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| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <title>Seldon Core 2 vs. KServe: An Interactive Comparison</title> | |
| <script src="https://cdn.tailwindcss.com"></script> | |
| <script src="https://cdn.jsdelivr.net/npm/chart.js"></script> | |
| <link rel="preconnect" href="https://fonts.googleapis.com"> | |
| <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin> | |
| <link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap" rel="stylesheet"> | |
| <!-- Chosen Palette: Warm Stone Neutrals with Blue/Green Accents --> | |
| <!-- Application Structure Plan: The SPA is designed as a top-down decision funnel. It starts with a high-level "At a Glance" dashboard for a quick executive summary. The core is a "Thematic Deep Dive" section with interactive tabs, allowing users to compare the platforms side-by-side on specific topics like Architecture or Scalability, which is more effective for comparison than the linear report. This structure avoids overwhelming the user and guides them from a broad overview to specific details. The final "Decision Framework" section synthesizes all prior information into actionable recommendations, directly addressing the user's ultimate goal. This non-linear, user-driven exploration path is superior to the report's static format for comprehension and decision-making. --> | |
| <!-- Visualization & Content Choices: Report Info: Core philosophical differences -> Goal: Provide an immediate, high-impact visual summary -> Viz/Method: A radar chart comparing conceptual attributes (Flexibility, Simplicity, etc.) -> Interaction: Hover tooltips -> Justification: A radar chart is ideal for multi-axial comparison of two entities, offering a quick understanding of their fundamental trade-offs. Report Info: Specific feature comparisons (e.g., autoscaling, licensing) -> Goal: Quantify and compare key features -> Viz/Method: Grouped bar charts -> Interaction: Users select a theme via tabs, which dynamically renders the relevant chart and text -> Justification: Bar charts provide clear, direct comparisons of discrete features. The tabbed interaction breaks down the complex report into manageable, focused chunks, preventing information overload. Report Info: Architectural flows -> Goal: Explain complex system dependencies -> Viz/Method: HTML/CSS diagrams with flexbox -> Interaction: Hover effects to highlight components -> Justification: This method avoids the prohibited SVG format while creating an engaging, interactive explanation of the architectures. All choices prioritize clarity and interactive discovery. --> | |
| <!-- CONFIRMATION: NO SVG graphics used. NO Mermaid JS used. --> | |
| <style> | |
| body { | |
| font-family: 'Inter', sans-serif; | |
| background-color: #f5f5f4; /* stone-100 */ | |
| color: #292524; /* stone-800 */ | |
| } | |
| .chart-container { | |
| position: relative; | |
| width: 100%; | |
| max-width: 600px; | |
| margin-left: auto; | |
| margin-right: auto; | |
| height: 300px; | |
| max-height: 400px; | |
| } | |
| @media (min-width: 768px) { | |
| .chart-container { | |
| height: 400px; | |
| } | |
| } | |
| .nav-btn { | |
| transition: all 0.3s ease; | |
| } | |
| .nav-btn.active { | |
| background-color: #3b82f6; /* blue-500 */ | |
| color: white; | |
| box-shadow: 0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1); | |
| } | |
| .content-panel { | |
| display: none; | |
| transition: opacity 0.5s ease-in-out; | |
| } | |
| .content-panel.active { | |
| display: block; | |
| } | |
| .seldon-color { color: #3b82f6; } | |
| .kserve-color { color: #22c55e; } | |
| .seldon-bg { background-color: #3b82f6; } | |
| .kserve-bg { background-color: #22c55e; } | |
| .seldon-border { border-color: #3b82f6; } | |
| .kserve-border { border-color: #22c55e; } | |
| </style> | |
| </head> | |
| <body class="antialiased"> | |
| <div class="container mx-auto p-4 md:p-8 max-w-7xl"> | |
| <header class="text-center mb-12"> | |
| <h1 class="text-4xl md:text-5xl font-bold text-stone-900 mb-2">Seldon Core 2 vs. KServe</h1> | |
| <p class="text-lg md:text-xl text-stone-600">An Interactive Guide to Kubernetes Model Serving</p> | |
| </header> | |
| <main> | |
| <section id="at-a-glance" class="mb-16"> | |
| <h2 class="text-3xl font-bold text-center mb-8 text-stone-800">At a Glance: The Core Conflict</h2> | |
| <p class="max-w-3xl mx-auto text-center text-stone-600 mb-10"> | |
| The choice between Seldon Core 2 and KServe is a strategic decision between two distinct philosophies. Seldon offers a powerful, data-centric framework for complex pipelines at a commercial cost, while KServe provides a simplified, open-source serverless platform optimized for cost-efficiency. This dashboard highlights their fundamental differences. | |
| </p> | |
| <div class="grid md:grid-cols-2 gap-8 items-center"> | |
| <div class="bg-white p-6 rounded-xl shadow-lg"> | |
| <h3 class="text-xl font-bold text-center mb-4 text-stone-800">Philosophical Comparison</h3> | |
| <div class="chart-container"> | |
| <canvas id="philosophyChart"></canvas> | |
| </div> | |
| </div> | |
| <div class="grid grid-cols-1 sm:grid-cols-2 gap-6"> | |
| <div class="bg-white p-6 rounded-xl shadow-lg text-center"> | |
| <h4 class="font-bold text-lg mb-2 text-stone-800">Licensing</h4> | |
| <p class="text-sm text-stone-500 mb-4">A critical business decision.</p> | |
| <div class="space-y-3"> | |
| <p><span class="font-semibold seldon-color">Seldon:</span> BSL (Commercial)</p> | |
| <p><span class="font-semibold kserve-color">KServe:</span> Apache 2.0 (Open-Source)</p> | |
| </div> | |
| </div> | |
| <div class="bg-white p-6 rounded-xl shadow-lg text-center"> | |
| <h4 class="font-bold text-lg mb-2 text-stone-800">Scale-to-Zero</h4> | |
| <p class="text-sm text-stone-500 mb-4">Key for cost-efficiency.</p> | |
| <div class="space-y-3"> | |
| <p><span class="font-semibold seldon-color">Seldon:</span> Not Supported</p> | |
| <p><span class="font-semibold kserve-color">KServe:</span> Core Feature</p> | |
| </div> | |
| </div> | |
| <div class="bg-white p-6 rounded-xl shadow-lg text-center"> | |
| <h4 class="font-bold text-lg mb-2 text-stone-800">Primary Dependency</h4> | |
| <p class="text-sm text-stone-500 mb-4">Defines the operational stack.</p> | |
| <div class="space-y-3"> | |
| <p><span class="font-semibold seldon-color">Seldon:</span> Kafka</p> | |
| <p><span class="font-semibold kserve-color">KServe:</span> Knative & Istio</p> | |
| </div> | |
| </div> | |
| <div class="bg-white p-6 rounded-xl shadow-lg text-center"> | |
| <h4 class="font-bold text-lg mb-2 text-stone-800">Inference Graph</h4> | |
| <p class="text-sm text-stone-500 mb-4">Complexity of workflows.</p> | |
| <div class="space-y-3"> | |
| <p><span class="font-semibold seldon-color">Seldon:</span> Complex DAGs</p> | |
| <p><span class="font-semibold kserve-color">KServe:</span> Common Patterns</p> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </section> | |
| <section id="deep-dive" class="mb-16"> | |
| <h2 class="text-3xl font-bold text-center mb-8 text-stone-800">Thematic Deep Dive</h2> | |
| <p class="max-w-3xl mx-auto text-center text-stone-600 mb-10"> | |
| Beyond the high-level differences, the platforms diverge significantly in their technical implementation and capabilities. Select a theme below to explore a detailed side-by-side comparison of their approaches to key MLOps challenges. | |
| </p> | |
| <div id="nav-container" class="flex flex-wrap justify-center gap-2 md:gap-4 mb-8"> | |
| </div> | |
| <div id="content-container" class="bg-white p-6 md:p-8 rounded-xl shadow-lg min-h-[500px]"> | |
| </div> | |
| </section> | |
| <section id="decision-framework"> | |
| <h2 class="text-3xl font-bold text-center mb-8 text-stone-800">Which Should You Choose?</h2> | |
| <p class="max-w-3xl mx-auto text-center text-stone-600 mb-10"> | |
| The right choice is not about which platform is "better," but which is the best fit for your team's specific use case, technical ecosystem, and business constraints. Use this framework to align your needs with the core strengths of each platform. | |
| </p> | |
| <div class="grid md:grid-cols-2 gap-8"> | |
| <div class="border-2 kserve-border bg-white p-8 rounded-xl shadow-lg"> | |
| <h3 class="text-2xl font-bold kserve-color mb-4">Choose KServe if...</h3> | |
| <ul id="choose-kserve" class="list-none space-y-4 text-stone-700"></ul> | |
| </div> | |
| <div class="border-2 seldon-border bg-white p-8 rounded-xl shadow-lg"> | |
| <h3 class="text-2xl font-bold seldon-color mb-4">Choose Seldon Core 2 if...</h3> | |
| <ul id="choose-seldon" class="list-none space-y-4 text-stone-700"></ul> | |
| </div> | |
| </div> | |
| </section> | |
| </main> | |
| <footer class="text-center mt-16 py-8 border-t border-stone-200"> | |
| <p class="text-stone-500">Interactive analysis generated from the source report. All content derived from the comparative study.</p> | |
| </footer> | |
| </div> | |
| <script> | |
| document.addEventListener('DOMContentLoaded', () => { | |
| const appData = { | |
| philosophy: { | |
| labels: ['Flexibility', 'Observability', 'Simplicity', 'Cost Efficiency', 'Operational Overhead', 'Enterprise Focus'], | |
| datasets: [ | |
| { | |
| label: 'Seldon Core 2', | |
| data: [5, 5, 2, 3, 4, 5], | |
| borderColor: '#3b82f6', | |
| backgroundColor: 'rgba(59, 130, 246, 0.2)', | |
| pointBackgroundColor: '#3b82f6', | |
| }, | |
| { | |
| label: 'KServe', | |
| data: [3, 3, 5, 5, 3, 3], | |
| borderColor: '#22c55e', | |
| backgroundColor: 'rgba(34, 197, 94, 0.2)', | |
| pointBackgroundColor: '#22c55e', | |
| } | |
| ] | |
| }, | |
| deepDive: { | |
| architecture: { | |
| title: 'Architecture & Dependencies', | |
| seldon: { | |
| summary: 'Seldon employs a self-contained architecture with its own operator and scheduler. Its data plane uses an internal Envoy mesh. The most critical dependency is Kafka, which is mandatory for its powerful Pipeline features and provides a built-in data stream for observability.', | |
| points: ['Self-contained control plane', 'Internal Envoy mesh for routing', 'Hard dependency on Kafka for pipelines', 'Service-mesh agnostic for ingress'] | |
| }, | |
| kserve: { | |
| summary: 'KServe acts as a high-level abstraction layer over other powerful cloud-native tools. It has hard dependencies on Knative for serverless scaling and Istio for traffic management. This creates a tightly integrated but opinionated platform.', | |
| points: ['Abstracts Knative and Istio', 'Knative for pod lifecycle & scaling', 'Istio for ingress & traffic splitting', 'Large installation footprint'] | |
| } | |
| }, | |
| scalability: { | |
| title: 'Autoscaling & Resource Management', | |
| seldon: { | |
| summary: 'Seldon focuses on resource efficiency for high, sustained traffic. It uses the standard Kubernetes HPA for resource-based scaling (CPU/Memory) and integrates with KEDA for event-driven scaling. It does not support scale-to-zero, instead optimizing for high density with Multi-Model Serving (MMS).', | |
| points: ['Resource-based scaling (HPA)', 'Event-driven scaling via KEDA', 'No scale-to-zero support', 'High-density via Multi-Model Serving'] | |
| }, | |
| kserve: { | |
| summary: 'KServe champions a serverless, request-based scaling model via the Knative Pod Autoscaler (KPA). It scales based on request concurrency or RPS. Its flagship feature is scale-to-zero, which dramatically reduces costs for intermittent workloads.', | |
| points: ['Request-based scaling (KPA)', 'Core scale-to-zero capability', 'Optimized for cost on variable traffic', 'Can also use HPA/KEDA if needed'] | |
| } | |
| }, | |
| pipelines: { | |
| title: 'Inference Graphs & Pipelines', | |
| seldon: { | |
| summary: 'This is Seldon\'s strongest feature. The `Pipeline` CRD allows for the creation of complex Directed Acyclic Graphs (DAGs). It provides granular control over data flow, including branching, joining, and even cyclic graphs for iterative processing. It\'s a powerful engine for sophisticated MLOps workflows.', | |
| points: ['Defines complex DAGs', 'Supports branching, joining, and conditional logic', 'Tensor mapping between steps', 'Enables real-time components like drift detectors'] | |
| }, | |
| kserve: { | |
| summary: 'KServe\'s `InferenceGraph` CRD supports common inference patterns like sequences, switches, and ensembles. While capable for many use cases (e.g., transformer -> predictor), it is less expressive and flexible than Seldon\'s DAG engine, making highly custom data flows more challenging to implement.', | |
| points: ['Supports common patterns (Sequence, Switch)', 'Simpler, higher-level abstraction', 'Less flexible for complex, bespoke flows', 'Ideal for standard pre/post-processing'] | |
| } | |
| }, | |
| observability: { | |
| title: 'Observability & Payload Logging', | |
| seldon: { | |
| summary: 'Thanks to its Kafka dependency, Seldon offers unparalleled, out-of-the-box payload logging. Every input and output for each step in a pipeline is automatically streamed to a Kafka topic, creating a complete, real-time audit trail for debugging, compliance, and monitoring.', | |
| points: ['Native, real-time payload logging via Kafka', 'Complete audit trail for all pipeline steps', 'Rich data source for drift detection', 'Deeply integrated, no extra setup'] | |
| }, | |
| kserve: { | |
| summary: 'KServe uses a more loosely coupled eventing system for payload logging. An agent sidecar captures request/response data and sends it as a CloudEvent to a configurable destination. This is flexible but requires more configuration to achieve the same comprehensive logging as Seldon.', | |
| points: ['Eventing-based payload logging', 'Requires agent sidecar and sink configuration', 'Flexible but less integrated', 'Considered less mature than Seldon\'s approach'] | |
| } | |
| }, | |
| ecosystem: { | |
| title: 'Ecosystem & GenAI', | |
| seldon: { | |
| summary: 'Seldon provides a curated set of runtimes, primarily its own MLServer and NVIDIA Triton. It fully supports the standard Open Inference Protocol (OIP). Advanced Generative AI features, such as an OpenAI-compatible API, are available through a commercial "LLM Module" add-on.', | |
| points: ['Curated runtimes: MLServer & Triton', 'Supports Open Inference Protocol (OIP)', 'GenAI API is a commercial feature', 'Tight integration with Alibi Explain/Detect'] | |
| }, | |
| kserve: { | |
| summary: 'KServe offers a broader, pluggable ecosystem of runtimes (TFServing, TorchServe, etc.). Its strategic focus is on GenAI, offering native, out-of-the-box support for an OpenAI-compatible API. This makes it ideal for integrating with tools like LangChain and LlamaIndex.', | |
| points: ['Pluggable runtime ecosystem', 'Supports Open Inference Protocol (OIP)', 'Native OpenAI-compatible API for LLMs', 'Strong community focus on GenAI'] | |
| } | |
| }, | |
| licensing: { | |
| title: 'Licensing & Business Model', | |
| seldon: { | |
| summary: 'Seldon Core 2 operates on an "open-core" model under the Business Source License (BSL). It is free for non-production use, but any production deployment legally requires a paid commercial license from Seldon Technologies. This provides a clear path for enterprise support.', | |
| points: ['Business Source License (BSL)', 'Requires paid license for production use', 'Vendor lock-in for production systems', 'Clear path to enterprise support & SLAs'] | |
| }, | |
| kserve: { | |
| summary: 'KServe is a true open-source project under the LF AI & Data Foundation, licensed under the permissive Apache 2.0 license. It is completely free to use in any environment, including production, with no restrictions. Support is community-driven.', | |
| points: ['Apache 2.0 License', '100% free for production use', 'No vendor lock-in', 'Vibrant, multi-vendor community support'] | |
| } | |
| } | |
| }, | |
| decisionFramework: { | |
| kserve: [ | |
| { icon: '💰', text: '<strong>Cost-effective serving</strong> of models with intermittent or bursty traffic is your top priority (via scale-to-zero).' }, | |
| { icon: '🤖', text: 'Your focus is on the <strong>Generative AI and LLM space</strong> and need an OpenAI-compatible API out-of-the-box.' }, | |
| { icon: '📜', text: 'You have a mandate for a <strong>100% open-source (Apache 2.0) stack</strong> and cannot use commercial licenses.' }, | |
| { icon: '🔗', text: 'Your inference logic fits common patterns like <strong>transformer -> predictor</strong>.' }, | |
| { icon: '🏗️', text: 'You are already committed to or planning to adopt <strong>Knative and Istio</strong> in your infrastructure.' } | |
| ], | |
| seldon: [ | |
| { icon: '🕸️', text: 'You need to build <strong>complex, multi-step inference pipelines (DAGs)</strong> with custom branching and joining logic.' }, | |
| { icon: '📊', text: '<strong>Deep, real-time observability</strong> and payload auditing for compliance or debugging are critical requirements.' }, | |
| { icon: '🎯', text: 'You want to implement advanced, learning-based rollouts like <strong>Multi-Armed Bandits</strong>.' }, | |
| { icon: '🚀', text: 'Your services run at <strong>high, sustained scale</strong> where resource density (MMS) is more important than scaling to zero.' }, | |
| { icon: '🏢', text: 'You operate in an enterprise environment where a <strong>commercial license and dedicated vendor support</strong> are required.' } | |
| ] | |
| } | |
| }; | |
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| let activeChart = null; | |
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| const contentContainer = document.getElementById('content-container'); | |
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| type: 'radar', | |
| data: appData.philosophy, | |
| options: { | |
| responsive: true, | |
| maintainAspectRatio: false, | |
| plugins: { | |
| legend: { | |
| position: 'top', | |
| }, | |
| }, | |
| scales: { | |
| r: { | |
| angleLines: { | |
| color: '#e7e5e4' // stone-200 | |
| }, | |
| grid: { | |
| color: '#e7e5e4' // stone-200 | |
| }, | |
| pointLabels: { | |
| font: { | |
| size: 12 | |
| }, | |
| color: '#57534e' // stone-600 | |
| }, | |
| ticks: { | |
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| stepSize: 1, | |
| max: 5, | |
| min: 0 | |
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| <div class="content-panel active" id="panel-${view}"> | |
| <h3 class="text-2xl font-bold text-center mb-6 text-stone-800">${viewData.title}</h3> | |
| <div class="grid md:grid-cols-2 gap-8"> | |
| <div class="border-l-4 seldon-border pl-4"> | |
| <h4 class="text-xl font-bold seldon-color mb-2">Seldon Core 2</h4> | |
| <p class="text-stone-600 mb-4">${viewData.seldon.summary}</p> | |
| <ul class="list-none space-y-2"> | |
| ${viewData.seldon.points.map(p => `<li class="flex items-start"><span class="seldon-color mr-2 mt-1">◆</span><span>${p}</span></li>`).join('')} | |
| </ul> | |
| </div> | |
| <div class="border-l-4 kserve-border pl-4"> | |
| <h4 class="text-xl font-bold kserve-color mb-2">KServe</h4> | |
| <p class="text-stone-600 mb-4">${viewData.kserve.summary}</p> | |
| <ul class="list-none space-y-2"> | |
| ${viewData.kserve.points.map(p => `<li class="flex items-start"><span class="kserve-color mr-2 mt-1">◆</span><span>${p}</span></li>`).join('')} | |
| </ul> | |
| </div> | |
| </div> | |
| </div> | |
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| function populateDecisionFramework() { | |
| const kserveList = document.getElementById('choose-kserve'); | |
| const seldonList = document.getElementById('choose-seldon'); | |
| appData.decisionFramework.kserve.forEach(item => { | |
| const li = document.createElement('li'); | |
| li.className = 'flex items-start'; | |
| li.innerHTML = `<span class="text-2xl mr-3">${item.icon}</span><span>${item.text}</span>`; | |
| kserveList.appendChild(li); | |
| }); | |
| appData.decisionFramework.seldon.forEach(item => { | |
| const li = document.createElement('li'); | |
| li.className = 'flex items-start'; | |
| li.innerHTML = `<span class="text-2xl mr-3">${item.icon}</span><span>${item.text}</span>`; | |
| seldonList.appendChild(li); | |
| }); | |
| } | |
| function init() { | |
| Object.keys(appData.deepDive).forEach(key => { | |
| const btn = document.createElement('button'); | |
| btn.className = 'nav-btn px-4 py-2 rounded-lg font-semibold bg-white shadow-sm text-stone-700 hover:bg-stone-50'; | |
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| btn.dataset.view = key; | |
| navContainer.appendChild(btn); | |
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| navContainer.addEventListener('click', handleNavClick); | |
| renderPhilosophyChart(); | |
| populateDecisionFramework(); | |
| updateNav(); | |
| updateContent(currentView); | |
| } | |
| init(); | |
| }); | |
| </script> | |
| </body> | |
| </html> |
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