Soft Introduction to Google's framework for taming containers in the cloud. For devs and architects that they just enter the world of cloud, microservices and containers
The document discusses Kubernetes networking. It describes how Kubernetes networking allows pods to have routable IPs and communicate without NAT, unlike Docker networking which uses NAT. It covers how services provide stable virtual IPs to access pods, and how kube-proxy implements services by configuring iptables on nodes. It also discusses the DNS integration using SkyDNS and Ingress for layer 7 routing of HTTP traffic. Finally, it briefly mentions network plugins and how Kubernetes is designed to be open and customizable.
This document discusses microservices and containers, and how Kubernetes can be used for container orchestration. It begins with an overview of microservices and the benefits of breaking monolithic applications into independent microservices. It then discusses how containers can be used to package and deploy microservices, and introduces Docker as a container platform. Finally, it explains that as container usage grows, an orchestrator like Kubernetes is needed to manage multiple containers and microservices, and provides a high-level overview of Kubernetes' architecture and capabilities for scheduling, self-healing, scaling, and other management of containerized applications.
Kubernetes is a platform for managing containerized workloads and services that provides a container-centric management environment. It aims to provide high utilization, high availability, minimize fault recovery time, and reduce the probability of correlated failures through a declarative job specification language, name service integration, real-time job monitoring, and analyzing and simulating system behavior using APIs and dashboards. Kubernetes can manage 100,000s of jobs, 1000s of applications across multiple clusters each with 10,000s of machines.
1) Kubernetes is an open-source system for managing containerized applications and services across multiple hosts. It was created by Google in 2014 to automate deployment, scaling, and operations of application containers.
2) Kubernetes allows for automatic deployment and scaling of applications. It makes applications portable and lightweight by running them in containers.
3) The document provides an overview of key Kubernetes concepts including pods, replication controllers, and services. Pods are the smallest deployable units that can contain one or more containers which share resources. Replication controllers ensure a specified number of pod replicas are running. Services define a policy to access pods through labels.
A Comprehensive Introduction to Kubernetes. This slide deck serves as the lecture portion of a full-day Workshop covering the architecture, concepts and components of Kubernetes. For the interactive portion, please see the tutorials here:
https://github.com/mrbobbytables/k8s-intro-tutorials
Kubespray and Ansible can be used to automate the installation of Kubernetes in a production-ready environment. Kubespray provides tools to configure highly available Kubernetes clusters across multiple Linux distributions. Ansible is an IT automation tool that can deploy software and configure systems. The document then provides a 6 step guide for installing Kubernetes on Ubuntu using kubeadm, including installing Docker, kubeadm, kubelet and kubectl, disabling swap, configuring system parameters, initializing the cluster with kubeadm, and joining nodes. It also briefly explains Kubernetes architecture including the master node, worker nodes, addons, CNI, CRI, CSI and key concepts like pods, deployments, networking,
This document provides an overview of Kubernetes, an open-source system for automating deployment, scaling, and management of containerized applications. It describes Kubernetes' architecture including nodes, pods, replication controllers, services, and networking. It also discusses how to set up Kubernetes environments using Minikube or kubeadm and get started deploying pods and services.
Docker allows building portable software that can run anywhere by packaging an application and its dependencies in a standardized unit called a container. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes can replicate containers, provide load balancing, coordinate updates between containers, and ensure availability. Defining applications as Kubernetes resources allows them to be deployed and updated easily across a cluster.
This document provides an overview of Kubernetes, a container orchestration system. It begins with background on Docker containers and orchestration tools prior to Kubernetes. It then covers key Kubernetes concepts including pods, labels, replication controllers, and services. Pods are the basic deployable unit in Kubernetes, while replication controllers ensure a specified number of pods are running. Services provide discovery and load balancing for pods. The document demonstrates how Kubernetes can be used to scale, upgrade, and rollback deployments through replication controllers and services.
Kubernetes: A Short Introduction (2019)Megan O'Keefe
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery called pods. Kubernetes can manage pods across a cluster of machines, providing scheduling, deployment, scaling, load balancing, volume mounting and networking. It is widely used by companies like Google, CERN and in large projects like processing images and analyzing particle interactions. Kubernetes is portable, can span multiple cloud providers, and continues growing to support new workloads and use cases.
Kubernetes for Beginners: An Introductory GuideBytemark
Kubernetes is an open-source tool for managing containerized workloads and services. It allows for deploying, maintaining, and scaling applications across clusters of servers. Kubernetes operates at the container level to automate tasks like deployment, availability, and load balancing. It uses a master-slave architecture with a master node controlling multiple worker nodes that host application pods, which are groups of containers that share resources. Kubernetes provides benefits like self-healing, high availability, simplified maintenance, and automatic scaling of containerized applications.
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery called pods. Kubernetes masters manage the cluster and make scheduling decisions while nodes run the pods and containers. It uses labels and selectors to identify and group related application objects together. Services provide a single endpoint for pods, while deployments help manage replicated applications. Kubernetes provides mechanisms for storage, configuration, networking, security and other functionality to help run distributed systems reliably at scale.
** 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
In this session, we will discuss the architecture of a Kubernetes cluster. we will go through all the master and worker components of a kubernetes cluster. We will also discuss the basic terminology of Kubernetes cluster such as Pods, Deployments, Service etc. We will also cover networking inside Kuberneets. In the end, we will discuss options available for the setup of a Kubernetes cluster.
This document provides an introduction to Kubernetes including:
- What Kubernetes is and what it does including abstracting infrastructure, providing self-healing capabilities, and providing a uniform interface across clouds.
- Key concepts including pods, services, labels, selectors, and namespaces. Pods are the atomic unit and services provide a unified access method. Labels and selectors are used to identify and group related objects.
- The Kubernetes architecture including control plane components like kube-apiserver, etcd, and kube-controller-manager. Node components include kubelet and kube-proxy. Optional services like cloud-controller-manager and cluster DNS are also described.
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes masters manage worker nodes, and pods which are the basic building blocks, containing one or more containers. It provides self-healing, horizontal pod autoscaling, service discovery, load balancing, configuration management.
The document introduces Docker, a container platform. It discusses how Docker addresses issues with deploying different PHP projects that have varying version requirements by allowing each project to run isolated in its own container with specified dependencies. It then covers key Docker concepts like images, containers, linking, exposing ports, volumes, and Dockerfiles. The document highlights advantages of Docker like enabling applications to run anywhere without compatibility issues and making deployment more efficient.
- Archeology: before and without Kubernetes
- Deployment: kube-up, DCOS, GKE
- Core Architecture: the apiserver, the kubelet and the scheduler
- Compute Model: the pod, the service and the controller
This presentation covers how app deployment model evolved from bare metal servers to Kubernetes World.
In addition to theoretical information, you will find free KATACODA workshops url to perform practices to understand the details of the each topics.
Traditional virtualization technologies have been used by cloud infrastructure providers for many years in providing isolated environments for hosting applications. These technologies make use of full-blown operating system images for creating virtual machines (VMs). According to this architecture, each VM needs its own guest operating system to run application processes. More recently, with the introduction of the Docker project, the Linux Container (LXC) virtualization technology became popular and attracted the attention. Unlike VMs, containers do not need a dedicated guest operating system for providing OS-level isolation, rather they can provide the same level of isolation on top of a single operating system instance.
An enterprise application may need to run a server cluster to handle high request volumes. Running an entire server cluster on Docker containers, on a single Docker host could introduce the risk of single point of failure. Google started a project called Kubernetes to solve this problem. Kubernetes provides a cluster of Docker hosts for managing Docker containers in a clustered environment. It provides an API on top of Docker API for managing docker containers on multiple Docker hosts with many more features.
Kubernetes Architecture and Introduction – Paris Kubernetes MeetupStefan Schimanski
The document provides an overview of Kubernetes architecture and introduces how to deploy Kubernetes clusters on different platforms like Mesosphere's DCOS, Google Container Engine, and Mesos/Docker. It discusses the core components of Kubernetes including the API server, scheduler, controller manager and kubelet. It also demonstrates how to interact with Kubernetes using kubectl and view cluster state.
Kubernetes is an open-source system for managing containerized applications across multiple hosts. It includes key components like Pods, Services, ReplicationControllers, and a master node for managing the cluster. The master maintains state using etcd and schedules containers on worker nodes, while nodes run the kubelet daemon to manage Pods and their containers. Kubernetes handles tasks like replication, rollouts, and health checking through its API objects.
DevoxxFR 2015 Talk http://cfp.devoxx.fr/2015/talk/WXY-1157/Scaling_Docker_with_Kubernetes
Kubernetes is an open source project to manage a cluster of Linux containers as a single system, managing and running Docker containers across multiple Docker hosts, offering co-location of containers, service discovery and replication control. It was started by Google and now it is supported by Microsoft, RedHat, IBM and Docker Inc amongst others.
Once you are using Docker containers the next question is how to scale and start containers across multiple Docker hosts, balancing the containers across them. Kubernetes also adds a higher level API to define how containers are logically grouped, allowing to define pools of containers, load balancing and affinity.
Kubernetes is an open-source system for managing containerized applications and services. It includes a master node that runs control plane components like the API server, scheduler, and controller manager. Worker nodes run the kubelet service and pods. Pods are the basic building blocks that can contain one or more containers. Labels are used to identify and select pods. Replication controllers ensure a specified number of pod replicas are running. Services define a logical set of pods and associated policy for access. They are exposed via cluster IP addresses or externally using load balancers.
OpenShift is Red Hat's container application platform that provides a full-stack platform for deploying and managing containerized applications. It is based on Docker and Kubernetes and provides additional capabilities for self-service, automation, multi-language support, and enterprise features like authentication, centralized logging, and integration with Red Hat's JBoss middleware. OpenShift handles building, deploying, and scaling applications in a clustered environment with capabilities for continuous integration/delivery, persistent storage, routing, and monitoring.
Red Hat OpenShift V3 Overview and Deep DiveGreg Hoelzer
OpenShift is a platform as a service product from Red Hat that allows developers to easily deploy and manage applications using containers. It provides developers with a common platform to build, deploy and update applications quickly using containers. For IT operations, OpenShift improves efficiency and infrastructure utilization through automated provisioning and management of application services. Some key customers highlighted include a large enterprise software company, a major online travel agency, and a leading financial analytics software provider.
From Zero to Cloud: Revolutionize your Application Life Cycle with OpenShift ...OpenShift Origin
From Zero to Cloud: Revolutionize your Application Life Cycle with OpenShift PaaS
Talk given by Diane Mueller, OpenShift Origin Community Manager at FISL 15 on May 9th, 2014
The document provides an overview of the Symfony Form component, including basic usage, validation, custom form types, events, data transformers, form type extensions, and rendering. It demonstrates how to create and handle forms, add validation, dynamically modify forms using events, transform data between representations, extend existing form types, and customize form rendering.
The document discusses Docker orchestration with Kubernetes. It describes how Kubernetes allows deploying entire applications as services made up of replication controllers that manage containers across a cluster of hosts. Deploying applications with Kubernetes decouples the application and provides greater flexibility than just deploying code.
Private PaaS for the Enterprise - Apache Stratos & WSO2 Private PaaSImesh Gunaratne
This document discusses private Platform as a Service (PaaS) solutions using Apache Stratos and WSO2 Private PaaS. It introduces Apache Stratos as an extensible PaaS framework. It then covers key container and container orchestration technologies like Docker, CoreOS, Flannel, and Kubernetes that Stratos integrates with. The WSO2 Private PaaS is presented as a complete enterprise PaaS built on Stratos that offers middleware cartridges and manages resources using Kubernetes. A demo of deploying a WSO2 ESB container on Kubernetes via the WSO2 Private PaaS is shown.
What's new in Kubernetes 1.3?
New things like:
Petsets, init-containers, ubernetes, federated clusters, improved kubernetes UI, minikube, support for rkt, etc.
Also find out sources to learn Kubernetes, how to participate with k8s community.
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.
Interoperability and scalability with microservices in scienceOla Spjuth
Microservices have emerged as a modern interpretation of service-oriented architectures where processes are small and communicate over a network using lightweight protocols to fulfill a goal.
In this talk I will present our work on microservices, and how they can be used to empower interoperable and scalable analysis services and pipelines in virtual infrastructures on cloud computing resources.
I will also give examples and experiences from the PhenoMeNal H2020 project where a developer community in metabolomics is moving to such architecture.
In the era of Microservices, Cloud Computing and Serverless architecture, it’s useful to understand Kubernetes and learn how to use it. However, the official Kubernetes documentation can be hard to decipher, especially for newcomers. In this book, I will present a simplified view of Kubernetes and give examples of how to use it for deploying microservices using different cloud providers, including Azure, Amazon, Google Cloud and even IBM.
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.
Kubernetes Architecture with ComponentsAjeet Singh
This document provides an overview of Kubernetes architecture and components. It describes how to run a simple Kubernetes setup using a Docker container. The container launches all key Kubernetes components including the API server, scheduler, etcd and controller manager. Using kubectl, the document demonstrates deploying an nginx pod and exposing it as a service. This allows curling the nginx default page via the service IP to confirm the basic setup is functioning.
Container Orchestration with Docker Swarm and KubernetesWill Hall
This presentation covers the basics of what container orchestration is providing pros and cons of Docker Swarm, Kubernetes and Amazon ECS and outlining the terms and tools you will need to successfully use them.
Docker is an open-source tool that allows developers to easily deploy applications inside isolated containers. Kubernetes is an open-source system for automating deployment and management of containerized applications across clusters of hosts. It coordinates containerized applications across nodes by providing mechanisms for scheduling, service discovery, and load balancing. The key components of Kubernetes include Pods, Services, ReplicationControllers, Scheduler, API Server, etcd and Nodes.
Kubernetes and CoreOS @ Athens Docker meetupMist.io
Using Kubernetes and CoreOS to increase scalability and availability. Presentation at the Athens Docker meetup http://www.meetup.com/Docker-Athens/events/226277352/
Containers and container orchestration platforms like Kubernetes provide benefits for development and deployment but also introduce challenges for monitoring. A container monitoring solution needs to collect metrics on hosts, containers, the orchestration framework and applications. It should provide features like real-time analysis, predictive analytics, automated dashboards and service maps to provide visibility into the dynamic container environment. Choosing a monitoring platform that supports OpenTelemetry avoids vendor lock-in and works across cloud and self-hosted environments.
Cloud technology with practical knowledgeAnshikaNigam8
Docker uses a client-server architecture with a Docker client communicating with the Docker daemon. The daemon manages Docker objects like images, containers, networks and volumes. Kubernetes is an open-source system that automates deployment, scaling, and management of containerized applications. It ensures containers run as expected and acquires necessary resources. Key Kubernetes components include pods, deployments, services, nodes, and the control plane which manages the cluster.
Kubernetes is an open-source system for managing containerized applications across multiple hosts. It provides mechanisms for deploying, maintaining, and scaling applications. Kubernetes uses declarative APIs and controllers to maintain the desired state of applications. The document then discusses key Kubernetes concepts like pods, containers, services, labels, replication controllers, and selectors. It explains how Kubernetes operations work through components like the API server, scheduler, controller manager, kubelet, and proxy.
Kubernetes Cluster vs Nodes vs Pods vs Containers Comparisonjeetendra mandal
Containers package applications and dependencies to run consistently across environments. Kubernetes uses containers grouped in pods, which are scheduled across nodes that provide computing resources. Nodes pool resources and run pods to distribute workloads, ensuring applications have necessary resources. Pods contain related containers and act as logical hosts, while nodes are physical or virtual machines that run pods.
Getting started with google kubernetes engineShreya Pohekar
This document provides an overview of Google Kubernetes Engine. It begins with introductions and defines key concepts like virtualization, containerization, Docker, and Kubernetes. It then explains what Kubernetes is and how it can orchestrate container infrastructure on-premises or in the cloud. Various Kubernetes architecture elements are outlined like pods, replica sets, deployments, and services. Security features are also summarized, including pod security policies, network policies, and using security contexts. The document concludes with a demonstration of Kubernetes Engine.
This document discusses serverless computing and functions as a service (FaaS). It provides an overview of serverless concepts like functions and function triggers. It also discusses specific serverless platforms like AWS Lambda, Azure Functions, Google Cloud Functions, Kubeless, Fission, and Spring Cloud Functions. It focuses on how serverless can provide development, resource, and operational efficiencies over traditional infrastructure models.
Avanti Patil gives an introduction to Kubernetes. She discusses containers, Docker, and what Kubernetes is. Kubernetes is an open-source platform for managing containerized workloads and services. It facilitates declarative configuration and automation. The presentation covers Kubernetes architecture including the master node, worker nodes, pods, replica sets, and deployments. It also provides options for local Kubernetes development and a link to a self-paced tutorial. Avanti concludes by answering questions about Kubernetes.
MongoDB Ops Manager is an enterprise-grade end-to-end database management, monitoring, and backup solution. Kubernetes has clearly won the orchestration-platform "wars". In this session we'll take a deep dive on how you can leverage both these technologies to host your MongoDB deployments within your Kubernetes infrastructure whether that's OpenShift, PKS, Azure AKS, or just upstream. This talk will review the core technologies, such as containers, Kubernetes, and MongoDB Ops Manager. You'll also have a chance to see real-live demos of MongoDB running on Kubernetes and managed with MongoDB Ops Manager with the MongoDB Enterprise Kubernetes Operator.
The document discusses various Kubernetes concepts including pods, deployments, services, ingress, labels, health checks, config maps, secrets, volumes, autoscaling, resource quotas, namespaces, Helm, and the Kubernetes Dashboard. Kubernetes is a container orchestration tool that manages container deployment, scaling, and networking. It uses pods to group containers, deployments to manage pods, and services for exposing applications.
Kubernetes (commonly referred to as "K8s") is an open-source system for automating deployment, scaling and management of containerized applications It aims to provide a "platform for automating deployment, scaling, and operations of application containers across clusters of hosts". We will see Kubernetes architecture, use cases, basics and live demo
This document provides an overview of containers, Kubernetes, and their key concepts. It discusses how Kubernetes manages containerized applications across clusters and abstracts away infrastructure details. The main components of Kubernetes include Pods (groups of tightly-coupled containers), ReplicationControllers (manages Pod replicas), Services (expose Pods to external traffic), and Namespaces (logical isolation of clusters). Kubernetes architecture separates the control plane running on the master from the nodes that run container workloads.
This presentation discusses the history and evolution of cloud computing models from bare metal servers to serverless computing. It begins with an overview of the different eras including IaaS, PaaS, SaaS, and the introduction of containers and Kubernetes for managing containers at scale. The presentation then discusses concepts like Docker, containers, container orchestrators, Kubernetes networking models, and conclusions about abstraction levels. It provides several links to additional resources on topics like containers, serverless computing, pets vs cattle, and Kubernetes.
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
How Netflix Builds High Performance Applications at Global ScaleScyllaDB
We all want to build applications that are blazingly fast. We also want to scale them to users all over the world. Can the two happen together? Can users in the slowest of environments also get a fast experience? Learn how we do this at Netflix: how we understand every user's needs and preferences and build high performance applications that work for every user, every time.
Scaling Connections in PostgreSQL Postgres Bangalore(PGBLR) Meetup-2 - MydbopsMydbops
This presentation, delivered at the Postgres Bangalore (PGBLR) Meetup-2 on June 29th, 2024, dives deep into connection pooling for PostgreSQL databases. Aakash M, a PostgreSQL Tech Lead at Mydbops, explores the challenges of managing numerous connections and explains how connection pooling optimizes performance and resource utilization.
Key Takeaways:
* Understand why connection pooling is essential for high-traffic applications
* Explore various connection poolers available for PostgreSQL, including pgbouncer
* Learn the configuration options and functionalities of pgbouncer
* Discover best practices for monitoring and troubleshooting connection pooling setups
* Gain insights into real-world use cases and considerations for production environments
This presentation is ideal for:
* Database administrators (DBAs)
* Developers working with PostgreSQL
* DevOps engineers
* Anyone interested in optimizing PostgreSQL performance
Contact info@mydbops.com for PostgreSQL Managed, Consulting and Remote DBA Services
Are you interested in dipping your toes in the cloud native observability waters, but as an engineer you are not sure where to get started with tracing problems through your microservices and application landscapes on Kubernetes? Then this is the session for you, where we take you on your first steps in an active open-source project that offers a buffet of languages, challenges, and opportunities for getting started with telemetry data.
The project is called openTelemetry, but before diving into the specifics, we’ll start with de-mystifying key concepts and terms such as observability, telemetry, instrumentation, cardinality, percentile to lay a foundation. After understanding the nuts and bolts of observability and distributed traces, we’ll explore the openTelemetry community; its Special Interest Groups (SIGs), repositories, and how to become not only an end-user, but possibly a contributor.We will wrap up with an overview of the components in this project, such as the Collector, the OpenTelemetry protocol (OTLP), its APIs, and its SDKs.
Attendees will leave with an understanding of key observability concepts, become grounded in distributed tracing terminology, be aware of the components of openTelemetry, and know how to take their first steps to an open-source contribution!
Key Takeaways: Open source, vendor neutral instrumentation is an exciting new reality as the industry standardizes on openTelemetry for observability. OpenTelemetry is on a mission to enable effective observability by making high-quality, portable telemetry ubiquitous. The world of observability and monitoring today has a steep learning curve and in order to achieve ubiquity, the project would benefit from growing our contributor community.
Details of description part II: Describing images in practice - Tech Forum 2024BookNet Canada
This presentation explores the practical application of image description techniques. Familiar guidelines will be demonstrated in practice, and descriptions will be developed “live”! If you have learned a lot about the theory of image description techniques but want to feel more confident putting them into practice, this is the presentation for you. There will be useful, actionable information for everyone, whether you are working with authors, colleagues, alone, or leveraging AI as a collaborator.
Link to presentation recording and transcript: https://bnctechforum.ca/sessions/details-of-description-part-ii-describing-images-in-practice/
Presented by BookNet Canada on June 25, 2024, with support from the Department of Canadian Heritage.
Paradigm Shifts in User Modeling: A Journey from Historical Foundations to Em...Erasmo Purificato
Slide of the tutorial entitled "Paradigm Shifts in User Modeling: A Journey from Historical Foundations to Emerging Trends" held at UMAP'24: 32nd ACM Conference on User Modeling, Adaptation and Personalization (July 1, 2024 | Cagliari, Italy)
MYIR Product Brochure - A Global Provider of Embedded SOMs & SolutionsLinda Zhang
This brochure gives introduction of MYIR Electronics company and MYIR's products and services.
MYIR Electronics Limited (MYIR for short), established in 2011, is a global provider of embedded System-On-Modules (SOMs) and
comprehensive solutions based on various architectures such as ARM, FPGA, RISC-V, and AI. We cater to customers' needs for large-scale production, offering customized design, industry-specific application solutions, and one-stop OEM services.
MYIR, recognized as a national high-tech enterprise, is also listed among the "Specialized
and Special new" Enterprises in Shenzhen, China. Our core belief is that "Our success stems from our customers' success" and embraces the philosophy
of "Make Your Idea Real, then My Idea Realizing!"
Quality Patents: Patents That Stand the Test of TimeAurora Consulting
Is your patent a vanity piece of paper for your office wall? Or is it a reliable, defendable, assertable, property right? The difference is often quality.
Is your patent simply a transactional cost and a large pile of legal bills for your startup? Or is it a leverageable asset worthy of attracting precious investment dollars, worth its cost in multiples of valuation? The difference is often quality.
Is your patent application only good enough to get through the examination process? Or has it been crafted to stand the tests of time and varied audiences if you later need to assert that document against an infringer, find yourself litigating with it in an Article 3 Court at the hands of a judge and jury, God forbid, end up having to defend its validity at the PTAB, or even needing to use it to block pirated imports at the International Trade Commission? The difference is often quality.
Quality will be our focus for a good chunk of the remainder of this season. What goes into a quality patent, and where possible, how do you get it without breaking the bank?
** Episode Overview **
In this first episode of our quality series, Kristen Hansen and the panel discuss:
⦿ What do we mean when we say patent quality?
⦿ Why is patent quality important?
⦿ How to balance quality and budget
⦿ The importance of searching, continuations, and draftsperson domain expertise
⦿ Very practical tips, tricks, examples, and Kristen’s Musts for drafting quality applications
https://www.aurorapatents.com/patently-strategic-podcast.html
How Social Media Hackers Help You to See Your Wife's Message.pdfHackersList
In the modern digital era, social media platforms have become integral to our daily lives. These platforms, including Facebook, Instagram, WhatsApp, and Snapchat, offer countless ways to connect, share, and communicate.
Kief Morris rethinks the infrastructure code delivery lifecycle, advocating for a shift towards composable infrastructure systems. We should shift to designing around deployable components rather than code modules, use more useful levels of abstraction, and drive design and deployment from applications rather than bottom-up, monolithic architecture and delivery.
The DealBook is our annual overview of the Ukrainian tech investment industry. This edition comprehensively covers the full year 2023 and the first deals of 2024.
How to Avoid Learning the Linux-Kernel Memory ModelScyllaDB
The Linux-kernel memory model (LKMM) is a powerful tool for developing highly concurrent Linux-kernel code, but it also has a steep learning curve. Wouldn't it be great to get most of LKMM's benefits without the learning curve?
This talk will describe how to do exactly that by using the standard Linux-kernel APIs (locking, reference counting, RCU) along with a simple rules of thumb, thus gaining most of LKMM's power with less learning. And the full LKMM is always there when you need it!
In this follow-up session on knowledge and prompt engineering, we will explore structured prompting, chain of thought prompting, iterative prompting, prompt optimization, emotional language prompts, and the inclusion of user signals and industry-specific data to enhance LLM performance.
Join EIS Founder & CEO Seth Earley and special guest Nick Usborne, Copywriter, Trainer, and Speaker, as they delve into these methodologies to improve AI-driven knowledge processes for employees and customers alike.
AC Atlassian Coimbatore Session Slides( 22/06/2024)apoorva2579
This is the combined Sessions of ACE Atlassian Coimbatore event happened on 22nd June 2024
The session order is as follows:
1.AI and future of help desk by Rajesh Shanmugam
2. Harnessing the power of GenAI for your business by Siddharth
3. Fallacies of GenAI by Raju Kandaswamy
Video traffic on the Internet is constantly growing; networked multimedia applications consume a predominant share of the available Internet bandwidth. A major technical breakthrough and enabler in multimedia systems research and of industrial networked multimedia services certainly was the HTTP Adaptive Streaming (HAS) technique. This resulted in the standardization of MPEG Dynamic Adaptive Streaming over HTTP (MPEG-DASH) which, together with HTTP Live Streaming (HLS), is widely used for multimedia delivery in today’s networks. Existing challenges in multimedia systems research deal with the trade-off between (i) the ever-increasing content complexity, (ii) various requirements with respect to time (most importantly, latency), and (iii) quality of experience (QoE). Optimizing towards one aspect usually negatively impacts at least one of the other two aspects if not both. This situation sets the stage for our research work in the ATHENA Christian Doppler (CD) Laboratory (Adaptive Streaming over HTTP and Emerging Networked Multimedia Services; https://athena.itec.aau.at/), jointly funded by public sources and industry. In this talk, we will present selected novel approaches and research results of the first year of the ATHENA CD Lab’s operation. We will highlight HAS-related research on (i) multimedia content provisioning (machine learning for video encoding); (ii) multimedia content delivery (support of edge processing and virtualized network functions for video networking); (iii) multimedia content consumption and end-to-end aspects (player-triggered segment retransmissions to improve video playout quality); and (iv) novel QoE investigations (adaptive point cloud streaming). We will also put the work into the context of international multimedia systems research.
2. About me
I come from Athens Greece, recently moved to
Luxembourg.
I love Java, Judo and Apple devices :P
Java EE enthusiast
Java Champion (2007) & JBoss Hero
co-Founder and admin of the first Java User Group in
Greece - www.jhug.gr
3. Goals
This is a soft introduction
Targeting mostly developers that now are entering
this new world of containers, microservices etc.
Save you some time from endless research and
experimentation.
Validate why kubernetes is the right framework
for the job - at least make you consider it!
Introduce basic concepts of kubernetes towards
system design and architecture.
4. A lot of buzzwords
a lot of trends
we are really good
at this
Microservices
Cloud
Containers
5. Some remarks
An new exciting world of
technologies.
Containers, microservices and the
‘cloud way’ are taking over.
There is a demand, sometimes not
clearly justified, to move existing
and new apps into this new world.
Devops is taking over but a gap is
created at the same time, ops vs
software developers.
6. Microservices
Containers
Cloud
Cloud : your private or a public one, a pool of
resources (machines), waiting to execute your
code.
Containers : another way of packaging -
containing applications (services) and OS
dependencies . They are expected to run on top
your ‘cloud’ machines.
Microservices : A new architectural trend on
designing and implementing apps. Separation of
concerns, decoupling, modular.
9. How?
How do we design applications that can not
make any assumptions about their runtime
environment? (filesystem/network)
How do we design applications that are
consisted of several moving parts, but can still
be deployed and orchestrated easily?
How do we design applications can move from
one cloud platform to another ?
How can we reuse our existing skills and
techniques on application design and
architecture without deep diving to other areas?
10. Common
misconceptions
Docker-izing your application
does not mean that you do
microservices.
2 processes (e.g wars) that
exchange JSON are not a
microservices platform.
Technical split of your good old
monolith, does not mean that you
actually moved to a microservices
architecture.
11. Common
misconceptions
A lot of technologies / frameworks claim to be
‘the operating system’ of the cloud.
The reality is that certain tools cover specific
areas of the overall problem.
Platforms that abstract the real hardware layer
(your good old server cluster).
Platforms that can ‘schedule’ and orchestrate
specific work on a cluster (aka schedulers)
Platforms with mix concerns that promise to act
as a ‘platform as a service’, where you will
design, host and operate your own service.
12. The reality
You need to invest money and skills on separate
tools and technologies.
The terms platform and infrastructure as a
service are sometimes interpreted in a very
obscure sense.
You find yourself deep diving on ops and
experimenting with OS level services rather than
your application
Currently most of the technologies are on their
infancy, ever changing and competing.
13. The question
Is there any technology that will abstract most of
the complexity imposed by many infrastructure
technologies?
Is there any technology that will enable me to
think again about application (parts) services and
their layout- rathern the specifics of the
underlying infrastructure?
Is there any technology that can be easy and
powerfull enough so that can be ‘setup’ by the
average Joe Developer in order to be evaluated
and then maybe use it actually?
17. Kubernetes
History
Google project started in 2014
10 year old experience derived from Google
internal container platform code name ‘Borg’
Project reached it’s 1.0 major release on July
2015.
Written in Go lang.
Heavily relies on Etcd
18. A less abstract
view
So in plain words either you have a cluster of VMs or a cluster of physical
machines, that are all Kubernetes aware, then they form a Kubernetes cluster.
Kubernetes then is the 'tool' so that you make use of the underlying docker engine
installed in each host (node) . (simplified description).
19. What is it?
“is an open source system for managing containerized
applications across multiple hosts, providing basic
mechanisms for deployment, maintenance, and scaling
of applications”
Is not a Infrastructure as a Service framework, it
abstracts the data center resources on a high level.
Is not a Platform as a Service framework, it can be use
as the basis so you can come up with one.
It enables you to deploy, manage and run on top of
abstracted pool of resources, your dockerized
applications.
It enables you to ‘design’ your application topology and
spread and interconnect your services with minimal or
changes to the actual service
20. Anatomy of a
Kubernetes Node
Each node basically runs
a number of services
(kubernetes related) and
a docker engine
We have 2 basic types of nodes
● master
● worker
21. The Master Node
The controller - controls and manages
the cluster
Run services of kubernetes
kubectl : command line client
rest api: rest api for communicating with the
workers
Scheduling and Replication logic
22. The Worker Node
The node that eventually host your
services - containers
Run services of kubernetes
kubelet : kubernetes agent (accepts commands
from master)
kubeproxy: network proxy service on a node
level
docker host
24. pod
Within the worker node, services will be
‘contained’ in a pod.
A pod can contain more than one
services (aka docker containers)
each pod has it’s own IP.
it is a logical host .
master schedules, replicates & creates
25. All together pods
one instance of
MySQL and one
Tomcat, scheduled in
different pods.
26. Labels
● Labels are metadata we can assign to
kubernetes resources - such as pods,services
when we create them (spin them).
● They are simple key value pairs.
● Labels are crucial to kubernetes since a lot of
core kubernetes functionality relies on
‘querying’ the cluster for ‘resources’ that have
certain label assigned! (Selectors)
we can query
the
kubernetes
cluster for all
the pods that
belong to an
application
named
‘testApp’
28. The replication
Controller
● Is responsible to maintain as many pods as they
have been requested by the user.
● It will start or kill pods depending on the replication
limit provided.
○ E.g if we ask for 3 pods running a tomcat
docker instance with a specific description,
then it will kill any attempt to spin a 4th one.
● The replication controller uses a ‘template’ which is
just a simple descriptor that describes exactly what
each pod should contain.
● We can dynamically call the replication controller of
the kubernetes cluster in order to scale up or down a
specific pod.
○ E.g I want to scale up these 3 tomcats and to
make them 6.
29. How I can group
these 3 pods and
load balance
them?
30. The Service
● A service is not - a running thing - there is no real
single load balancer.
● It is information stored in the kubernetes cluster
state and networking information propagated to all
the nodes.
● It groups a set of pods, providing a single point of
access.
● For example if we want to access the ‘RestApi’
service we no longer need to know each pod’s ip
address.
● By grouping similar pods into service(s) we
eventually solve the discoverability and connectivity
between our containers.
● A Service with 3 pods of MySQL and another
Service with 3 pods of Wildfly can ‘talk’ to each by
this single ‘domain’ name - cluster internal IP and on
predefined (if we wish ports).
31. The Service- env
variables?
● Once a service is declared then related
Environment Variables are accessible on the node.
● TOMCAT_SERVICE_HOST=10.0.0.11
TOMCAT_SERVICE_HOST_PORT=80
TOMCAT_PORT=tcp://10.0.0.11:6379
32. The Service- How?
● Every time we create a service, all the nodes of the
cluster - get aware of it.
● The kube-proxy service running on all workers
allocates a specific port.
● IP-Tables are being populated so that traffic can be
redirected to the related services
● A service is eventually a cluster wide ‘information’
that each node is aware.
33. Volumes
● Another powerful abstraction
● File access for your services.
● It lives as the pod lives!
● A container can die in the pod, the volume still
lives.
● The volume can point to the Node (host), pod only
or to an external file /storage provider.
34. Volumes
● The most important thing is to foresee the need of
the volume in your topology.
● Once you have selected the type and you have
integrated it on your app design, you won't have to
worry about, no matter how your pods or
containers run or scale.
35. Secrets
● Sensitive information, that containers need to read
or consume.
● Secrets are another kubernetes abstraction
● Technically they are end up as special volumes
mounted automatically so that your containers can
read their contents.
● Each entry has it’s own path.
36. So how I Install
kubernetes - for
the first time?
The easiest way is a local cluster - with vagrant managed
vms. But there are several other ways, as documented
here.
1. Install Vagrant on your machine, make sure it works
2. Download the latest release of kubernetes from here
(releases) e.g 1.0.6
3. Unzip the folder to a path of your choice e.g
~kubernetes_home
1. Set the following env variables on your environment
or just export them beforehand.
export KUBERNETES_PROVIDER=vagrant
export VAGRANT_DEFAULT_PROVIDER=virtualbox
export NUM_MINIONS=3
export KUBERNETES_MASTER_MEMORY=1536
export KUBERNETES_MINION_MEMORY=1024
1. Execute the following script
kubernetes_homeclusterkube-up.sh
1. Wait a bit (depending on the number of nodes) to
complete - you are done!!!
Number of
Nodes
37. So how do I issue
commands to my
cluster?
Kubectl is the command line tool to ‘talk’ to your cluster
master.
● Kubectl is already included in the download archive
export KUBECTL=~kubernetes_homeplatformsxxxamd64
● add KUBECTL to your $PATH, or always navigate to
the above path.
38. Some kubectl
commands
#Get the state of your cluster
$ kubectl cluster-info
#Get all the nodes of your cluster
$ kubectl get nodes -o wide
#Get info about the pods of your cluster
$ kubectl get pods -o wide
#Get info about the replication controllers of your cluster
$ kubectl get rc -o wide
#Get info about the services of your cluster
$ kubectl get services
#Get full config info about a Service
$ kubectl get service <NAME_OF_SERVICE> -o json
#Get the IP of a Pod
$ kubectl get pod <NAME_OF_POD> -template={{.status.podIP}}
#Delete a Pod
$ kubectl delete pod NAME
#Delete a Service
$ kubectl delete service NAME_OF_THE_SERVICE
39. Schedule a simple
pod
# official documentation here
# Schedule to start a pod that will contain the latest
# Wildfly Image.
$ kubectl run myjboss --image=jboss/wildfly --port=8080
# Check our created pod(s).
$ kubectl get pods
NAME READY STATUS RESTARTS
AGE
myjboss-jvqob 1/1 Running 0
3m
40. Schedule a simple
pod - with template
{
"kind": "Pod",
"apiVersion": "v1",
"metadata": {
"name": "anotherJboss",
"labels": {
"app": "myapp"
}
},
"spec": {
"containers": [
{
"name": "backend-core-jboss",
"image": "jboss/wildfly",
"ports": [
{
"containerPort": 8080,
"protocol": "TCP"
}
]
}
]
}
}
$ kubectl create -f ./single-pod.json
Save it as
single-pod.json
41. Schedule a simple
service - with
template
{
"kind": "Service",
"apiVersion": "v1",
"metadata": {
"name": "test-service"
},
"spec": {
"selector": {
"app": "myapp"
},
"ports": [
{
"protocol": "TCP",
"port": 80,
"targetPort": 8080
}
]
}
}
$ kubectl create -f ./single-service.json
Save it as
single-
service.json
43. Who is embracing
Kubernetes?
● Google Container Engine
○ You can spina a cluster of VMs that run
kubernetes in a matter of minutes
● OpenShift version 3
○ The new P.a.a.S of RedHat is based on
Kubernetes!
○ Available as a service and as private
cloud installation.
● Tectonic - by CoreOS
○ a new platform
○ CoreOS+Kubernetes
● Fabric 8
○ O.S platform based on Kubernetes
○ + extra services
● OpenStack Support
○ Murano
● Apache Mesos
○ Kubernetes
44. Available
documentation
and resources?
Documentation
● Official Documentation here
● Code
● Google Container Engine documentation here
● Google Group - for questions.
● kubernetes.slack.com
● StackOverflow #kubernetes
Books
● Kubernetes Up and Running Oreilly (K.H)
● Scheduling the future at cloud scale - OpenShift
● Kubernetes-book (upcoming)
Articles
● Kubernetes Design Patterns (Arun Gupta)
● Kubernetes Key Concepts (Arun Gupta)
● Recipes for deploying JavaEE Apps (Arun. Gupta)
● Intro to Kubernetes
● Kubernetes for Developers
● The new PAAS
Video
● Tech overview of Kubernetes
● Container Orchestration using CoreOS and Kubernetes (1 ,2
, 3)
46. Well it was just a
start..
This was just a soft introduction, but you
need to understand the basic ideas and then
project them to your current or future project.
Don’t rush into every technology there is a
chance you lose your focus and forget about
the real problem, which is delivering your
app.
The power of kubernetes is that does not
distract you 100% from your application
design and topology.
It does try not to become yet another
technical milestone in order for you to reach
your end goal - which is eventually to deploy
a scalable and easily maintained application.