We're really happy to say that today we made the first meetup about Kubernetes in Russia! Thanks to all speakers and guests! Join us: https://twitter.com/kubernetesMSK
Bitnami, Deis, Google and the Kubernetes community have been working on developing Helm, a tool for streamlining the deployment of containerized applications on Kubernetes. Bitnami currently offers a set of Helm packages, known as charts, to make it easy to deploy your favorite open source applications on Kubernetes with a single command. Join our webinar to learn how to quickly get started with Helm:
In this webinar you will learn:
- How to deploy Kubernetes-native applications
- How to manage the lifecycle of applications on Kubernetes using Helm
- The benefits of using Bitnami Helm Charts
- The best practices we've learned while creating and configuring - Bitnami Helm charts
- How to get started with Bitnami Helm Charts
1. Kubectx and Kubens are utilities that help manage and switch between Kubernetes contexts and namespaces, saving time when working with multiple clusters.
2. Kustomize is a tool for managing Kubernetes manifests and applying patches, making it easier to maintain configurations than templates. It can be used to apply common labels, annotations, and add prefixes to all resource names.
3. Skaffold automates the build, push and deploy pipeline, enabling fast local Kubernetes development. It works with build tools like Docker, Jib, and deploy tools like Helm and Kustomize. It supports profiles for different environments.
This talk will focus on a brief history, including a demo and overview of how we at Superbalist use Kubernetes, and how Kubernetes uses Docker, does load balancing, deployments, and data migrations.
Talk from Cape Town DevOps meetup on Jun 21, 2016:
https://www.meetup.com/Cape-Town-DevOps/events/231530172/
Code: https://github.com/zoidbergwill/kubernetes-examples
Slides as markdown: http://www.zoidbergwill.com/presentations/2016/kubernetes-1.2-and-spread/index.md
Slides from the talk given to the Startup Berlin Slack Group that demonstrates how TruckIN is implementing its continuous delivery workflow using technologies and open-source tools.
Topics that are covered: Automated Cloud Provisioning (Network, Subnets, VMs, Kubernetes Cluster, Firewall, Disks, Credentials, Private Docker Registry); Configuration Management (Salt Stack), Continuous Integration (Jenkins CI), Continuous Delivery/Deployment (Salt API/Reactor + Kubernetes) to a Google Cloud Kubernetes Cluster, Remote Application Debugging, Managing Google Cloud Kubernetes Cluster, Logging, Monitoring and ChatOps (Slack and operable.io)
Building Cloud-Native Applications with Kubernetes, Helm and KubelessBitnami
This document discusses building cloud-native applications with Kubernetes, Helm, and Kubeless. It introduces cloud-native concepts like containers and microservices. It then explains how Kubernetes provides container orchestration and Helm provides application packaging. Finally, it discusses how Kubeless enables serverless functionality on Kubernetes.
Introduction to Kubernetes - Docker Global Mentor Week 2016Opsta
Kubernetes is an open-source system for automating
deployment, scaling, and management of containerized
applications. This presentation will show you overview of Kubernetes concept.
Docker Global Mentor Week 2016 #DockerInThai at Kaidee on November 18, 2016
Integration kubernetes with docker private registryHungWei Chiu
What's the problem when we want to use the private registry in the kubernetes.
We also want to run a Docker-In-Docker Pod to push the private image to that private registry and the kubernetes node will pull the private image to run
Bitnami, Deis, Google and the Kubernetes community have been working on developing Helm, a tool for streamlining the deployment of containerized applications on Kubernetes. Bitnami currently offers a set of Helm packages, known as charts, to make it easy to deploy your favorite open source applications on Kubernetes with a single command. Join our webinar to learn how to quickly get started with Helm:
In this webinar you will learn:
- How to deploy Kubernetes-native applications
- How to manage the lifecycle of applications on Kubernetes using Helm
- The benefits of using Bitnami Helm Charts
- The best practices we've learned while creating and configuring - Bitnami Helm charts
- How to get started with Bitnami Helm Charts
1. Kubectx and Kubens are utilities that help manage and switch between Kubernetes contexts and namespaces, saving time when working with multiple clusters.
2. Kustomize is a tool for managing Kubernetes manifests and applying patches, making it easier to maintain configurations than templates. It can be used to apply common labels, annotations, and add prefixes to all resource names.
3. Skaffold automates the build, push and deploy pipeline, enabling fast local Kubernetes development. It works with build tools like Docker, Jib, and deploy tools like Helm and Kustomize. It supports profiles for different environments.
This talk will focus on a brief history, including a demo and overview of how we at Superbalist use Kubernetes, and how Kubernetes uses Docker, does load balancing, deployments, and data migrations.
Talk from Cape Town DevOps meetup on Jun 21, 2016:
https://www.meetup.com/Cape-Town-DevOps/events/231530172/
Code: https://github.com/zoidbergwill/kubernetes-examples
Slides as markdown: http://www.zoidbergwill.com/presentations/2016/kubernetes-1.2-and-spread/index.md
Slides from the talk given to the Startup Berlin Slack Group that demonstrates how TruckIN is implementing its continuous delivery workflow using technologies and open-source tools.
Topics that are covered: Automated Cloud Provisioning (Network, Subnets, VMs, Kubernetes Cluster, Firewall, Disks, Credentials, Private Docker Registry); Configuration Management (Salt Stack), Continuous Integration (Jenkins CI), Continuous Delivery/Deployment (Salt API/Reactor + Kubernetes) to a Google Cloud Kubernetes Cluster, Remote Application Debugging, Managing Google Cloud Kubernetes Cluster, Logging, Monitoring and ChatOps (Slack and operable.io)
Building Cloud-Native Applications with Kubernetes, Helm and KubelessBitnami
This document discusses building cloud-native applications with Kubernetes, Helm, and Kubeless. It introduces cloud-native concepts like containers and microservices. It then explains how Kubernetes provides container orchestration and Helm provides application packaging. Finally, it discusses how Kubeless enables serverless functionality on Kubernetes.
Introduction to Kubernetes - Docker Global Mentor Week 2016Opsta
Kubernetes is an open-source system for automating
deployment, scaling, and management of containerized
applications. This presentation will show you overview of Kubernetes concept.
Docker Global Mentor Week 2016 #DockerInThai at Kaidee on November 18, 2016
Integration kubernetes with docker private registryHungWei Chiu
What's the problem when we want to use the private registry in the kubernetes.
We also want to run a Docker-In-Docker Pod to push the private image to that private registry and the kubernetes node will pull the private image to run
Introduction of Kubernetes - Trang NguyenTrang Nguyen
This presentation provides the basic concepts of the Kubernetes for Beginners.
1) Introduction of Kubernetes
Before Kubernetes
What is Kubernetes
What Kubernetes can do?
What Kubernetes can't do?
Features of Kubernetes
Kubernetes Architecture
Kubernetes vs Docker Swarm
Kubernetes 7 use cases
...
2) Kubernetes Component
What is Kubelet?
What is Kubectl?
What is Kubeadm?
3) Nodes in Kubernetes
What is a node in Kubernetes?
Master node
Worker node
4) Kubernetes Development Process
What is blue green deployment?
How to automate the deployment?
5) Networking in Kubernetes
Kubernetes networking model
Ingress networking in Kubernetes
6) Security Measures in Kubernetes
Best security measures in Kubernetes
** Kubernetes Certification Training: https://www.edureka.co/kubernetes-certification **
This Edureka tutorial on "Kubernetes Architecture" will give you an introduction to popular DevOps tool - Kubernetes, and will deep dive into Kubernetes Architecture and its working. The following topics are covered in this training session:
1. What is Kubernetes
2. Features of Kubernetes
3. Kubernetes Architecture and Its Components
4. Components of Master Node and Worker Node
5. ETCD
6. Network Setup Requirements
DevOps Tutorial Blog Series: https://goo.gl/P0zAfF
Hybrid and multicloud deployments are critical approaches for bridging the gap between legacy and modern architectures. Sandeep Parikh discusses common patterns for creating scalable cross-environment deployments using Kubernetes and explores best practices and repeatable patterns for leveraging Kubernetes as a consistent abstraction layer across multiple environments.
The document discusses container runtimes and Docker Engine. It provides information on what containers are, how Docker Engine works as both a high-level runtime and incorporates building, packaging, sharing, and running containers. It also discusses the Open Container Initiative (OCI) specifications and the Container Runtime Interface (CRI) that Kubernetes uses to interface with container runtimes like Docker Engine and alternatives.
Extended and embedding: containerd update & project use casesPhil Estes
A talk given at FOSDEM 2020 in the containers devroom on the current status of the CNCF containerd project as well as a dive into the ways users are extending and embedding containerd in other platforms and projects.
This document discusses containers without Docker. It introduces alternatives to Docker like Runc, Podman, Buildah and Img for launching and building containers. It also discusses deploying Kubernetes using CRI-O as a container runtime instead of Docker. Key points covered include why consider non-Docker options, what containers and images are, and how to launch containers without Docker on Linux, Windows and in Kubernetes. Alternatives provide valuable choices and the future is seen as Kubernetes with CRI-O rather than Docker.
Platform Orchestration with Kubernetes and DockerJulian Strobl
Big companies like Google containerize theirs environments for easier maintaining, scaling, and reliability. This talk gives an introduction how to build such an environment and maintain applications written in distinct programming languages. The container orchestration is done with Kubernetes by Google and Docker containers. For mass deployment CoreOS is used.
This document provides an overview of Cloud Spanner including:
1. What Cloud Spanner is and how it compares to other database offerings.
2. Key product highlights such as it being fully managed, providing relational database capabilities at massive scale with strong consistency, and high availability.
3. Common use cases such as user data, order management, and electronic medical records.
4. Details on Spanner's architecture including splits, TrueTime, reads/writes, and Paxos.
5. Current areas of focus such as new features, developer productivity, and growing the open source ecosystem.
Kubernetes design principles, patterns and ecosystemSreenivas Makam
Kubernetes began as Google's internal container orchestration system called Borg and was open sourced as Kubernetes in 2014. It uses a declarative model where users describe their application components and infrastructure as code to manage the desired state. Key principles include being extensible through custom resources and controllers, meeting users where they are through integration with applications, and decoupling applications from infrastructure. Common extension points allow customizing authorization, scheduling, resources, and controllers. Operators help manage custom applications and Prometheus is a widely used monitoring operator. Best practices for day 2 operations focus on cluster design, application patterns, and security. A rich ecosystem of tools has grown around Kubernetes.
This presentation will introduce you to Container, Docker, and Kubernetes with a live demo. This also explains Kubernetes basic concepts such as Pod, Deployment, Service, Ingress, and Rolling Update.
Facebook Live: https://www.facebook.com/imcinstitute/videos/4199946253380670
Youtube Recorded: https://youtu.be/vW1Yq5ftWZ4
IMC Live Webinar on July 17, 2020
1. Docker EE will include an unmodified Kubernetes distribution to provide orchestration capabilities alongside Docker Swarm.
2. When running mixed workloads across orchestrators, resource contention is a risk and it is recommended to separate workloads by orchestrator on each node for now.
3. Docker EE aims to address the shortcomings of running mixed workloads to better support this in the future.
Rekcurd is a tool for deploying and managing machine learning models on Kubernetes. It provides a dashboard for uploading models, switching between models without stopping services, and versioning models. Rekcurd integrates with Kubernetes for high availability, auto-scaling, load balancing and auto-healing of machine learning services. The presentation demonstrates how Rekcurd addresses common tasks in serving machine learning models on Kubernetes.
This document provides an overview of Kubernetes concepts including architecture, fundamental objects like pods and services, and demonstrations. It begins with an agenda then covers Kubernetes architecture including the master node, worker nodes, and control loop. It describes core objects like pods, replica sets, deployments, services, and labels/selectors. The document demonstrates deploying and accessing the guestbook application using these objects. It concludes with asking for questions and describing goals for educational meetups on cloud native technologies.
Kubernetes - how to orchestrate containersinovex GmbH
http://www.meetup.com/Docker-Karlsruhe/events/220797663/
mehr Meetups von inovex:
http://www.meetup.com/inovex-karlsruhe
http://www.meetup.com/inovex-munich
http://www.meetup.com/inovex-cologne
An overview of the Kubernetes architectureIgor Sfiligoi
This talk provides a 101 introdution to Kubernetes from a user point of view.
Aimed at service providers, it was presented at the GPN Annual Meeting 2019. https://conferences.k-state.edu/gpn/
Since last DockerCon, Kubernetes has been integrated into both the Desktop and Enterprise editions of the Docker Platform. In this deep dive session, we’ll showcase live demos and explore where Kubernetes fits in the architecture of both the Desktop and the Enterprise editions and which community tools make this integration possible. We’ll be covering topics ranging from hypervisor control, storage and networking all the way to the integration of a custom RBAC system, native Compose file support and providing a rich user interface for Kubernetes.
We're really happy to say that today we made the first meetup about Kubernetes in Russia! Thanks to all speakers and guests! Join us: https://twitter.com/kubernetesMSK
Monitoring, Logging and Tracing on KubernetesMartin Etmajer
The document discusses monitoring, logging and tracing tools for Kubernetes including Heapster, Grafana, Fluentd, Elastic Stack, Jolokia and OpenTracing. It provides examples of deploying Heapster with InfluxDB and Grafana for metrics collection, Fluentd to ingest container logs into Elasticsearch, and using Jolokia and OpenTracing for remote access to JMX metrics and distributed tracing functionality.
Introduction of Kubernetes - Trang NguyenTrang Nguyen
This presentation provides the basic concepts of the Kubernetes for Beginners.
1) Introduction of Kubernetes
Before Kubernetes
What is Kubernetes
What Kubernetes can do?
What Kubernetes can't do?
Features of Kubernetes
Kubernetes Architecture
Kubernetes vs Docker Swarm
Kubernetes 7 use cases
...
2) Kubernetes Component
What is Kubelet?
What is Kubectl?
What is Kubeadm?
3) Nodes in Kubernetes
What is a node in Kubernetes?
Master node
Worker node
4) Kubernetes Development Process
What is blue green deployment?
How to automate the deployment?
5) Networking in Kubernetes
Kubernetes networking model
Ingress networking in Kubernetes
6) Security Measures in Kubernetes
Best security measures in Kubernetes
** Kubernetes Certification Training: https://www.edureka.co/kubernetes-certification **
This Edureka tutorial on "Kubernetes Architecture" will give you an introduction to popular DevOps tool - Kubernetes, and will deep dive into Kubernetes Architecture and its working. The following topics are covered in this training session:
1. What is Kubernetes
2. Features of Kubernetes
3. Kubernetes Architecture and Its Components
4. Components of Master Node and Worker Node
5. ETCD
6. Network Setup Requirements
DevOps Tutorial Blog Series: https://goo.gl/P0zAfF
Hybrid and multicloud deployments are critical approaches for bridging the gap between legacy and modern architectures. Sandeep Parikh discusses common patterns for creating scalable cross-environment deployments using Kubernetes and explores best practices and repeatable patterns for leveraging Kubernetes as a consistent abstraction layer across multiple environments.
The document discusses container runtimes and Docker Engine. It provides information on what containers are, how Docker Engine works as both a high-level runtime and incorporates building, packaging, sharing, and running containers. It also discusses the Open Container Initiative (OCI) specifications and the Container Runtime Interface (CRI) that Kubernetes uses to interface with container runtimes like Docker Engine and alternatives.
Extended and embedding: containerd update & project use casesPhil Estes
A talk given at FOSDEM 2020 in the containers devroom on the current status of the CNCF containerd project as well as a dive into the ways users are extending and embedding containerd in other platforms and projects.
This document discusses containers without Docker. It introduces alternatives to Docker like Runc, Podman, Buildah and Img for launching and building containers. It also discusses deploying Kubernetes using CRI-O as a container runtime instead of Docker. Key points covered include why consider non-Docker options, what containers and images are, and how to launch containers without Docker on Linux, Windows and in Kubernetes. Alternatives provide valuable choices and the future is seen as Kubernetes with CRI-O rather than Docker.
Platform Orchestration with Kubernetes and DockerJulian Strobl
Big companies like Google containerize theirs environments for easier maintaining, scaling, and reliability. This talk gives an introduction how to build such an environment and maintain applications written in distinct programming languages. The container orchestration is done with Kubernetes by Google and Docker containers. For mass deployment CoreOS is used.
This document provides an overview of Cloud Spanner including:
1. What Cloud Spanner is and how it compares to other database offerings.
2. Key product highlights such as it being fully managed, providing relational database capabilities at massive scale with strong consistency, and high availability.
3. Common use cases such as user data, order management, and electronic medical records.
4. Details on Spanner's architecture including splits, TrueTime, reads/writes, and Paxos.
5. Current areas of focus such as new features, developer productivity, and growing the open source ecosystem.
Kubernetes design principles, patterns and ecosystemSreenivas Makam
Kubernetes began as Google's internal container orchestration system called Borg and was open sourced as Kubernetes in 2014. It uses a declarative model where users describe their application components and infrastructure as code to manage the desired state. Key principles include being extensible through custom resources and controllers, meeting users where they are through integration with applications, and decoupling applications from infrastructure. Common extension points allow customizing authorization, scheduling, resources, and controllers. Operators help manage custom applications and Prometheus is a widely used monitoring operator. Best practices for day 2 operations focus on cluster design, application patterns, and security. A rich ecosystem of tools has grown around Kubernetes.
This presentation will introduce you to Container, Docker, and Kubernetes with a live demo. This also explains Kubernetes basic concepts such as Pod, Deployment, Service, Ingress, and Rolling Update.
Facebook Live: https://www.facebook.com/imcinstitute/videos/4199946253380670
Youtube Recorded: https://youtu.be/vW1Yq5ftWZ4
IMC Live Webinar on July 17, 2020
1. Docker EE will include an unmodified Kubernetes distribution to provide orchestration capabilities alongside Docker Swarm.
2. When running mixed workloads across orchestrators, resource contention is a risk and it is recommended to separate workloads by orchestrator on each node for now.
3. Docker EE aims to address the shortcomings of running mixed workloads to better support this in the future.
Rekcurd is a tool for deploying and managing machine learning models on Kubernetes. It provides a dashboard for uploading models, switching between models without stopping services, and versioning models. Rekcurd integrates with Kubernetes for high availability, auto-scaling, load balancing and auto-healing of machine learning services. The presentation demonstrates how Rekcurd addresses common tasks in serving machine learning models on Kubernetes.
This document provides an overview of Kubernetes concepts including architecture, fundamental objects like pods and services, and demonstrations. It begins with an agenda then covers Kubernetes architecture including the master node, worker nodes, and control loop. It describes core objects like pods, replica sets, deployments, services, and labels/selectors. The document demonstrates deploying and accessing the guestbook application using these objects. It concludes with asking for questions and describing goals for educational meetups on cloud native technologies.
Kubernetes - how to orchestrate containersinovex GmbH
http://www.meetup.com/Docker-Karlsruhe/events/220797663/
mehr Meetups von inovex:
http://www.meetup.com/inovex-karlsruhe
http://www.meetup.com/inovex-munich
http://www.meetup.com/inovex-cologne
An overview of the Kubernetes architectureIgor Sfiligoi
This talk provides a 101 introdution to Kubernetes from a user point of view.
Aimed at service providers, it was presented at the GPN Annual Meeting 2019. https://conferences.k-state.edu/gpn/
Since last DockerCon, Kubernetes has been integrated into both the Desktop and Enterprise editions of the Docker Platform. In this deep dive session, we’ll showcase live demos and explore where Kubernetes fits in the architecture of both the Desktop and the Enterprise editions and which community tools make this integration possible. We’ll be covering topics ranging from hypervisor control, storage and networking all the way to the integration of a custom RBAC system, native Compose file support and providing a rich user interface for Kubernetes.
We're really happy to say that today we made the first meetup about Kubernetes in Russia! Thanks to all speakers and guests! Join us: https://twitter.com/kubernetesMSK
Monitoring, Logging and Tracing on KubernetesMartin Etmajer
The document discusses monitoring, logging and tracing tools for Kubernetes including Heapster, Grafana, Fluentd, Elastic Stack, Jolokia and OpenTracing. It provides examples of deploying Heapster with InfluxDB and Grafana for metrics collection, Fluentd to ingest container logs into Elasticsearch, and using Jolokia and OpenTracing for remote access to JMX metrics and distributed tracing functionality.
This talk will focus on a brief overview of Kubernetes, with a brief demo, and then more of an in-depth focus on issues we've faced moving PHP projects into Docker and Kubernetes like signal propagation, init systems, and logging.
Talk from Cape Town PHP meetup on Feb. 7, 2016:
https://www.meetup.com/Cape-Town-PHP-Group/events/237226310/
Code: https://github.com/zoidbergwill/kubernetes-php-examples
Slides as markdown: http://www.zoidbergwill.com/presentations/2017/kubernetes-php/index.md
Teaching Apache Spark Clusters to Manage Their Workers Elastically: Spark Sum...Spark Summit
Devops engineers have applied a great deal of creativity and energy to invent tools that automate infrastructure management, in the service of deploying capable and functional applications. For data-driven applications running on Apache Spark, the details of instantiating and managing the backing Spark cluster can be a distraction from focusing on the application logic. In the spirit of devops, automating Spark cluster management tasks allows engineers to focus their attention on application code that provides value to end-users.
Using Openshift Origin as a laboratory, we implemented a platform where Apache Spark applications create their own clusters and then dynamically manage their own scale via host-platform APIs. This makes it possible to launch a fully elastic Spark application with little more than the click of a button.
We will present a live demo of turn-key deployment for elastic Apache Spark applications, and share what we’ve learned about developing Spark applications that manage their own resources dynamically with platform APIs.
The audience for this talk will be anyone looking for ways to streamline their Apache Spark cluster management, reduce the workload for Spark application deployment, or create self-scaling elastic applications. Attendees can expect to learn about leveraging APIs in the Kubernetes ecosystem that enable application deployments to manipulate their own scale elastically.
Deploying deep learning models with Docker and KubernetesPetteriTeikariPhD
Short introduction for platform agnostic production deployment with some medical examples.
Alternative download: https://www.dropbox.com/s/qlml5k5h113trat/deep_cloudArchitecture.pdf?dl=0
RackN is a software company based in Austin, TX that provides a unified operational control platform for hybrid cloud and infrastructure. Their platform aims to help operations teams improve productivity and automate lifecycle management of complex technology stacks at scale across multiple platforms like Mesos, Kubernetes, OpenStack, and tools like Terraform. RackN uses intelligent template-based workflows to compose and simplify operations across physical, cloud and platform infrastructures and APIs.
This document provides information about the builderscon conference, including that tickets sold out quickly, it will feature talks on topics like AI, IoT, and programming languages, and aims to have diversity and break down walls. It also announces details for builderscon Tokyo 2017, with dates in August and around 1000 expected attendees.
Net core, mssql, container und kubernetesThomas Fricke
This document discusses Google Cloud Platform and related technologies like .NET Core, SQL Server, containers, and Kubernetes. It provides an agenda for a user group meeting that will cover containers, Kubernetes, CoreOS, creating and running a .NET application in a Docker container, container registries, setting up a local Kubernetes cluster, and using pods and services. There is also information about Endocode, a company that provides software solutions and open source projects using technologies like these.
This document discusses learnings from Google's experience with microservices and the Stubby framework. It covers why HTTP/JSON is insufficient, the importance of establishing common protocols and data formats, designing for fault tolerance, collecting service analytics and tracing, and load balancing. It then introduces gRPC as an open source framework that addresses these lessons by providing language-independent service definitions, performance via HTTP/2, pluggable features, and usability across platforms and languages.
With so many different tools at our disposable, how do you pick which ones to learn? At our latest meetup for Denver Code Club, we explored some best practices on evaluating new technology and how you can choose the right tools for you.
The document summarizes a presentation about containers in Azure. It introduces Docker and Kubernetes as tools for running open source applications on Azure. It notes shortcomings of traditional virtual servers, such as difficulty scaling and versioning applications. Docker is presented as a way to package code and dependencies, while Kubernetes provides container orchestration for tasks like scheduling and updating containers. The presentation demonstrates using OpenShift on APPUiO, a managed container platform, as an alternative to running containers directly on Azure.
Kubernetes as Orchestrator for A10 Lightning ControllerAkshay Mathur
The document discusses using Kubernetes as an orchestrator for A10 Lightning Controller. Some key points:
1) Kubernetes allows for automatic recovery of pods on failure, easy rolling upgrades of code, and automated scaling of microservices.
2) Using Kubernetes allows the controller to be deployed on-premise and scaled across multiple VMs, with automated launching and scaling. Installation is also now independent of the underlying infrastructure.
3) The journey involved moving from a manual deployment to a Kubernetes deployment, which simplified overlay networking, environment variable passing, and simplified adding/replacing nodes.
Google Cloud Computing compares GCE, GAE and GKESimon Su
Google Cloud Computing compares GCE, GKE and GAE. GCE provides raw compute, storage and networking resources and requires more management overhead. GAE focuses on application logic and requires less management. GKE offers managed Kubernetes infrastructure and services. Each option has different strengths for workloads like microservices, containerized services, or large-scale applications requiring quick scaling. Monitoring and management features like Stackdriver are also compared.
The document discusses the Kubernetes API server and its RESTful HTTP API. It describes the API endpoints for accessing different Kubernetes resources, how API groups and versions are organized, how API requests are routed and processed, how Kubernetes objects are converted between different versions, and how storage and code generation are used.
Bangalore Container Conference 2017 (BCC '17) is the first conference on container technologies in India. Organizations are increasingly adopting containers and related technologies in production. Hence, the main focus of this conference is “Containers in Production”. This one-day conference sets the perfect stage for container enthusiasts, developers, users and experts to meet together and learn from each others experiences. This deck provides details for sponsoring the conference.
Running Docker in Production - The Good, the Bad and The UglyKontena, Inc.
When beginning to run Docker in production choosing the right path is critical. This presentation gives you some tips and suggestions on how to make this process easier.
This document provides an overview of container management and Kubernetes concepts. It discusses delivery and deployment methods like classic deployment, containers, virtualization, and container orchestration. It then covers Kubernetes components like etcd, the control plane, and nodes. It outlines cluster administration tasks and best practices for cluster usage. Finally, it provides examples of Kubernetes resource types like pods, replica sets, and deployments.
Idea to Production - with Gitlab and KubernetesSimon Dittlmann
Setting up a continuous delivery pipeline form scratch with gitlab.com and Kubernetes (Google Container Service GKE) on Google Cloud Platform.
The entire source code is available at https://github.com/Pindar/gcloud-k8s-express-app
Blog post https://www.itnotes.de/gitlab/kubernetes/k8s/gke/gcloud/2017/03/05/idea-to-production-with-gitlab-and-kubernetes/
Kubernetes 1.12 Update and Container Security with Liz RiceCloudOps2005
This document summarizes a meetup about Kubernetes and cloud native technologies in Montreal. It announces upcoming presentations on CNCF and Kubernetes 1.12 updates, and securing container deployments. It also provides information about getting involved with local user groups, upcoming hands-on workshops from CloudOps, the Rook and Cortex projects joining CNCF, and TiKV key-value store.
Herding Kats - Netflix’s Journey to Kubernetes Publicaspyker
An update from Netflix Compute's container management platform, Titus, covering the work to move from Mesos to Kubernetes. Lessons learned, next steps, and challenges.
Containers are changing development and deployment using technologies like Docker and Kubernetes. Containers leverage cgroups and namespaces in Linux kernels to isolate processes and share resources without full virtual machines. Docker popularized containers by making them easy to build, run and share. Kubernetes is the most popular container orchestrator, allowing containers to run together across clusters with services for load balancing, scaling and failover. Developers can now develop in containers for consistent environments, while operations teams can deploy containerized applications with automation and roll back updates if needed.
GL DevOps Experts are committed to sharing with our community as much knowledge about Docker and Kubernetes as possible.
Thinking about Kubernetes?
Join Vadym Fabiianskiy and Andrii Mandubyra, GlobalLogic Lviv DevOps Experts and learn:
Container Runtime specifics
What are the building blocks of K8S?
How does Kubernetes work?
Deployment and release strategies
Craig Box (Google) - The road to Kubernetes 1.0Outlyer
Review Kubernetes history as the project moves towards a 1.0 release.
Video: https://www.youtube.com/watch?v=_JDUbitRYws
Join DevOps Exchange London here: http://www.meetup.com/DevOps-Exchange-London
Follow DOXLON on twitter http://www.twitter.com/doxlon
Scalable Spark deployment using Kubernetesdatamantra
The document discusses deploying Spark clusters on Kubernetes. It introduces Kubernetes as a container orchestration platform for deploying containerized applications at scale across cloud and on-prem environments. It describes building a custom Spark 2.1 Docker image and using it to deploy a Spark cluster on Kubernetes with master and worker pods, exposing the Spark UI through a service.
Modern big data and machine learning in the era of cloud, docker and kubernetesSlim Baltagi
There is a major shift in web and mobile application architecture from the ‘old-school’ one to a modern ‘micro-services’ architecture based on containers. Kubernetes has been quite successful in managing those containers and running them in distributed computing environments.
Now enabling Big Data and Machine Learning on Kubernetes will allow IT organizations to standardize on the same Kubernetes infrastructure. This will propel adoption and reduce costs.
Kubeflow is an open source framework dedicated to making it easy to use the machine learning tool of your choice and deploy your ML applications at scale on Kubernetes. Kubeflow is becoming an industry standard as well!
Both Kubernetes and Kubeflow will enable IT organizations to focus more effort on applications rather than infrastructure.
Multi-Cloud Orchestration for Kubernetes with CloudifyCloudify Community
This presentation details Cloudify's Kubernetes plugin as well as Kubernetes Provider, offering complete integration with K8s and delivering multi-cloud container-based orchestration.
From development to production: Deploying Java and Scala apps to kubernetesOlanga Ochieng'
Presented at NairobiJVM meetup "From Development to Production: Deploying Java and Scala Apps on Kubernetes" https://www.meetup.com/nairobi-jvm/events/258119823
Multi-Cloud Orchestration for Kubernetes with Cloudify - Webinar PresentationCloudify Community
Watch the webinar at:
http://cloudify.co/webinars/multi-cloud-orchestration-kubernetes
Tune in as we unveil the new capabilities for maximizing use of Kubernetes with the new Cloudify Kubernetes Plugin, and the new Cloudify Kubernetes provider. Using Kubernetes with Cloudify has never been easier or more powerful, as you can now easily provision workloads on both cloud based VM’s and containers, or have total control and flexibility by using Cloudify as a Kubernetes IaaS.
The rise of microservices details how the software infrastructure of the future are changing. As corporations strive for competitive advantage, they must redesign their brownfield legacy applications and move them to the cloud. Agile Cloud applications follow microservices and cloudnative development patterns. Microservices architectures are enabled by Docker and Kubernetes. Both software are hosted by CNCF.
microservices architectures are being enhanced with a service mesh layer which simplifies the communication and management of cloudnative applications.
A Tale of Three Tools: Kubernetes, Jsonnet, and BazelDatabricks
As part of the long term goal to contribute to the Kubernetes ecosystem of components and tools, at Databricks we've implemented a Python tool called kubecfg to allow us to succinctly describe deployment configurations in a highly modular way. In its current version, kubecfg will compile Jsonnet files using the Python _jsonnet library from Google, accepting command-line arguments to override specific fields in a generated dictionary or to pass arguments to a Jsonnet script that accepts top-level arguments.
Containers are widely used today for consolidation and cloud native applications, with emerging uses in edge computing and serverless technologies. Containers provide efficiency, repeatability, isolation, and portability. Traditional uses include consolidation to reduce infrastructure costs and improve server utilization. Cloud native applications are also well suited to containers due to their microservices architecture enabling rapid deployment and scalability. For day 2 operations, container orchestration platforms like Kubernetes are used for lifecycle management, placement, and service discovery. Container storage interfaces provide pluggable storage solutions, while observability tools help debug complex microservices interactions through application performance monitoring and distributed tracing. Open APIs and standards are important to avoid vendor lock-in and allow flexibility in building, deploying and
This document discusses LINE's private cloud platform Verda and two new services: Verda Kubernetes as a Service (KaaS) and Verda Event Handler. Verda KaaS provides managed Kubernetes clusters to developers. It is built using Rancher and aims to simplify Kubernetes usage. Verda Event Handler aims to improve automation by defining operations as functions that are triggered by events. It will utilize Knative to provide a functions-as-a-service platform and improve visibility, operability, and maintenance of automation scripts. The status and future plans of these new services are also outlined.
Speed & Agility of Innovation with Docker & KubernetesICS
This document discusses how Docker and Kubernetes can help companies improve speed and agility of innovation. It provides an overview of Docker and Kubernetes, explaining how containers and orchestration allow for flexible infrastructure and streamlined development workflows. It also discusses strategies for moving applications to these technologies incrementally.
The document discusses using TOSCA modeling to orchestrate Kubernetes on OpenStack in a hybrid environment. It describes defining custom node types for Kubernetes, MongoDB, and microservices to model the target architecture. Workflows then execute to render the modeled infrastructure by deploying the necessary VMs, containers, and services. Metrics collected by a Diamond container are sent to Riemann, which triggers Kubernetes scaling through the orchestrator when thresholds are breached. TOSCA allows portably modeling multi-cloud orchestrations and hiding cloud implementation details.
D2iQ (formerly Mesosphere) Konvoy provides a standalone production-ready Kubernetes cluster with best-in-class components for operation and lifecycle management and Kommander to supercharge Day 2 operations.
Based on the leading open source Container Attached Storage software, MayaData OpenEBS Enterprise Platform reduces the risk and increases the agility of running stateful applications on Kubernetes.
In this webinar, experts from MayaData and D2iQ will talk about the benefits of using Konvoy and OpenEBS as part of an integrated solution on any cloud infrastructure. What makes Konvoy unique, it’s deployment and the typical use cases and show you how OpenEBS can be used to deploy and update Konvoy and also how OpenEBS can be deployed on Konvoy to simplify the deployment, management and monitoring of stateful applications.
Before we get into Q&A, MayaData team will live demonstrate the combined solution of D2iQ Konvoy and OpenEBS.
The combination of StackPointCloud with NetApp creates NetApp Kubernetes Service, the industry’s first complete Kubernetes platform for multi-cloud deployments and a complete cloud-based stack for Azure, Google Cloud, AWS, and NetApp HCI. Further, Trident is a fully supported open source project maintained by NetApp, designed from the ground up to help meet the sophisticated persistence demands of containerized applications.
This document discusses implementing multi-cloud deployments using Kubernetes. It outlines two reference architectures for Kubernetes multi-cloud - a monolithic approach with a single load balancer and a decoupled hierarchical approach. The core challenges of location affinity, cross-cluster service discovery, scheduling and migration are also covered. WSO2 Private PaaS is presented as a solution that addresses these challenges through network partitioning, a composite application model and runtime topology definitions. A comparison of features between Kubernetes and WSO2 Private PaaS is provided. The document concludes with WSO2's vision to contribute to Kubernetes and potentially use it as the foundation for their PaaS and microservices platform going forward.
An RSVP app designed to be deployed by the dockers on the Kubernetes Minikube Cluster. Front end with flask framework and MongoDB as a backend database.
Youtube video:https://youtu.be/KnjnQj-FvfQ
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2. 2017 | www.mirantis.com
● Why we’re getting involved in Kubernetes
community?
○ Containers and Kubernetes are the future
○ Need to improve the state of Kubernetes on Bare Metal
○ Our customers want Kubernetes
○ Open contribution process
■ Much more meritocratic approach then in case of Docker Swarm or
Mesos
● It started with Kubernetes on OpenStack via Murano
The beginning of the story
3. 2017 | www.mirantis.com
● Fixing bugs, writing tests
● Participating in SIG and Community meetings
● Helping with project management
● Trying to add features we need
Getting started with participating in k8s community
4. 2017 | www.mirantis.com
● Lack of reviewers
● Complicated discussions about new functionality
○ DaemonSet upgrades and anti-affinity
○ Multiple runtimes in Kubelet
○ Node evacuation / maintenance (partially in)
○ ConfigMap templates (rejected)
● It’s hard to land XXL patches in general
● The upstream wants to keep the core small
○ They want Kubernetes to be “the Linux kernel of distributed
systems”
Problems with working upstream
5. 2017 | www.mirantis.com
● Third Party Resources
● Container Runtime Interface
● External controllers that connect to apiserver
● Provide external tooling around kubernetes,
including one used for cluster setup
Extending Kubernetes without changing the core
6. 2017 | www.mirantis.com
● k8s-AppController: managing complex deployments
● k8s-externalipcontroller: external IP support for bare
metal k8s clusters
● Kargo: setting up a Kubernetes cluster
○ It was not Mirantis project in the beginning, but as of now it’s
mostly ours
● Virtlet: running VM workloads on Kubernetes clusters
Mirantis projects belonging to k8s ecosystem
7. 2017 | www.mirantis.com
● kubeadm-dind-cluster: running multinode
development clusters locally using Docker-in-Docker
● We didn’t stop being active in k8s core
○ we continue fixing bugs
○ also adding new features, e.g. for example, we’re working on
DaemonSet upgrades
● We lead SIG On-Prem, SIG-OpenStack and SIG-PM
● Mirantis is a member of CNCF
Mirantis projects belonging to k8s ecosystem
8. 2017 | www.mirantis.com
● The very initial purpose of k8s was mostly running
“cattle” workloads
● Support for stateful workloads is improving over time
○ For instance, there’s support for PVs, StatefulSets, init
containers etc.
● Defining dependencies between Kubernetes objects
is hard
○ E.g. a web app pod may need to wait for its database to
become ready. This may be a problem for legacy apps
AppController: managing complex deployments
9. 2017 | www.mirantis.com
AppController: managing complex deployments
Kubernetes cluster
AppController
pod
ThirdPartyResources
Resource
Definitions
Dependencies
Kubernetes
Objects
Kubectl (operator)
Creates
Extends API
Creates
Creates
Creates when
dependencies are met
Reads
Starts
Retrieves status
10. 2017 | www.mirantis.com
● AppController represents k8s objects and their
dependencies as TPRs
● k8s objects are created when their dependencies are
satisfied
○ E.g. pod can depend on a service or a job that needs to be
complete before the pod is created
○ Objects can depend on objects that are created by
AppController or pre-existing k8s objects
● Helm integration is WiP
● Application Lifecycle Management (planned)
AppController: managing complex deployments
11. 2017 | www.mirantis.com
● Ansible-based Kubernetes installer
● Supports AWS, GCE, Azure, OpenStack and BM
● Supports HA
● Flexible deployment options
○ A possibility to choose network plugin, load balancer, rkt
support for core services etc.
● Support most popular Linux distributions
● The project has extensive CI setup
● Battle-tested on Scale Lab (up to 1000 nodes)
● There are kubeadm integration plans
Kargo: setup a Kubernetes cluster
12. 2017 | www.mirantis.com
● Some legacy applications can’t be easily
containerized
○ Substantial effort may be necessary for the transition, there
can be licensing problems, there’s need for extra isolation and
so on
● Virtlet runs VMs as Pods, supports QCOW2 images
● VMs can communicate with other Pods and access
cluster services
Virtlet: running VM workloads on k8s clusters
14. 2017 | www.mirantis.com
● The implementation is based on Container Runtime
Interface
○ CRI is also being used by cri-o, hyper, rkt
○ It will be also be used for Docker in Kubernetes soon
● We’re making it easy to install Virtlet on k8s clusters
○ It can run as a DaemonSet and still avoid chicken-and-egg
problem thanks to multiple runtime support provided by CRI
Proxy
● “Futuristic” use case: running Unikernel applications
on Kubernetes cluster
Virtlet: running VM workloads on k8s clusters
15. 2017 | www.mirantis.com
● We will be speaking about more of our projects on
following meetups
● Questions?
Thanks for your attention!