Provisioning & Deploying with Docker

•

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This document discusses using Chef configuration management with Docker containers. It describes using Chef at both the build stage and runtime stage of containers. At build time, Chef can configure and install applications into an image. At runtime, Chef can further configure running containers based on environment variables. Combining Chef and Docker provides immutable infrastructure, faster deployments, and testable configurations.

Technology Business

Deploying with Docker
Atlanta Docker Meetup
2014.05.13

Do I still need Chef 
<or insert tool here>?

Why do we still need 
<or insert tool here>?

It’s a shell-script?
$ cat SomeApp/Dockerﬁle 
 
FROM ubuntu:13.10 
 
RUN apt-get update; apt-get install apache 
RUN sed ’s/something/else/‘ /etc/apache/httpd.conf 
 
ADD shell-script.sh 
RUN shell-script.sh 
 
RUN [‘/usr/bin/apachectl’, ‘start’]

How do we do it?
$ cat Dockerfile 
FROM fedora 
RUN yum update  
yum -y install chef

Traditional Chef
Hardware
OS
Linux
Chef
Installs Chef
Runs
Conﬁgures

Images on HW 
is usually mutable
Hardware
Image
Linux
Chef
Installs Chef
Image'
Linux
Chef
Creates
Replaces
Runs

Ephemeral environments 
are (somewhat) immutable.
Hypervisor
Image
Linux
Chef
Runs
Image'
Linux
Chef
Chef
Runs
Conﬁgures
VM
Accesses
COW

Containers are like
ephemeral VMs*
* Docker containers don’t HAVE to be ephemeral,
but it’s TheRightThing
Docker
Image
Linux
Chef
Runs
Image'
Linux
Chef
Chef
Runs
Conﬁgures
Container
Accesses
COW
TM

Runtime Conﬁguration
• One image, several
conﬁgurations
• Conﬁguration based on
container environment
• Specify metadata or roles via
environment variables
(passed to ‘docker run -e’)

Chef-for-runtime
$ cat Dockerfile 
FROM fedora 
RUN yum update  
yum -y install chef 
ADD http://x/receipes.tar.gz /opt/chef"
ADD solo.rb /etc/chef/solo.rb"
CMD chef-solo -c /etc/chef/solo.rb ; !
apachectl start

Does it converge?
$ docker build —rm . 
$ echo $? # pass or fail
(This is great use of Docker as an
alternative to VMs for testing Chef recipes
targeting non-Docker production systems)

Bootstrapping
Conﬁguration Management
on every boot is expensive

Build-time conﬁguration
• Speed up Chef-based
deployments (do it once!)
• Eliminate run-time network
requirements
• Conﬁg-management CI

Chef-for-build
$ cat Dockerfile 
FROM fedora 
RUN yum update  
yum -y install chef"
 
ADD http://x/receipes.tar.gz /opt/chef"
ADD solo.rb /etc/chef/solo.rb"
RUN chef-solo -c /etc/chef/solo.rb

Burning conﬁguration 
into images.
Docker ContainerInitiates Creates
Image
Linux
Chef
Chef
Runs
Conﬁgures
Build Creates

Expanded view: 
Burning conﬁguration into images.
Docker Image tagInitiates
Image'
Linux
Chef
Chef
Build
Image
Linux
Chef
Creates
Creates
Runs Creates
References
1
2

Anatomy of a Docker+Chef
build & run
Docker ContainerInitiates Creates
Image
Linux
Chef
Chef
Runs
Conﬁgures
Chef
Runs
Conﬁgures
Build Creates
Stage 1 Stage 2

Chef-for-all-the-things
$ cat Dockerfile 
FROM fedora 
RUN yum update  
yum -y install chef 
 
ADD http://x/receipes.tar.gz /opt/chef"
ADD solo-stage1.rb /etc/chef/solo-stage1.rb"
ADD solo-stage2.rb /etc/chef/solo-stage2.rb"
RUN chef-solo -c /etc/chef/solo-stage1.rb"
CMD chef-solo -c /etc/chef/solo-stage2.rb ;"
apachectl start

This document discusses deployment automation using Docker. It begins by introducing Docker terminology like images, containers, and registries. It then covers installing Docker, building images from Dockerfiles, tagging and pushing images to private registries, and running containers. The document also discusses mounting host directories in containers, cluster operations, and next steps around orchestration, monitoring, and continuous delivery.

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Docker 캐주얼 토크 #1 (2014-10-15)에서 발표하기 위해 만든 자료. 원래 'Docker 실서비스 도입기'를 발표하려고 했으나, 아직 도입이 마무리되지 못한 관계로 그 과정에서 의미 있는 부분을 찾아보았다. 그래서 Chef와 Docker가 도입되면 StudyGPS에서 어플리케이션을 업데이트하는 기존의 방식이 어떻게 변화하는지에 대해 설명하고, 그 변화의 의미에 대해서 생각해보고 정리하였다.

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This document discusses Docker containers and how they compare to virtual machines and configuration management tools like Puppet. It provides an overview of Docker, including how to build Docker images using Dockerfiles. It then compares Dockerfiles to shell scripts and configuration management, noting advantages and disadvantages of each. The document suggests using Puppet to install Docker and build Docker images, but not running Puppet inside containers. It provides examples of building Docker images that use Puppet for configuration.

Docker orchestration

Open Source Consulting

This document summarizes how to use Docker and orchestrate containers using Docker Compose and Docker Swarm. It begins with setting up a private Docker registry to store images. It then demonstrates building a WordPress site using Docker Compose, with linked MySQL and PHP containers. The images are committed and pushed to the private registry. Finally, it discusses running the composed WordPress application using images from the private registry.

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The document outlines an 90 minute introduction to Ansible using Docker. It discusses setting up the environment with Docker, using ad-hoc commands and playbooks to automate tasks like installing Apache and configuring variables. Exercises demonstrate inventory management, templating configurations with Jinja2, and other core Ansible concepts. The document provides an overview but does not cover more advanced topics like dynamic inventory, roles, writing custom modules, or Ansible Tower.

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Yonghwee Kim

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Extend Continuous Integration to automatically test your infrastructure. Continuous Integration can be extended to test deployments and production environments, in a Continuous Delivery cycle, using infrastructure-as-code tools like Puppet, allowing to manage multiple servers and their configurations, and test the infrastructure the same way continuous integration tools do with developers’ code. Puppet is an infrastructure-as-code tool that allows easy and automated provisioning of servers, defining the packages, configuration, services, … in code. Enabling DevOps culture, tools like Puppet help drive Agile development all the way to operations and systems administration, and along with continuous integration tools like Jenkins, it is a key piece to accomplish repeatability and continuous delivery, automating the operations side during development, QA or production, and enabling testing of systems configuration. Using Vagrant, a command line automation layer for VirtualBox, we can easily spin off virtual machines with the same configuration as production servers, run our test suite, and tear them down afterwards. We will show how to set up automated testing of an application and associated infrastructure and configurations, creating on demand virtual machines for testing, as part of your continuous integration process.

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For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/ Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit. The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers. Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.

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Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless community. Java is known for its high cold start times and high memory footprint, comparing to other programming languages like Node.js and Python. In this talk I'll look at the general best practices and techniques we can use to decrease memory consumption, cold start times for Java Serverless development on AWS including GraalVM (Native Image) and AWS own offering SnapStart based on Firecracker microVM snapshot and restore and CRaC (Coordinated Restore at Checkpoint) runtime hooks. I'll also provide a lot of benchmarking on Lambda functions trying out various deployment package sizes, Lambda memory settings, Java compilation options and HTTP (a)synchronous clients and measure their impact on cold and warm start times.

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Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots. To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.

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Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!

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5th Power Grid Model Meet-up It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology. Power Grid Model The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services. Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability. Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization. What to expect For the upcoming meetup we are organizing, we have an exciting lineup of activities planned: -Insightful presentations covering two practical applications of the Power Grid Model. -An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024. -An interactive brainstorming session to discuss and propose new feature requests. -An opportunity to connect with fellow Power Grid Model enthusiasts and users.

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2. @ewindisch

3. Deploying with Docker Atlanta Docker Meetup 2014.05.13

4. Do I still need Chef  <or insert tool here>?

5. There is no easy answer

8. Why do we still need  <or insert tool here>?

9. But… we have Dockerﬁles!

10. It’s a shell-script? $ cat SomeApp/Dockerﬁle    FROM ubuntu:13.10    RUN apt-get update; apt-get install apache  RUN sed ’s/something/else/‘ /etc/apache/httpd.conf    ADD shell-script.sh  RUN shell-script.sh    RUN [‘/usr/bin/apachectl’, ‘start’]

11. How do we do it? $ cat Dockerfile  FROM fedora  RUN yum update   yum -y install chef 

12. Traditional Chef Hardware OS Linux Chef Installs Chef Runs Conﬁgures

13.

14. Images on HW  is usually mutable Hardware Image Linux Chef Installs Chef Image' Linux Chef Creates Replaces Runs

15.

16. Ephemeral environments  are (somewhat) immutable. Hypervisor Image Linux Chef Runs Image' Linux Chef Chef Runs Conﬁgures VM Accesses COW

17.

18. Containers are like ephemeral VMs* * Docker containers don’t HAVE to be ephemeral, but it’s TheRightThing Docker Image Linux Chef Runs Image' Linux Chef Chef Runs Conﬁgures Container Accesses COW TM

19. Runtime Configuration • One image, several configurations • Configuration based on container environment • Specify metadata or roles via environment variables (passed to ‘docker run -e’)

20. Chef-for-runtime $ cat Dockerfile  FROM fedora  RUN yum update   yum -y install chef  ADD http://x/receipes.tar.gz /opt/chef" ADD solo.rb /etc/chef/solo.rb" CMD chef-solo -c /etc/chef/solo.rb ; ! apachectl start

21. Does it converge? $ docker build —rm .  $ echo $? # pass or fail (This is great use of Docker as an alternative to VMs for testing Chef recipes targeting non-Docker production systems)

22. Bootstrapping Conﬁguration Management on every boot is expensive

23. Let us use images!

24. Build-time conﬁguration • Speed up Chef-based deployments (do it once!) • Eliminate run-time network requirements • Conﬁg-management CI

25. Chef-for-build $ cat Dockerfile  FROM fedora  RUN yum update   yum -y install chef"   ADD http://x/receipes.tar.gz /opt/chef" ADD solo.rb /etc/chef/solo.rb" RUN chef-solo -c /etc/chef/solo.rb 

26. Burning conﬁguration  into images. Docker ContainerInitiates Creates Image Linux Chef Chef Runs Conﬁgures Build Creates

27. Expanded view:  Burning conﬁguration into images. Docker Image tagInitiates Image' Linux Chef Chef Build Image Linux Chef Creates Creates Runs Creates References 1 2

28. Anatomy of a Docker+Chef build & run Docker ContainerInitiates Creates Image Linux Chef Chef Runs Conﬁgures Chef Runs Conﬁgures Build Creates Stage 1 Stage 2

29. Chef-for-all-the-things $ cat Dockerfile  FROM fedora  RUN yum update   yum -y install chef    ADD http://x/receipes.tar.gz /opt/chef" ADD solo-stage1.rb /etc/chef/solo-stage1.rb" ADD solo-stage2.rb /etc/chef/solo-stage2.rb" RUN chef-solo -c /etc/chef/solo-stage1.rb" CMD chef-solo -c /etc/chef/solo-stage2.rb ;" apachectl start

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