🚀 Transform Your Container Management with Morpheus! 🚀 Tired of switching between multiple tools to monitor and manage your containerized environments? Meet Morpheus—your all-in-one solution that unifies Docker, Kubernetes, and AI-powered insights into a single, intuitive platform. 🔍 Real-Time Monitoring: Get at-a-glance views of your CPU, memory, and network performance metrics. 🤖 AI-Driven Optimization: Leverage AWS Bedrock to analyze system data and provide actionable insights. 🖥️ Unified Interface: Manage all your containers and clusters from one seamless dashboard—no more app juggling! Say goodbye to fragmented workflows and hello to efficiency and clarity. Start optimizing smarter, not harder. Check us out on GitHub and experience the power of unified container management with Morpheus! https://lnkd.in/gj9wpD8b #DevOps #ContainerManagement #Docker #Kubernetes #AI #Monitoring #DeveloperTools #CloudComputing #Productivity

GitHub actions are 𝗙𝗥𝗘𝗘 computing that makes your life easier. Here are 3 use cases for ML projects ↓ ---------- Hi there! It's Pau 👋 Every day I share free, hands-on content, on production-grade ML, to help you build real-world ML products. 𝗙𝗼𝗹𝗹𝗼𝘄 𝗺𝗲 and 𝗰𝗹𝗶𝗰𝗸 𝗼𝗻 𝘁𝗵𝗲 🔔 so you don't miss what's coming next #machinelearning #mlops #realworldml #github

Kubernetes at 10: When K8s ‘won’ and life now as a ‘surly teenager’ We talk to DataStax’s @Patrick McFadin about Kubernetes’ success against competitors and how StatefulSet and operators solved key challenges, but why there are still obstacles to clear https://lnkd.in/eWdFJ3-b

I shared a few weeks ago that I was working on something with James Eastham and we've reached a point that it's ready to be shared! And probably no surprise that it's around Serverless and Rust. We are launching https://lnkd.in/gGszFsPs as a one-stop for learning about building and running Rust-based applications on serverless technologies. In addition to tutorials and how-to articles, you can find working sample code which will provide great starting point for accelerating your serverless and Rust builds. At the moment, we've got coverage around APIs, Data, Messaging and Security and over the coming weeks and months we will be adding more categories and depths. The best part about all of this? It's 100% open source! And here's the repository (https://lnkd.in/gcZ-zS_p). We are excited for others to submit new patterns as Issues, start Discussions or even contribute if you are so inclined. This isn't about James and Ben, it's about empowering the serverless and Rust developer communities as we see a need for more Rust in your builds and want to do everything we can to support that. So, Hello World! #rust #serverless #aws #opensource #awscommunity

At Cheerio AI 📣 , NGINX serves as our go-to tool for Reverse Proxy, Load Balancer, HTTP Cache, and TLS/SSL Termination. However, recently some drama was happening in the repository of Nginx. Nginx is a neat product but the essential features are in the paid version. For open-source developers like us, this creates a dilemma. When we seek to contribute new features to the open-source NGINX repository, we often find our pull requests rejected if features are already there or are exclusive to NGINX Plus. As a result, developers are forking the repository and maintaining their version with additional features they want. What do you use at your organisation as an alternative to NGINX? #nginx #opensource #opensourcecommunity #github #loadbalancer #reverseproxy

Want to know more about our #hackathon? Discover how Metal Toad's team utilized AWS services and ML to create a simple social network platform: Toadbook! Explore the innovative infrastructure and application structure in this detailed post. https://lnkd.in/dBV2zmBz

🚀 Yugabyte on #Kubernetes combines distributed #PostgreSQL with Kubernetes for powerful scalability, resilience, and automation. Ideal for mission-critical apps! Learn more here:https://lnkd.in/emKAmW5i CC Yu-Shen Ng #Yugabyte #Kubernetes #Database #SQL #SoftwareArchitecture

Getting ready for RunWhen's first Authors meet-up in London this eve! When our enterprise customers use RunWhen's AI Assistants to run troubleshooting automation, we pay the original automation Author a royalty. When our customers need coverage of something specific, we help connect them with Authors and a bounty. This is open source, but I like to think of it as a modern (transparent!) open source business model where everyone can do well. If you like writing *high quality* automation and have earned your scars troubleshooting Kubernetes, Kafka, Vault, Redis, Postgres, Nginx, Elastic, etc, etc, etc -- anything in the top few hundred helm charts -- we'd love to hear from you. #sre #platformengineering #devops #kubernetes #whatdoirunwhen

GitHub now joins the party of providing access to models on their platform! Apart from the major players like AWS, Microsoft and Google, there are already other smaller players like Together AI, Anyscale, Inferless etc. Then there’s, of course, HuggingFace. I remember when HuggingFace started they wanted to be the ‘GitHub of AI’. Well looks like GitHub wants be the GitHub of AI as well. They want to enable the rise of the AI Engineer by offering different models on their platform. This is the path they envision - Web UI Playground (GitHub) -> Dev Environment (Codespaces, VS Code) -> Prod Environment (Azure AI). In theory, it’s a nice pipeline to get customers to try out and funnel into buying Azure AI products. However, I feel they’re slightly late to the party. Today, the discovery of newer models happens mostly via X/social media launches or a launch on HuggingFace. And from here the developer pulls a copy into their dev environment and starts working on it. For the GitHub strategy to work, they need to incentivise users to start on their platform. I think one way in which they can actually catch up is doing exclusive model launches. Another way is to make the developer experience of launching newer models dead simple so that developers prefer GitHub to HuggingFace. I have more ideas around how GitHub can catch up, but maybe I’ll keep them for a consultation session with their team (if they’d like to talk me, of course). But what’s interesting is the general direction of having hosted models on different platforms seems to be growing. What are your thoughts? #github #aiengineer #huggingface

Day 2!!! Today I dove into Dockerizing an application which is the 2nd day of hashtag #40DaysOfKubernetes challenge by Piyush sachdeva and The CloudOps Community! I demonstrated the complete process of building an image from a Dockerfile. This involved constructing the image and then pushing it to a container registry. Subsequently, I illustrated how to pull the image from the registry and run it as a container, which serves as an instance of the pulled image, across development, testing, and production environments. key takeaways: 1. Writing a Dockerfile 2. Building an Image from a Dockerfile 3. Pushing to Image registry 4. Pulling an Image from a registry 5. Running a container on a specific port Checkout my blog on medium https://lnkd.in/eXMDvntN