Kubernetes Introduction - talk given by Daniel Smith at Kubenetes User Group meetup #2 in Mountain View on 4/21/2015.
Explains the basic concepts and principles of the Kubernetes container orchestration system.
WSO2Con US 2015 Kubernetes: a platform for automating deployment, scaling, an...Brian Grant
Kubernetes can run application containers on clusters of physical or virtual machines.
It can also do much more than that.
Kubernetes satisfies a number of common needs of applications running in production, such as co-locating helper processes, mounting storage systems, distributing secrets, application health checking, replicating application instances, horizontal auto-scaling, load balancing, rolling updates, and resource monitoring.
However, even though Kubernetes provides a lot of functionality, there are always new scenarios that would benefit from new features. Ad hoc orchestration that is acceptable initially often requires robust automation at scale. Application-specific workflows can be streamlined to accelerate developer velocity.
This is why Kubernetes was also designed to serve as a platform for building an ecosystem of components and tools to make it easier to deploy, scale, and manage applications. The Kubernetes control plane is built upon the same APIs that are available to developers and users, implementing resilient control loops that continuously drive the current state towards the desired state. This design has enabled Apache Stratos and a number of other Platform as a Service and Continuous Integration and Deployment systems to build atop Kubernetes.
This presentation introduces Kubernetes’s core primitives, shows how some of its better known features are built on them, and introduces some of the new capabilities that are being added.
XP Days Ukraine 2015 Talk http://xpdays.com.ua/programs/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.
A basic introduction to Kubernetes. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications.
WSO2Con US 2015 Kubernetes: a platform for automating deployment, scaling, an...Brian Grant
Kubernetes can run application containers on clusters of physical or virtual machines.
It can also do much more than that.
Kubernetes satisfies a number of common needs of applications running in production, such as co-locating helper processes, mounting storage systems, distributing secrets, application health checking, replicating application instances, horizontal auto-scaling, load balancing, rolling updates, and resource monitoring.
However, even though Kubernetes provides a lot of functionality, there are always new scenarios that would benefit from new features. Ad hoc orchestration that is acceptable initially often requires robust automation at scale. Application-specific workflows can be streamlined to accelerate developer velocity.
This is why Kubernetes was also designed to serve as a platform for building an ecosystem of components and tools to make it easier to deploy, scale, and manage applications. The Kubernetes control plane is built upon the same APIs that are available to developers and users, implementing resilient control loops that continuously drive the current state towards the desired state. This design has enabled Apache Stratos and a number of other Platform as a Service and Continuous Integration and Deployment systems to build atop Kubernetes.
This presentation introduces Kubernetes’s core primitives, shows how some of its better known features are built on them, and introduces some of the new capabilities that are being added.
XP Days Ukraine 2015 Talk http://xpdays.com.ua/programs/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.
A basic introduction to Kubernetes. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications.
Author: Oleg Chunikhin, www.eastbanctech.com
Kubernetes is a portable open source system for managing and orchestrating containerized cluster applications. Kubernetes solves a number of DevOps related problems out of the box in a simple and unified way – rolling updates and update rollback, canary deployment and other complicated deployment scenarios, scaling, load balancing, service discovery, logging, monitoring, persistent storage management, and much more. You will learn how in less than 30 minutes a reliable self-healing production-ready Kubernetes cluster may be deployed on AWS and used to host and operate multiple environments and applications.
- 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
On Friday 5 June 2015 I gave a talk called Cluster Management with Kubernetes to a general audience at the University of Edinburgh. The talk includes an example of a music store system with a Kibana front end UI and an Elasticsearch based back end which helps to make concrete concepts like pods, replication controllers and services.
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
Kubernetes is a great tool to run (Docker) containers in a clustered production environment. When deploying often to production we need fully automated blue-green deployments, which makes it possible to deploy without any downtime. We also need to handle external HTTP requests and SSL offloading. This requires integration with a load balancer like Ha-Proxy. Another concern is (semi) auto scaling of the Kubernetes cluster itself when running in a cloud environment. E.g. partially scale down the cluster at night.
In this technical deep dive you will learn how to setup Kubernetes together with other open source components to achieve a production ready environment that takes code from git commit to production without downtime.
Orchestrating Docker Containers with Google Kubernetes on OpenStackTrevor Roberts Jr.
Kubernetes, Docker, CoreOS, and OpenStack for container workload management.
No audio, but there are annotations to follow along with the workload.
A video accompanies a Microservices Meetup talk that I presented on February 18, 2015 at https://www.youtube.com/watch?v=RfyIYhOzyPY
Acknowledgements to Kelsey Hightower for the workflow that I used, and Google for the example application shown.
History and Basics of containers, LXC, Docker and Kubernetes. This presentation is given to Engineering colleage students at VIT DevFest 2018. Beginner to Intermediate level.
Red Hat Forum Tokyo - OpenStack ArchitectureDan Radez
This was presented at the Red Hat Forum in Tokyo, November 2012. It's a basic getting started with OpenStack using RDO. It's the same as the OpenStack meetups presentation from November 2012
Author: Oleg Chunikhin, www.eastbanctech.com
Kubernetes is a portable open source system for managing and orchestrating containerized cluster applications. Kubernetes solves a number of DevOps related problems out of the box in a simple and unified way – rolling updates and update rollback, canary deployment and other complicated deployment scenarios, scaling, load balancing, service discovery, logging, monitoring, persistent storage management, and much more. You will learn how in less than 30 minutes a reliable self-healing production-ready Kubernetes cluster may be deployed on AWS and used to host and operate multiple environments and applications.
- 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
On Friday 5 June 2015 I gave a talk called Cluster Management with Kubernetes to a general audience at the University of Edinburgh. The talk includes an example of a music store system with a Kibana front end UI and an Elasticsearch based back end which helps to make concrete concepts like pods, replication controllers and services.
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
Kubernetes is a great tool to run (Docker) containers in a clustered production environment. When deploying often to production we need fully automated blue-green deployments, which makes it possible to deploy without any downtime. We also need to handle external HTTP requests and SSL offloading. This requires integration with a load balancer like Ha-Proxy. Another concern is (semi) auto scaling of the Kubernetes cluster itself when running in a cloud environment. E.g. partially scale down the cluster at night.
In this technical deep dive you will learn how to setup Kubernetes together with other open source components to achieve a production ready environment that takes code from git commit to production without downtime.
Orchestrating Docker Containers with Google Kubernetes on OpenStackTrevor Roberts Jr.
Kubernetes, Docker, CoreOS, and OpenStack for container workload management.
No audio, but there are annotations to follow along with the workload.
A video accompanies a Microservices Meetup talk that I presented on February 18, 2015 at https://www.youtube.com/watch?v=RfyIYhOzyPY
Acknowledgements to Kelsey Hightower for the workflow that I used, and Google for the example application shown.
History and Basics of containers, LXC, Docker and Kubernetes. This presentation is given to Engineering colleage students at VIT DevFest 2018. Beginner to Intermediate level.
Red Hat Forum Tokyo - OpenStack ArchitectureDan Radez
This was presented at the Red Hat Forum in Tokyo, November 2012. It's a basic getting started with OpenStack using RDO. It's the same as the OpenStack meetups presentation from November 2012
About docker cluster management tools
1. Base concepts of cluster
management and docker
2. Docker Swarm
3. Amazon EC2 Container Service
4. Kubernetes
5. Mesosphere
Forecast 2014: TOSCA: An Open Standard for Business Application Agility and P...Open Data Center Alliance
Business applications are the crown jewels of the new, cloud-based, application-centric economy. Cloud service providers and their diverse platform technologies are striving to serve these increasingly complex, mission-critical business applications. However, rapidly accelerating business, technical, and even regulatory requirements for applications make it increasingly difficult for cloud service providers and cloud platform technologies to meet the needs of innovative businesses for speed, accuracy and agility.
What was missing, until recently, was an open standard that would enable business to capture and automate the use of expert knowledge regarding essential details such as business application components, dependencies, and a wide range of requirements that could be automatically matched to corresponding cloud service provider capabilities. Cloud vendor software leveraging such an open standard would enable, for the first time, a truly competitive ecosystem where cloud platform and service providers can leap beyond commoditization in order to compete, innovate, and better serve the accelerating needs of cloud-based businesses.
The Topology and Orchestration Specification for Cloud Applications (TOSCA) is a new open standard created with the active participation of leading technology vendors, cloud service providers, and customers that facilitates all of the above goals and more. TOSCA defines the interoperable description of applications; including their components, relationships, dependencies, requirements, and capabilities, thereby enabling portability and semi-automatic management across cloud providers regardless of underlying platform or infrastructure; thus expanding customer choice, improving reliability, and reducing cost and time-to-value. These characteristics also facilitate the portable, continuous delivery of applications (DevOps) across their entire lifecycle. In short, they empower a much higher level of agility and accuracy for business in the cloud.
The growing impact of TOSCA has already inspired an OASIS Interop with six vendors demonstrating cross-cloud interoperability, an ODCA Proof-of-Concept demonstration, and several open source projects. This lively and fast-paced session is suitable for both business and technology focused thought-leaders, and will provide you with a better understanding of the potential and business impact of TOSCA.
Building IAM for OpenStack, presented at CIS (Cloud Identity Summit) 2015.
Discuss Identity Sources, Authentication, Managing Access and Federating Identities
A brief study on Kubernetes and its componentsRamit Surana
Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions. Using the concepts of "labels" and "pods", it groups the containers which make up an application into logical units for easy management and discovery.
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.
Big Data visualization with Apache Spark and Zeppelinprajods
This presentation gives an overview of Apache Spark and explains the features of Apache Zeppelin(incubator). Zeppelin is the open source tool for data discovery, exploration and visualization. It supports REPLs for shell, SparkSQL, Spark(scala), python and angular. This presentation was made on the Big Data Day, at the Great Indian Developer Summit, Bangalore, April 2015
Kubernetes is an open source container cluster orchestration platform founded by Google. This presentation covers an overview of it's main concepts, plus how it fits into Google Cloud Platform. This was delivered by Kit Merker at DevNexus 2015 in Atlanta.
Kubernetes Architecture - beyond a black box - Part 2Hao H. Zhang
This continues the Kubernetes architecture deep dive series. (Part 1 see https://www.slideshare.net/harryzhang735/kubernetes-beyond-a-black-box-part-1)
In Part 2 I'm going to cover the following:
- Kubernetes's 3 most import design choices: Micro-service Choreography, Level-Triggered Control, Generalized Workload and Centralized Controller
- Default scheduler limitation and community's next step
- Interface to production environment
- Workload abstraction: strength and limitations
This concludes my work and knowledge sharing about Kubernetes.
Slides used for Orchestructure May 2018 workshop.
Labs:
https://github.com/mrbobbytables/k8s-intro-tutorials
Event Information:
https://www.meetup.com/orchestructure/events/250189685/
Kube Overview and Kube Conformance Certification OpenSource101 RaleighBrad Topol
This is my Introduction to Kubernetes and Overview of the Kubernetes Conformance Certification Program talk presented at OpenSource101 Raleigh on Feb 17, 2018
Kubernetes is an open-source system and is quickly becoming the new standard for automating deployment, scaling, and management of containerized applications.
In the presentation we will have a high-level overview of the most important components of Kubernetes and how they fit together. We will start with having an overview of Container and Orchestration and what Kubernetes is capable of and how it helps in automating deployment and scaling software in the cloud. Afterwards we will discuss Kubernetes objects (Pod, ReplicaSet, Deployment, Services, Namespaces) with some examples.
These slides were used during a technical session for the Cloud-Native El Salvador community. It covers the basic Kubernetes components, some installers and main Kubernetes resources. For the demo, it was used the capabilites provided by the Horizontal Pod Autoscaler.
Staying on Topic - Invoke OpenFaaS functions with KafkaRichard Gee
This talk introduced both OpenFaaS & OpenFaaS Cloud before demonstrating the Kafka Connector. Based on the Connector SDK, the Kafka Connector enables Kubernetes based functions to be triggered using messages consumed from Kafka topics. The connector easily integrates with your existing Kafka installations enabling you to flexibly complement your existing systems' functionality with serverless functions.
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdfJay Das
With the advent of artificial intelligence or AI tools, project management processes are undergoing a transformative shift. By using tools like ChatGPT, and Bard organizations can empower their leaders and managers to plan, execute, and monitor projects more effectively.
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
2. Everything at Google runs in
containers:
• Gmail, Web Search, Maps, ...
• MapReduce, batch, ...
• GFS, Colossus, ...
• Even GCE itself: VMs in
containers
We launch over 2 billion
containers per week.
3. Kubernetes
Greek for “Helmsman”; also the root of
the word “Governor”
• Container orchestration
• Runs Docker containers
• Supports multiple cloud and bare-metal
environments
• Inspired and informed by Google’s
experiences and internal systems
• Open source, written in Go
Manage applications, not machines
4. Design principles
Declarative > imperative: State your desired results, let the system actuate
Control loops: Observe, rectify, repeat
Simple > Complex: Try to do as little as possible
Modularity: Components, interfaces, & plugins
Legacy compatible: Requiring apps to change is a non-starter
No grouping: Labels are the only groups
Cattle > Pets: Manage your workload in bulk
Open > Closed: Open Source, standards, REST, JSON, etc.
6. Primary concepts
Container: A sealed application package (Docker)
Pod: A small group of tightly coupled Containers
example: content syncer & web server
Controller: A loop that drives current state towards desired state
example: replication controller
Service: A set of running pods that work together
example: load-balanced backends
Labels: Identifying metadata attached to other objects
example: phase=canary vs. phase=prod
Selector: A query against labels, producing a set result
example: all pods where label phase == prod
8. Pods
Small group of containers & volumes
Tightly coupled
The atom of cluster scheduling &
placement
Shared namespace
• share IP address & localhost
Ephemeral
• can die and be replaced
Example: data puller & web server
Pod
File Puller Web Server
Volume
Consumers
Content
Manager
9. Pod lifecycle
Once scheduled to a node, pods do not move
• restart policy means restart in-place
Pods can be observed pending, running, succeeded, or failed
• failed is really the end - no more restarts
• no complex state machine logic
Pods are not rescheduled by the scheduler or apiserver
• even if a node dies
• controllers are responsible for this
• keeps the scheduler simple
Apps should consider these rules
• Services hide this
• Makes pod-to-pod communication more formal
10. Labels
Arbitrary metadata
Attached to any API object
Generally represent identity
Queryable by selectors
• think SQL ‘select ... where ...’
The only grouping mechanism
• pods under a ReplicationController
• pods in a Service
• capabilities of a node (constraints)
Example: “phase: canary”
App: Nifty
Phase: Dev
Role: FE
App: Nifty
Phase: Dev
Role: BE
App: Nifty
Phase: Test
Role: FE
App: Nifty
Phase: Test
Role: BE
12. App == NiftyApp: Nifty
Phase: Dev
Role: FE
App: Nifty
Phase: Test
Role: FE
App: Nifty
Phase: Dev
Role: BE
App: Nifty
Phase: Test
Role: BE
Selectors
13. App == Nifty
Role == FE
App: Nifty
Phase: Dev
Role: FE
App: Nifty
Phase: Test
Role: FE
App: Nifty
Phase: Dev
Role: BE
App: Nifty
Phase: Test
Role: BE
Selectors
14. App == Nifty
Role == BE
App: Nifty
Phase: Dev
Role: FE
App: Nifty
Phase: Test
Role: FE
App: Nifty
Phase: Dev
Role: BE
App: Nifty
Phase: Test
Role: BE
Selectors
15. App == Nifty
Phase == Dev
App: Nifty
Phase: Dev
Role: FE
App: Nifty
Phase: Test
Role: FE
App: Nifty
Phase: Dev
Role: BE
App: Nifty
Phase: Test
Role: BE
Selectors
16. App == Nifty
Phase == Test
App: Nifty
Phase: Dev
Role: FE
App: Nifty
Phase: Test
Role: FE
App: Nifty
Phase: Dev
Role: BE
App: Nifty
Phase: Test
Role: BE
Selectors
17. Replication Controllers
Canonical example of control loops
Runs out-of-process wrt API server
Have 1 job: ensure N copies of a pod
• if too few, start new ones
• if too many, kill some
• group == selector
Cleanly layered on top of the core
• all access is by public APIs
Replicated pods are fungible
• No implied ordinality or identity
Replication Controller
- Name = “nifty-rc”
- Selector = {“App”: “Nifty”}
- PodTemplate = { ... }
- NumReplicas = 4
API Server
How
many?
3
Start 1
more
OK
How
many?
4
24. Pod networking
Pod IPs are routable
• Docker default is private IP
Pods can reach each other without NAT
• even across nodes
No brokering of port numbers
This is a fundamental requirement
• several SDN solutions
25. Services
A group of pods that act as one == Service
• group == selector
Defines access policy
• only “load balanced” for now
Gets a stable virtual IP and port
• called the service portal
• also a DNS name
VIP is captured by kube-proxy
• watches the service constituency
• updates when backends change
Hide complexity - ideal for non-native apps
Portal (VIP)
Client
26. Services
10.0.0.1 : 9376
Client
kube-proxy
Service
- Name = “nifty-svc”
- Selector = {“App”: “Nifty”}
- Port = 9376
- ContainerPort = 8080
Portal IP is assigned
iptables
DNAT
TCP / UDP
apiserver
watch
10.240.2.2 : 808010.240.1.1 : 8080 10.240.3.3 : 8080
TCP / UDP
27. Events
A central place for information about your cluster
• filed by any component: kubelet, scheduler, etc
Real-time information on the current state of your pod
• kubectl describe pod foo
Real-time information on the current state of your cluster
• kubectl get --watch-only events
• You can also ask only for events that mention some object you care about.
28. Monitoring
Optional add-on to Kubernetes clusters
Run cAdvisor as a pod on each node
• gather stats from all containers
• export via REST
Run Heapster as a pod in the cluster
• just another pod, no special access
• aggregate stats
Run Influx and Grafana in the cluster
• more pods
• alternately: store in Google Cloud Monitoring
29. Logging
Optional add-on to Kubernetes clusters
Run fluentd as a pod on each node
• gather logs from all containers
• export to elasticsearch
Run Elasticsearch as a pod in the cluster
• just another pod, no special access
• aggregate logs
Run Kibana in the cluster
• yet another pod
• alternately: store in Google Cloud Logging
30. Kubernetes is Open Source
We want your help!
http://kubernetes.io
https://github.com/GoogleCloudPlatform/kubernetes
irc.freenode.net #google-containers
@kubernetesio
