Asynchronous Data Streams with RxJava

Mesos + Singularity: PaaS automation & Sustainable Development Velocity for mortals

Singularity is an open source, battle-tested framework for Mesos Clusters. It combines distributed job scheduling and lifecycle automation of resilient microservices. It is ideal for building PaaS infrastructures that can help high growth companies to sustain development velocity by significantly reducing the operational complexity and deployment friction. In this presentation, we share our experiences in developing the HubSpot PaaS / Deploy pipeline and in moving all our QA and production environment to Mesos. Our key goals are: a) to demonstrate that Mesos clusters provide a mature, safe and proven solution for deploying highly available, complex software architectures comprised of thousands of components, b) to prove that Mesos clusters are not only for the big boys and invite medium size companies to follow HubSpot example and start reaping the benefits of Mesos.

Warehouse-scale computing with Mesos and Singularity: PaaS Infrastructure Automation and sustainable development velocity

Use mesos and singularity to automate infrastructure, remove service deployment frictions and sustain the development velocity of your product

Large Scale Mission-Critical Service and Job Deployment with Singularity

Use Singularity, a mesos framework, to automate the deployment of microservices, scheduled jobs, workers and on-demand processes in mesos clusters.

Delivering a "Big Data Ready" Minimum Viable Product

In most cases talking about big data follows an "a posteriori" view where an organization overwhelmed by huge amounts of log files and numerous data sources scattered among its departments decides to put some order to the mess and get some value out of the "big data", usually building a Hadoop cluster. In this presentation I take the opposite direction and try to demonstrate how to proactively design and build product architectures that manage to remain simple and lean while at the same time anticipate the big data complexities and solve them easily and elegantly from day one.