Pulumi’s Post

Let's talk about containers and why they're changing the game for developers. Before Docker and Kubernetes, deploying applications was a hassle, with countless compatibility issues between environments. Containers solve this by packaging software and its dependencies into a cohesive unit. This means consistent and reliable performance, no matter where they're deployed. Moreover, the integration of AI simplifies scaling and managing these containers, making operations smoother and more efficient. It's this seamless blend of cloud tech and AI that allows us to innovate faster and more reliably. Have you embraced containers yet? What differences have they made for your deployment process? #webevolution #webdeveloper #ai

Remember the days when setting up a development environment took hours or even days? With containerisation and cloud infrastructure, that's history. Tools like Docker and Kubernetes enable developers to replicate production environments in minutes. Pair that with AI-driven diagnostics, and you have a recipe for rapid, reliable development cycles. The synergy between cloud tech and AI is not just boosting efficiency; it's transforming how we approach software development. #webevolution #webdeveloper #ai

🚀 Choosing the Right Container for Azure AI Services can be challenging, especially with options like Docker, Azure Container Instances (ACI), and Azure Kubernetes Service (AKS). In my latest guide, I break down the strengths and use cases of each platform to help you select the best container solution for your AI workloads in Azure. From simplicity and scalability to orchestration and automation, discover the key factors to consider when deploying your AI services. 🧠💡 Check out "Selecting the Optimal Container for Azure AI: Docker, ACI, or AKS?" and make an informed choice for your next project! #Azure #AI #Kubernetes #Docker #ACI #CloudComputing #Containerization #AKS #TechInnovation

Exciting news for AI developers! Docker and Release have joined forces to streamline GenAI development. We've integrated Docker's GenAI Stack into our template library, making cloud deployment as easy as local setup. Learn how this collaboration is transforming AI workflows: https://hubs.li/Q02KtSVy0

The latest update for #Lumigo includes "Leveraging #AI for Predictive #Analytics in #Observability" and "Five Ways to Improve #Serverless Performance". #monitoring #devops #AWS https://lnkd.in/dH5CzYQ

"Automation in cloud-based projects can drastically streamline development." Manually setting up cloud resources can be time-consuming and error-prone. But through my 5th project with BankerBot, I’ve seen how AWS CloudFormation changes the game: 💡 Infrastructure as Code (IaC): Instead of configuring each resource manually, I used a YAML template to define all component's intents, slots, and Lambda functions in one go. This simplified setup and ensured consistency. ⚙️ Automated Deployment: CloudFormation handled everything—from the chatbot’s CheckBalance intent to connecting Lambda—saving valuable time on infrastructure tasks. 🔄 Efficient Resource Management: Not only can I deploy resources quickly, but I can also manage updates and deletions with a single command. Clean and efficient! 🔧 Reduced Errors: Automation minimized human errors during setup. Even with a permissions issue, the structured environment made troubleshooting easier. Through this project, I've solidified my skills in automation, AWS Lambda, and IaC, enhancing both speed and accuracy in cloud development. #AWS #CloudFormation #Automation #AI #CloudComputing #Project5 #AIxAWS #TechSkillsSand TechnologiesAmazon Web Services (AWS)NextWork

Deploying Azure AI services in containers—whether Docker, Azure Container Instances (ACI), or Azure Kubernetes Service (AKS)—empowers businesses to scale AI applications effectively. Shyam Yadav shares how Docker shines in local development and testing, while ACI offers simplicity for lightweight, quick deployments. For large-scale, mission-critical AI workloads, AKS provides unparalleled scalability and orchestration. By choosing the right container, organizations can achieve fast deployment, seamless integration, and cost-efficiency. Which container strategy fits your AI needs? https://lnkd.in/gm86Di7G #AzureAI #AIContainers #Kubernetes #CloudComputing

🚀 𝗨𝗻𝗹𝗼𝗰𝗸𝗶𝗻𝗴 𝘁𝗵𝗲 𝗣𝗼𝘄𝗲𝗿 𝗼𝗳 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀: 𝗦𝗰𝗮𝗹𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗿𝗻 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 🛠️ In today’s fast-paced tech environment, #Kubernetes has become the go-to solution for 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 and 𝗰𝗹𝗼𝘂𝗱-𝗻𝗮𝘁𝗶𝘃𝗲 app management. Its ability to automate application container deployment, scaling, and operations makes it a game-changer for companies aiming to stay agile and efficient. 🔑 𝗞𝗲𝘆 𝗯𝗲𝗻𝗲𝗳𝗶𝘁𝘀 𝗼𝗳 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀: 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Seamlessly manage hundreds or thousands of containers. 𝗥𝗲𝘀𝗶𝗹𝗶𝗲𝗻𝗰𝗲: Automatic restarts and self-healing of apps. 𝗣𝗼𝗿𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Run workloads anywhere, from on-premise to any cloud. 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆: Optimize resource allocation with intelligent scheduling. If your infrastructure is evolving, it’s time to explore Kubernetes. Its robust architecture is paving the way for modern DevOps teams to innovate faster and manage complexity with ease. 💡 Ready to dive in? Let’s discuss how Kubernetes can transform your infrastructure and future-proof your business. 𝗩𝗶𝘀𝗶𝘁: https://bit.ly/3UW3rei #Kubernetes #CloudNative #DevOps #Containers #TechInnovation #Opsninja #aws

🚀 Discover how easy it is to deploy a Flask microblog on Kubernetes with just few clicks using Toystack AI! No need to worry about the complex setup, scaling, or security—ToyStack AI handles everything from code to production. Whether it's deploying applications, ToyStack's Neo-Cloud Platform makes it incredibly easy. Say goodbye to DevOps headaches and focus on what matters: building great apps. Curious to try it out? Join the future of cloud deployment with ToyStack AI! https://lnkd.in/gSytKhZW #neocloud #Kubernetes #Flask #DevOps #CloudNative #ToyStackAI

🤯 The Cloud Native Landscape can be overwhelming, can't it?  🚶🏽 As we begin our journey in cloud native computing, let me take you on a stroll along these 🔟 steps: When introducing newcomers to the cloud native world, I always start with presenting them the CNCF Trail Map first. Rather than throwing at them over 2 000 items, I show this easy to follow ten steps and related Open Source and CNCF projects: 1️⃣ 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫𝐢𝐳𝐚𝐭𝐢𝐨𝐧 Open Source Projects: Podman, Buildah 2️⃣ 𝐂𝐈/𝐂𝐃 CNCF Projects: Argo & Flux 3️⃣ 𝐎𝐫𝐜𝐡𝐞𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 & 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐃𝐞𝐟𝐢𝐧𝐢𝐭𝐢𝐨𝐧 CNCF Projects: Kubernetes & Helm 4️⃣ 𝐎𝐛𝐬𝐞𝐫𝐯𝐚𝐛𝐢𝐥𝐢𝐭𝐲 & 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 CNCF Projects: Prometheus, Fluentd, Jaeger, Opentracing 5️⃣ 𝐒𝐞𝐫𝐯𝐢𝐜𝐞 𝐏𝐫𝐨𝐱𝐲, 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲 & 𝐌𝐞𝐬𝐡 CNCF Projects: Envoy, CoreDNS, Istio, Linkerd 6️⃣ 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐢𝐧𝐠, 𝐏𝐨𝐥𝐢𝐜𝐲 & 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 CNCF Projects: CNI, OPA, Falco 7️⃣ 𝐃𝐢𝐬𝐭𝐫𝐢𝐛𝐮𝐭𝐞𝐝 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 & 𝐒𝐭𝐨𝐫𝐚𝐠𝐞 CNCF Projects: Vitess, Rook, etcd, TiKV 8️⃣ 𝐒𝐭𝐫𝐞𝐚𝐦𝐢𝐧𝐠 & 𝐌𝐞𝐬𝐬𝐚𝐠𝐢𝐧𝐠 CNCF Projects: gRPC, NATS, cloudevents 9️⃣ 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫 𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐲 & 𝐑𝐮𝐧𝐭𝐢𝐦𝐞 CNCF Projects: containerd, Harbor, cri-o 🔟 𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐃𝐢𝐬𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧 CNCF Projects: TUF, notary ___ Do you think the Cloud Native Trail Map is still relevant? What would you improve in it? ⬇️ Please comment below! ⬇️ ___ My name is Jakub Krzywda, PhD. I post about: #kubernetes, #cloudnative technologies and #devops practices. #K8sWithK5a 𝗖𝗟𝗜𝗖𝗞 my name + 𝗙𝗢𝗟𝗟𝗢𝗪 + 🔔 so you don’t miss my next posts! 𝗟𝗜𝗞𝗘 👍 to support | 𝗖𝗢𝗠𝗠𝗘𝗡𝗧 💬 to add your perspective | 𝗥𝗘𝗣𝗢𝗦𝗧 ♻️ to share with your network Looking for training in Kubernetes or other Cloud Native technologies? 🔝 𝗘𝗡𝗥𝗢𝗟 today in the course that best suits your needs (link on the top of my profile)