Kube Resource Orchestrator: Simplify Kubernetes Resource Management

🔥 What if your developers spent hours solving business problems instead of wrestling with APIs? For many companies, connecting REST APIs is a time sink — hours spent writing custom code, updating broken integrations, and troubleshooting endpoints. That’s time your team could have spent innovating. Enter ARC (Autonomous REST Connector) from Progress Software. ARC automates REST API connections to your data tools (ODBC, JDBC, etc.), so developers focus on what actually moves the business forward. ✅ Instant API connectivity ✅ Less maintenance, fewer headaches ✅ More time for innovation Teams using ARC are slashing integration times and freeing up developer bandwidth — turning tedious work into strategic impact. Curious to see ARC in action? Let’s connect for a quick 15-min intro with the Progress Software specialists. 📧 jdiaz@anteriad.com #ProgressSoftware #ARC #DataIntegration #DeveloperProductivity #APIManagement #DigitalTransformation

We get this question a fair bit: “If I’m going to need Infrahub Enterprise, can I start testing with Community and migrate later?” Technically you can. But we don’t recommend it. Here’s why: Infrahub Enterprise includes major performance upgrades and scaling improvements that are specifically designed for large or complex environments. Testing with Community might give you an incomplete picture, and in some cases, performance bottlenecks that wouldn’t exist in Enterprise. If you’re evaluating Infrahub for scaled production use, it’s better to start with the real thing. Enterprise is available for free for non-production testing, and it’s built to show you what Infrahub can actually do under real-world conditions. So there's no reason not to start there. Want to chat about your requirements? Request a demo from the OpsMill home page, or DM Pete Crocker or Ramzi Lahoud to chat.

The Krateo Core Provider is a Kubernetes operator that manages Helm charts as custom resources, generating CRDs from values.schema.json, handling versioned compositions, and managing chart lifecycle with validation. More: https://ku.bz/FpJXRvvhW

Friendly Reminder: Grafana Alloy isn’t just Promtail replacement—it's a central telemetry hub for logs and metrics. It combines Promtail, Loki plugins, and Cadvisor into one workflow, simplifying your HomeLab! - It can pull or push telemetry and export rules to Loki and Prometheus. - It replaces multiple tools (Promtail, Loki plugins, Cadvisor) with a single, flexible agent. - You configure pipelines as Components (each with a name and labels) and chain them to form your data flow. - You can filter, transform, and enrich data before it leaves the host, which reduces noise and maintenance. - Alloy scales from a simple single-host setup to a clustered deployment for high availability. Notes and caveats: the learning curve can be real because the configuration model is different from older tools. Start small—pick one host, add a couple of components (local.file_match, loki.write), and verify end-to-end before expanding. For reference, check Grafana’s Alloy docs and the boilerplates repo I mentioned in the video description.

System administrators can reduce manual steps by automating package deployment in #JDEdwards using an orchestration. This OBE shows you how to run it from the #Orchestrator Studio: https://bit.ly/3BVzMKV

🚀 Introducing Workspace Version Aligner (WVA) Ever struggled with mismatched package versions in a monorepo? I’ve built a CLI tool — Workspace Version Aligner — to help developers preview, fix, and align package versions across a monorepo effortlessly. It ensures every workspace uses the right dependency versions — reducing bugs, build conflicts, and version drift. 🧩 Key Features: Scan and list all workspace dependencies Highlight mismatched versions Automatically fix and align them Easy to integrate into your CI/CD 💡 Tech Stack: Node.js, Commander.js, Chalk, and FS modules 👉 Try it out https://lnkd.in/dPb2h5tD

The recent announcement of alpha support for a changed block tracking mechanism in Kubernetes is a significant development for enhancing data management efficiency. I found it interesting that this feature aims to optimize performance for workloads that require rapid data access. As Kubernetes continues to evolve, what capabilities do you think will be most impactful for developers in the next few years?

Exciting news in the Kubernetes community! The announcement of alpha support for a changed block tracking mechanism is a significant step forward. I found it interesting that this feature aims to improve efficiency in data management, which is critical for modern cloud-native applications. How do you see this impacting your workflows or projects? Read more here: https://lnkd.in/drHMVCUj

Kubernetes CRD (Custom Resource Definition) 🧩 What Kubernetes Gives You Out-of-the-Box When you install Kubernetes, you get: Pods, Deployments, ReplicaSets ConfigMaps, Secrets, Namespaces And many more… These cover most use cases — but what if you need something custom? The Three Key Components 1️⃣ CRD (Custom Resource Definition) → The blueprint or template that defines your new resource type. 2️⃣ CR (Custom Resource) → The actual instance created from that CRD. 3️⃣ Custom Controller → Manages the lifecycle of your custom resources and ensures the desired state. Analogy: CRD = Class definition CR = Object (instance) Controller = Manager that keeps it in sync 🔑 Key Takeaway CRDs let you extend Kubernetes not replace it. You’re adding new capabilities while using the same powerful Kubernetes API. That’s exactly how tools like: ArgoCD Prometheus Operator cert-manager …extend Kubernetes under the hood 📚 Resources for Learning https://lnkd.in/g3wmvjuW https://lnkd.in/gTMF5HYB What’s the most interesting custom resource you’ve built? 👇

Lots of people want to know what the full agent stack looks like. Which tools do I use? How do I handle orchestration, tool use, large context, memory, etc? Brief thread to help you choose 🧵 1. Letta