Kubernetes: one cluster or many
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When we think about establishing a Kubernetes capability for our organization, our instinct, or perhaps just habit, might lead us to stand up a single cluster that will then be a shared resource across numerous tenants. Kubernetes offers namespaces that are intended to carve up the capacity across different users or groups of users. And while this may work well in some scenarios, it does impose certain constraints and limitations on its use. For example, it is well understood that the multitenancy in Kubernetes is soft, meaning it does not guard against deliberately malicious attacks from one tenant to another. If instead, we align tenant boundaries to Kubernetes clusters, effectively creating many single tenant clusters we can not only avoid certain limitations but we gain some significant advantages. Add a control plane for managing these sets of clusters and we have a powerful solution built on decades of maturity in machine virtualization. In this session we will present both models, multi-tenant clusters and multi-clusters and study the tradeoffs of each.
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● how to deploy and upgrade an application from source to production on Kubernetes.
Presenter:
Paul Czarkowski, Principal Technologist, Pivotal Software
Kubermatic.pdf
Kubermatic.pdfLibbySchulze This document summarizes a webinar about spinning up Kubernetes infrastructure in a GitOps way. It introduces Kubermatic and their start.kubermatic project, which provides a wizard to easily bootstrap infrastructure on cloud providers and install Kubermatic Kubernetes Platform (KKP) using GitOps. The webinar demonstrates how tools like Terraform, KubeOne, Helm, Flux, and SOPS are used to automate the provisioning and management of the Kubernetes cluster and KKP configuration. It also discusses security aspects and provides a live demo.
Kubermatic CNCF Webinar - start.kubermatic.pdf
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Episode 3: Kubernetes and Big Data Services
Episode 3: Kubernetes and Big Data ServicesMesosphere Inc. Kubernetes is great for deploying stateless containers, but what about the big data ecosystem? Episode 3 of our Kubernetes series covers how DC/OS enables you to connect your Kubernetes-based applications to co-located big data services.
Slides cover:
1. Why persistence is challenging in distributed architectures
How DC/OS helps you take advantage of the services available in the big data ecosystem
2. How to connect Kubernetes to your data services through networking
3. How Apache Flink and Apache Spark work with Kubernetes to enable real-time data processing on DC/OS
Cloud-native .NET Microservices mit Kubernetes
Cloud-native .NET Microservices mit KubernetesQAware GmbH Mario-Leander Reimer presented on building cloud-native .NET microservices with Kubernetes. He discussed key principles of cloud native applications including designing for distribution, performance, automation, resiliency and elasticity. He also covered containerization with Docker, composing services with Kubernetes and common concepts like deployments, services and probes. Reimer provided examples of Dockerfiles, Kubernetes definitions and using tools like Steeltoe and docker-compose to develop cloud native applications.
Kubernetes One-Click Deployment: Hands-on Workshop (Mainz)
Kubernetes One-Click Deployment: Hands-on Workshop (Mainz)QAware GmbH Cloud Native Night, April 2018, Mainz: Workshop led by Jörg Schad (@joerg_schad, Technical Community Lead / Developer at Mesosphere)
Join our Meetup: https://www.meetup.com/de-DE/Cloud-Native-Night/
PLEASE NOTE:
During this workshop, Jörg showed many demos and the audience could participate on their laptops. Unfortunately, we can't provide these demos. Nevertheless, Jörg's slides give a deep dive into the topic.
DETAILS ABOUT THE WORKSHOP:
Kubernetes has been one of the topics in 2017 and will probably remain so in 2018. In this hands-on technical workshop you will learn how best to deploy, operate and scale Kubernetes clusters from one to hundreds of nodes using DC/OS. You will learn how to integrate and run Kubernetes alongside traditional applications and fast data services of your choice (e.g. Apache Cassandra, Apache Kafka, Apache Spark, TensorFlow and more) on any infrastructure.
This workshop best suits operators focussed on keeping their apps and services up and running in production and developers focussed on quickly delivering internal and customer facing apps into production.
You will learn how to:
- Introduction to Kubernetes and DC/OS (including the differences between both)
- Deploy Kubernetes on DC/OS in a secure, highly available, and fault-tolerant manner
- Solve operational challenges of running a large/multiple Kubernetes cluster
- One-click deploy big data stateful and stateless services alongside a Kubernetes cluster
Webinar: End-to-End CI/CD with GitLab and DC/OS
Webinar: End-to-End CI/CD with GitLab and DC/OSMesosphere Inc. Seven years ago, Apache Mesos was born as a platform to bring the distributed computing capabilities that powered the largest digital companies to the masses. Today, Mesosphere DC/OS technologies power more containers in production than any other software stack in the world, and has emerged as the premier platform for building and elastically scaling data-rich, modern applications and the associated CI/CD infrastructure across any infrastructure, public or private.
GitLab is an end-to-end software development and delivery platform with built-in CI/CD, monitoring, and performance metrics. With a unified experience for every step of the development lifecycle and seamless integration with container schedulers, GitLab provides the most efficient approach to reduce cycle time, increase velocity, and improve software quality.
In this webinar, you will learn how to combine DC/OS and GitLab to easily build a CI/CD infrastructure and build a complete CI/CD pipeline in minutes.
Slides cover:
1. An introduction to Apache Mesos and Mesosphere DC/OS and overview of DC/OS features and capabilities for developing, deploying, and operating containerized applications, microservices and CI/CD
2. An introduction to GitLab
3. How to use DC/OS and GitLab to build a CI/CD solution and go from idea to production
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Episode 4: Operating Kubernetes at Scale with DC/OSMesosphere Inc. You’ve installed your Kubernetes cluster on DC/OS — now what? Operating Kubernetes efficiently can be challenging. In the final episode of our Kubernetes series, we will share best practices for operating your DC/OS Kubernetes cluster and maintaining performance. During this presentation, Joerg Schad and Chris Gaun show you how to successfully operate Kubernetes at scale in your environment.
During this session, we discuss:
1. How to upgrade DC/OS and Kubernetes with no downtime
2. How DC/OS guards against failure and enables fault domains that are resistant to outages within racks, availability zones, or cloud environments
3. How the monitoring and metrics capabilities on DC/OS improve operational analytics and help you get the most from your cluster
4. How cloud bursting extends your on-prem environment with resources from the cloud to handle spikes in your workload
Project Gardener - EclipseCon Europe - 2018-10-23
Project Gardener - EclipseCon Europe - 2018-10-23msohn Open Source project Gardener (https://gardener.cloud) is a production-grade Kubernetes-as-a-Service management tool that works across various cloud-platforms (e.g, AWS, Azure, GCP, Alibaba & SAP Datacenters) and on-premise (e.g. with OpenStack)
Use GitLab with Chaos Engineering to Harden your Applications + OpenEBS 1.3 ...
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Java one kubernetes, jenkins and microservices
Java one kubernetes, jenkins and microservicesChristian Posta This document discusses microservices with Docker, Kubernetes and Jenkins. It provides an overview of Kubernetes concepts like pods, replication controllers, services and labels. It also discusses how Kubernetes can help manage containers across multiple hosts and address challenges of scaling, avoiding port conflicts and keeping containers running. The document promotes using Jenkins and Kubernetes for continuous integration and delivery of containerized microservices applications. It recommends Fabric8 as a tool that can help create and deploy microservices on Kubernetes.
Kubernetes Clusters as a Service with Gardener
Kubernetes Clusters as a Service with GardenerQAware GmbH Cloud Native Night November 2018, Munich: Talk by Dirk Marwinski (SAP).
Join our Meetup: www.meetup.com/cloud-native-muc
Abstract: There are many Open Source tools which help in creating and updating single Kubernetes clusters. Corporations usually require many clusters, depending on their size they may require hundreds or even thousands of clusters. However, the more clusters you need the harder it becomes to operate, monitor, manage, and keep all of them alive and up-to-date.
That is exactly what open source project “Gardener” focuses on. It is not just another provisioning tool, but it is rather designed to manage Kubernetes clusters as a service. It provides Kubernetes-conformant clusters on various cloud providers and the ability to maintain hundreds or thousands of them at scale. At SAP, we face this heterogeneous multi-cloud & on-premise challenge not only in our own platform, but also encounter the same demand at all our larger and smaller customers implementing Kubernetes & Cloud Native.
Inspired by the possibilities of Kubernetes and the ability to self-host, the foundation of Gardener is Kubernetes itself. While self-hosting, as in, to run Kubernetes components inside Kubernetes is a popular topic in the community, we apply a special pattern catering to the needs of operating a huge number of clusters with minimal total cost of ownership.
In this session Dirk will provide a comprehensive overview of Gardener, the underlying concepts, and talk about interesting implementation details. In addition there will be a hands-on sessions where attendants will be given free access to a Gardener instance and given the opportunity to dynamically create Kubernetes cluster and test them.
Javaone kubernetesjenkins
Javaone kubernetesjenkinsPravat Bhusan Parida This document discusses microservices with Docker, Kubernetes and Jenkins. It provides an overview of Kubernetes concepts like pods, replication controllers, services and labels. It also discusses how Kubernetes can help manage containers across multiple hosts and address challenges of scaling, port conflicts and availability. The document promotes using Jenkins and Kubernetes for continuous integration and delivery of containerized microservices applications and introduces the Fabric8 tool for developing microservices on Kubernetes.
Microservices with Docker, Kubernetes, and Jenkins
Microservices with Docker, Kubernetes, and JenkinsRed Hat Developers By Rafael Benevides and Christian Posta
A lot of functionality necessary for running in a microservices architecture have been built into Kubernetes; why would you re-invent the wheel with lots of complicated client-side libraries? Have you ever asked why you should use containers and what are the benefits for your application? This talk will present a microservices application that have been built using different Java platforms: WildFly Swarm and Vert.x. Then we will deploy this application in a Kubernetes cluster to present the advantages of containers for MSA (Microservices Architectures) and DevOps. The attendees will learn how to create, edit, build, deploy Java Microservices, and also how to perform service discovery, rolling updates, persistent volumes and much more. Finally we will fix a bug and see how a CI/CD Pipeline automates the process and reduces the deployment time.
Microservices with Kubernetes, Docker, and Jenkins
Microservices with Kubernetes, Docker, and JenkinsRafael Benevides Presentation made with Christian Posta at JavaOne 2016
Online Google slides version: http://bit.ly/javaone-kb8s-jenkins
TIAD 2016 : Application delivery in a container world
TIAD 2016 : Application delivery in a container worldThe Incredible Automation Day This document discusses application delivery in a container world. It summarizes using Docker from development to production, including local development, continuous integration, deploying to servers using schedulers like Kubernetes and ECS, service discovery using tools like Consul, and updating applications safely using blue-green deployments and feature toggling. It then demonstrates these concepts using Docker, AWS ECS, Consul, and Consul Template to deploy a voting application.
KubeCon EU 2016: Leveraging ephemeral namespaces in a CI/CD pipeline
KubeCon EU 2016: Leveraging ephemeral namespaces in a CI/CD pipelineKubeAcademy One of the most underrated features of Kubernetes is namespaces. In the market, instead of using this feature, people are still stuck with having different clusters for their environments. This talk will try to break this approach, and will introduce how we end up using ephemeral namespaces within our CI/CD pipeline. It will cover the architecture of our system for running the user acceptance tests on isolated ephemeral namespaces with every bits and pieces running within pods. While doing this, we will set up our CI/CD pipeline on top of TravisCI, GoCD, and Selenium that is controlled by Nightwatch.js.
Sched Link: http://sched.co/6Bcb
Docker vs. Kubernetes vs. Serverless
Docker vs. Kubernetes vs. ServerlessLogicworksNY Speakers: Phil Christensen, Sr. DevOps Engineer, Solutions Architect
Phil is an open source software engineer and cloud solutions architect with 15+ years of experience. He focuses on Puppet automation, containers, and Amazon Web Services infrastructure and holds all five AWS Certifications.
If you are interested in learning more about Logicworks' unique approach to cloud migration and management, contact us or talk to a cloud expert at (212) 625-5300.
Kubernetes Architecture and Introduction
Kubernetes Architecture and IntroductionStefan Schimanski - Archeology: before and without Kubernetes
- Deployment: kube-up, DCOS, GKE
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- Compute Model: the pod, the service and the controller
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In this talk Cornelia goes over a host of software architectural patterns and their relationship to some of the key goals of Devops - "higher throughput and higher quality and stability." Cloud native applications and cloud native data are both covered.
Cloud-native Data
Cloud-native Datacornelia davis <November 2017 Updated from earlier presentations on Cloud-native Data>
Cloud-native applications form the foundation for modern, cloud-scale digital solutions, and the patterns and practices for cloud-native at the app tier are becoming widely understood – statelessness, service discovery, circuit breakers and more. But little has changed in the data tier. Our modern apps are often connected to monolithic shared databases that have monolithic practices wrapped around them. As a result, the autonomy promised by moving to a microservices application architecture is compromised.
What we need are patterns and practices for cloud-native data. The anti-patterns of shared databases and simple proxy-style web services to front them give way to approaches that include use of caches (Netflix calls caching their hidden microservice), database per service and polyglot persistence, modern versions of ETL and data integration and more. In this session, aimed at the application developer/architect, Cornelia will look at those patterns and see how they serve the needs of the cloud-native application.
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Cloud Native: Designing Change-tolerant Softwarecornelia davis To see this presentation given live, go to http://bit.ly/DesignPatternsReplay
There is a special (discount) offer in there! :-)
Cloud-native applications are characterized by highly distributed topologies consisting of many relatively small components (yup, usually called microservices). But the thing that sets them apart even more from the previous generation of apps is that they are expected to function flawlessly even while the environment they are running in is constantly changing, or even failing.
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Devops: Who Does What? - Devops Enterprise Summit 2016
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In this talk I will take traditional roles that are distributed across fairly standard IT structures and sort them into a new organizational context. What is the role of the Enterprise Architect? Who does capacity planning and how? How can change management step out of the way all while still satisfying the requirements of safe deployments? How do agile teams interface with personnel responsible for maintaining legacy systems? I’ll leave the audience with a blueprint for a new organizational structure.
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Top “Ah-ha” Moments As Former ...cornelia davis After spending her entire career as a software developer, with nary a moment doing operations, Cornelia Davis found herself working on an application platform that serves operations as much as development. In order to better understand that world, she spent one month on the team that runs that platform in production. The experience brought lessons in organizational design, the value of pair-ops (in addition to pair programming) and test-driven development, the importance of addressing continuous integration as a first class concern, and how separating infrastructure ops from application ops serves the business and their customers better. In this session Cornelia will share the “prod incidents” that brought these teachings; the audience will gain an appreciation not only for what, but why the lessons are so important.
Linux Collaboration Summit Keynote: Transformation: It Takes a Platform
Linux Collaboration Summit Keynote: Transformation: It Takes a Platformcornelia davis - A cloud-native application platform can enable organizations to transform by providing speed to market, better customer experiences, and engaging their workforce.
- Key elements of such a platform include continuous delivery, immutable infrastructure, blue/green deployments, self-service provisioning, environment parity, and a self-healing elastic runtime.
- A cloud-native microservices architecture can provide benefits like independent scaling of services, independent development cycles, experimentation, and resilience. Managing microservices requires services for configuration, service registration, circuit breaking, and monitoring.
Devops: Enabled Through a Recasting of Operational Roles
Devops: Enabled Through a Recasting of Operational Rolescornelia davis Delivered at CF Summit Berlin, 2 Nov 2015.
One thing that everyone agrees on is that “Devops” is about reducing the friction between dev and ops. While it might not be immediately apparent, CF enables a separation of “operations” into two roles: platform ops and application ops. Platform ops is responsible for maintaining a secure platform with sufficient functionality and capacity so that application developers and application operators can perform their work. And application operators are responsible for keeping business applications up and running, so that consumers receive superior service, 24x7x365. By moving further up the stack, app operators can be far closer to the line of business owners, getting them speaking the same language. In this session we demonstrate how Cloud Foundry enables this, we talk about customers who are taking advantage of it, and we cover the tools available for each of the roles.
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Removing Barriers Between Dev and Opscornelia davis Devops @ VMworld 2015 Presentation.
DevOps requires a separation of concerns between the application-focused teams and the platform-focused teams. While Platform and Application Operations have many similarities (monitor, logs, scale, upgrade, etc.) each is done with a different frame of reference. This workshop will provide an in-depth view into how a modern platform like Pivotal Cloud Foundry can eliminate the barriers between Development and Operations.
The workshop will showcase the difference in contexts for the application operations and platform operations teams, including monitoring, log analysis, capacity management, and upgrading. As well as show how separating the concerns of application operators (and application teams) from platform operators can remove the barriers between Dev and Ops. At this session we bring together both Dev and Ops with a combination of presentations and demos highlighting the capabilities of a modern platform. Monitor, log, scale, upgrade, and more, all with an integrated and auditable workflow for developers and operators.
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Cloud Foundry Diego, Lattice, Docker and morecornelia davis The document discusses Cloud Foundry developments including Diego, Lattice, Docker, and Cloud Rocker. Diego is a rewrite of the Cloud Foundry runtime that uses etcd instead of NATS for shared memory and supports different container formats. Lattice is a tool that allows deploying Cloud Foundry in different environments and demonstrates Docker support. Cloud Rocker builds Docker images from Cloud Foundry applications. Together these tools provide improved application scheduling, Windows support, and use of container technologies within Cloud Foundry.
Cloud Foundry Platform Operations - CF Summit 2015
Cloud Foundry Platform Operations - CF Summit 2015cornelia davis In this session Cornelia will share lessons learned from a month spent on a team that operates a production instance of Cloud Foundry. From her first morning addressing a prod incident, through building ops dashboards, documenting how a crashed micro-bosh is recovered, and prod deploys, she will share lessons on the value of declarative, immutable infrastructure, cloud-native application design and proper abstractions. Tried and true practices such as checklists and jumpboxes remain, while new ones such as primetime deploys and even live experimentation in prod emerge. The punchline? Even as an ops novice, she was immediately productive. In this session Cornelia will present specific techniques for using BOSH, system metrics and logging, dashboards, alerting systems and more to manage your CF deployment.
Competing with Software: It Takes a Platform -- Devops @ EMC World
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In Mark Andreessen’s 2010 piece for the Wall Street Journal, in which he declared “Software is Eating the World,” he talked about well established, large enterprises loosing footing to small, nimble startup companies who are far better at bringing software to their consumers. In fact, it’s not as much that these upstarts are better at meeting customer demands, rather they are the cause of the increased expectations, providing consumers with things they didn’t even know they wanted. What are the factors behind their success? New development and operational approaches including extreme agile & test driven development, continuous delivery and devops practices all play a significant role, and while a part of the difference is cultural, tools matter. In this session we’ll look at why a software-driven enterprise needs platform. Google has one. Facebook has one. Netflix has one. Your enterprise needs one.
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Pivotal Cloud Platform Roadshow Keynotecornelia davis Keynote presentation for the Pivotal Cloud Platform Roadshow. Introduces the market drivers for the Cloud Foundry Platform as a Service, discusses open source softwared (Cloud Foundry is OSS) and introduces the fundamentals of the platform.
Evolving Devops: The Benefits of PaaS and Application Dial Tone
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These slides were presented as a part a Pivotal webinar - a replay can be accessed here: http://www.pivotal.io/platform-as-a-service/evolving-devops-the-benefits-of-paas-and-application-dial-tone
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Societal challenges of AI: biases, multilinguism and sustainability
Societal challenges of AI: biases, multilinguism and sustainabilityJordi Cabot Towards a fairer, inclusive and sustainable AI that works for everybody.
Reviewing the state of the art on these challenges and what we're doing at LIST to test current LLMs and help you select the one that works best for you
TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest (MSR...
TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest (MSR...Andre Hora Unittest and pytest are the most popular testing frameworks in Python. Overall, pytest provides some advantages, including simpler assertion, reuse of fixtures, and interoperability. Due to such benefits, multiple projects in the Python ecosystem have migrated from unittest to pytest. To facilitate the migration, pytest can also run unittest tests, thus, the migration can happen gradually over time. However, the migration can be timeconsuming and take a long time to conclude. In this context, projects would benefit from automated solutions to support the migration process. In this paper, we propose TestMigrationsInPy, a dataset of test migrations from unittest to pytest. TestMigrationsInPy contains 923 real-world migrations performed by developers. Future research proposing novel solutions to migrate frameworks in Python can rely on TestMigrationsInPy as a ground truth. Moreover, as TestMigrationsInPy includes information about the migration type (e.g., changes in assertions or fixtures), our dataset enables novel solutions to be verified effectively, for instance, from simpler assertion migrations to more complex fixture migrations. TestMigrationsInPy is publicly available at: https://github.com/altinoalvesjunior/TestMigrationsInPy.
Designing AI-Powered APIs on Azure: Best Practices& Considerations
Designing AI-Powered APIs on Azure: Best Practices& ConsiderationsDinusha Kumarasiri AI is transforming APIs, enabling smarter automation, enhanced decision-making, and seamless integrations. This presentation explores key design principles for AI-infused APIs on Azure, covering performance optimization, security best practices, scalability strategies, and responsible AI governance. Learn how to leverage Azure API Management, machine learning models, and cloud-native architectures to build robust, efficient, and intelligent API solutions
Secure Test Infrastructure: The Backbone of Trustworthy Software Development
Secure Test Infrastructure: The Backbone of Trustworthy Software DevelopmentShubham Joshi A secure test infrastructure ensures that the testing process doesn’t become a gateway for vulnerabilities. By protecting test environments, data, and access points, organizations can confidently develop and deploy software without compromising user privacy or system integrity.
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Microsoft AI Nonprofit Use Cases and Live Demo_2025.04.30.pdfTechSoup In this webinar we will dive into the essentials of generative AI, address key AI concerns, and demonstrate how nonprofits can benefit from using Microsoft’s AI assistant, Copilot, to achieve their goals.
This event series to help nonprofits obtain Copilot skills is made possible by generous support from Microsoft.
What You’ll Learn in Part 2:
Explore real-world nonprofit use cases and success stories.
Participate in live demonstrations and a hands-on activity to see how you can use Microsoft 365 Copilot in your own work!
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Adobe Master Collection CC (Creative Cloud) is a comprehensive subscription-based package that bundles virtually all of Adobe's creative software applications. It provides access to a wide range of tools for graphic design, video editing, web development, photography, and more. Essentially, it's a one-stop-shop for creatives needing a broad set of professional tools.
Key Features and Benefits:
All-in-one access:
The Master Collection includes apps like Photoshop, Illustrator, InDesign, Premiere Pro, After Effects, Audition, and many others.
Subscription-based:
You pay a recurring fee for access to the latest versions of all the software, including new features and updates.
Comprehensive suite:
It offers tools for a wide variety of creative tasks, from photo editing and illustration to video editing and web development.
Cloud integration:
Creative Cloud provides cloud storage, asset sharing, and collaboration features.
Comparison to CS6:
While Adobe Creative Suite 6 (CS6) was a one-time purchase version of the software, Adobe Creative Cloud (CC) is a subscription service. CC offers access to the latest versions, regular updates, and cloud integration, while CS6 is no longer updated.
Examples of included software:
Adobe Photoshop: For image editing and manipulation.
Adobe Illustrator: For vector graphics and illustration.
Adobe InDesign: For page layout and desktop publishing.
Adobe Premiere Pro: For video editing and post-production.
Adobe After Effects: For visual effects and motion graphics.
Adobe Audition: For audio editing and mixing.
Meet the Agents: How AI Is Learning to Think, Plan, and Collaborate
Meet the Agents: How AI Is Learning to Think, Plan, and CollaborateMaxim Salnikov Imagine if apps could think, plan, and team up like humans. Welcome to the world of AI agents and agentic user interfaces (UI)! In this session, we'll explore how AI agents make decisions, collaborate with each other, and create more natural and powerful experiences for users.
Explaining GitHub Actions Failures with Large Language Models Challenges, In...
Explaining GitHub Actions Failures with Large Language Models Challenges, In...ssuserb14185 GitHub Actions (GA) has become the de facto tool that developers use to automate software workflows, seamlessly building, testing, and deploying code. Yet when GA fails, it disrupts development, causing delays and driving up costs. Diagnosing failures becomes especially challenging because error logs are often long, complex and unstructured. Given these difficulties, this study explores the potential of large language models (LLMs) to generate correct, clear, concise, and actionable contextual descriptions (or summaries) for GA failures, focusing on developers’ perceptions of their feasibility and usefulness. Our results show that over 80% of developers rated LLM explanations positively in terms of correctness for simpler/small logs. Overall, our findings suggest that LLMs can feasibly assist developers in understanding common GA errors, thus, potentially reducing manual analysis. However, we also found that improved reasoning abilities are needed to support more complex CI/CD scenarios. For instance, less experienced developers tend to be more positive on the described context, while seasoned developers prefer concise summaries. Overall, our work offers key insights for researchers enhancing LLM reasoning, particularly in adapting explanations to user expertise.
https://arxiv.org/abs/2501.16495
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Adobe Illustrator is a powerful, professional-grade vector graphics software used for creating a wide range of designs, including logos, icons, illustrations, and more. Unlike raster graphics (like photos), which are made of pixels, vector graphics in Illustrator are defined by mathematical equations, allowing them to be scaled up or down infinitely without losing quality.
Here's a more detailed explanation:
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Vector-Based Design:
Illustrator's foundation is its use of vector graphics, meaning designs are created using paths, lines, shapes, and curves defined mathematically.
Scalability:
This vector-based approach allows for designs to be resized without any loss of resolution or quality, making it suitable for various print and digital applications.
Design Creation:
Illustrator is used for a wide variety of design purposes, including:
Logos and Brand Identity: Creating logos, icons, and other brand assets.
Illustrations: Designing detailed illustrations for books, magazines, web pages, and more.
Marketing Materials: Creating posters, flyers, banners, and other marketing visuals.
Web Design: Designing web graphics, including icons, buttons, and layouts.
Text Handling:
Illustrator offers sophisticated typography tools for manipulating and designing text within your graphics.
Brushes and Effects:
It provides a range of brushes and effects for adding artistic touches and visual styles to your designs.
Integration with Other Adobe Software:
Illustrator integrates seamlessly with other Adobe Creative Cloud apps like Photoshop, InDesign, and Dreamweaver, facilitating a smooth workflow.
Why Use Illustrator?
Professional-Grade Features:
Illustrator offers a comprehensive set of tools and features for professional design work.
Versatility:
It can be used for a wide range of design tasks and applications, making it a versatile tool for designers.
Industry Standard:
Illustrator is a widely used and recognized software in the graphic design industry.
Creative Freedom:
It empowers designers to create detailed, high-quality graphics with a high degree of control and precision.
Who Watches the Watchmen (SciFiDevCon 2025)
Who Watches the Watchmen (SciFiDevCon 2025)Allon Mureinik Tests, especially unit tests, are the developers’ superheroes. They allow us to mess around with our code and keep us safe.
We often trust them with the safety of our codebase, but how do we know that we should? How do we know that this trust is well-deserved?
Enter mutation testing – by intentionally injecting harmful mutations into our code and seeing if they are caught by the tests, we can evaluate the quality of the safety net they provide. By watching the watchmen, we can make sure our tests really protect us, and we aren’t just green-washing our IDEs to a false sense of security.
Talk from SciFiDevCon 2025
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Kubernetes: one cluster or many
- 1. © Copyright 2018 Pivotal Software, Inc. All rights Reserved. Cornelia Davis · @cdavisafc Sr. Director of Technology CF Day, Seattle December 2018 Kubernetes: One Cluster or Many?
- 2. Master Worker Worker Worker API Server Controller Mgr DNSScheduler Kube Proxy Kube Proxy Kube Proxy
- 3. @cdavisafc Master Namespace 2 API Server Controller Mgr DNSScheduler Kube Proxy Kube Proxy Kube Proxy Namespace 1
- 4. @cdavisafc Master Namespace 2 API Server Controller Mgr DNSScheduler Kube Proxy Kube Proxy Kube Proxy Namespace 1 Many Shared Components = soft multitenancy: ● Same configurations (i.e. API Server, Controller Mgr) ● Ops affects all tenants ● Same version of K8s for all tenants Single Cluster
- 5. @cdavisafc The multi-tenancy working group has been looking at some of this...
- 6. @cdavisafc Master Namespace 2 API Server Controller Mgr DNSScheduler Kube Proxy Kube Proxy Kube Proxy Namespace 1 Make tenant aware OR... ... ...
- 7. @cdavisafc Give each tenant their own components https://blog.jessfraz.com/post/hard-multi-tenancy-in-kubernetes/
- 8. @cdavisafc Tenant 1 Master API Server Controller Mgr DNSScheduler Worker Kube Proxy Worker Kube Proxy Worker Kube Proxy ... Single Tenant Clusters ● Virtual Machines for hard multitenancy ● Limit Blast Radius ● Different Configs (i.e. API Server, Controller Mgr.) ● Different versions of K8s for each tenant Multiple Clusters Tenant 2 Master API Server Controller Mgr DNSScheduler Worker Kube Proxy Worker Kube Proxy Worker Kube Proxy
- 9. @cdavisafc ● Same configurations (i.e. API Server, Controller Mgr) ● Ops affects all tenants ● Same version of K8s for all tenants Single, multitenant Cluster ● Virtual Machines for hard multitenancy ● Limit Blast Radius ● Different Configs (i.e. API Server, Controller Mgr.) ● Different versions of K8s for each tenant Multiple, single tenant Clusters
- 10. Thank you.
- 11. @cdavisafc Transforming How The World Builds Software © Copyright 2018 Pivotal Software, Inc. All rights Reserved.