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.
Docker at Shopify: From This-Looks-Fun to Production by Simon Eskildsen (Shop...Docker, Inc.
Since July 2014 Shopify's been serving thousands of requests per second of production web traffic from Docker containers. This was an 8 month effort, with multiple pivots of direction from the team—and we're only getting started. This talk covers the lessons learned through the trial and error of an in-flight architecture redesign, spanning hundreds of hosts, as well as the technical vision of the future of our platform.
Containers are everywhere these days. Many of us are containerizing our applications to take advantage of the ease of a single artifact, but what can we do to make deploying these containers to a fleet of servers easier? Kubernetes is arguably the most popular container orchestration system to date. Kubernetes was born out of a decade of research at Google and has seen success; by itself as a fantastic way to orchestrate containers across multiple machines and as a component in other platforms.
This talk will begin with the anatomy and setup of a Kubernetes cluster. We'll demonstrate (live) taking a container containing a simple web service and launch our application into a small Kubernetes cluster. Next we'll perform a rolling update to deploy a new container version with zero downtime. Also, we'll check out some cool debugging features Kubernetes provides over the course of our demo.
A basic introduction to Kubernetes. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications.
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.
Docker at Shopify: From This-Looks-Fun to Production by Simon Eskildsen (Shop...Docker, Inc.
Since July 2014 Shopify's been serving thousands of requests per second of production web traffic from Docker containers. This was an 8 month effort, with multiple pivots of direction from the team—and we're only getting started. This talk covers the lessons learned through the trial and error of an in-flight architecture redesign, spanning hundreds of hosts, as well as the technical vision of the future of our platform.
Containers are everywhere these days. Many of us are containerizing our applications to take advantage of the ease of a single artifact, but what can we do to make deploying these containers to a fleet of servers easier? Kubernetes is arguably the most popular container orchestration system to date. Kubernetes was born out of a decade of research at Google and has seen success; by itself as a fantastic way to orchestrate containers across multiple machines and as a component in other platforms.
This talk will begin with the anatomy and setup of a Kubernetes cluster. We'll demonstrate (live) taking a container containing a simple web service and launch our application into a small Kubernetes cluster. Next we'll perform a rolling update to deploy a new container version with zero downtime. Also, we'll check out some cool debugging features Kubernetes provides over the course of our demo.
A basic introduction to Kubernetes. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications.
3 years ago, Meetic chose to rebuild it's backend architecture using microservices and an event driven strategy. As we where moving along our old legacy application, testing features became gradually a pain, especially when those features rely on multiple changes across multiple components. Whatever the number of application you manage, unit testing is easy, as well as functional testing on a microservice. A good gherkin framework and a set of docker container can do the job. The real challenge is set in end-to-end testing even more when a feature can involve up to 60 different components.
To solve that issue, Meetic is building a Kubernetes strategy around testing. To do such a thing we need to :
- Be able to generate a docker container for each pull-request on any component of the stack
- Be able to create a full testing environment in the simplest way
- Be able to launch automated test on this newly created environment
- Have a clean-up process to destroy testing environment after tests To separate the various testing environment, we chose to use Kubernetes Namespaces each containing a variant of the Meetic stack. But when it comes to Kubernetes, managing multiple namespaces can be hard. Yaml configuration files need to be shared in a way that each people / automated job can access to them and modify them without impacting others.
This is typically why Meetic chose to develop it's own tool to manage namespace through a cli tool, or a REST API on which we can plug a friendly UI.
In this talk we will tell you the story of our CI/CD evolution to satisfy the need to create a docker container for each new pull request. And we will show you how to make end-to-end testing easier using Blackbeard, the tool we developed to handle the need to manage namespaces inspired by Helm.
This is a presentation I held at "DevOps and Security" -meetup on 5th of April 2016 at RedHat.
Source is available at: https://github.com/jerryjj/devsec_050416
Orchestration tool roundup kubernetes vs. docker vs. heat vs. terra form vs...Nati Shalom
Video recording: https://www.youtube.com/watch?v=tGlIgUeoGz8
It’s no news that containers represent a portable unit of deployment, and OpenStack has proven an ideal environment for running container workloads. However, where it usually becomes more complex is that many times an application is often built out of multiple containers. What’s more, setting up a cluster of container images can be fairly cumbersome because you need to make one container aware of another and expose intimate details that are required for them to communicate which is not trivial especially if they’re not on the same host.
These scenarios have instigated the demand for some kind of orchestrator. The list of container orchestrators is growing fairly fast. This session will compare the different orchestation projects out there - from Heat to Kubernetes to TOSCA - and help you choose the right tool for the job.
Session link from teh summit: https://openstacksummitmay2015vancouver.sched.org/event/abd484e0dedcb9774edda1548ad47518#.VV5eh5NViko
The Operator Pattern - Managing Stateful Services in KubernetesQAware GmbH
Cloud Native Night, January 2018, Mainz: Talk by Jakob Karalus (@krallistic, IT Consultant at codecentric)
Join our Meetup: https://www.meetup.com/de-DE/Cloud-Native-Night
Abstract: While it's easy to deploy stateless application with Kubernetes, it's harder for stateful software. Since applications often require custom functionality that Kubernetes can't provide, developers want to add more specialized patterns like automatic backups, failover or rebalancing to their Kubernetes deployments. In this talk, we will look at the Operator Pattern and other possibilities to extend the functionality of Kubernetes and how to use them to operate stateful applications.
Scaling Development Environments with DockerDocker, Inc.
We set out to solve the problems of quickly building high quality games for a fragmented mobile market. Taking advantage of HTML5 allowed a fast, familiar and highly iterative local development process, and a hybrid build process for native apps meant high performance games on mobile. Our product is designed to comprehensively handle complex UI flows, related server tasks as well as deep integrations with any social platform. This is necessarily complex piece of engineering, with dozens of large dependencies, and 5 local web servers powering a single user’s experience. When we set out to make this easily available to 3rd parties, we used Docker to solve to major challenges: 1) Fitting many users, each with a unique development environment, on to one machine; 2) Managing all of these development environments in a scalable way.
Orchestrating Linux Containers while tolerating failuresDocker, Inc.
lthough containers are bringing a refreshing flexibility when deploying services in production, the management of those containers in such an environment still requires special care in order to keep the application up and running. In this regard, orchestration platforms like Docker, Kubernetes and Nomad have been trying to alleviate this responsibility, facilitating the task of deploying and maintaining the entire application stack in its desired state. This ensures that a service will be always running, tolerating machine failures, network erratic behavior or software updates and downtime. The purpose of this talk is to explain the mechanisms and architecture of the Docker Engine orchestration platform (using a framework called swarmkit) to tolerate failures of services and machines, from cluster state replication and leader-election to container re-scheduling logic when a host goes down.
Service Discovery in kubernetes is all about how services of kubernetes get discovered internally and externally. How does a single POD communicate to another POD the within the cluster and how does a user request reach to a specific POD in the cluster? These are some questions that are answered by this TOPIC.
Dockerizing Windows Server Applications by Ender Barillas and Taylor BrownDocker, Inc.
A session covering the container workflow from the developers inner loop, CI/CD, to deployment in a container orchestration solution. We'll cover Visual Studio Code from a Mac, Visual Studio Code from Windows with Bash and Visual Studio as an in-container local development environment targeting both Windows and Linux Containers. We'll walk through CI, Validation and CD to the Azure Container Service running Docker Swarm as one example of how you can convert your existing config as code and VM deployments to the containerized workflows startups and early adopter enterprises are using today.
From the Philly Kubernetes December 2016 Meetup.
https://www.meetup.com/Kubernetes-Philly/events/234829676/
Kubernetes accelerates technical and business innovation through rapid development and deployment of applications. Learn how to deploy, scale, and manage your applications in a containerized environments using Kubernetes.
In this 60-minute workshop, Ross Kukulinski will review fundamental Kubernetes concepts and architecture and then will show how to containerize and deploy a multi-tier web application to Kubernetes.
Topics that will be covered include:
• Working with the Kubernetes CLI (kubectl)
• Pods, Deployments, & Services
• Manual & Automated Application Scaling
• Troubleshooting and debugging
• Persistent storage
Curious about serverless / function-as-a-service [FAAS] / cloud functions technologies, but haven't had a chance to dig in? Wondering what all the excitement is about? In this hands-on workshop, you'll learn: -- the current state of the FAAS ecosystem & major players (including IBM Cloud Functions) -- recognized ideal use cases for serverless solutions -- emerging best practices for serverless architectures -- good sources of information to keep abreast of new developments.
Docker Meetup - Melbourne 2015 - Kubernetes Deep DiveKen Thompson
Presentation given at the October 2015 Docker Meetup in Melbourne. A deep dive in to Kubernetes networking and storage and how this is being utilised in OpenShift 3.
3 years ago, Meetic chose to rebuild it's backend architecture using microservices and an event driven strategy. As we where moving along our old legacy application, testing features became gradually a pain, especially when those features rely on multiple changes across multiple components. Whatever the number of application you manage, unit testing is easy, as well as functional testing on a microservice. A good gherkin framework and a set of docker container can do the job. The real challenge is set in end-to-end testing even more when a feature can involve up to 60 different components.
To solve that issue, Meetic is building a Kubernetes strategy around testing. To do such a thing we need to :
- Be able to generate a docker container for each pull-request on any component of the stack
- Be able to create a full testing environment in the simplest way
- Be able to launch automated test on this newly created environment
- Have a clean-up process to destroy testing environment after tests To separate the various testing environment, we chose to use Kubernetes Namespaces each containing a variant of the Meetic stack. But when it comes to Kubernetes, managing multiple namespaces can be hard. Yaml configuration files need to be shared in a way that each people / automated job can access to them and modify them without impacting others.
This is typically why Meetic chose to develop it's own tool to manage namespace through a cli tool, or a REST API on which we can plug a friendly UI.
In this talk we will tell you the story of our CI/CD evolution to satisfy the need to create a docker container for each new pull request. And we will show you how to make end-to-end testing easier using Blackbeard, the tool we developed to handle the need to manage namespaces inspired by Helm.
This is a presentation I held at "DevOps and Security" -meetup on 5th of April 2016 at RedHat.
Source is available at: https://github.com/jerryjj/devsec_050416
Orchestration tool roundup kubernetes vs. docker vs. heat vs. terra form vs...Nati Shalom
Video recording: https://www.youtube.com/watch?v=tGlIgUeoGz8
It’s no news that containers represent a portable unit of deployment, and OpenStack has proven an ideal environment for running container workloads. However, where it usually becomes more complex is that many times an application is often built out of multiple containers. What’s more, setting up a cluster of container images can be fairly cumbersome because you need to make one container aware of another and expose intimate details that are required for them to communicate which is not trivial especially if they’re not on the same host.
These scenarios have instigated the demand for some kind of orchestrator. The list of container orchestrators is growing fairly fast. This session will compare the different orchestation projects out there - from Heat to Kubernetes to TOSCA - and help you choose the right tool for the job.
Session link from teh summit: https://openstacksummitmay2015vancouver.sched.org/event/abd484e0dedcb9774edda1548ad47518#.VV5eh5NViko
The Operator Pattern - Managing Stateful Services in KubernetesQAware GmbH
Cloud Native Night, January 2018, Mainz: Talk by Jakob Karalus (@krallistic, IT Consultant at codecentric)
Join our Meetup: https://www.meetup.com/de-DE/Cloud-Native-Night
Abstract: While it's easy to deploy stateless application with Kubernetes, it's harder for stateful software. Since applications often require custom functionality that Kubernetes can't provide, developers want to add more specialized patterns like automatic backups, failover or rebalancing to their Kubernetes deployments. In this talk, we will look at the Operator Pattern and other possibilities to extend the functionality of Kubernetes and how to use them to operate stateful applications.
Scaling Development Environments with DockerDocker, Inc.
We set out to solve the problems of quickly building high quality games for a fragmented mobile market. Taking advantage of HTML5 allowed a fast, familiar and highly iterative local development process, and a hybrid build process for native apps meant high performance games on mobile. Our product is designed to comprehensively handle complex UI flows, related server tasks as well as deep integrations with any social platform. This is necessarily complex piece of engineering, with dozens of large dependencies, and 5 local web servers powering a single user’s experience. When we set out to make this easily available to 3rd parties, we used Docker to solve to major challenges: 1) Fitting many users, each with a unique development environment, on to one machine; 2) Managing all of these development environments in a scalable way.
Orchestrating Linux Containers while tolerating failuresDocker, Inc.
lthough containers are bringing a refreshing flexibility when deploying services in production, the management of those containers in such an environment still requires special care in order to keep the application up and running. In this regard, orchestration platforms like Docker, Kubernetes and Nomad have been trying to alleviate this responsibility, facilitating the task of deploying and maintaining the entire application stack in its desired state. This ensures that a service will be always running, tolerating machine failures, network erratic behavior or software updates and downtime. The purpose of this talk is to explain the mechanisms and architecture of the Docker Engine orchestration platform (using a framework called swarmkit) to tolerate failures of services and machines, from cluster state replication and leader-election to container re-scheduling logic when a host goes down.
Service Discovery in kubernetes is all about how services of kubernetes get discovered internally and externally. How does a single POD communicate to another POD the within the cluster and how does a user request reach to a specific POD in the cluster? These are some questions that are answered by this TOPIC.
Dockerizing Windows Server Applications by Ender Barillas and Taylor BrownDocker, Inc.
A session covering the container workflow from the developers inner loop, CI/CD, to deployment in a container orchestration solution. We'll cover Visual Studio Code from a Mac, Visual Studio Code from Windows with Bash and Visual Studio as an in-container local development environment targeting both Windows and Linux Containers. We'll walk through CI, Validation and CD to the Azure Container Service running Docker Swarm as one example of how you can convert your existing config as code and VM deployments to the containerized workflows startups and early adopter enterprises are using today.
From the Philly Kubernetes December 2016 Meetup.
https://www.meetup.com/Kubernetes-Philly/events/234829676/
Kubernetes accelerates technical and business innovation through rapid development and deployment of applications. Learn how to deploy, scale, and manage your applications in a containerized environments using Kubernetes.
In this 60-minute workshop, Ross Kukulinski will review fundamental Kubernetes concepts and architecture and then will show how to containerize and deploy a multi-tier web application to Kubernetes.
Topics that will be covered include:
• Working with the Kubernetes CLI (kubectl)
• Pods, Deployments, & Services
• Manual & Automated Application Scaling
• Troubleshooting and debugging
• Persistent storage
Curious about serverless / function-as-a-service [FAAS] / cloud functions technologies, but haven't had a chance to dig in? Wondering what all the excitement is about? In this hands-on workshop, you'll learn: -- the current state of the FAAS ecosystem & major players (including IBM Cloud Functions) -- recognized ideal use cases for serverless solutions -- emerging best practices for serverless architectures -- good sources of information to keep abreast of new developments.
Docker Meetup - Melbourne 2015 - Kubernetes Deep DiveKen Thompson
Presentation given at the October 2015 Docker Meetup in Melbourne. A deep dive in to Kubernetes networking and storage and how this is being utilised in OpenShift 3.
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.
Microservices, Containers, Docker and a Cloud-Native Architecture in the Midd...Kai Wähner
Microservices are the next step after SOA: Services implement a limited set of functions. Services are developed, deployed and scaled independently. Continuous Integration and Continuous Delivery automate deployments. This way you get shorter time to results and increased flexibility. Containers improve these even more offering a very lightweight and flexible deployment option.
In the middleware world, you use concepts and tools such as an Enterprise Service Bus (ESB), Complex Event Processing (CEP), Business Process Management (BPM) or API Gateways. Many people still think about complex, heavyweight central brokers here. However, Microservices and containers are relevant not just for custom self-developed applications, but they are also a key requirement to make the middleware world more flexible, agile and automated.
This session discusses the requirements, best practices and challenges for creating a good Microservices architecture in the middleware world. A live demo with the open source PaaS framework CloudFoundry shows how technologies and frameworks such as Java, SOAP / REST Web Services, Jenkins and Docker are used to create an agile software development lifecycle to realize “Middleware Microservices”. It also discusses other modern cloud-native alternatives such as Kubernetes, Docker, Mesos, Mesosphere or Amazon ECS / AWS.
The Information Technology have led us into an era where the production, sharing and use of information are now part of everyday life and of which we are often unaware actors almost: it is now almost inevitable not leave a digital trail of many of the actions we do every day; for example, by digital content such as photos, videos, blog posts and everything that revolves around the social networks (Facebook and Twitter in particular). Added to this is that with the "internet of things", we see an increase in devices such as watches, bracelets, thermostats and many other items that are able to connect to the network and therefore generate large data streams. This explosion of data justifies the birth, in the world of the term Big Data: it indicates the data produced in large quantities, with remarkable speed and in different formats, which requires processing technologies and resources that go far beyond the conventional systems management and storage of data. It is immediately clear that, 1) models of data storage based on the relational model, and 2) processing systems based on stored procedures and computations on grids are not applicable in these contexts. As regards the point 1, the RDBMS, widely used for a great variety of applications, have some problems when the amount of data grows beyond certain limits. The scalability and cost of implementation are only a part of the disadvantages: very often, in fact, when there is opposite to the management of big data, also the variability, or the lack of a fixed structure, represents a significant problem. This has given a boost to the development of the NoSQL database. The website NoSQL Databases defines NoSQL databases such as "Next Generation Databases mostly addressing some of the points: being non-relational, distributed, open source and horizontally scalable." These databases are: distributed, open source, scalable horizontally, without a predetermined pattern (key-value, column-oriented, document-based and graph-based), easily replicable, devoid of the ACID and can handle large amounts of data. These databases are integrated or integrated with processing tools based on the MapReduce paradigm proposed by Google in 2009. MapReduce with the open source Hadoop framework represent the new model for distributed processing of large amounts of data that goes to supplant techniques based on stored procedures and computational grids (step 2). The relational model taught courses in basic database design, has many limitations compared to the demands posed by new applications based on Big Data and NoSQL databases that use to store data and MapReduce to process large amounts of data.
Course Website http://pbdmng.datatoknowledge.it/
Contact me to download the slides
Oscon 2017: Build your own container-based system with the Moby projectPatrick Chanezon
Build your own container-based system
with the Moby project
Docker Community Edition—an open source product that lets you build, ship, and run containers—is an assembly of modular components built from an upstream open source project called Moby. Moby provides a “Lego set” of dozens of components, the framework for assembling them into specialized container-based systems, and a place for all container enthusiasts to experiment and exchange ideas.
Patrick Chanezon and Mindy Preston explain how you can leverage the Moby project to assemble your own specialized container-based system, whether for IoT, cloud, or bare-metal scenarios. Patrick and Mindy explore Moby’s framework, components, and tooling, focusing on two components: LinuxKit, a toolkit to build container-based Linux subsystems that are secure, lean, and portable, and InfraKit, a toolkit for creating and managing declarative, self-healing infrastructure. Along the way, they demo how to use Moby, LinuxKit, InfraKit, and other components to quickly assemble full-blown container-based systems for several use cases and deploy them on various infrastructures.
Building Distributed Systems without Docker, Using Docker Plumbing Projects -...Patrick Chanezon
Docker provides an integrated and opinionated toolset to build, ship and run distributed applications. Over the past year, the Docker codebase has been refactored extensively to extract infrastructure plumbing components that can be used independently, following the UNIX philosophy of small tools doing one thing well: runC, containerd, swarmkit, hyperkit, vpnkit, datakit and the newly introduced InfraKit.
This talk will give an overview of these tools and how you can use them to build your own distributed systems without Docker.
Patrick Chanezon & David Chung, Docker & Phil Estes, IBM
Gentle introduction to Azure ARM templates and other deployment options, both imperative and declarative, such as Terraform, Ansible, or even azcli or PowerShell.
Microservices and containers for the unitiatedKevin Lee
In this presentation I provide a high level explanation of why applications are now being developed using in a Microservice architecture. I look at how Microservice applications are typically developed and deployed using container technology and look at some of the challenges of using container technology for applications in production.
Erik Skytthe - Monitoring Mesos, Docker, Containers with Zabbix | ZabConf2016Zabbix
At DBC we are running docker and other container types in a mesos/marathon cluster environment. I will demonstrate how we collect statistics, logs etc. and monitor this environment, showing configuration examples, data flows and templates.
Some of the covered topics:
- Mesos master and agents
- Marathon Framework
- Docker engine
- Containers
- Zookeeper
- Elasticserach/ELK
LAMP Stack (Reloaded) - Infrastructure as Code with Terraform & PackerJan-Christoph Küster
Talk given at Coding Leipzig Meetup (8th August, 2018).
Why infrastructure should be managed as code (IaC), a small intro to the IaC-tooling Terraform (and Packer), and a demo that shows how to use Terraform to deploy a good old LAMP Stack into the Cloud by the push of a button (https://github.com/cloudetc/lamp-stack-for-aws).
Infrastructure as Code: Manage your Architecture with GitDanilo Poccia
Containers make packaging and distribution of your application easy. With the AWS Cloud you have an on-demand, programmable infrastructure that you can manage using tools and practices from software development. You can create resources when you need and dispose of them when you don’t. Using Amazon CloudFormation you can describe your architecture in text files. To change your infrastructure, you edit those files. Having application and infrastructure code in a single, robust, versioned repository like Git gives a lot of advantages. Using AWS Elastic Beanstalk you can link your Git branches to different infrastructure environments (e.g. test, production) and automate deployments. You can create test environments on-demand, even for a short time. Instead of continuously update your resources, you can recreate them quickly from scratch, simplifying lifecycle management and making deployments immutable. Using Amazon EC2 Container Service (ECS) you can manage containers at scale. As a result, you have more time to focus on the unique features of your application.
[FDD 2016] Marek Śledziński - Microsoft Windows a sprawa kontenerówFuture Processing
Idea „konteneryzacji” zadomowiła się na dobre w świecie Linuxa. Ostatnie lata pokazują zmianę myślenia Microsoftu w bardzo ciekawym kierunku, tzn. do podejścia OSS i większej współpracy z innymi firmami. Nie dziwi więc, że dziura w ofercie natywnych rozwiązań w temacie kontenerów musiała zostać zapełniona. W ramach Open Container Initiative i współpracy z twórcami Dockera, Microsoft przygotował własną wersję silnika, będącego hybrydą rozwiązań z Windowsa, Hyper-V i Dockera, pozwalającego na używanie kontenerów na systemach Windows Server 2016 (Core, Nano) i Windows 10. Rozwiązania te nie są jeszcze gotowe do masowego użycia na produkcji, ale widać, że jest to droga, której Microsoft łatwo nie porzuci. Dlatego warto już dzisiaj zapoznać się z możliwościami tych rozwiązań – jak to wszystko działa, jak zacząć, co można, a z czym są jeszcze problemy.
Kubernetes is exploding in popularity right now and has all the buzz and cargo-culting that Docker enjoyed just a few years ago. But what even is Kubernetes? How do I run my PHP apps in it? Should I run my PHP apps in it ?
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.
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.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
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!
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.
A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
Traditional software testing methods are being challenged in retail, where customer expectations and technological advancements continually shape the landscape. Enter generative AI—a transformative subset of artificial intelligence technologies poised to revolutionize software testing.
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/
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.
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.
Experience our free, in-depth three-part Tendenci Platform Corporate Membership Management workshop series! In Session 1 on May 14th, 2024, we began with an Introduction and Setup, mastering the configuration of your Corporate Membership Module settings to establish membership types, applications, and more. Then, on May 16th, 2024, in Session 2, we focused on binding individual members to a Corporate Membership and Corporate Reps, teaching you how to add individual members and assign Corporate Representatives to manage dues, renewals, and associated members. Finally, on May 28th, 2024, in Session 3, we covered questions and concerns, addressing any queries or issues you may have.
For more Tendenci AMS events, check out www.tendenci.com/events
Custom Healthcare Software for Managing Chronic Conditions and Remote Patient...Mind IT Systems
Healthcare providers often struggle with the complexities of chronic conditions and remote patient monitoring, as each patient requires personalized care and ongoing monitoring. Off-the-shelf solutions may not meet these diverse needs, leading to inefficiencies and gaps in care. It’s here, custom healthcare software offers a tailored solution, ensuring improved care and effectiveness.
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
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 ?
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Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
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TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
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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.
9. Facts
» OS level virtualisation tool suite
» Client-Server architecture
– Server communicates via Unix- or INET-
Sockets with a REST API
» Docker commands via CLI
» Written in Go
» Current version: 1.6
10. Lightweight Container vs. VM
Containers are isolated, but
sharing the kernel and (some) files
➜ faster & lighter
11. Concepts
» Image
– Read-only filesystem layer
– Deploy & Share
– Blueprint for a container
» Container
– Read-write filesystem layer (copy-on-write)
– Instance of an image
– Has a lifecycle (start & stop)
12. Concepts
» Repository
– Collection of layered images
– often synonym for “Image”
– Has a name: registry/user/repository:tag
» Registry
– Storage for repositories
– Default: docker.io (public docker hub)
13. docker
» CLI for managing Docker
– docker <sub-command> …
ps Show all containers
images Show all images
run Create and run a container
search Seaarch for images on a registry
pull Dowmload of images
rm Remove container
rmi Remove image
15. Facts
» Open Source orchestration platform for
Docker containers
– Rewrite of Google’s internal framework “Borg”
» Declarative specification of a desired state
» Self-healing
» Service discovery
» Scheduling across hosts
» Simple replication
17. Concepts
» Pods
– Collection of one or more Docker containers
» Replication Controller
– Creates and takes care of Pods
» Services
– Proxy for a collection of Pods
» Labels
– Grouping and organisation of Objects
18. Pod
» Collection of Docker containers running
on the same host.
» Pods have a unique IP
» Containers in a Pod ….
– …. share the same IP
– …. can reach each other via local ports
– …. can share data via volumes
» Pods can have one or more Labels
19. Replication Controller
» Controls Pods selected by Labels
» Ensures that a specified number of Pod
replicas is running
» Holds Pod Templates for creating new
Pods
» Autoscaling
» Rolling Updates
21. Service
» View on a set of Pods with
single IP address and port
» Pods are selected by Label
» Services are referenced by
environment variables
» Service addresses stay
stable
– Pods come and go (with
different IPs)
23. kubectl
» CLI for managing Kubernetes
– kubectl <sub-command> …
get pods
get services
get rc
Show pods/service/replication
controllers
create Create objects
update Update objects
delete Delete objects
resize New size for a RC
24.
25. History
» 2011: Platform-as-a-Service (PaaS) from
Red Hat
» Three variants:
– Online - Public PaaS
– Enterprise - Private PaaS
– Origin - Community PaaS
» OpenShift V3: Complete rewrite on basis
of Kubernetes
26. Features
» Adds the “Build” aspect to Kubernetes
» Developer and Operation Tools
» Application Component Libraries
» Infrastructure Services
– Registry, Router, OAuth2 Security
» Team and user isolation (multi-tenancy)
» Management UI
27. Builds
» Extension for building images
» Docker Builds
– Build images get access to enclosing Docker
daemon.
» Source-To-Image
– Assembly of new image from a builder image
and source code
– Often combined with a Webhook for automatic
builds
28. Templates
» Templates allow the specifications of
replication controller, services, …
» Parameter slots can be filled in …
– from the CLI wit osc process
– from the User Interface
» might become a Kubernetes feature in the
future
30. Deployments
» Update of a replication controller’s pod
template
– based on triggers
‣ image change
‣ configuration change
– custom deployment strategies
– rollback support
– replication scaling
31. Registry
» OpenShift provides an own Docker
registry as service
» OpenShift projects are mapped to registry
user
– e.g. for an image “fabric8/console” to be
pushed there must exist a OpenShift project
“fabric8”
32. Router
» External DNS mapping to services
– based on HAProxy
» Different types of TLS termination
– edge : TLS terminates at the router
– passthrough: TLS stream is handle through
to the service
– re-encryption: TLS terminates at the router
and is re-encrypted for the service
34. osc
» OpenShift CLI
» Extension to kubectl
process Process Templates
project Change namespace/project
get routes Show created routes
port-forward Port forwarding into pod
exec Execute process in running pod
35.
36. fabric8
» Tools and Services for value add to
Kubernetes and OpenShift
– Management: console, logging, metrics, …
– Continous Delivery Workflow
– iPaaS: Camel route visualisation, API registry,
Messaging as a Service, …
– Tools: Kubernetes/OpenShift build integration,
Kubernetes component test support, CDI
extensions
37. History
» Fuse ESB: Open Source integration
platform by FuseSource
» Fabric: Extension for managing many
ESBs
» Red Hat acquired FuseSource in 2012
– Fuse ESB JBoss Fuse
– Fabric (closed) fabric8 (open source)
38. » fabric8 1.x is based on Zookeeper as
central view of the system
– JBoss Fuse 6.1: fabric8 1.0
– JBoss Fuse 6.2: fabric8 1.2.x
» fabric8 2.x sits on top of Kubernetes
– fabric8 1.x functionality became Jube, a pure
Java implementation of the Kubernetes API
39. Management
» Web console for Kubernetes
– Starting/Stopping of pods
– Changing Replicas
– Individual management of pods
– based on hawt.io
42. iPaas
» Console for visualising and working with
integration services
– e.g. showing the Camel routes
» API registry for a global view of all
RESTful and WebServices
» MQ provides Messaging as a Service
– based on ActiveMQ
– allows autoscaling
43. Tools
» fabric8-maven-plugin
– Creates and apply Kubernetes
descriptors out of build informations
– Creates OpenShift routes
– Deploys kubernetes.json as Maven
artefacts
44. Tools
» Arquillian extension for testing
– Provision containers to Kubernetes
– Separate namespace per test (isolation)
– Annotations for injecting Kubernetes objects
– Assertions on Kubernetes objects
» Java Libraries
– Access to Kubernetes API
– CDI injections of Kubernetes Services
– ….
45. Summary
» Docker is the perfect foundation for a
container based infrastructure
» Kubernetes is a powerful Docker
orchestration platform backed with great
momentum
» OpenShift as a PaaS adds the “Build”
dimension to Kubernetes
» Fabric8 adds services and Java tooling to
Docker, Kubernetes and OpenShift
