Kasper Nissen gives a presentation on container orchestration on AWS. He discusses containers and why they are used, as well as the need for container orchestration to manage scheduling, resources, consensus, resilience and scalability. The main orchestration options covered are Docker Swarm, Apache Mesos, and Kubernetes. Kasper demos setting up Kubernetes clusters on AWS using both Rancher and Kops orchestration tools.
This document discusses Kubernetes operations (Kops), a tool for provisioning and managing Kubernetes clusters on AWS. Kops allows users to create, destroy, upgrade and maintain production-grade Kubernetes clusters from the command line. It automates the provisioning of Kubernetes clusters on AWS, deploying highly available Kubernetes masters and supporting upgrading and customizing clusters. The document demonstrates how to use Kops to build single and multi-master Kubernetes clusters on AWS with different configuration options.
Two Years In Production With Kubernetes - An Experience ReportKasper Nissen
This document summarizes a presentation about two years of experience using Kubernetes in production. It discusses how the company shifted to being application-oriented rather than machine-oriented, and introduced tools like Shuttle and Ham to improve developer experience and implement continuous delivery. It also covers how they used Kops to manage Kubernetes clusters across multiple availability zones and Dextre to improve node rollouts. While there were initial challenges, the presenter concludes that Kubernetes was the right choice and has allowed the company to scale their services.
Should developers care about dockerfiles and kubernetes resourcesKasper Nissen
Developers should not need to care directly about Dockerfiles and Kubernetes resources. The presenter's company centralized these files and used tools like Shuttle and Ham to automate builds and deployments. This improved velocity by removing duplication and providing a single source of truth. It ensured auditability and disaster recovery capability. While Kubernetes is important, it is part of the overall cloud native journey rather than the final destination. Developers are thus freed to focus on their applications rather than infrastructure details.
This document outlines the agenda for Cloud Native Aarhus #5 event hosted by Praqma at Phennex. The agenda includes welcome and introductions, presentations on the state of cloud native technologies and Kubernetes, workshops on cloud native topics, and a networking session over food. Attendees can join online discussions on the Cloud Native DK Slack channel or on Twitter using the hashtag #cloudnativeaarhus. The event will provide Kubernetes 101 tutorials and demos of running Kubernetes on Raspberry Pi clusters.
This document discusses Contentful Engineering's migration from using AWS alone to using Kubernetes on AWS. Some key points:
1) Contentful migrated to take advantage of Kubernetes' focus on application delivery and open source development model over their previous Chef-based deployment platform.
2) They use Kops to manage Kubernetes clusters on AWS, deploying clusters in the same VPC and using kubenet networking and kube2iam to integrate with AWS services.
3) The migration process involved moving services to Kubernetes deployments and exposing them via LoadBalancer services, and updating service discovery in Route53.
4) Lessons learned include staying up to date with Kubernetes and Kops releases, customizing Kops outputs
Deploying Highly Available Cluster with KOPS. What should be the major production consideration? Creating Kubernetes cluster on AWS by using Kubernetes Operations.
KubeCon EU 2016 Keynote: Kubernetes State of the UnionKubeAcademy
Kubernetes is growing rapidly with over 5,000 commits in the 1.2 release and 50% more contributors. The 1.2 release focuses on getting started quicker and getting big faster with a new UI, improved scaling, and simplified deployments. Key features in 1.2 include the deployment API for automated application updates, configmaps for late-binding configuration, and daemonsets to ensure a pod runs on each node. Version 1.3 is planned for the coming weeks with additional features to support legacy applications, federated clusters, auto-scaling, and more.
DevOps with Azure, Kubernetes, and Helm WebinarCodefresh
This document discusses DevOps tools for working with containers and Kubernetes. It introduces Helm as a package manager for Kubernetes that allows defining complex Kubernetes applications as charts that can be installed, upgraded, and rolled back easily. Codefresh is presented as a DevOps platform that integrates with Kubernetes and provides built-in steps for working with containers in CI/CD pipelines. The document provides an overview of concepts like containers, Docker, Kubernetes, orchestration, and Helm architecture. It also describes how to get started with installing Helm.
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.
A look at kubeless a serverless framework on top of kubernetes. We take a look at what serverless is and why it matters then introduce kubeless which leverages Kubernetes API resources to provide a Function as a Services solution.
This document discusses using Kubernetes on AWS and provides tips across three main topics: designing clusters, installation, and operations. For design, it recommends automating as much as possible, properly sizing clusters based on network and server capacities, and using permissions and tags to control access. For installation, it discusses using multiple AWS accounts for access control and tools like Kops to deploy and manage clusters. For operations, it discusses using AWS services for databases and logging instead of running them on Kubernetes, and considerations for custom registries and secrets. The overall message is how to leverage AWS services while deploying and managing Kubernetes clusters at scale.
In this webinar, Alex Casalboni will overview the main FaaS concepts and best practices (Function as a Service), explore the open-source FaaS options and discuss pros and cons of deploying and managing your own serverless platform on Kubernetes.
Zero downtime deployment of micro-services with KubernetesWojciech Barczyński
Talk on deployment strategies with Kubernetes covering kubernetes configuration files and the actual implementation of your service in Golang and .net core.
You will find demos for recreate, rolling updates, blue-green, and canary deployments.
Source and demos, you will find on github: https://github.com/wojciech12/talk_zero_downtime_deployment_with_kubernetes
Effective Building your Platform with Kubernetes == Keep it Simple Wojciech Barczyński
Effective Kubernetes is a continuous deployment process that the team understands. Keep it Simple. Think twice before going for more complex solutions.
Source: https://github.com/wojciech12/talk_effective_kubernetes
Presented at Cloud Native Talks #2 (Online Meetup) - https://www.meetup.com/Cloud-Native-Kubernetes-Warsaw/events/257125529/
This document discusses autoscaling in Kubernetes. It describes horizontal and vertical autoscaling, and how Kubernetes can autoscale nodes and pods. For nodes, it proposes using Google Compute Engine's managed instance groups and cloud autoscaler to automatically scale the number of nodes based on resource utilization. For pods, it discusses using an autoscaler controller to scale the replica counts of replication controllers based on metrics from cAdvisor or Google Cloud Monitoring. Issues addressed include rebalancing pods and handling autoscaling during rolling updates.
In this talk we explore ways to leverage new and improved features of the Google Cloud Platform for your applications - based on an Android demo using Cloud Vision API to detect sleeping students in class. We also look at a number of patterns for mobile backends with Firebase and AppEngine and discuss machine learning and Cloud Speech API.
Talk given at a Google Developer Group meetup in Aarhus by Kasper Løvborg Jensen on April 28, 2016.
Using source code management patterns to configure and secure your Kubernetes...Giovanni Galloro
In this session we will show how to set up, from scratch, a git repository to centrally manage, with Anthos Config Management, all the configurations and security policies of multiple Kubernetes clusters in different environments, using git as the source of truth and applying the processes typically used in source code lifecycle. We will also explore what is possible to do with ACM Policy Controller, based on Open Policy Agent Gatekeeper, and configure constraints to enforce many of the possible security policies that an enterprise organization would require.
Continuous Deployment with Jenkins on KubernetesMatt Baldwin
Google Senior Software Engineer Evan Brown's presentation from the March 18, 2016 Seattle Kubernetes meetup hosted by StackPointCloud. Evan shows how you deploy Jenkins into Kubernetes, then takes us through CD and canary deployments. Join us in Seattle: http://www.meetup.com/Seattle-Kubernetes-Meetup/
This document provides an overview of a workshop on running Kubernetes on AWS. It outlines the prerequisites including installing Git, AWS CLI, kubectl, and cloning a GitHub repository. The workshop will cover basic Kubernetes concepts like pods, labels, replication controllers, deployments and services. It will demonstrate how to build a Kubernetes cluster on AWS using CloudFormation for infrastructure as code. Hands-on portions will include deploying containers, creating services, and observing the cluster architecture and networking. Additional topics are cluster add-ons like Kubernetes Dashboard and DNS, deploying applications, and cleaning up resources.
The “rise” of the containers created very interesting opportunities for running and deploying micro-services and distributed software in general, like any good thing, it comes with a price. Building a Cloud-Native CI/CD infrastructure utilizing the advantages of containers is quite challenging. In this session, we will introduce the challenges of CI/CD in the cloud native world including building our CI/CD infrastructure as code and working with dynamic workers. We will explore popular projects aiming to help us with these challenges: Bloody Jenkins, Jenkins X and more.
PuppetConf 2016: Scaling Puppet on AWS ECS with Terraform and Docker – Maxime...Puppet
Here are the slides from Maxime Visonneau's PuppetConf 2016 presentation called Scaling Puppet on AWS ECS with Terraform and Docker. Watch the videos at https://www.youtube.com/playlist?list=PLV86BgbREluVjwwt-9UL8u2Uy8xnzpIqa
This document summarizes Chen Fisher's presentation on Kubernetes at nanit. The key points are:
1) Nanit uses Kubernetes for service orchestration, taking advantage of its built-in service discovery, high availability features, and port management capabilities.
2) Kubernetes is preferred over Amazon ECS due to ECS lacking service discovery and only supporting basic health checks.
3) Nanit runs two Kubernetes clusters for staging and production, with over 100 pods across more than 20 instances in production.
4) Nanit uses Kubernetes for deploying microservices from development to production, with Jenkins doing automated testing and deployment via Slack notifications.
Presented at AI NEXTCon Seattle 1/17-20, 2018
http://aisea18.xnextcon.com
join our free online AI group with 50,000+ tech engineers to learn and practice AI technology, including: latest AI news, tech articles/blogs, tech talks, tutorial videos, and hands-on workshop/codelabs, on machine learning, deep learning, data science, etc..
Kubernetes in Highly Restrictive EnvironmentsKublr
Installing Kubernetes is easy. Ensuring it complies with your organization’s enterprise governance and security requirements isn’t.
How do you use the technologies while meeting enterprise security requirements? We'll summarize common prerequisites for running Kubernetes in production, and how to leverage fine-grained controls and separation of responsibilities to meet enterprise governance and security needs.
This deck includes basic requirements for audit, security, authentication, authorization, integration with existing identity broker, logging, and monitoring. Additionally, we'll go into whether cloud-hosted Kubernetes cover these requirements, how to integrate a compliant Kubernetes installation with their existing cloud infrastructure and how to handle cross-team communication (network/compute/storage/security).
Since on-premise Kubernetes deployments have their challenges, limitations of a bare-metal installation, interactions with vSphere’s API, achieving HA, reliability and disaster recovery, as well as handling OS upgrades, security patches, and Kubernetes upgrades are also considered.
What do the terms serverless, containers, and virtual machines mean? Which should I use to build my app? The answer (as always) is "it depends." In this session learn the tradeoffs between these different approaches, whether you're building your app from scratch or want to move an existing web or mobile application to the cloud. We'll discuss open source tools such as Kubernetes, Istio, and Knative, and we'll discuss Google Cloud Platform tools like Compute Engine, Google Kubernetes Engine (GKE), App Engine, and Cloud Functions.
Cloud Native Night, April 2018, Mainz: Workshop led by Jörg Schad (@joerg_schad, Technical Community Lead / Developer at Mesosphere)
Join our Meetup: https://www.meetup.com/de-DE/Cloud-Native-Night/
PLEASE NOTE:
During this workshop, Jörg showed many demos and the audience could participate on their laptops. Unfortunately, we can't provide these demos. Nevertheless, Jörg's slides give a deep dive into the topic.
DETAILS ABOUT THE WORKSHOP:
Kubernetes has been one of the topics in 2017 and will probably remain so in 2018. In this hands-on technical workshop you will learn how best to deploy, operate and scale Kubernetes clusters from one to hundreds of nodes using DC/OS. You will learn how to integrate and run Kubernetes alongside traditional applications and fast data services of your choice (e.g. Apache Cassandra, Apache Kafka, Apache Spark, TensorFlow and more) on any infrastructure.
This workshop best suits operators focussed on keeping their apps and services up and running in production and developers focussed on quickly delivering internal and customer facing apps into production.
You will learn how to:
- Introduction to Kubernetes and DC/OS (including the differences between both)
- Deploy Kubernetes on DC/OS in a secure, highly available, and fault-tolerant manner
- Solve operational challenges of running a large/multiple Kubernetes cluster
- One-click deploy big data stateful and stateless services alongside a Kubernetes cluster
DevOps with Azure, Kubernetes, and Helm WebinarCodefresh
This document discusses DevOps tools for working with containers and Kubernetes. It introduces Helm as a package manager for Kubernetes that allows defining complex Kubernetes applications as charts that can be installed, upgraded, and rolled back easily. Codefresh is presented as a DevOps platform that integrates with Kubernetes and provides built-in steps for working with containers in CI/CD pipelines. The document provides an overview of concepts like containers, Docker, Kubernetes, orchestration, and Helm architecture. It also describes how to get started with installing Helm.
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.
A look at kubeless a serverless framework on top of kubernetes. We take a look at what serverless is and why it matters then introduce kubeless which leverages Kubernetes API resources to provide a Function as a Services solution.
This document discusses using Kubernetes on AWS and provides tips across three main topics: designing clusters, installation, and operations. For design, it recommends automating as much as possible, properly sizing clusters based on network and server capacities, and using permissions and tags to control access. For installation, it discusses using multiple AWS accounts for access control and tools like Kops to deploy and manage clusters. For operations, it discusses using AWS services for databases and logging instead of running them on Kubernetes, and considerations for custom registries and secrets. The overall message is how to leverage AWS services while deploying and managing Kubernetes clusters at scale.
In this webinar, Alex Casalboni will overview the main FaaS concepts and best practices (Function as a Service), explore the open-source FaaS options and discuss pros and cons of deploying and managing your own serverless platform on Kubernetes.
Zero downtime deployment of micro-services with KubernetesWojciech Barczyński
Talk on deployment strategies with Kubernetes covering kubernetes configuration files and the actual implementation of your service in Golang and .net core.
You will find demos for recreate, rolling updates, blue-green, and canary deployments.
Source and demos, you will find on github: https://github.com/wojciech12/talk_zero_downtime_deployment_with_kubernetes
Effective Building your Platform with Kubernetes == Keep it Simple Wojciech Barczyński
Effective Kubernetes is a continuous deployment process that the team understands. Keep it Simple. Think twice before going for more complex solutions.
Source: https://github.com/wojciech12/talk_effective_kubernetes
Presented at Cloud Native Talks #2 (Online Meetup) - https://www.meetup.com/Cloud-Native-Kubernetes-Warsaw/events/257125529/
This document discusses autoscaling in Kubernetes. It describes horizontal and vertical autoscaling, and how Kubernetes can autoscale nodes and pods. For nodes, it proposes using Google Compute Engine's managed instance groups and cloud autoscaler to automatically scale the number of nodes based on resource utilization. For pods, it discusses using an autoscaler controller to scale the replica counts of replication controllers based on metrics from cAdvisor or Google Cloud Monitoring. Issues addressed include rebalancing pods and handling autoscaling during rolling updates.
In this talk we explore ways to leverage new and improved features of the Google Cloud Platform for your applications - based on an Android demo using Cloud Vision API to detect sleeping students in class. We also look at a number of patterns for mobile backends with Firebase and AppEngine and discuss machine learning and Cloud Speech API.
Talk given at a Google Developer Group meetup in Aarhus by Kasper Løvborg Jensen on April 28, 2016.
Using source code management patterns to configure and secure your Kubernetes...Giovanni Galloro
In this session we will show how to set up, from scratch, a git repository to centrally manage, with Anthos Config Management, all the configurations and security policies of multiple Kubernetes clusters in different environments, using git as the source of truth and applying the processes typically used in source code lifecycle. We will also explore what is possible to do with ACM Policy Controller, based on Open Policy Agent Gatekeeper, and configure constraints to enforce many of the possible security policies that an enterprise organization would require.
Continuous Deployment with Jenkins on KubernetesMatt Baldwin
Google Senior Software Engineer Evan Brown's presentation from the March 18, 2016 Seattle Kubernetes meetup hosted by StackPointCloud. Evan shows how you deploy Jenkins into Kubernetes, then takes us through CD and canary deployments. Join us in Seattle: http://www.meetup.com/Seattle-Kubernetes-Meetup/
This document provides an overview of a workshop on running Kubernetes on AWS. It outlines the prerequisites including installing Git, AWS CLI, kubectl, and cloning a GitHub repository. The workshop will cover basic Kubernetes concepts like pods, labels, replication controllers, deployments and services. It will demonstrate how to build a Kubernetes cluster on AWS using CloudFormation for infrastructure as code. Hands-on portions will include deploying containers, creating services, and observing the cluster architecture and networking. Additional topics are cluster add-ons like Kubernetes Dashboard and DNS, deploying applications, and cleaning up resources.
The “rise” of the containers created very interesting opportunities for running and deploying micro-services and distributed software in general, like any good thing, it comes with a price. Building a Cloud-Native CI/CD infrastructure utilizing the advantages of containers is quite challenging. In this session, we will introduce the challenges of CI/CD in the cloud native world including building our CI/CD infrastructure as code and working with dynamic workers. We will explore popular projects aiming to help us with these challenges: Bloody Jenkins, Jenkins X and more.
PuppetConf 2016: Scaling Puppet on AWS ECS with Terraform and Docker – Maxime...Puppet
Here are the slides from Maxime Visonneau's PuppetConf 2016 presentation called Scaling Puppet on AWS ECS with Terraform and Docker. Watch the videos at https://www.youtube.com/playlist?list=PLV86BgbREluVjwwt-9UL8u2Uy8xnzpIqa
This document summarizes Chen Fisher's presentation on Kubernetes at nanit. The key points are:
1) Nanit uses Kubernetes for service orchestration, taking advantage of its built-in service discovery, high availability features, and port management capabilities.
2) Kubernetes is preferred over Amazon ECS due to ECS lacking service discovery and only supporting basic health checks.
3) Nanit runs two Kubernetes clusters for staging and production, with over 100 pods across more than 20 instances in production.
4) Nanit uses Kubernetes for deploying microservices from development to production, with Jenkins doing automated testing and deployment via Slack notifications.
Presented at AI NEXTCon Seattle 1/17-20, 2018
http://aisea18.xnextcon.com
join our free online AI group with 50,000+ tech engineers to learn and practice AI technology, including: latest AI news, tech articles/blogs, tech talks, tutorial videos, and hands-on workshop/codelabs, on machine learning, deep learning, data science, etc..
Kubernetes in Highly Restrictive EnvironmentsKublr
Installing Kubernetes is easy. Ensuring it complies with your organization’s enterprise governance and security requirements isn’t.
How do you use the technologies while meeting enterprise security requirements? We'll summarize common prerequisites for running Kubernetes in production, and how to leverage fine-grained controls and separation of responsibilities to meet enterprise governance and security needs.
This deck includes basic requirements for audit, security, authentication, authorization, integration with existing identity broker, logging, and monitoring. Additionally, we'll go into whether cloud-hosted Kubernetes cover these requirements, how to integrate a compliant Kubernetes installation with their existing cloud infrastructure and how to handle cross-team communication (network/compute/storage/security).
Since on-premise Kubernetes deployments have their challenges, limitations of a bare-metal installation, interactions with vSphere’s API, achieving HA, reliability and disaster recovery, as well as handling OS upgrades, security patches, and Kubernetes upgrades are also considered.
What do the terms serverless, containers, and virtual machines mean? Which should I use to build my app? The answer (as always) is "it depends." In this session learn the tradeoffs between these different approaches, whether you're building your app from scratch or want to move an existing web or mobile application to the cloud. We'll discuss open source tools such as Kubernetes, Istio, and Knative, and we'll discuss Google Cloud Platform tools like Compute Engine, Google Kubernetes Engine (GKE), App Engine, and Cloud Functions.
Cloud Native Night, April 2018, Mainz: Workshop led by Jörg Schad (@joerg_schad, Technical Community Lead / Developer at Mesosphere)
Join our Meetup: https://www.meetup.com/de-DE/Cloud-Native-Night/
PLEASE NOTE:
During this workshop, Jörg showed many demos and the audience could participate on their laptops. Unfortunately, we can't provide these demos. Nevertheless, Jörg's slides give a deep dive into the topic.
DETAILS ABOUT THE WORKSHOP:
Kubernetes has been one of the topics in 2017 and will probably remain so in 2018. In this hands-on technical workshop you will learn how best to deploy, operate and scale Kubernetes clusters from one to hundreds of nodes using DC/OS. You will learn how to integrate and run Kubernetes alongside traditional applications and fast data services of your choice (e.g. Apache Cassandra, Apache Kafka, Apache Spark, TensorFlow and more) on any infrastructure.
This workshop best suits operators focussed on keeping their apps and services up and running in production and developers focussed on quickly delivering internal and customer facing apps into production.
You will learn how to:
- Introduction to Kubernetes and DC/OS (including the differences between both)
- Deploy Kubernetes on DC/OS in a secure, highly available, and fault-tolerant manner
- Solve operational challenges of running a large/multiple Kubernetes cluster
- One-click deploy big data stateful and stateless services alongside a Kubernetes cluster
In this WebHack talk I shared my experience about microservices, Docker, Kubernetes and Kong, an API gateway by Mashape. Since they are based on a real working system, this slides is majorly for how to build the whole thing up, not about detailed internal implementation. Although I included some details and reference in order to make it more comprehensive.
Ultimate Guide to Microservice Architecture on Kuberneteskloia
This document provides an overview of microservice architecture on Kubernetes. It discusses:
1. Benefits of microservice architecture like independent deployability and scalability compared to monolithic applications.
2. Best practices for microservices including RESTful design, distributed configuration, client code generation, and API gateways.
3. Tools for microservices on Kubernetes including Prometheus for monitoring, Elasticsearch (ELK) stack for logging, service meshes, and event sourcing with CQRS.
How to build "AutoScale and AutoHeal" systems using DevOps practices by using modern technologies.
A complete build pipeline and the process of architecting a nearly unbreakable system were part of the presentation.
These slides were presented at 2018 DevOps conference in Singapore. http://claridenglobal.com/conference/devops-sg-2018/
Pivotal Container Service (PKS) provides an enterprise-grade Kubernetes platform that can be deployed on any cloud infrastructure using the open source BOSH tool. PKS handles operations tasks like provisioning and upgrading Kubernetes clusters, integrates with VMware technologies for networking and security, and provides a centralized control plane for managing multiple clusters and tenants. It aims to deliver the benefits of Kubernetes to enterprises by adding capabilities for high availability, multi-tenancy, security and automation.
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups related containers into logical units called pods and manages the pods' lifecycles and services. Key Kubernetes objects include pods, deployments, services, and secrets. The declarative model defines the desired state and Kubernetes ensures the actual state matches it.
Faster, more Secure Application Modernization and Replatforming with PKS - Ku...VMware Tanzu
Faster, more Secure Application Modernization and Replatforming with PKS - Kubernetes for the Enterprise - London
Alex Ley
Associate Director, App Transformation, Pivotal EMEA
28th March 2018
The Kubernetes cloud native landscape is vast. Delivering a solution requires managing a puzzling array of required tooling, monitoring, disaster recovery, and other solutions that lie outside the realm of the central cluster. The governing body of Kubernetes, the Cloud Native Computing Foundation, has developed guidance for organizations interested in this topic by publishing the Cloud Native Landscape, but while a list of options is helpful it does not give operations and DevOps professionals the knowledge they need to execute.
Learn best practices of setting up and managing the tools needed around Kubernetes. This presentation covers popular open source options (to avoid lock in) and how one can implement and manage these tools on an ongoing basis. Learn from, and do not repeat, the mistakes of previous centralized platforms.
In this session, attendees will learn:
1. Cloud Native Landscape 101 - Prometheus, Sysdig, NGINX, and more. Where do they all fit in Kubernetes solution?
2. Avoiding the OpenStack sprawl of managing a multiverse of required tooling in the Kubernetes world.
3. Leverage technology like Kubernetes, now available on DC/OS, to provide part of the infrastructure framework that helps manage cloud native application patterns.
Persistent Storage for stateful applications on Kubernetes made easy with Ope...MayaData Inc
In this webinar, Director of Community of Rancher Labs Jason van Brackel joins forces with Sr. Developer Advocate Patrick Hoolboom from MayaData to talk about benefits of OpenEBS and Rancher as a combined solution.
Rancher's multi-cluster Kubernetes management solution allows development teams to iterate fast, deploy efficiently and operate at scale. Kubernetes allows you to orchestrate containers that are highly available. However, in the case of container reschedule, Kubernetes does not provide a great set of primitives to manage your persistent data along with your application containers. In this webinar, we will present some of the challenges associated with managing persistent data in Kubernetes and how we can make day 2 operations easier to manage. We will briefly introduce the combined offering and talk about a couple of approaches to solving data persistence problems in multi-cloud environments with Rancher and OpenEBS. During the demos, we will showcase how we address data availability with OpenEBS.
We will also talk about project updates in the latest releases and preview of upcoming Kubecon announcements.
Move fast and make things with microservicesMithun Arunan
1. How to apply microservices patterns & anti-patterns to design the right architecture
2. Why & how to build a core framework to ensure consistency & manage complexity
3. What are the challenges in adopting gRPC for inter-service communication
4. How to orchestrate & manage microservices at scale with Kubernetes
5. How to leverage Cloud Native ecosystem to move fast & avoid vendor lock-in
This document provides an overview of Container as a Service (CaaS) with Docker. It discusses key concepts like Docker containers, images, and orchestration tools. It also covers DevOps practices like continuous delivery that are enabled by Docker. Specific topics covered include Docker networking, volumes, and orchestration with Docker Swarm and compose files. Examples are provided of building and deploying Java applications with Docker, including Spring Boot apps, Java EE apps, and using Docker for builds. Security features of Docker like content trust and scanning are summarized. The document concludes by discussing Docker use cases across different industries and how Docker enables critical transformations around cloud, DevOps, and application modernization.
The DevOps paradigm - the evolution of IT professionals and opensource toolkitMarco Ferrigno
This document discusses the DevOps paradigm and tools. It begins by defining DevOps as focusing on communication and cooperation between development and operations teams. It then discusses concepts like continuous integration, delivery and deployment. It provides examples of tools used in DevOps like Docker, Kubernetes, Ansible, and monitoring tools. It discusses how infrastructure has evolved to be defined through code. Finally, it discusses challenges of security in DevOps and how DevOps works aligns with open source principles like meritocracy, metrics, and continuous improvement.
This document summarizes the DevOps paradigm and tools. It discusses how DevOps aims to improve communication and cooperation between development and operations teams through practices like continuous integration, delivery, and deployment. It then provides an overview of common DevOps tools for containers, cluster management, automation, CI/CD, monitoring, and infrastructure as code. Specific tools mentioned include Docker, Kubernetes, Ansible, Jenkins, and AWS CloudFormation. The document argues that adopting open source principles and emphasizing leadership, culture change, and talent growth are important for successful DevOps implementation.
Kubernetes: від знайомства до використання у CI/CDStfalcon Meetups
Kubernetes: від знайомства до використання у CI/CD
Олександр Занічковський
Technical Lead у компанії SoftServe
14+ років досвіду розробки різноманітного програмного забезпечення, як для десктопа, так і для веб
Працював фріланс-програмістом та в команді
Цікавиться архітектурою ПЗ, автоматизацією процесів інтеграції та доставки нових версій продукту, хмарними технологіями
Віднедавна займається менторінгом майбутніх техлідів
У вільний від роботи час грає на гітарі і мріє про велику сцену
Олександр поділиться власним досвідом роботи з Kubernetes:
ознайомить з базовими поняттями та примітивами K8S
опише можливі сценарії використання Kubernetes для CI/CD на прикладі GitLab
покаже, як можна використовувати постійне сховище, збирати метрики контейнерів, використовувати Ingress для роутинга запитів за певними правилами
покаже, як можна самому встановити K8S для ознайомлення чи локальної роботи
Reference architectures shows a microservices deployed to KubernetesRakesh Gujjarlapudi
The document discusses microservices architecture on Kubernetes. It describes microservices as minimal, independently deployable services that interact to provide broader functionality. It contrasts this with monolithic applications. It then covers key aspects of microservices like ownership, tradeoffs compared to traditional applications, common adoption cases, and differences from SOA. It provides a reference architecture diagram for microservices on Kubernetes including components like ingress, services, CI/CD pipelines, container registry, and data stores. It also discusses design considerations for Kubernetes microservices including using Kubernetes services for service discovery and load balancing, and using an API gateway for routing between clients and services.
Fluentd is an open source data collector that allows flexible data collection, processing, and output. It supports streaming data from sources like logs and metrics to destinations like databases, search engines, and object stores. Fluentd's plugin-based architecture allows it to support a wide variety of use cases. Recent versions of Fluentd have added features like improved plugin APIs, nanosecond time resolution, and Windows support to make it more suitable for containerized environments and low-latency applications.
Pivotal Container Service (PKS) at SF Cloud Foundry Meetupcornelia davis
Overview of Pivotal Container Service (PKS), built on the open source Cloud Foundry Container Runtime (CFCR). Covers what Kubernetes is, how PKS presents a complete platform that includes Kubernetes and much more, and key cloud principles.
Presented at the San Francisco-Bay Area Cloud Foundry meetup.
The path to a serverless-native era with Kubernetessparkfabrik
In this talk we'll talk about how the Serverless paradigms are changing the way we develop applications and cloud infrastructure and how we can implement them in a
efficient and seamless way with Kubernetes.
We'll go through the latest Kubernetes Serverless technologies, talking about all the aspects
including pricing, scalability, observability and best practices.
IT Minds Mindblown Networking Event 2016Kasper Nissen
Presentation from the IT Minds Mindblown Networking Event at Turbinehallen in Aarhus, Denmark.
Topics include Cloud Computing, Microservices, Containers, Cluster Management, etc.
The document provides an overview of cloud platforms and Kubernetes. It introduces cloud computing concepts like virtualization, deployment models, and service models. It then discusses Kubernetes, including concepts like pods, services, labels, replica sets, and deployments. It demonstrates how Kubernetes manages and scales containers across nodes and provides a demo of Kubernetes on a Raspberry Pi cluster and Google Container Engine.
Let's tak Productivity (Let's talk Apple #4)Kasper Nissen
The document summarizes updates from WWDC including improvements to iOS 9 like NSUserActivity API, CoreSpotlight framework, and search features. It also discusses updates to Swift 2 like error handling and availability checking. watchOS 2 is highlighted as running natively on the Apple Watch instead of iPhone. The agenda then shifts to presentations about using Fastlane for iOS deployment automation and the importance of version control tools. It closes by announcing a barbecue social following the presentations.
This is the keynote of the Into the Box conference, highlighting the release of the BoxLang JVM language, its key enhancements, and its vision for the future.
Massive Power Outage Hits Spain, Portugal, and France: Causes, Impact, and On...Aqusag Technologies
In late April 2025, a significant portion of Europe, particularly Spain, Portugal, and parts of southern France, experienced widespread, rolling power outages that continue to affect millions of residents, businesses, and infrastructure systems.
Designing Low-Latency Systems with Rust and ScyllaDB: An Architectural Deep DiveScyllaDB
Want to learn practical tips for designing systems that can scale efficiently without compromising speed?
Join us for a workshop where we’ll address these challenges head-on and explore how to architect low-latency systems using Rust. During this free interactive workshop oriented for developers, engineers, and architects, we’ll cover how Rust’s unique language features and the Tokio async runtime enable high-performance application development.
As you explore key principles of designing low-latency systems with Rust, you will learn how to:
- Create and compile a real-world app with Rust
- Connect the application to ScyllaDB (NoSQL data store)
- Negotiate tradeoffs related to data modeling and querying
- Manage and monitor the database for consistently low latencies
AI and Data Privacy in 2025: Global TrendsInData Labs
In this infographic, we explore how businesses can implement effective governance frameworks to address AI data privacy. Understanding it is crucial for developing effective strategies that ensure compliance, safeguard customer trust, and leverage AI responsibly. Equip yourself with insights that can drive informed decision-making and position your organization for success in the future of data privacy.
This infographic contains:
-AI and data privacy: Key findings
-Statistics on AI data privacy in the today’s world
-Tips on how to overcome data privacy challenges
-Benefits of AI data security investments.
Keep up-to-date on how AI is reshaping privacy standards and what this entails for both individuals and organizations.
What is Model Context Protocol(MCP) - The new technology for communication bw...Vishnu Singh Chundawat
The MCP (Model Context Protocol) is a framework designed to manage context and interaction within complex systems. This SlideShare presentation will provide a detailed overview of the MCP Model, its applications, and how it plays a crucial role in improving communication and decision-making in distributed systems. We will explore the key concepts behind the protocol, including the importance of context, data management, and how this model enhances system adaptability and responsiveness. Ideal for software developers, system architects, and IT professionals, this presentation will offer valuable insights into how the MCP Model can streamline workflows, improve efficiency, and create more intuitive systems for a wide range of use cases.
Dev Dives: Automate and orchestrate your processes with UiPath MaestroUiPathCommunity
This session is designed to equip developers with the skills needed to build mission-critical, end-to-end processes that seamlessly orchestrate agents, people, and robots.
📕 Here's what you can expect:
- Modeling: Build end-to-end processes using BPMN.
- Implementing: Integrate agentic tasks, RPA, APIs, and advanced decisioning into processes.
- Operating: Control process instances with rewind, replay, pause, and stop functions.
- Monitoring: Use dashboards and embedded analytics for real-time insights into process instances.
This webinar is a must-attend for developers looking to enhance their agentic automation skills and orchestrate robust, mission-critical processes.
👨🏫 Speaker:
Andrei Vintila, Principal Product Manager @UiPath
This session streamed live on April 29, 2025, 16:00 CET.
Check out all our upcoming Dev Dives sessions at https://community.uipath.com/dev-dives-automation-developer-2025/.
UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager APIUiPathCommunity
Join this UiPath Community Berlin meetup to explore the Orchestrator API, Swagger interface, and the Test Manager API. Learn how to leverage these tools to streamline automation, enhance testing, and integrate more efficiently with UiPath. Perfect for developers, testers, and automation enthusiasts!
📕 Agenda
Welcome & Introductions
Orchestrator API Overview
Exploring the Swagger Interface
Test Manager API Highlights
Streamlining Automation & Testing with APIs (Demo)
Q&A and Open Discussion
Perfect for developers, testers, and automation enthusiasts!
👉 Join our UiPath Community Berlin chapter: https://community.uipath.com/berlin/
This session streamed live on April 29, 2025, 18:00 CET.
Check out all our upcoming UiPath Community sessions at https://community.uipath.com/events/.
Semantic Cultivators : The Critical Future Role to Enable AIartmondano
By 2026, AI agents will consume 10x more enterprise data than humans, but with none of the contextual understanding that prevents catastrophic misinterpretations.
Book industry standards are evolving rapidly. In the first part of this session, we’ll share an overview of key developments from 2024 and the early months of 2025. Then, BookNet’s resident standards expert, Tom Richardson, and CEO, Lauren Stewart, have a forward-looking conversation about what’s next.
Link to recording, presentation slides, and accompanying resource: https://bnctechforum.ca/sessions/standardsgoals-for-2025-standards-certification-roundup/
Presented by BookNet Canada on May 6, 2025 with support from the Department of Canadian Heritage.
Linux Support for SMARC: How Toradex Empowers Embedded DevelopersToradex
Toradex brings robust Linux support to SMARC (Smart Mobility Architecture), ensuring high performance and long-term reliability for embedded applications. Here’s how:
• Optimized Torizon OS & Yocto Support – Toradex provides Torizon OS, a Debian-based easy-to-use platform, and Yocto BSPs for customized Linux images on SMARC modules.
• Seamless Integration with i.MX 8M Plus and i.MX 95 – Toradex SMARC solutions leverage NXP’s i.MX 8 M Plus and i.MX 95 SoCs, delivering power efficiency and AI-ready performance.
• Secure and Reliable – With Secure Boot, over-the-air (OTA) updates, and LTS kernel support, Toradex ensures industrial-grade security and longevity.
• Containerized Workflows for AI & IoT – Support for Docker, ROS, and real-time Linux enables scalable AI, ML, and IoT applications.
• Strong Ecosystem & Developer Support – Toradex offers comprehensive documentation, developer tools, and dedicated support, accelerating time-to-market.
With Toradex’s Linux support for SMARC, developers get a scalable, secure, and high-performance solution for industrial, medical, and AI-driven applications.
Do you have a specific project or application in mind where you're considering SMARC? We can help with Free Compatibility Check and help you with quick time-to-market
For more information: https://www.toradex.com/computer-on-modules/smarc-arm-family
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfAbi john
Analyze the growth of meme coins from mere online jokes to potential assets in the digital economy. Explore the community, culture, and utility as they elevate themselves to a new era in cryptocurrency.
Enhancing ICU Intelligence: How Our Functional Testing Enabled a Healthcare I...Impelsys Inc.
Impelsys provided a robust testing solution, leveraging a risk-based and requirement-mapped approach to validate ICU Connect and CritiXpert. A well-defined test suite was developed to assess data communication, clinical data collection, transformation, and visualization across integrated devices.
How Can I use the AI Hype in my Business Context?Daniel Lehner
𝙄𝙨 𝘼𝙄 𝙟𝙪𝙨𝙩 𝙝𝙮𝙥𝙚? 𝙊𝙧 𝙞𝙨 𝙞𝙩 𝙩𝙝𝙚 𝙜𝙖𝙢𝙚 𝙘𝙝𝙖𝙣𝙜𝙚𝙧 𝙮𝙤𝙪𝙧 𝙗𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙣𝙚𝙚𝙙𝙨?
Everyone’s talking about AI but is anyone really using it to create real value?
Most companies want to leverage AI. Few know 𝗵𝗼𝘄.
✅ What exactly should you ask to find real AI opportunities?
✅ Which AI techniques actually fit your business?
✅ Is your data even ready for AI?
If you’re not sure, you’re not alone. This is a condensed version of the slides I presented at a Linkedin webinar for Tecnovy on 28.04.2025.
AI Changes Everything – Talk at Cardiff Metropolitan University, 29th April 2...Alan Dix
Talk at the final event of Data Fusion Dynamics: A Collaborative UK-Saudi Initiative in Cybersecurity and Artificial Intelligence funded by the British Council UK-Saudi Challenge Fund 2024, Cardiff Metropolitan University, 29th April 2025
https://alandix.com/academic/talks/CMet2025-AI-Changes-Everything/
Is AI just another technology, or does it fundamentally change the way we live and think?
Every technology has a direct impact with micro-ethical consequences, some good, some bad. However more profound are the ways in which some technologies reshape the very fabric of society with macro-ethical impacts. The invention of the stirrup revolutionised mounted combat, but as a side effect gave rise to the feudal system, which still shapes politics today. The internal combustion engine offers personal freedom and creates pollution, but has also transformed the nature of urban planning and international trade. When we look at AI the micro-ethical issues, such as bias, are most obvious, but the macro-ethical challenges may be greater.
At a micro-ethical level AI has the potential to deepen social, ethnic and gender bias, issues I have warned about since the early 1990s! It is also being used increasingly on the battlefield. However, it also offers amazing opportunities in health and educations, as the recent Nobel prizes for the developers of AlphaFold illustrate. More radically, the need to encode ethics acts as a mirror to surface essential ethical problems and conflicts.
At the macro-ethical level, by the early 2000s digital technology had already begun to undermine sovereignty (e.g. gambling), market economics (through network effects and emergent monopolies), and the very meaning of money. Modern AI is the child of big data, big computation and ultimately big business, intensifying the inherent tendency of digital technology to concentrate power. AI is already unravelling the fundamentals of the social, political and economic world around us, but this is a world that needs radical reimagining to overcome the global environmental and human challenges that confront us. Our challenge is whether to let the threads fall as they may, or to use them to weave a better future.
3. Lunar Way
• The Partner model
• Leverage the partner banks infrastructure
• All money is in the partner bank
• Currently only in Denmark, will move to the nordics in the near future
4. Kasper Nissen
DevOps & Infrastructure Engineer @thelunarway
Experience
DevOps & Infrastructure Engineer @ LEGO (CITMABIS) (oursourced by
IT Minds) for 5 months
Senior/Software Engineer @ IT Minds (~4 years part time)
Master thesis: KubeCloud - A Small-Scale Tangible Cloud Computing
Environment.
Interview with Software Engineering Daily: bit.ly/2paZ5lg
Blogging about Cloud Native Tech @ www.kubecloud.io
M. Eng. Computer Technology from Aarhus University - Department of
Engineering.
B. Eng. Information and Communication Technology from Aarhus
University - School of Engineering
5. What do we have running?
19services
215containers
in prod
13infrastructure
services
3node rabbitmq
cluster
1rails
monolith
2100 GB
postgresql
DB’s
3kubernetes
clusters
3AWS Accounts
13. Why ?
• Development
• Freedom and autonomy
• Best tool for the job
• Speed
• Architecture
• Fault tolerance
• Flexibility
• Coherence, decoupling,
encapsulation
• Deployment
• Independence
• Scalability
• Speed
• Resource utilisation
1. 2. 3.
(our Microservice vision)
14. How are we building our services?
Asynchronous first
Decoupling in time and space allows for autonomy
Shared dependencies
Common packages, such as logging, monitoring, communication
Each service has it’s own repository
Containing source code, deployment spec, pipeline, etc.
HTTP REQ
event
Repo
20. Why?
Isolation
Services are isolated and contained in their environment
Consistency in portability
The container will run in the same way in local env as in prod
Versioning
Versioning a container is easy, rolling back and forth becomes easy
Container
App
Runtime
OS
Container
App
Runtime
OS
Container
App
Runtime
OS
Container
App
Runtime
OS
Development
Container
App
Runtime
OS
Production
Container
App V1
Runtime
OS
Container
App V2
Runtime
OS
Container
App
Runtime
OS
image:v1 image:v2 image:v3
23. Why?
Scheduling
The scheduler will schedule your service on a node
Resource optimization
Scheduling allows for better packaging of services in hosts
Resiliency
If a node dies, the scheduler will reschedule on another node
Scalability
Scaling a dynamically cluster is easy, just add more nodes
27. Why Kubernetes?
Community
48k+ commits, 22+ GitHub stars, 1.1k contributors
Crossplatform
Multiple arcs, multiple cloud providers
Resource optimization
Packing nodes to utilize available resources
Tooling
A lot of great tools
Scaling
Great integration with auto-scaling, both
on node- and container-level
High availability
Automatic failover, redundancy
Pure Awesomeness!
It’s just awesome!
1.5 release:
Estimated 400 years of work hours
28. What does it do?
Node Node Node Node Node
Node Node Node Node Node
big dataapp Bapp A database
datacenter
Cluster Manager
29. Where does it run?
eu-west-1a
eu-west-1b
eu-west-1c
Private
Public
30. Services running in kubernetes
Networking
infrastructure
elb
internal
elb
api
elb
nginx-ingress linkerd route53 default-backend
Logging
es-proxy
Dev Demo
service 1 service #
…
service 1 service #
…
Monitoring
prometheus
Misc
sanity-checks
release-notifier
pushgateway
alertmanager
grafana
fluentd
kibana
node-exporter
postgresql-exporter
rabbitmq-exporter
cloudwatch-
exporter
31. What do we think of it?
Freedom
Squads can deploy and more or less implement
how they see fit
Autonomous services
Squads can work independent of other squads
Continuous Delivery
Kubernetes allows us to deploy multiple times
a day. It’s easy to rollback in case something
went wrong
Flexibility
We run many different type of workloads in the
cluster. Gives us mobility to become cloud
agnostic
Scalable infrastructure
Scaling the infrastructure is easy, both on
node and container level
High availability
Kubernetes takes care of container
failures, AWS Auto Scaling groups takes
care of node failures
Easy maintenance
We are using Kubernetes Operations to
help us spin up our clusters, and maintain
them.
33. Why fluentd?
Simple and Easy
Provides a simple interface for specifying input and output. Works great with Kubernetes and containers.
Community
Big community around fluentd, validates our choice.
Small memory footprint
Do not require a lot of resources in the cluster
Proven reliability and performance
It’s a fairly battle tested project
34. What does it do?
<source>
@type tail
path /var/log/containers/*.log
pos_file /var/log/containers/es-containers.log.pos
tag kubernetes.application.*
format json
time_key event_time
time_format %Y-%m-%dT%H:%M:%S.%3NZ
</source>
<filter kubernetes.application.**>
@type kubernetes_metadata
merge_json_log true
preserve_json_log false
</filter>
<match kubernetes.application.**>
type elasticsearch
host es-proxy
port 9200
include_tag_key true
logstash_format true
logstash_prefix application-
reload_on_failure true
</match>
1.
2.
3.
36. What do we think of it?
Very easy to use
Set up is easy!
Works great with Kubernetes
Awesome plugin for adding Kubernetes metadata - making it easy to identify pods etc.
Run as a daemonset
Easy to run in every node of the cluster as a daemonset
39. What does it do?
Multi-dimensional data model
Time series identified by metric name and key/value pairs
Flexible query language
Comes with a builtin query language for al kinds of operations, sums, averages, increase, rate, etc.
Easy and simple
Easy to setup, and works great with Kubernetes service discovery
Alerting and great integration with Grafana
Prometheus has a builtin alerting system, and Grafana provides easy integration for making
metrics visible in dashboards
Pull-based approach
Prometheus scrapes it’s targets at a regular interval
40. What metrics are we collecting?
Kubernetes specific metrics
Pods running, health of Kubernetes system components, etc.
RabbitMQ
Activity in queues, unacknowledged messages
Nodes
CPU, Memory
Traffic
Incoming traffic, upstream latency in cluster, etc.
Containers
CPU, Memory
Application Specific metrics
Relevant metrics, instrumented by the services owners
42. What do we think of it?
Provides great insights
Provides valuable insights in the state of the cluster
Makes is easy to developers to instrument their services
We provide a simple package for instrumentation, making squads able to do their own
monitoring. YOU BUILT IT, YOU RUN IT!
Grafana integrations is sweet!
Grafana and Prometheus works well together, making Grafana the interface for building dashboards
and alerts
Kubernetes <3 Prometheus
The only thing a service owner has to do in the cluster to make Prometheus scrape their services is to
add:
annotations:
prometheus.io/scrape: 'true'
45. What do we use it for?
It will be our default choice for synchronous calls
Synchronous service to service communication will be aligned on gRPC
Internal support system will use it to fetch data from our services
Our internal support system needs information from different services on demand, the service
will use gRPC to fetch the data
service 4
service 3
service 1
service 2
Support
46. Why gRPC?
Simple service definition using Protocol buffers
Simpler request handling, no need for serialization and deserialization
Binary protocol
Less overhead in communication.
Works across multiple languages and platforms
gRPC has a widespread support for multiple languages, making it a perfect fit in our current
polyglot architecture
Works great with go and the rest of the ecosystem
Docker, Kubernetes uses gRPC as long with Go. It’s a natural extension for service to service
communication. Based on many years of Google experience!
48. Are we there yet?
YES! and no..
We deploy multiple times a day
Deployment is autonomous, squads can deploy to production as they please.
We can easily scale to larger demands, if necessary
Scaling our infrastructure is easy
HOWEVER, doing microservices are complex!
We still need to implement better tracing, using the CNCF project OpenTracing and Zipkin
We need more insights and smarter routing in our service to service communication, we will be
using linkerd.
We can tolerate AZ failures to some extend
Our services are spread across availability zones
50. Thank you for listening!
That was it for me!
If you wanna know more, send me a message in the Cloud Native DK Slack Community.
Remember to sign up at: https://cloudnative-dk.herokuapp.com/
Catch me on Twitter @phennex
I will be speaking again:
• CoDe:U - Continuous Delivery Users Århus (June 20th in INCUBA, Åbogade 15, Aarhus N)
• Link: https://www.meetup.com/CoDe-U-AROS/events/239847862/
• GOTOCon Copenhagen - October 1st
• Link: https://gotocph.com/2017/sessions/237