#Kubernetes AI platform
268 related articles
·3 min
Getting Started with Jenkins: The Core Hub of CI/CD Automation Explained
A beginner's guide to Jenkins: its role as the CI/CD and DevOps hub, JDK requirements, and the four plugin categories (source control, build, security scanning, deployment) that power automation pipelines.
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·3 min
Flyte Deep Dive: A Practical Guide to Choosing Your ML Workflow Orchestration Tool
Deep dive into Flyte's core capabilities: cloud-native GPU scheduling, intelligent caching, checkpoint recovery, and conditional deployment — plus a full comparison with Argo and KubeFlow Pipelines.
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·3 min
MLOps from Scratch: A 100-Day Learning Challenge Roadmap and Practical Guide
A college student's MLOps 100-day challenge documents the full journey from Python engineering and Git to Docker, model deployment, and monitoring. A practical roadmap for data scientists transitioning to ML engineering.
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·2 min
Karma: An AI Coding Agent Orchestration Tool for Building Multi-Agent Collaborative Systems
Karma is an orchestration layer for AI coding agent frameworks, solving multi-agent collaboration, task decomposition, state management, and observability challenges. Compatible with Aider, OpenHands, and more.
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SendLang: Rethinking Email Automation …
·3 min
SendLang: Rethinking Email Automation with a Domain-Specific Language
SendLang is a DSL for email automation that uses declarative syntax to separate trigger conditions, content templates, and send timing — tackling logic coupling in traditional email systems.
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Production-Grade LangGraph Template: A…
·2 min
Production-Grade LangGraph Template: A Practical Guide to Engineering AI Agents for Production
A deep dive into production-grade LangGraph templates covering state management, observability, error handling, and containerized deployment to bridge the gap from demo to production.
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·3 min
Bun Rewrote a Million Lines of Code in 11 Days with Claude Code: A New Paradigm for AI-Assisted Programming
Bun author Jared Sumner used Claude Code's dynamic workflows to rewrite 1M+ lines of Zig code into Rust in 11 days for $165K — what 3 engineers would need a year to do.
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Cross-Platform MicroVM Sandbox: Runnin…
·3 min
Cross-Platform MicroVM Sandbox: Running AI-Generated Code Safely in Isolated Environments
Explore cross-platform MicroVM sandbox technology supporting Windows/Mac/Linux with a built-in policy engine for fine-grained access control in AI Agent and multi-tenant code execution scenarios.
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LLM Evaluation Tools Compared: An In-D…
·3 min
LLM Evaluation Tools Compared: An In-Depth Look at LangSmith, Langfuse, and Three More
Deep comparison of LangSmith, Langfuse, Phoenix, Braintrust, and Galileo across self-hosting, open-source licensing, and real-time guardrails to find the best LLM eval tool for production.
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·2 min
Learning MLOps from Scratch: A Deep Dive into the 24-Month Roadmap
Can you learn MLOps from scratch? This guide breaks down core skill requirements and offers a practical 4-phase, 24-month roadmap covering Python, ML, DevOps, and MLflow.
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·4 min
The Complete Roadmap from DevOps to MLOps: Skill Transfer and Toolchain Guide
How can DevOps engineers transition to MLOps? This guide explains the core differences between MLOps and DevOps, offers a phased learning path, tool recommendations (MLflow, DVC, Kubeflow), and practical project ideas.
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·4 min
A Deep Dive into ASP.NET Core: The Complete Guide to Microsoft's Cross-Platform Web Framework
A comprehensive analysis of ASP.NET Core's architecture and technical strengths: cross-platform deployment, high-performance Kestrel server, modular middleware, built-in DI, and modern web capabilities like Blazor, gRPC, and SignalR.
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Coinbase Outage Postmortem: The Deeper…
·4 min
Coinbase Outage Postmortem: The Deeper Causes of Failed Zone Failover and Its Lessons
A deep dive into Coinbase's global trading system outage—why multi-AZ deployment still couldn't prevent the disruption. Analyzing the missing automated zone failover, the core elements of financial-grade HA architecture, and reliability lessons for every team.
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·3 min
Career Switch to AI Engineer Without a CS Degree: A Self-Study Roadmap from Scratch
A real case study of an agriculture student breaking into AI: how to start with CS50 and systematically master Python, machine learning, and MLOps skills, with a three-phase transition plan for self-learners.
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·3 min
Decoding Databricks' AI Strategy: The Omnigents Orchestration Platform and LTAP Unified Storage Architecture
An in-depth look at the AI strategy of Databricks co-founders Matei Zaharia and Reynold Xin: the open-source Agent platform Omnigents, the unified storage architecture LTAP, and how Dream Engine reshapes data and intelligence.
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·5 min
The Five Unsolved Challenges of Production MLOps: A Deep Dive into GPU Scheduling, Fault-Tolerant Training, and Model Observability
A deep dive into the five genuinely tough challenges of production MLOps: fault-tolerant training on Spot instances, cross-team GPU scheduling, data reproducibility, model observability, and inference cost optimization.
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·3 min
The Complete Guide to Terraform: The Core Tool and Practices of Infrastructure as Code
An in-depth look at Terraform's core principles and workflow, covering declarative configuration, the multi-cloud Provider ecosystem, IaC best practices, and license changes. Helps DevOps engineers master the industry-standard tool for infrastructure automation.
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·3 min
Farewell to a Decade-Old VPS: Technical and Emotional Insights from Retiring an Old Server
A tweet saying "rest well, old friend" resonated across the tech community. This article explores VPS lifecycle management, best practices for retiring old servers, and the unique emotional bond between engineers and infrastructure.
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·4 min
From New Grad SWE to Platform Engineer: Career Paths and Tech Stack Choices in the AI Era
How can new graduates transition from software engineer to platform engineer? This article breaks down the path of joining as a Grad SWE first, then transferring internally, analyzes C# vs Python trade-offs, and offers a 14-month prep plan for AI/ML infrastructure.
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·3 min
Inside the ML Engineer Coding Assessment at Top US Tech Companies: What's Tested and How to Prepare
A firsthand account shared on Reddit reveals what a machine learning engineer online assessment (OA) at a top US tech company is really like. This article breaks down OA modules, role differences, and prep strategies for FAANG job seekers.
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