This document discusses cluster management and containerization. It describes the challenges of managing clusters at scale, including failures, maintenance, and utilization. It introduces Mesos as a modern cluster manager that can help address these challenges by coordinating resources across clusters and launching and monitoring tasks. Mesos provides a general purpose platform for scheduling different types of workloads like services, batch jobs, and streaming applications.
What is Apache Mesos and how to use it. A short introduction to distributed fault-tolerant systems with using ZooKeeper and Mesos. #installfest Prague 2014
Apache Mesos is the first open source cluster manager that handles the workload efficiently in a distributed environment through dynamic resource sharing and isolation.
Strata SC 2014: Apache Mesos as an SDK for Building Distributed FrameworksPaco Nathan
O'Reilly Media - Strata SC 2014
Apache Mesos is an open source cluster manager that provides efficient resource isolation for distributed frameworks—similar to Google’s “Borg” and “Omega” projects for warehouse scale computing. It is based on isolation features in the modern kernel: “cgroups” in Linux, “zones” in Solaris.
Google’s “Omega” research paper shows that while 80% of the jobs on a given cluster may be batch (e.g., MapReduce), 55-60% of cluster resources go toward services. The batch jobs on a cluster are the easy part—services are much more complex to schedule efficiently. However by mixing workloads, the overall problem of scheduling resources can be greatly improved.
Given the use of Mesos as the kernel for a “data center OS”, two additional open source components Chronos (like Unix “cron”) and Marathon (like Unix “init.d”) serve as the building blocks for creating distributed, fault-tolerant, highly-available apps at scale.
This talk will examine case studies of Mesos uses in production at scale: ranging from Twitter (100% on prem) to Airbnb (100% cloud), plus MediaCrossing, Categorize, HubSpot, etc. How have these organizations leveraged Mesos to build better, more scalable and efficient distributed apps? Lessons from the Mesos developer community show that one can port an existing framework with a wrapper in approximately 100 line of code. Moreover, an important lesson from Spark is that based on “data center OS” building blocks one can rewrite a distributed system much like Hadoop to be 100x faster within a relatively small amount of source code.
These case studies illustrate the obvious benefits over prior approaches based on virtualization: scalability, elasticity, fault-tolerance, high availability, improved utilization rates, etc. Less obvious outcomes also include: reduced time for engineers to ramp-up new services at scale; reduced latency between batch and services, enabling new high-ROI use cases; and enabling dev/test apps to run on a production cluster without disrupting operations.
Adobe has packaged HBase in Docker containers and uses Marathon and Mesos to schedule them—allowing them to decouple the HBase RegionServer from the host, express resource requirements declaratively, and open the door for unassisted real-time deployments, elastic (up and down) real-time scalability, and more.
Mesos: The Operating System for your DatacenterDavid Greenberg
Maybe you’ve heard of Mesos—that thing that you can run Hadoop on. I think it powers Twitter? Isn’t it an Apache project, or something?
In this talk, we’ll learn all about Mesos—what it is, how you can leverage it to simplify your infrastructure and reduce AWS/cloud computing costs, and why you should develop your next application on top of it. This talk will give you the tools you need to understand whether Mesos is the right fit for your infrastructure, and several starting points for learning more about Mesos.
Cassandra on Mesos Across Multiple Datacenters at Uber (Abhishek Verma) | C* ...DataStax
Traditionally, machines were statically partitioned across the different services at Uber. In an effort to increase the machine utilization, Uber has recently started transitioning most of its services, including the storage services, to run on top of Mesos. This presentation will describe the initial experience building and operating a framework for running Cassandra on top of Mesos running across multiple datacenters at Uber. This framework automates several Cassandra operations such as node repairs, addition of new nodes and backup/restore. It improves efficiency by co-locating CPU-intensive services as well as multiple Cassandra nodes on the same Mesos agent. It handles failure and restart of Mesos agents by using persistent volumes and dynamic reservations. This talk includes statistics about the number of Cassandra clusters in production, time taken to start a new cluster, add a new node, detect a node failure; and the observed Cassandra query throughput and latency.
About the Speaker
Abhishek Verma Software Engineer, Uber
Dr. Abhishek Verma is currently working on running Cassandra on top of Mesos at Uber. Prior to this, he worked on BorgMaster at Google and was the first author of the Borg paper published in Eurosys 2015. He received an MS in 2010 and a PhD in 2012 in Computer Science from the University of Illinois at Urbana-Champaign, during which he authored more than 20 publications in conferences, journals and books and presented tens of talks.
What is Apache Mesos and how to use it. A short introduction to distributed fault-tolerant systems with using ZooKeeper and Mesos. #installfest Prague 2014
Apache Mesos is the first open source cluster manager that handles the workload efficiently in a distributed environment through dynamic resource sharing and isolation.
Strata SC 2014: Apache Mesos as an SDK for Building Distributed FrameworksPaco Nathan
O'Reilly Media - Strata SC 2014
Apache Mesos is an open source cluster manager that provides efficient resource isolation for distributed frameworks—similar to Google’s “Borg” and “Omega” projects for warehouse scale computing. It is based on isolation features in the modern kernel: “cgroups” in Linux, “zones” in Solaris.
Google’s “Omega” research paper shows that while 80% of the jobs on a given cluster may be batch (e.g., MapReduce), 55-60% of cluster resources go toward services. The batch jobs on a cluster are the easy part—services are much more complex to schedule efficiently. However by mixing workloads, the overall problem of scheduling resources can be greatly improved.
Given the use of Mesos as the kernel for a “data center OS”, two additional open source components Chronos (like Unix “cron”) and Marathon (like Unix “init.d”) serve as the building blocks for creating distributed, fault-tolerant, highly-available apps at scale.
This talk will examine case studies of Mesos uses in production at scale: ranging from Twitter (100% on prem) to Airbnb (100% cloud), plus MediaCrossing, Categorize, HubSpot, etc. How have these organizations leveraged Mesos to build better, more scalable and efficient distributed apps? Lessons from the Mesos developer community show that one can port an existing framework with a wrapper in approximately 100 line of code. Moreover, an important lesson from Spark is that based on “data center OS” building blocks one can rewrite a distributed system much like Hadoop to be 100x faster within a relatively small amount of source code.
These case studies illustrate the obvious benefits over prior approaches based on virtualization: scalability, elasticity, fault-tolerance, high availability, improved utilization rates, etc. Less obvious outcomes also include: reduced time for engineers to ramp-up new services at scale; reduced latency between batch and services, enabling new high-ROI use cases; and enabling dev/test apps to run on a production cluster without disrupting operations.
Adobe has packaged HBase in Docker containers and uses Marathon and Mesos to schedule them—allowing them to decouple the HBase RegionServer from the host, express resource requirements declaratively, and open the door for unassisted real-time deployments, elastic (up and down) real-time scalability, and more.
Mesos: The Operating System for your DatacenterDavid Greenberg
Maybe you’ve heard of Mesos—that thing that you can run Hadoop on. I think it powers Twitter? Isn’t it an Apache project, or something?
In this talk, we’ll learn all about Mesos—what it is, how you can leverage it to simplify your infrastructure and reduce AWS/cloud computing costs, and why you should develop your next application on top of it. This talk will give you the tools you need to understand whether Mesos is the right fit for your infrastructure, and several starting points for learning more about Mesos.
Cassandra on Mesos Across Multiple Datacenters at Uber (Abhishek Verma) | C* ...DataStax
Traditionally, machines were statically partitioned across the different services at Uber. In an effort to increase the machine utilization, Uber has recently started transitioning most of its services, including the storage services, to run on top of Mesos. This presentation will describe the initial experience building and operating a framework for running Cassandra on top of Mesos running across multiple datacenters at Uber. This framework automates several Cassandra operations such as node repairs, addition of new nodes and backup/restore. It improves efficiency by co-locating CPU-intensive services as well as multiple Cassandra nodes on the same Mesos agent. It handles failure and restart of Mesos agents by using persistent volumes and dynamic reservations. This talk includes statistics about the number of Cassandra clusters in production, time taken to start a new cluster, add a new node, detect a node failure; and the observed Cassandra query throughput and latency.
About the Speaker
Abhishek Verma Software Engineer, Uber
Dr. Abhishek Verma is currently working on running Cassandra on top of Mesos at Uber. Prior to this, he worked on BorgMaster at Google and was the first author of the Borg paper published in Eurosys 2015. He received an MS in 2010 and a PhD in 2012 in Computer Science from the University of Illinois at Urbana-Champaign, during which he authored more than 20 publications in conferences, journals and books and presented tens of talks.
Presentation delivered by David Smith to NY R Conference https://www.rstats.nyc/, April 2018:
Minecraft is an open-world creativity game, and a hit with kids. To get kids interested in learning to program with R, we created the "miner" package. This package is a collection of simple functions that allow you to connect with a Minecraft instance, manipulate the world within by creating blocks and controlling the player, and to detect events within the world and react accordingly.
The miner package is intended mainly for kids, to inspire them to learn R while playing Minecraft. But the development of the package also provides some useful insights into how to build an R package to interface with a persistent API, and how to instruct others on its use. In this talk I'll describe how to set up your own Minecraft server, and how to use and extend the package. I'll also provide a few examples of the package in action in a live Minecraft session.
Presented to eRum (Budapest), May 2018
There are many common workloads in R that are "embarrassingly parallel": group-by analyses, simulations, and cross-validation of models are just a few examples. In this talk I'll describe the doAzureParallel package, a backend to the "foreach" package that automates the process of spawning a cluster of virtual machines in the Azure cloud to process iterations in parallel. This will include an example of optimizing hyperparameters for a predictive model using the "caret" package.
This presentation answer a lot of your questions about PostgreSQL and the Red Hat Cluster Suite.
It reviews how you can create failover/standby capabilities with the following activities:
General PostgreSQL clustering options
Overview of Red Hat Cluster Service
Identification of candidate databases for clustering
Identification of hardware for clustering
Analysis of uptime requirements and data latency
Implementation of clustering
Testing of clustering
PostgreSQL installation tips for RHCS
Sanger OpenStack presentation March 2017Dave Holland
A description of the Sanger Institute's journey with OpenStack to date, covering RHOSP, Ceph, S3, user applications, and future plans. Given at the Sanger Institute's OpenStack Day.
OpenStack is rapidly gaining popularity with businesses as they realize the benefits of a private cloud architecture. This presentation was delivered by Dave Page, Chief Architect, Tools & Installers at EnterpriseDB & PostgreSQL Core Team member during PG Open 2014. He addressed some of the common components of OpenStack deployments, how they can affect Postgres servers, and how users might best utilize some of the features they offer when deploying Postgres, including:
• Different configurations for the Nova compute service
• Use of the Cinder block store
• Virtual networking options with Neutron
• WAL archiving with the Swift object store
Learn from Accubits Technologies
High Performance Computing (HPC) most generally refers to the practice of aggregating computing power in a way that delivers much higher performance than one could get out of a typical desktop computer or workstation in order to solve large problems in science, engineering, or business.
The Anatomy Of The Google Architecture Fina Lv1.1Hassy Veldstra
A comprehensive overview of Google's architecture - starting from the search page and all the way to its internal networks.
By Ed Austin, talk given at Edinburgh Techmeetup in December 2009
http://techmeetup.co.uk
Mesosphere and Contentteam: A New Way to Run CassandraDataStax Academy
We, Ben Whitehead and Robert Stupp, will show you how to run Cassandra on Mesos. We will go through all the technical steps how to plan, setup and operate even large scale Cassandra clusters on Mesos. Further we illustrate how the Cassandra-on-Mesos framework helps you to setup Cassandra on Mesos, schedule regular maintenance tasks and manage hardware failures in the heart of your data center.
Using schedulers like Marathon and Aurora help to get your applications scheduled and executing on Mesos. In many cases it makes sense to build a framework and integrate directly. This talk will breakdown what is involved in building a framework, how to-do this with examples and why you would want to-do this. Frameworks are not only for generally available software applications (like Kafka, HDFS, Spark ,etc) but can also be used for custom internal R&D built software applications too.
For this upcoming meetup, we welcome Patrick Eaton PhD, Systems Architect at Stackdriver, and Joey Imbasciano, Cloud Platform Engineer at Stackdriver.
What You'll Learn At This Meetup:
• Why Stackdriver chose Cassandra over other DB offerings
• Stackdriver's data pipeline that runs into Cassandra
• Operating Cassandra Running on AWS
• Stackdriver's approach to disaster recovery
Patrick and Joey will be presenting their use of Apache Cassandra at Stackdriver, some lesson's learned, technical tips and a Q&A to end the evening.
Presentation delivered by David Smith to NY R Conference https://www.rstats.nyc/, April 2018:
Minecraft is an open-world creativity game, and a hit with kids. To get kids interested in learning to program with R, we created the "miner" package. This package is a collection of simple functions that allow you to connect with a Minecraft instance, manipulate the world within by creating blocks and controlling the player, and to detect events within the world and react accordingly.
The miner package is intended mainly for kids, to inspire them to learn R while playing Minecraft. But the development of the package also provides some useful insights into how to build an R package to interface with a persistent API, and how to instruct others on its use. In this talk I'll describe how to set up your own Minecraft server, and how to use and extend the package. I'll also provide a few examples of the package in action in a live Minecraft session.
Presented to eRum (Budapest), May 2018
There are many common workloads in R that are "embarrassingly parallel": group-by analyses, simulations, and cross-validation of models are just a few examples. In this talk I'll describe the doAzureParallel package, a backend to the "foreach" package that automates the process of spawning a cluster of virtual machines in the Azure cloud to process iterations in parallel. This will include an example of optimizing hyperparameters for a predictive model using the "caret" package.
This presentation answer a lot of your questions about PostgreSQL and the Red Hat Cluster Suite.
It reviews how you can create failover/standby capabilities with the following activities:
General PostgreSQL clustering options
Overview of Red Hat Cluster Service
Identification of candidate databases for clustering
Identification of hardware for clustering
Analysis of uptime requirements and data latency
Implementation of clustering
Testing of clustering
PostgreSQL installation tips for RHCS
Sanger OpenStack presentation March 2017Dave Holland
A description of the Sanger Institute's journey with OpenStack to date, covering RHOSP, Ceph, S3, user applications, and future plans. Given at the Sanger Institute's OpenStack Day.
OpenStack is rapidly gaining popularity with businesses as they realize the benefits of a private cloud architecture. This presentation was delivered by Dave Page, Chief Architect, Tools & Installers at EnterpriseDB & PostgreSQL Core Team member during PG Open 2014. He addressed some of the common components of OpenStack deployments, how they can affect Postgres servers, and how users might best utilize some of the features they offer when deploying Postgres, including:
• Different configurations for the Nova compute service
• Use of the Cinder block store
• Virtual networking options with Neutron
• WAL archiving with the Swift object store
Learn from Accubits Technologies
High Performance Computing (HPC) most generally refers to the practice of aggregating computing power in a way that delivers much higher performance than one could get out of a typical desktop computer or workstation in order to solve large problems in science, engineering, or business.
The Anatomy Of The Google Architecture Fina Lv1.1Hassy Veldstra
A comprehensive overview of Google's architecture - starting from the search page and all the way to its internal networks.
By Ed Austin, talk given at Edinburgh Techmeetup in December 2009
http://techmeetup.co.uk
Mesosphere and Contentteam: A New Way to Run CassandraDataStax Academy
We, Ben Whitehead and Robert Stupp, will show you how to run Cassandra on Mesos. We will go through all the technical steps how to plan, setup and operate even large scale Cassandra clusters on Mesos. Further we illustrate how the Cassandra-on-Mesos framework helps you to setup Cassandra on Mesos, schedule regular maintenance tasks and manage hardware failures in the heart of your data center.
Using schedulers like Marathon and Aurora help to get your applications scheduled and executing on Mesos. In many cases it makes sense to build a framework and integrate directly. This talk will breakdown what is involved in building a framework, how to-do this with examples and why you would want to-do this. Frameworks are not only for generally available software applications (like Kafka, HDFS, Spark ,etc) but can also be used for custom internal R&D built software applications too.
For this upcoming meetup, we welcome Patrick Eaton PhD, Systems Architect at Stackdriver, and Joey Imbasciano, Cloud Platform Engineer at Stackdriver.
What You'll Learn At This Meetup:
• Why Stackdriver chose Cassandra over other DB offerings
• Stackdriver's data pipeline that runs into Cassandra
• Operating Cassandra Running on AWS
• Stackdriver's approach to disaster recovery
Patrick and Joey will be presenting their use of Apache Cassandra at Stackdriver, some lesson's learned, technical tips and a Q&A to end the evening.
Managing Docker Containers In A Cluster - Introducing KubernetesMarc Sluiter
Containerising your applications with Docker gets more and more attraction. While managing your Docker containers on your developer machine or on a single server is not a big hassle, it can get uncomfortable very quickly when you want to deploy your containers in a cluster, no matter if in the cloud or on premises. How do you provide high availability, scaling and monitoring? Fortunately there is a rapidly growing ecosystem around docker, and there are tools available which support you with this. In this session I want to introduce you to Kubernetes, the Docker orchestration tool started and open sourced by Google. Based on the experience with their data centers, Google uses some interesting declarative concepts like pods, replication controllers and services in Kubernetes, which I will explain to you. While Kubernetes still is a quite young project, it reached its first stable version this summer, thanks to many contributions by Red Hat, Microsoft, IBM and many more.
In this video from ChefConf 2014 in San Francisco, Cycle Computing CEO Jason Stowe outlines the biggest challenge facing us today, Climate Change, and suggests how Cloud HPC can help find a solution, including ideas around Climate Engineering, and Renewable Energy.
"As proof points, Jason uses three use cases from Cycle Computing customers, including from companies like HGST (a Western Digital Company), Aerospace Corporation, Novartis, and the University of Southern California. It’s clear that with these new tools that leverage both Cloud Computing, and HPC – the power of Cloud HPC enables researchers, and designers to ask the right questions, to help them find better answers, faster. This all delivers a more powerful future, and means to solving these really difficult problems."
Watch the video presentation: http://insidehpc.com/2014/09/video-hpc-cluster-computing-64-156000-cores/
9 ways to consume kubernetes on open stack in 15 mins (k8s meetup)Stacy Véronneau
Like that title states, this is a quick slide deck to help people consume OpenStack resources from Kubernetes. It covers elements running on a laptop to consuming a full production cloud.
Above is a talk I made for the Integrated Marketing Conference in Cape Town, entitled Learn, Unlearn, Relearn.
The talk takes you through a brief history of advertising showing what has changed, what is new, and what has fundamentally remained the same.
It then shares some tips and advice on how to help make sure your work remains relevant in today’s ever evolving world.
I gave the talk with Chris Gotz and Luca Gallarelli, both from Ogilvy Cape Town.
A Project Report on Linux Server AdministrationAvinash Kumar
This is a Project Report on Linux Server Admin. It contains key network features which are installed on Linux. This project was conducted on RedHat Enterprise Linux 7.2.
This is the presentation on clusters computing which includes information from other sources too including my own research and edition. I hope this will help everyone who required to know on this topic.
DockerCon EU 2015: It's in the game: the path to micro-services at Electronic...Docker, Inc.
Presented by Andrew Hately, CTO - Cloud Architecture, IBM and Scott Porter, Sr. Developer, Electronic Arts
Learn how Docker can be used to achieve near bare-metal performance and a scale-out architecture that enables game backends to scale and stay responsive during load spikes. Game popularity can change with every feature and content pack release, and IBM and Electronic Arts have transitioned a mobile game engine to leverage Docker to enable rapid rollouts while handling more game users. In this session you'll learn design tips from the development of this next-gen gaming platform in an industry where user loyalty and performance are everything. Docker packaging of the game services is enabling a transition to a more flexible, micro-service based architecture, and this session will discuss the development lessons learned during that transition as well as the transition to using Docker in production.
DockerCon SF 2015: How to talk to humansDocker, Inc.
Slides from Sharon Steed's talk at DockerCon SF 2015
Talk Description: Developers are trained to communicate to things with a goal in mind. When you're talking to a computer, you type in your code and it responds by giving you back what you want. Simple and straight forward. When talking to people? Not always the case. Why? Because talking to people requires a special set of skills - namely, empathy and a little bit of storytelling. In an industry filled with brilliant minds, great ideas and mass disruption, so few of the best and brightest know how to tell their compelling story. This talk teaches you how.
OSDC 2015: Bernd Mathiske | Why the Datacenter Needs an Operating SystemNETWAYS
Developers are moving away from their host-based patterns and adopting a new mindset around the idea that the datacenter is the computer. It?s quickly becoming a mainstream model that you can view a warehouse full of servers as a single computer (with terabytes of memory and tens of thousands of cores). There is a key missing piece, which is an operating system for the datacenter (DCOS), which would provide the same OS functionality and core OS abstractions across thousands of machines that an OS provides on a single machine today. In this session, we will discuss:
How the abstraction of an OS has evolved over time and can cleanly scale to spand thousands of machines in a datacenter.
How key open source technologies like the Apache Mesos distributed systems kernel provide the key underpinnings for a DCOS.
How developers can layer core system services on top of a distributed systems kernel, including an init system (Marathon), cron (Chronos), service discovery (DNS), and storage (HDFS)
What would the interface to the DCOS look like? How would you use it?
How you would install and operate datacenter services, including Apache Spark, Apache Cassandra, Apache Kafka, Apache Hadoop, Apache YARN, Apache HDFS, and Google's Kubernetes.
How will developers build datacenter-scale apps, programmed against the datacenter OS like it?s a single machine?
ContainerDays Boston 2015: "CoreOS: Building the Layers of the Scalable Clust...DynamicInfraDays
Slides from Barak Michener's talk "CoreOS: Building the Layers of the Scalable Cluster for Containers" at ContainerDays Boston 2015: http://dynamicinfradays.org/events/2015-boston/programme.html#layers
Choosing PaaS: Cisco and Open Source Options: an overviewCisco DevNet
A session in the DevNet Zone at Cisco Live, Berlin. Confused by all the open source PaaS options out there? What criteria should you use to evaluate them? We seek to answer these questions in a systematic manner and will explore top technologies such as Mesos, Apprenda, Cloud Foundry and Kubernetes along with Cisco's Project Shipped and open source Mantl. The aim of this session will be to shed light on which platforms add value to your needs, applications and workloads.
Docker is a key player in the microservices movement and is arguably the leader in containerization technology.
That said, there are many ways to “do Docker”.
Between the leading cloud providers AWS, Azure, and Google; plus other platform stacks like Docker/Swarm, Apache Mesos – DC/OS, and Kubernetes; it can get confusing.In this session, Michele will bring her customer experiences building solutions across most of these platforms – to provide you with the highlights, the architecture topologies, and some perspective on the way she helps her customers choose the right platform for their cloud, on premise or hybrid solutions.
Learning from ZFS to Scale Storage on and under Containersinside-BigData.com
Evan Powell presented this deck at the MSST 2107 Mass Storage Conference.
"What is so new about the container environment that a new class of storage software is emerging to address these use cases? And can container orchestration systems themselves be part of the solution? As is often the case in storage, metadata matters here. We are implementing in the open source OpenEBS.io some approaches that are in some regards inspired by ZFS to enable much more efficient scale out block storage for containers that itself is containerized. The goal is to enable storage to be treated in many regards as just another application while, of course, also providing storage services to stateful applications in the environment."
Watch the video: http://wp.me/p3RLHQ-gPs
Learn more: blog.openebs.io
and
http://storageconference.us
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
AWS re:Invent 2016: Service Integration Delivery and Automation Using Amazon ...Amazon Web Services
Through a combination of Amazon ECS and open source technologies, customers are able to build portable CI/CD pipelines on AWS. As container based deployments become more complex, they require additional rigging for integration. In this session, we show how popular Apache products like Kakfa, Storm, and Zookeeper are being deployed on top of Amazon ECS. We hear from HERE, a provider of mapping data, technologies, and services to the automotive, consumer, and enterprise sectors about an approach that leverages Consul from Hashicorp and Amazon ECS clusters for short-cycle deployments and tag-based environment promotion.
Similar to DockerCon14 Cluster Management and Containerization (20)
Containerize Your Game Server for the Best Multiplayer Experience Docker, Inc.
Raymond Arifianto, AccelByte and
Mark Mandel, Google -
We have been deploying containerized micro-services for our Game Backend Services for a while. Now we are tackling the challenge to scale up fleets of game dedicated servers in multiple regions, multiple data centers and multiple providers - some in bare metal, some in Cloud. So we leverage docker containerization to deploy Game Servers to achieve Portability, Fast Deployment and Predictability, enabling us to scale up to thousands of servers, on demand, without a sweat.
How to Improve Your Image Builds Using Advance Docker BuildDocker, Inc.
Nicholas Dille, Haufe-Lexware + Docker Captain -
Docker continues to be the standard tool for building container images. For more than a year Docker ships with BuildKit as an alternative image builder, providing advanced features for secret and cache management. These features help to make image builds faster and more secure. In this session, Docker Captain Nicholas Dille will teach you how to use Buildkit features to your advantage.
Build & Deploy Multi-Container Applications to AWSDocker, Inc.
Lukonde Mwila, Entelect -
As the cloud-native approach to development and deployment becomes more prevalent, it's an exciting time for software engineers to be equipped on how to dockerize multi-container applications and deploy them to the cloud.
In this talk, Lukonde Mwila, Software Engineer at Entelect, will cover the following topics:
- Docker Compose
- Containerizing an Nginx Server
- Containerizing an React App
- Containerizing an Node.JS App
- Containerizing anMongoDB App
- Runing Multi-Container App Locally
- Creating a CI/CD Pipeline
- Adding a build stage to test containers and push images to Docker Hub
- Deploying Multi-Container App to AWS Elastic Beanstalk
Lukonde will start by giving an overview of how Docker Compose works and how it makes it very easy and straightforward to startup multiple Docker containers at the same time and automatically connect them together with some form of networking.
After that, Lukonde will take a hands on approach to containerize an Nginx server, a React app, a NodeJS app and a MongoDB instance to demonstrate the power of Docker Compose. He'll demonstrate usage of two Docker files for an application, one production grade and the other for local development and running of tests. Lastly, he'll demonstrate creating a CI/CD pipeline in AWS to build and test our Docker images before pushing them to Docker Hub or AWS ECR, and finally deploying our multi-container application AWS Elastic Beanstalk.
Securing Your Containerized Applications with NGINXDocker, Inc.
Kevin Jones, NGNIX -
NGINX is one of the most popular images on Docker Hub and has been at the forefront of the web since the early 2000's. In this talk we will discuss how and why NGINX's lightweight and powerful architecture makes it a very popular choice for securing containerized applications as a sidecar reverse proxy within containers. We will highlight important aspects of application security that NGINX can help with, such as TLS, HTTP, AuthN, AuthZ and traffic control.
How To Build and Run Node Apps with Docker and ComposeDocker, Inc.
Kathleen Juell, Digital Ocean -
Containers are an essential part of today's microservice ecosystem, as they allow developers and operators to maintain standards of reliability and reproducibility in fast-paced deployment scenarios. And while there are best practices that extend across stacks in containerized environments, there are also things that make each stack distinct, starting with the application image itself.
This talk will dive into some of these particularities, both at the image and service level, while also covering general best practices for building and running Node applications with database backends using Docker and Compose.
Jessica Deen, Microsoft -
Helm 3 is here; let's go hands-on! In this demo-fueled session, I'll walk you through the differences between Helm 2 and Helm 3. I'll offer tips for a successful rollout or upgrade, go over how to easily use charts created for Helm 2 with Helm 3 (without changing your syntax), and review opportunities where you can participate in the project's future.
Distributed Deep Learning with Docker at SalesforceDocker, Inc.
Jeff Hajewski, Salesforce -
There is a wealth of information on building deep learning models with PyTorch or TensorFlow. Anyone interested in building a deep learning model is only a quick search away from a number of clear and well written tutorials that will take them from zero knowledge to having a working image classifier. But what happens when you need to deploy these models in a production setting? At Salesforce, we use TensorFlow models to help us provide customers with insights into their data, and we do this as close to real-time as possible. Designing these systems in a scalable manner requires overcoming a number of design challenges, but the core component is Docker. Docker enables us to design highly scalable systems by allowing us to focus on service interactions, rather than how our services will interact with the hardware. Docker is also at the core of our test infrastructure, allowing developers and data scientists to build and test the system in an end to end manner on their local machines. While some of this may sound complex, the core message is simplicity - Docker allows us to focus on the aspects of the system that matter, greatly simplifying our lives.
The First 10M Pulls: Building The Official Curl Image for Docker HubDocker, Inc.
James Fuller, webcomposite s.r.o. -
Curl is the venerable (yet very modern) 'swiss army knife' command line tool and library for transferring data with URLs. Recently we (the Curl team) decided to build a release for Docker Hub. This talk will outline our current development workflow with respect to the docker image and provide insights on what it takes to build a docker image for mass public consumption. We are also keen to learn from users and other developers how we might improve and enhance the official curl docker image.
Fabian Stäber, Instana -
In recent years, we saw a great paradigm shift in software engineering away from static monolithic applications towards dynamic distributed horizontally scalable architectures. Docker is one of the key technologies enabling this development. This shift poses a lot of new challenges for application monitoring, ranging from practical issues (need for automation) to technical challenges (Docker networking) to organizational topics (blurring line between software engineers and operations) to fundamental questions (define what is an application). In this talk we show how Docker changed the way we do monitoring, how modern application monitoring systems work, and what future developments we expect.
COVID-19 in Italy: How Docker is Helping the Biggest Italian IT Company Conti...Docker, Inc.
Clemente Biondo, Engineering Ingegneria Informatica -
When the COVID 19 pandemic started, Engineering Ingegneria Informatica Group (1.25 billion euros of revenues, 65 offices around the world, 12.000 employees) was forced to put their digital transformation to the test in order to maintain operational continuity. In this session, Clemente Biondo, the Tech Lead of the Information Systems Department, will share how his company is reacting to this unforeseeable scenario and how Docker-driven digital transformation had paved the path for work to continue remotely. Clemente will discuss learnings moving from colocated teams, manual approaches, email based-business processes, and a monolithic application to a mature DevOps culture characterized by a distributed autonomous workforce and a continuous deployment process that deploys backward-compatible Docker containerized microservices into hybrid multi cloud datacenters an average of twice a day with zero-downtime. He will detail how they use Docker to unify dev, test and production environments, and as an efficient and automated mechanism for deploying applications. Lastly, Clemente shares how, in our darkest hour, he and others are working to shine their brightest light.
Chris Lauer, NOAA Space Weather Prediction Center -
This is the story of how adopting a containerized workflow changed the way our small software team works at NOAA’s Space Weather Prediction Center. Our old architecture, a big ball of mud shared-database integration, just wasn’t cutting it - it was killing our agility. Over the past two years, our small team has adopted a microservice style architecture, using Docker with docker-compose and environment files as our deployment strategy for all new development. We’ve discovered the joys of using containers for identical dev, staging, and production environments. We work closely with scientists: much of the code we’re running has complicated and conflicting library dependencies. Docker captures these beautifully - we’ve even had some success teaching our scientists to use it! I’ll share what we’ve learned, some of the persistent challenges we face, and one place we really got it wrong. This talk builds off of a popular hallway track from DockerCon 2019.
Become a Docker Power User With Microsoft Visual Studio CodeDocker, Inc.
Brian Christner, 56k + Docker Captain -
In this session, we will unlock the full potential of using Microsoft Visual Studio Code (VS Code) and Docker Desktop to turn you into a Docker Power User. When we expand and utilize the VS Code Docker plugin, we can take our projects and Docker skills to the next level. In addition to using VS Code, we streamline our Docker Desktop development workflow with less context switching and built-in shortcuts. You will learn how to bootstrap new projects, quickly write Dockerfiles utilizing templates, build, run, and interact with containers all from VS Code.
How to Use Mirroring and Caching to Optimize your Container RegistryDocker, Inc.
Brandon Mitchell, Boxboat + Docker Captain -
How do you make your builds more performant? This talk looks at options to configure caching and mirroring of images that you need to save on bandwidth costs and to keep running even if something goes down upstream.
Monolithic to Microservices + Docker = SDLC on Steroids!Docker, Inc.
Ashish Sharma, SS&C Eze -
SS&C Eze provides various products in the stock market domain. We spent the last couple of years building Eclipse which is an investment suite born in cloud. The journey so far has been very interesting. The very first version of the product were a bunch of monolithic windows services and deployed using Octopus tool. We successfully managed to bring all the monolithic problem to the cloud and created a nightmare for ourselves. We then started applying microservices architecture principles and started breaking the monolithic into small services. Very soon we realized that we need a better packaging/deployment tool. Docker looked like a magical solution to our problem. Since its adoption, It has not only solved the deployment problem for us but has made a deep impact on different aspects of SDLC. It allowed us to use heterogeneous technology stacks, simplified development environment setup, simplified our testing strategy, improved our speed of delivery, and made our developers more productive. In this talk I would like to share our experience of using Docker and its positive impact on our SDLC.
Ara Pulido, Datadog -
Container technologies, although not new, have increased their popularity in the past few years, with container orchestrators allowing companies around the world to adopt these technologies to help them ship and scale microservices with precision and velocity. Kubernetes is currently the most popular container orchestration platform, and while many organizations are migrating their workloads to it, Kubernetes is still relatively immature. New corner cases, errors, and quirks are regularly discovered as users push the boundaries of size and scale. When Datadog adopted Kubernetes we discovered some of these boundaries the hard way, and we continuously challenge and modify our infrastructure decisions in order to fit our use case. Join me in this talk for our story on what we learned while we scaled our Kubernetes clusters, the contributions to Kubernetes we made along the way, and how you can apply those learnings when growing your Kubernetes clusters from a handful to hundreds or thousands of nodes.
Andy Clemenko, StackRox -
One underutilized, and amazing, thing about the docker image scheme is labels. Labels are a built in way to document all aspects about the image itself. Think about all the information that the tags inside your clothing carry. If you care to look you can find out everything about the garment. All that information can be very valuable. Now think about how we can leverage labels to carry similar information. We can even use the labels to contain Docker Compose or even Kubernetes Yaml. We can even include labels into the CI/CD process making things more secure and smoother. Come find out some fun techniques on how to leverage labels to do some fun and amazing things.
Using Docker Hub at Scale to Support Micro Focus' Delivery and Deployment ModelDocker, Inc.
Patrick Deloulay, Micro Focus -
Micro Focus started their digital transformation 3 years ago, moving the entire portfolio into hundreds of container images. Leveraging Docker Hub as our primary registry service, we will cover how we ended up building a simple but secure push/pull model to publish and deliver our premium assets to our customers and partners to both meet the high agility of our DevOps teams while greatly simplifying the deployment of our applications.
Build & Deploy Multi-Container Applications to AWSDocker, Inc.
Lukonde Mwila, Entelect
As the cloud-native approach to development and deployment becomes more prevalent, it's an exciting time for software engineers to be equipped on how to dockerize multi-container applications and deploy them to the cloud.
In this talk, Lukonde Mwila, Software Engineer at Entelect, will cover the following topics:
- Docker Compose
- Containerizing an Nginx Server
- Containerizing an React App
- Containerizing an Node.JS App
- Containerizing anMongoDB App
- Runing Multi-Container App Locally
- Creating a CI/CD Pipeline
- Adding a build stage to test containers and push images to Docker Hub
- Deploying Multi-Container App to AWS Elastic Beanstalk
Lukonde will start by giving an overview of how Docker Compose works and how it makes it very easy and straightforward to startup multiple Docker containers at the same time and automatically connect them together with some form of networking.
After that, Lukonde will take a hands on approach to containerize an Nginx server, a React app, a NodeJS app and a MongoDB instance to demonstrate the power of Docker Compose. He'll demonstrate usage of two Docker files for an application, one production grade and the other for local development and running of tests. Lastly, he'll demonstrate creating a CI/CD pipeline in AWS to build and test our Docker images before pushing them to Docker Hub or AWS ECR, and finally deploying our multi-container application AWS Elastic Beanstalk.
From Fortran on the Desktop to Kubernetes in the Cloud: A Windows Migration S...Docker, Inc.
Elton Stoneman, Docker Captain + Container Consultant and Trainer
How do you provide a SaaS offering when your product is a 10-year old Fortran app, currently built to run on Windows 10? With Docker and Kubernetes of course - and you can do it in a week (... to prototype level at least).
In this session I'll walk through the processes and practicalities of taking an older Windows app, making it run in containers with Kubernetes, and then building a simple API wrapper to host the whole stack as a cloud-based SaaS product.
There's a lot of technology here from a real world case study, and I'll focus on:
- running Windows apps in Docker containers
- building a .NET Core API which can run in Linux or Windows containers
- running the stack in Kubernetes with Docker Desktop locally and AKS in the cloud
- configuring AKS workloads in Azure to burst out to Azure Container Instances
And there's a core theme to this session: Docker and Kubernetes are complex technologies, but they're the key to modern development. If you invest time learning them, they make projects like this simple, portable, fast and fun.
Developing with Docker for the Arm ArchitectureDocker, Inc.
This virtual meetup introduces the concepts and best practices of using Docker containers for software development for the Arm architecture across a variety of hardware systems. Using Docker Desktop on Windows or Mac, Amazon Web Services (AWS) A1 instances, and embedded Linux, we will demonstrate the latest Docker features to build, share, and run multi-architecture images with transparent support for Arm.
10. configuration/package
management
“what/how
do
things
get
installed?”
(10’s
of
machines)
hosts.txt
web1.twttr.com
web2.twttr.com
web3.twttr.com
web4.twttr.com
$
ssh
host
./configure
&&
make
install
11. configuration/package
management
“what/how
do
things
get
installed?”
(10’s
of
machines)
hosts.txt
web1.twttr.com
web2.twttr.com
web3.twttr.com
web4.twttr.com
$
ssh
host
rpm
-‐ivh
pkg-‐x.y.z.rpm
12. deployment
“what
should
run
where?”
“how
should
it
be
started/stopped?”
$
ssh
host
nohup
myapp
(10’s
of
machines)
hosts.txt
web1.twttr.com
web2.twttr.com
web3.twttr.com
web4.twttr.com
13. deployment
“what
should
run
where?”
“how
should
it
be
started/stopped?”
$
ssh
host
monit
start
myapp
(10’s
of
machines)
hosts.txt
web1.twttr.com
web2.twttr.com
web3.twttr.com
web4.twttr.com
14. deployment
“what
should
run
where?”
“how
should
it
be
started/stopped?”
$
scp
myapp
host
$
ssh
host
monit
myapp
(10’s
of
machines)
hosts.txt
web1.twttr.com
web2.twttr.com
web3.twttr.com
web4.twttr.com
15. deployment
“what
should
run
where?”
“how
should
it
be
started/stopped?”
(10’s
of
machines)
$
ssh
host
git
pull
&&
monit
myapp
hosts.txt
web1.twttr.com
web2.twttr.com
web3.twttr.com
web4.twttr.com
16. “how
should
apps
find
each
other?”
naming
webhosts.txt
web1.twttr.com
web2.twttr.com
web3.twttr.com
web4.twttr.com
dbhosts.txt
db1.twttr.com
db2.twttr.com
db3.twttr.com
db4.twttr.com
(10’s
of
machines)
17. (10’s
of
machines)
(100’s
-‐>
1000’s
of
machines)
to
scale,
need
more
automation
65. Mesos
service
batch
storage
…
streaming
(1) when
resources
become
idle,
can
be
scheduled
and
reused
by
other
schedulers
66. Mesos
service
batch
storage
…
streaming
(1) when
resources
become
idle,
can
be
scheduled
and
reused
by
other
schedulers
67. Mesos
service
batch
storage
…
streaming
(1) when
resources
become
idle,
can
be
scheduled
and
reused
by
other
schedulers
68. Mesos
service
batch
storage
…
streaming
(1) when
resources
become
idle,
can
be
scheduled
and
reused
by
other
schedulers
69. Mesos
service
batch
storage
…
streaming
(1) when
resources
become
idle,
can
be
scheduled
and
reused
by
other
schedulers
70. Mesos
service
batch
storage
…
streaming
(1) when
resources
become
idle,
can
be
scheduled
and
reused
by
other
schedulers
(2) multi-‐tenancy
on
individual
machines
71. Mesos
service
batch
storage
…
streaming
(1) when
resources
become
idle,
can
be
scheduled
and
reused
by
other
schedulers
(2) multi-‐tenancy
on
individual
machines
77. deployment
Apache
Aurora
(incubating),
a
scheduler
for
running
stateless
services
written
in
any
language
(but
primarily
used
at
Twitter
for
JVM
services)
78. deployment
(via
Aurora)
developers
(1) describe
service
using
Python
based
DSL
(2)
submit
service
to
Aurora
using
CLI
79. deployment
(via
Marathon)
developers
(1) describe
services
using
JSON
(2)
submit
service
to
Marathon
via
REST
81. naming
(1) task
gets
launched
on
machine
Apache
ZooKeeper
using
Apache
ZooKeeper
and
server
sets
(github.com/twitter/commons)
82. naming
(2)
service
gets
registered
in
a
server
set
in
ZooKeeper
(1) task
gets
launched
on
machine
Apache
ZooKeeper
using
Apache
ZooKeeper
and
server
sets
(github.com/twitter/commons)
83. naming
(2)
service
gets
registered
in
a
server
set
in
ZooKeeper
(1) task
gets
launched
on
machine
(3)
other
services
use
ZooKeeper
to
find
services
they
need
Apache
ZooKeeper
using
Apache
ZooKeeper
and
server
sets
(github.com/twitter/commons)
84. naming
(2)
service
gets
registered
in
a
server
set
in
ZooKeeper
(1) task
gets
launched
on
machine
(3)
other
services
use
ZooKeeper
to
find
services
they
need
(4)
services
connect
directly
with
one
another
Apache
ZooKeeper
using
Apache
ZooKeeper
and
server
sets
(github.com/twitter/commons)
85. naming
alternative
(2)
update
HAProxy
with
new
service
location
(1) task
gets
launched
on
machine
(3)
other
services
send
traffic
through
HAProxy
ZooKeeper/server sets requires injecting code into your clients!
87. where
are
we
today?
ops
developers
deploys
decoupled
from
ops
(many
deploys
per
day,
per
service)
maintenance
consists
of
“draining”
hosts,
getting
tasks
rescheduled,
then
pulling
the
cord
95. challenges revisited
① failures
② maintenance
③ utilization
public
or
private
IaaS,
failures
still
occur
(on
EC2,
instead
of
racks,
have
availability
zones,
instead
of
datacenters,
have
regions)
96. challenges revisited
① failures
② maintenance
③ utilization
provider
wins
with
public
IaaS,
better
resource
sharing
with
private
IaaS,
but
a
static
partition
of
VMs
is
still
a
static
partition!
118. operating
system
“a
collection
of
software
that
manages
the
computer
hardware
resources
and
provides
common
services
for
computer
programs”
- Wikipedia
119. datacenter
operating
system
“a
collection
of
software
that
manages
the
datacenter
computer
hardware
resources
and
provides
common
services
for
computer
programs”
- Wikipedia
120. datacenter
operating
system
“a
collection
of
software
that
manages
the
datacenter
computer
hardware
resources
and
provides
common
services
for
computer
programs”
- Wikipedia
121. today
Your App
API
tomorrow
datacenter
OS
provides
common
functionality
every
new
distributed
system
re-‐
implements:
•
failure
detection
•
package
distribution
•
task
starting
•
resource
isolation
•
resource
monitoring
•
task
killing,
cleanup
•
…
122. today
Your App
API
tomorrow
provides
common
functionality
every
new
distributed
system
re-‐
implements:
•
failure
detection
•
package
distribution
•
task
starting
•
resource
isolation
•
resource
monitoring
•
task
killing,
cleanup
•
…
datacenter
OS
Don’t
reinvent
the
wheel!