusses the motivation, performance, and technical challenges of Go's low latency concurrent GC and why the approach fits Go well.
Erran Berger discusses how they scaled architecture at LinkedIn across multiple data centers.
Stuart Bargon discusses how to “descale” an organization, removing the extra weight and making it agile, showcasing the transformation of one of the oldest Australian public institutions.
Danny Yuan discusses how Uber uses stream processing to solve a wide range of problems, including real-time aggregation and prediction on geospatial time series, and much more.
Nicolas Frankel demoes some of the many important Non-Functional Requirements out-of-the-box that come with Spring Boot: monitoring, metrics, exposing those over HTTP.
Emad Benjamin covers various GC tuning techniques and how to best build platform engineered systems; in particular the focus is on tuning large scale JVM deployments.
Mitchell Hashimoto shows how Terraform and Consul can be used together to easily deploy and scale large-scale containerized workloads using container runtimes like Docker.
Chris Dennis and Alex Snaps discuss introducing caching into a Spring application to solve real world problems.
Jason McCreary takes a look at using background job processes, messaging queues, and cache to help an application scale.
Atlassian Hybrid Cloud/On-Premise Software Delivery and the Journey to 300,000 Applications in the Cloud
George Barnett discusses techniques for building the supporting infrastructure for a hybrid model, and how to make monitoring, deployment tools, and shared services work effectively.