Presentations
Debugging a deadlocking Python process can be a very frustrating issue, especially if it occurs infrequently or on code running remotely or in production. In those situations having a working knowledge of GDB, GDB Python Extensions, and strace is very helpful.
This talk explores what to do in those situations specifically for Python, but the techniques should be applicable to other intepreted languages with C based interpreters.
This session will cover the two main approaches to managing infrastructure and services, declarative/model based, and procedural/run-book approach, where they are both useful and how they can work together. We will give an overview of some of the tooling available such as Puppet and Chef, and various workflow options.
The typical workflow for delivering an application on top of Kubernetes involves managing a bunch of manifest files in your Git repositories, and writing new manifests usually means copying lots of boilerplate. There are no standard ways to share and manage what’s running in your cluster. Enter Helm, a tool that streamlines the creation, deployment and management of Kubernetes-native applications. In this demo-led session, members of the CNCF Helm team show you how you can use Helm to improve your deployment workflows.
Covering an overview of the various options and choices for setting up and deploying your applications and services to a public cloud. We will be using Amazon Web Services as the reference example, but most content will be applicable to other public clouds such as Azure and GCP.
This session will detail how to deploy a multi-service application in Kubernetes, using Pulp as the example. Pulp is a multi-service web application that manages repositories of content, such as software packages, and makes it available for installation. With a REST API, async worker processes, a scheduler process, and a service to curate job queues, Pulp is a natural fit for the orchestration provided by Kubernetes.
You will learn to manage shared persistent storage, scale individual services, and configure a "traditional" app not originally designed for containers.
Hey, I’m an application developer and I’m done managing my server infrastructure. Stop slowing me down. Application developers are sick and tired of being slowed down by having to learn new tasks and care about mundane details. I don’t care about server infrastructure. In fact, I hate DevOps! I don’t need to worry about the differences between cloud and a data center; the applications I create are brilliant, running them is not my job. Let’s talk about walls and boundaries. You do your job, I’ll do mine, and we can both get back to moving fast.
Network Mapper (Nmap) is an open source utility that allows the user to gain insight into the network operating system. This tool sends its own raw packet to the host and records and analyzes its response, obtaining info regarding the host and services on the OS, firewalls, and current state of the computer. Developers have implemented scripts to evolve Nmap's service and vulnerability detections, redirection services, and more. Nmap can be used to infiltrate networks, but more importantly serves as a crucial line of defense for students who aim to be system and network administrators.
Traditional machine learning solutions are massive batch processes where data is accumulated and analyzed as whole. This means days, weeks or even months before taking advantage of new data. Using Lambda Architecture, Ticketmaster has adopted open source tools for a data sciences infrastructure that can make decisions *and learn* in realtime.
Thought Leaders. DevOps Heroes. Public Speakers. We listen to them as they talk about their solutions, their approaches, and their inevitable triumphs. But are we starting down a dark path, as we forget that 'what makes a great talk' and 'what makes sense for your environment' may not be the same thing?