Taming Infrastructure Workflow at Scale
RootConf Hyderabad 2019
As more operations choices are added to your data center, whether through company acquisitions, a growing development team, or general technical debt, managing infrastructure complexity becomes a nightmare. Yet the end goal is still the same — safely deploy your application to your infrastructure. We need to tame our data centers by managing change across systems, enforcing policies, and by establishing a workflow for both developers and operations engineers to build in a collaborative environment. This talk will discuss the problems faced in managing a modern cloud infrastructure, and how a set of innovative open source tools like Terraform can be used to tame the rising complexity curve. Join me as I take you on a journey of exploring Infrastructure as Code techniques as we take control of our cloud infrastructure. This goal of this demo driven talk is to showcase how you can build multi-tier application infrastructure supporting multiple cloud platforms and services using IAC.
HCL: A human-friendly language for developers and operators
OSCON 2019
In 2018, HashiCorp Configuration Language (HCL) was second on GitHub’s list of fastest-growing languages. Anubhav Mishra explores the history behind the creation of HCL and explains what has made it a popular language of choice, used by tools like HashiCorp Terraform and GitHub Actions. Along the way, he details the language’s syntax and engine behind HCL and showcases real-world examples using HCL to express production infrastructure, and outlines the benefits of doing so. Live demos include: * Using HCL as the language for operators practicing infrastructure as code using Terraform * Using HCL as the language for developers using GitHub Actions to create an end-to-end pipeline for their organization
Secrets Store CSI Driver - Bring Your Own Enterprise Secrets Store to K8s
KubeCon + CloudNativeCon EU 2019
So you are running your applications in Kubernetes, but you already have a solution for managing and storing all your application secrets. How do you tell Kubernetes to use the same source of truth for secrets? Meet Secrets Store CSI driver, a simple way to retrieve sensitive data from enterprise-grade external stores such as Azure Key Vault and HashiCorp Vault using volumes. Learn how to use Secrets Store CSI Driver to mount secrets, keys, and certs stored in common external stores into their Kubernetes applications using a volume. We will also look at how you can add your own external secret store via the provider interface.
Intro: Virtual Kubelet
KubeCon + CloudNativeCon EU 2019
Virtual Kubelet has most recently been accepted into the CNCF as a sandboxed project. In this session we will go through the benefits of the project and the landscape of providers that contribute to VK in the open. We will highlight the HashiCorp Nomad provider and the Azure provider for Azure Container Instances. Folks can expect to learn about three different use-cases for Virtual Kubelet including, burst capacity, abstraction of infrastructure, and translating any APIs into Kubernetes APIs. We hope to spark new ideas, and conversation by bringing up a new way to connect Kubernetes to "any" service or technology.
Scheduling Applications at Scale with Nomad
Open Source Summit North America 2019
Scheduler frameworks enable reliable and repeatable application deploys. In this session, attendees will use Nomad, a single binary cluster scheduler, to build a multi-region, self-healing production environment that runs a diverse set of workloads. They will also get hands on experience in writing and submitting job specifications, interacting with the API, and deployment strategies. This session will cover the following: * Nomad Overview * Installing and Configuring Nomad * Creating, Running, and Inspecting Jobs * Service Registration * Interacting via the HTTP API * Advanced Job Strategies (rolling updates, blue-green) * Failure simulation In second part of this session, we will spend time destructively testing applications scheduled in Nomad by injecting failures like process failure, machine failure, network connectivity issues, loss of quorum that can happen in production.