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Software Developer, RELIANOID

how to migrate ADC services from Array Networks APV Series to RELIANOID—step by step.

Migrating from legacy ADC platforms doesn’t have to be complex. In our latest Knowledge Base article, we walk you through how to migrate ADC services from Array Networks APV Series to RELIANOID—step by step. 🔍 What you’ll find inside: - Clear terminology mapping between both platforms - Practical mi..

Knowledge base migrate ADC services from ARRAY NETWORKS APV SERIES to RELIANOID
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@laura_garcia shared a post, 1 week, 6 days ago
Software Developer, RELIANOID

DevOpsCon Amsterdam 2026

- 𝗗𝗲𝘃𝗢𝗽𝘀𝗖𝗼𝗻 𝗔𝗺𝘀𝘁𝗲𝗿𝗱𝗮𝗺 𝟮𝟬𝟮𝟲 𝗶𝘀 𝗷𝘂𝘀𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝘁𝗵𝗲 𝗰𝗼𝗿𝗻𝗲𝗿! - Amsterdam, Netherlands April 20–24, 2026 Simplify complexity, amplify agility, and accelerate innovation. Join DevOpsCon Amsterdam 2026 — one of the leading conferences for professionals working with CI/CD, Kubernetes, Platform Engineering, ..

devopscon amsterdam april 26
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@sanjayjoshi shared a post, 2 weeks, 1 day ago

10+ Shadcn Table Components, Blocks & Tools

A curated list of Shadcn table components and blocks you can use in React and Next.js projects to build clean, flexible, and production-ready data tables faster.

Thumbnail Shadcn Table
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Black Box Testing Techniques to Improve Test Coverage

Learn black box testing techniques to improve test coverage. Explore methods like equivalence partitioning, boundary value analysis, and more with practical examples.

black box testing techniques
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@laura_garcia shared a post, 2 weeks, 1 day ago
Software Developer, RELIANOID

𝗪𝗼𝗿𝗹𝗱 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗗𝗮𝘆

🚀 𝗪𝗼𝗿𝗹𝗱 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗗𝗮𝘆 𝗶𝘀 𝗵𝗲𝗿𝗲… and it’s not just science fiction anymore. Quantum computing is rapidly moving from theory to reality—and with it comes a 𝗺𝗮𝘀𝘀𝗶𝘃𝗲 𝘀𝗵𝗶𝗳𝘁 𝗶𝗻 𝗰𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 that organizations simply can’t ignore. Here’s the uncomfortable truth: 👉 The same technology that promises breakthrou..

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@hamzmu shared a link, 2 weeks, 1 day ago
Fellow, Rootly

Using Graphify to turn Incident Data into a Knowledge Graph

Karpathy said we should build LLM knowledge bases. 48 hours later made Graphify was made: one command, full semantic knowledge graph.

We applied the idea to incident data turning them into a queryable and interactable semantic graph. This lets us see past fixes, predict failures, cluster services, cut alert noise, and reveal team load in seconds.

If you’re using Rootly, here is a small plugin to explore your incident data.

Check it out: github.com/Rootly-AI-Labs/rootly-graphify-importer

Interactive knowledge graph visualization of incident management data showing clustered services, alerts, and responders with connected nodes and relationships in Graphify
Vertex AI is Google Cloud’s end-to-end machine learning and generative AI platform, designed to help teams build, deploy, and operate AI systems reliably at scale. It unifies data preparation, model training, evaluation, deployment, and monitoring into a single managed environment, reducing operational complexity while supporting advanced AI workloads.

Vertex AI supports both custom models and foundation models, including Google’s Gemini model family. It enables organizations to fine-tune models, run large-scale inference, orchestrate agentic workflows, and integrate AI into production systems with strong security, governance, and observability controls.

The platform includes tools for AutoML, custom training with TensorFlow and PyTorch, managed pipelines, feature stores, vector search, and online and batch prediction. For generative AI use cases, Vertex AI provides APIs for text, image, code, multimodal generation, embeddings, and agent-based systems, including support for Model Context Protocol (MCP) integrations.

Built for enterprise environments, Vertex AI integrates deeply with Google Cloud services such as BigQuery, Cloud Storage, IAM, and VPC, enabling secure data access and compliance. It is widely used across industries like finance, healthcare, retail, and science for applications ranging from recommendation systems and forecasting to autonomous research agents and AI-powered products.