KubeCon EU 2016: Full Automatic Database: PostgreSQL HA with Kubernetes

Mar 21, 20164 likes1,984 views

Why pay for always-on relational database service when you can deploy it yourself so easily? This demo-heavy talk will show off a deceptively simple high availability stack for PostgreSQL, using Docker, Etcd, Kubernetes, Patroni and Atomic. Not only is this open source solution ready to go to give you HA Postgres right now, it represents an approach which can be adapted to other relational databases with replication. Sched Link: http://sched.co/6BV4

Full
Auto
Database
Josh Berkus
Red Hat Project Atomic
KubeCon.EU 2016

KubeCon EU 2016: Full Automatic Database: PostgreSQL HA with Kubernetes

Single Master DBs:
Problem
low availability
unidirectional replication
very manual HA solutions

Why not multimaster
DBs?
just moving the problem around
"eventual" consistency
network lag
maturity issues
feature poverty
app compatibility

But PG Replicaton is
Awesome!
Easy to set up
Guaranteed
Corruptionfree
Antifootgun
Combines with DR

"Automated
failover is too
complicated.
You don't want
it."

Hard != Impossible
general autofailover is prohibitive
but ... we can implement common
use cases

The 80% Solution
1. Pool of async replicas
2. Cheap/replacable nodes
Containers
3. Watchdog service
4. Autopromote one replica
5. Other nodes remaster
6. Update routing

Handyrep
mastercontroller architecture
based on Python Fabric + SSH
worked in production
worked with any Postgres config
pluggable
www.handyrep.org

Handyrep: too general
Difficult to install
Difficult to debug
Over 100 configuration options
Scaled poorly
HR server was SPoF

Zalando
no1 European online fashion
15m customers
150 databases
24/7/365 operation
... needed automated,
decentralized HA

False failover
Misfires
Race
conditions
Failover Failure

Split Brain and SM
DBs
worst possible outcome
automated recovery impossible
manual recovery painful

1. Postgres is a poor store of its own
replication state
2. Smart agents > topdown
controllers

Compose Governor
Containers
Etcdbased consensus
Simple PostgreSQL controller
... so we forked it.

failover est omnis divisa in
partes tres

Patroni controller
Python daemon
Runs in each container as PID 1
Controls Postgres
startup/shutdown/config
Provides external REST API
Enforces opinionated config

Etcd
distributed consensus HTTP data
store
Raft algoritm
implements CA
great for config + metadata
not for data data

Etcd Alternatives
Zookeeper
larger scale
supported
Consul
integrates discovery
not (yet) suppported

What's AtomicDB?
WIP project
PostgreSQL
Patroni
Atomic Host
Kubernetes
Dynamic proxy (dev)
Cockpit UI (dev)

The Proxy Problem
differentiate master and readonly
connections
master service needs to follow
failover
failover logic too complex for
kubernetes (1.1)

pgbouncer?
current implementation in
pgbouncer
master, read slaves separate
services/ports
depends on flannel LB
not good enough. Waiting for
1.2/1.3!

More features
pg_rewind support (9.4+)
configurable node imaging
WALE
PITR
synchronous replication
nonfailover replicas

More Stuff Under
development
cascading replication
integrated proxy
BDR support?
fork us on Github!

Resources
This Presentation:
jberkus.github.io/full_auto_db
Patroni Project:
github.com/zalando/patroni
AtomicDB Project:
github.com/jberkus/atomicdb

more
jberkus:
project
atomic:

@fuzzychef
www.databasesoup.com
www.projectatomic.io
RedHat booth for
Cockpit Kube demo
¿questions?

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The building industry in the world today is at large, far behind the rest of the world, technically. Alongside this, it is at threat of being dominated by a small selection of software vendors. These vendors push specific software solutions to the technically unskilled consumers in the AEC industry. The software they provide however is monolithic, native and heavy. Containers, distributed computing, and open source microservices and applications offer a solution to turn the construction industries future on its head. When computing is ubiquitous in our buildings with the internet of things, the whole way we think about building design has to change. We need to think in advance about how our applications which will run our buildings are developed. Each building is bespoke and the offers currently on the software market simply wont fit the bill in the near future. We are trying to develop a kubernetes based platform to lay the foundations for the future of lightweight bespoke apps developed for our built environment. Sched Link:

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ChatOps is a term often credited to GitHub, and it is all about putting the tools in the middle of the conversations. At Unacast, most of our conversations go through Slack. When we integrated ChatOps into our workflow, we got the tools closer to the conversation. We are using a version of GitHub Flow for our development process. That means all new features goes in a branch, someone opens a pull request and we merge continuously from master into the feature branch. When we have something that is ready to deploy to a server we trigger a deploy of the branch to a test environment. When the new feature gets verified it gets deployed to production, gets verified again, and then merged back into master. This workflow enables us to maintain a clean master branch so we can roll back in case something fails. Sched Link: http://sched.co/67c1

KubeCon EU 2016: A Practical Guide to Container SchedulingKubeAcademy

Containers are at the forefront of a new wave of technology innovation but the methods for scheduling and managing them are still new to most developers. In this talk we'll look at the kind of problems that container scheduling solves and at how maximising efficiency and maiximising QoS don't have to be exclusive goals. We'll take a behind the scenes look at the Kubernetes scheduler: How does it prioritize? What about node selection and external dependencies? How do you schedule based on your own specific needs? How does it scale and what’s in it both for developers already using containers and for those that aren't? We’ll use a combination of slides, code, demos to answer all these questions and hopefully all of yours. Sched Link: http://sched.co/6BZa

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Being able to trust your containers requires that you be able to trust the systems your containers are running on. Trusted computing makes it possible for computers to prove what they’ve booted, making it practical for clusters to verify that systems haven’t been compromised, but up until now it’s been a heroic task to deploy a trusted computing environment. This presentation will describe the integration of trusted computing technologies into Kubernetes, making it possible to define policies that provide fine-grained access control to cluster resources and distribute secrets in a secure manner. It will then introduce functionality added to the rkt runtime, making it possible to extend trusted computing from initial system state to validation of individual containers. Sched Link: http://sched.co/67eX

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One of the most underrated features of Kubernetes is namespaces. In the market, instead of using this feature, people are still stuck with having different clusters for their environments. This talk will try to break this approach, and will introduce how we end up using ephemeral namespaces within our CI/CD pipeline. It will cover the architecture of our system for running the user acceptance tests on isolated ephemeral namespaces with every bits and pieces running within pods. While doing this, we will set up our CI/CD pipeline on top of TravisCI, GoCD, and Selenium that is controlled by Nightwatch.js. Sched Link: http://sched.co/6Bcb

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Arkena's video-on-demand platform is used as backend by major european channels (TF1 / beIN SPORTS / Elisa) to propose a non-linear experience to their customers. Previously hosted on Heroku, the number of our users is increasing constantly. In order to optimize resources we decided to move on a bare metal infrastructure powered by Kubernetes. We'll share thoughts, feedbacks and technical details about this successful transition. Sched Link:

KubeCon EU 2016: Transforming the Government KubeAcademy

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When you hear words such as Kubernetes or OpenShift you immediately start thinking about long running processes you can easily scale at will. However, Kubernetes includes a lesser known feature which allows you to run pretty much anything from simple tasks up to highly-complicated ones. During this presentation, the author of the Job resource in Kubernetes will guide you through several techniques for performing anything ranging from simple Pi calculations to rendering a movie. No matter if you're a data scientist running large scale calculations across several data centers or a hobby programmer running simple day-to-day tasks, this presentation is to teach you how to efficiently use Kubernetes Jobs on their own or as the building blocks of something bigger. This presentation will feature a number of live demos to help illustrate the various ways that you can put Jobs to work. Don’t miss out on learning about one of the coolest features of Kubernetes! Sched Link: http://sched.co/6BUw

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Testing applications is important, as shown by the rise of continuous integration and automated testing. In this talk, I will focus on one area of testing that is difficult to automate: poor network connectivity. Developers usually work within reliable networking conditions so they might not notice issues that arise in other networking conditions. I will give examples of software that would benefit from test scenarios with varying connectivity. I will explain how traffic control on Linux can help to simulate various network connectivity. Finally, I will run a demo showing how an application running in Kubernetes behaves when changing network parameters. Sched Link: http://sched.co/6Bb3

KubeCon EU 2016: Kubernetes in Production in The New York Times newsroomKubeAcademy

The New York Times’ is a US media company serves digital journalism to millions of visitors every day. The format of our stories is constantly experimented with; for example we publish graphics based on election data ingested from APIs, question and answer led discussions, breaking news live coverage, and quizzes. This leads to a lot of applications. Our previous experience with infrastructure may be a familiar one: an unruly number of virtual machines, which led us to containers. Containers give our web developers who are not infrastructure engineers the opportunity to configure and launch their applications with little oversight. Kubernetes offers us an infrastructure for our numerous applications at scale. Leveraging the Kubernetes API, we’ve built a self-service admin interface for developers (not sysadmins) to configure and launch their applications at scale, similar to the Kubernetes Dashboard project, tailored to our development workflow. Sched Link: http://sched.co/67f2

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With growing demand for containers in the enterprise, build pipelines are a bottleneck to success. Traditional workflows can't release application candidates quickly enough to fulfill demand. With over 400 development teams across many different business units, Pearson had to move away from massive installs of traditional build pipeline tools and rethink the entire concept. In this talk we'll demonstrate how we have built in security compliance, performance testing, quality assurance, abstracted away complexity, reduced overhead, aim to recover 10% of developers time and turned build tools into cattle. This represents the story to date of an in-flight engineering project to modernise the digital estate of a global enterprise organisation and how scale of the operation is leading us to challenge many established beliefs. Attendees will walk away with everything from workflows to code which they can use to get started in their own endeavors. Sched Link:

KubeCon EU 2016: SmartCity IoT on KubernetesKubeAcademy

Modern cities are rapidly adopting smart technologies to deliver realtime data about a number of city services. These technologies heavily rely on a high quality network interconnecting all sensors and reactors as lamps with controlling services. Many low level PLC systems solve the automation, but their purpose is limited to narrow areas of usage as these device have limited computational power. On the other hand, the rise of single-board computers as Raspberry Pi with multi-core processors and plenty of memory can serve as a platform for virtualized services based on Kubernetes. The distributed cluster across whole city on public streetlights gives operators the possibility to adapt to rapidly changing conditions. We propose distribution of HA clusters of single-board devices in key topological points of smart city mesh networks connected together by reliable SDN network. These virtualized services fulfill various tasks as data collection, data processing or and all of these services can rely on cloud backends, that provide much more computational and storage capacity. Services can be operated at both locations to serve local as well as foreign users. We will share whole concept and architecture of SmartCity project, which covers deployment of more than 3000 endpoints[, both sensoric and reactive devices,] and about 30 smart gateways running in HA mode on Kubernetes Nodes. Sched Link: http://sched.co/6BUM

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Kubernetes gives developers a platform on which to run images and many configuration objects to control those images, but constructing a cohesive application made up of images and configuration objects is currently a challenge. Reconstructing or sharing that configuration can also be a challenge. This talk will cover the Template feature implemented in OpenShift to simplify the process of defining and repeatably deploying coordinated objects, discuss what is coming to Kubernetes with respect to this capability, and touch on several other existing projects that enable templatizing application definitions. Sched Link: http://sched.co/6BVH

KubeCon EU 2016 Keynote: Pushing Kubernetes ForwardKubeAcademy

The Kubernetes community has aspirations of becoming the Linux kernel of distributed systems. Together we want to build a scalable, stable, and secure platform for distributed system that is the ubiquitous choice for people building server infrastructure. This talk will discuss the major community efforts made in recent months to deliver this goal and the work we need to do to continue our momentum. Sched Link: http://sched.co/68lU

KubeCon EU 2016: Creating an Advanced Load Balancing Solution for Kubernetes ...KubeAcademy

Load balancing is an important part of any resilient web application. Kubernetes supports a few options for external load balancing, but they are limited in features. After a brief discussion of those options and the features they lack, we’ll show how to build an advanced load balancing solution for Kubernetes on top of NGINX, utilizing Kubernetes features including Ingress, Annotations, and ConfigMap. We’ll conclude with a demo of how to use NGINX and NGINX Plus to expose services to the Internet. Sched Link: http://sched.co/6Bc9

KubeCon EU 2016: Killing containers to make weather beautifulKubeAcademy

The Met Office Informatics Lab includes scientists, developers and designers. We build prototypes exploring new technologies to make environmental data useful. Here we describe a recent project to process multi-dimensional weather data to create a fully interactive 4D browser application. We used long-running containers to serve data and web pages and short-running processes to ingest and compress the data. Forecast data is issued every three hours so our data ingestion goes through regular and predictable bursts (i.e. perfect for autoscaling). We built a Kubernetes cluster in an AWS group which auto-scales based on load. We used replication controllers to process the data. Every three hours ingestion jobs are added to a queue and the number of ingestion containers are set in proportion to the queue length. Each worker completes exactly one ingestion job from the queue and then exits, at which point Kubernetes creates a new one to process the next message. This has allowed us to remove the lifespan logic from the containers and keep them light, fast and massively scalable. We are now in the process of using this in our production systems. Sched Link: http://sched.co/6BWQ

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