updates

Author: ramkrishnsaini

BEDROCK_SAGEMAKER_BLOG_MANIFEST.md

@@ -0,0 +1,99 @@
+# Amazon Bedrock & SageMaker Blog Cluster — Content Manifest
+
+Purpose: an informational → technical → commercial funnel that ranks for AWS
+GenAI / ML long-tail queries and passes contextual authority to the existing
+Bedrock / SageMaker / AWS AI-ML **service** and **guide** pages, then to the
+WhatsApp / contact funnel.
+
+- Blog articles live in `content/blog-articles/{slug}/` (`meta.ts`, `Article.tsx`, `body.html`)
+  and are registered in `content/blog-articles/index.ts` (hand-edited, additive).
+- Slugs deliberately **omit** `job-support` / `job-help`, so canonical resolves to
+  `/blog/{slug}/` (see `lib/post-canonical.ts`) and they do **not** compete with the
+  commercial service pages that already own the `-job-support` phrases.
+- Every article: unique title/H1/slug, direct-answer intro, deep technical body,
+  FAQ (FAQPage JSON-LD via `meta.faqs`), `about` topic, internal links out, and a
+  WhatsApp/commercial CTA. Sitemap + Article/Breadcrumb schema are automatic.
+- Technical state aligned to repo-verified AWS through **August 2026**: Bedrock
+  AgentCore GA Oct 2025 (Policy/Cedar GA Mar 2026, Harness GA Jun 2026), Amazon Nova 2 GA,
+  SageMaker Unified Studio / Lakehouse / Catalog GA 2025, SageMaker AI (training,
+  HyperPod, JumpStart, Managed MLflow, Pipelines, Model Registry).
+
+## Cannibalization check
+
+No existing **blog** article targets Bedrock or SageMaker (the closest, `rag-aimlops-…-guide`,
+is generic RAG). The Bedrock/SageMaker **commercial** and **guide** pages exist but are
+different search intent (transactional / definitional) — blogs support them, not replace them.
+Result: **0 collisions**; all 12 = `create`.
+
+## Articles
+
+### Pillar A — Bedrock Job Support (informational / technical)
+1. `amazon-bedrock-production-architecture-2026`
+   - Title: Amazon Bedrock Production Architecture in 2026: RAG, AgentCore, Guardrails & Inference
+   - Intent: implementation/architecture · Target: `/amazon-bedrock-job-support/`
+   - Links: what-is-amazon-bedrock-guide, rag-guide, agentcore-architecture-guide, knowledge-bases, agentcore, guardrails, inference, production-support, hub
+2. `amazon-bedrock-rag-knowledge-bases-troubleshooting`
+   - Title: How to Build and Troubleshoot Amazon Bedrock RAG with Knowledge Bases
+   - Intent: implementation + troubleshooting · Target: `/amazon-bedrock-rag-job-support/`
+   - Links: rag-guide, knowledge-bases, rag-job-support, rag-troubleshooting, opensearch-vs-pgvector(blog), kb-vs-custom-rag
+3. `amazon-bedrock-agentcore-architecture-troubleshooting`
+   - Title: Amazon Bedrock AgentCore Architecture & Production Troubleshooting: Runtime, Memory, Gateway, Identity, Policy
+   - Intent: architecture/troubleshooting · Target: `/amazon-bedrock-agentcore-job-support/`
+   - Links: agentcore-architecture-guide, agentcore hub + subpages, agentcore-troubleshooting, interview-proxy
+
+### Pillar B — Bedrock Proxy Interview (educational prep)
+4. `amazon-bedrock-interview-questions-2026`
+   - Title: Amazon Bedrock Interview Questions: RAG, AgentCore, Guardrails & Production Scenarios (2026)
+   - Intent: interview · Target: `/amazon-bedrock-interview-proxy-support/`
+   - Links: how-to-explain-aws-ai-project-in-interview-guide, bedrock-interview-proxy, agentcore-interview-proxy, aws-ai-ml-interview-support
+5. `how-to-explain-amazon-bedrock-project-in-interview`
+   - Title: How to Explain an Amazon Bedrock Project in a Technical Interview
+   - Intent: interview · Target: `/amazon-bedrock-interview-proxy-support/`
+   - Links: how-to-explain-aws-ai-project-in-interview-guide, bedrock-interview-proxy, aws-ai-ml-interview-support
+
+### Pillar C — SageMaker Job Support (informational / technical)
+6. `amazon-sagemaker-production-architecture-2026`
+   - Title: Amazon SageMaker AI Production Architecture in 2026: Training, MLOps & Inference
+   - Intent: architecture · Target: `/amazon-sagemaker-ai-job-support/`
+   - Links: sagemaker-mlops-guide, sagemaker-job-support, ai-inference, pipelines, mlflow, model-registry, mlops
+7. `amazon-sagemaker-mlops-pipelines-mlflow-model-registry`
+   - Title: Amazon SageMaker MLOps Architecture: Pipelines, MLflow & Model Registry in Production
+   - Intent: implementation · Target: `/amazon-sagemaker-mlflow-job-support/` + pipelines + model-registry + aws-mlops
+   - Links: sagemaker-mlops-guide, pipelines, mlflow, model-registry, aws-mlops, sagemaker-ai
+8. `amazon-sagemaker-inference-troubleshooting-guide`
+   - Title: Amazon SageMaker Inference Troubleshooting: Endpoint, GPU, Latency & Autoscaling Issues
+   - Intent: troubleshooting · Target: `/amazon-sagemaker-inference-troubleshooting-support/`
+   - Links: ai-inference, inference-troubleshooting, sagemaker-ai, sagemaker-job-support
+
+### Pillar D — SageMaker Proxy Interview (educational prep)
+9. `amazon-sagemaker-interview-questions-2026`
+   - Title: Amazon SageMaker Interview Questions: Training, Inference, MLflow, Pipelines & MLOps (2026)
+   - Intent: interview · Target: `/amazon-sagemaker-interview-proxy-support/`
+   - Links: sagemaker-interview-proxy, aws-ai-ml-interview-support, sagemaker-mlops-guide
+10. `how-to-explain-sagemaker-mlops-project-in-interview`
+    - Title: How to Explain a SageMaker MLOps Project in an AWS ML Interview
+    - Intent: interview · Target: `/amazon-sagemaker-interview-proxy-support/`
+    - Links: how-to-explain-aws-ai-project-in-interview-guide, sagemaker-interview-proxy, aws-ai-ml-interview-support
+
+### P1 — Cross / comparison (decision-stage)
+11. `amazon-bedrock-vs-sagemaker-ai-architecture-guide`
+    - Title: Amazon Bedrock vs SageMaker AI: Architecture, Use Cases & Interview Decisions
+    - Intent: comparison/decision (informational — NOT the commercial `-job-support` compare page)
+    - Target: `/amazon-bedrock-job-support/` + `/amazon-sagemaker-ai-job-support/`
+12. `opensearch-vs-pgvector-bedrock-rag-guide`
+    - Title: OpenSearch vs pgvector for Amazon Bedrock RAG: Choosing a Vector Store
+    - Intent: comparison/decision (informational) · Target: `/amazon-bedrock-knowledge-bases-job-support/`
+
+## Reverse links (service/guide → blog) — additive to `relatedLinks.additionalLinks`
+- `amazon-bedrock-job-support` → article 1
+- `amazon-bedrock-rag-job-support` + `amazon-bedrock-knowledge-bases-job-support` → article 2
+- `amazon-bedrock-agentcore-job-support` → article 3
+- `amazon-bedrock-interview-proxy-support` → article 4
+- `amazon-sagemaker-ai-job-support` → article 6
+- `amazon-sagemaker-mlflow-job-support` / `aws-mlops-job-support` → article 7
+- `amazon-sagemaker-ai-inference-job-support` / `amazon-sagemaker-inference-troubleshooting-support` → article 8
+- `amazon-sagemaker-interview-proxy-support` → article 9
+
+## Zero-orphan guarantee
+Each article receives inbound links from (1) blog index/category, (2) ≥1 service page
+(reverse link above), (3) sibling articles in its pillar. Orphan target = 0.

app/blog/page.tsx

@@ -83,6 +83,46 @@ export default async function BlogPage() {
           />
         </div>
 
+        {/* Featured cluster: AWS AI/ML — Amazon Bedrock & SageMaker */}
+        <section className="card" style={{ padding: '1.5rem', marginBottom: '2.5rem' }}>
+          <h2 style={{ fontSize: '1.15rem', fontWeight: 700, color: 'var(--pts-text)', marginBottom: '0.35rem' }}>
+            AWS AI/ML — Amazon Bedrock &amp; SageMaker
+          </h2>
+          <p style={{ fontSize: '0.9rem', color: 'var(--pts-text-muted)', marginBottom: '1rem', lineHeight: 1.6 }}>
+            Deep technical guides on Amazon Bedrock, RAG and AgentCore, and Amazon SageMaker training,
+            MLOps and inference — plus interview preparation for AWS GenAI and ML engineer roles.
+          </p>
+          <div style={{ display: 'flex', flexWrap: 'wrap', gap: '0.5rem' }}>
+            {[
+              { label: 'Bedrock production architecture', href: '/blog/amazon-bedrock-production-architecture-2026/' },
+              { label: 'Build & troubleshoot Bedrock RAG', href: '/blog/amazon-bedrock-rag-knowledge-bases-troubleshooting/' },
+              { label: 'AgentCore architecture & troubleshooting', href: '/blog/amazon-bedrock-agentcore-architecture-troubleshooting/' },
+              { label: 'Bedrock interview questions', href: '/blog/amazon-bedrock-interview-questions-2026/' },
+              { label: 'Explain a Bedrock project in an interview', href: '/blog/how-to-explain-amazon-bedrock-project-in-interview/' },
+              { label: 'SageMaker production architecture', href: '/blog/amazon-sagemaker-production-architecture-2026/' },
+              { label: 'SageMaker MLOps: Pipelines, MLflow & Registry', href: '/blog/amazon-sagemaker-mlops-pipelines-mlflow-model-registry/' },
+              { label: 'SageMaker inference troubleshooting', href: '/blog/amazon-sagemaker-inference-troubleshooting-guide/' },
+              { label: 'SageMaker interview questions', href: '/blog/amazon-sagemaker-interview-questions-2026/' },
+              { label: 'Explain a SageMaker MLOps project', href: '/blog/how-to-explain-sagemaker-mlops-project-in-interview/' },
+              { label: 'Bedrock vs SageMaker AI', href: '/blog/amazon-bedrock-vs-sagemaker-ai-architecture-guide/' },
+              { label: 'OpenSearch vs pgvector for RAG', href: '/blog/opensearch-vs-pgvector-bedrock-rag-guide/' },
+            ].map((item) => (
+              <Link
+                key={item.href}
+                href={item.href}
+                style={{ fontSize: '0.82rem', color: 'var(--pts-forest)', textDecoration: 'none', fontWeight: 600, border: '1px solid var(--pts-border)', borderRadius: '6px', padding: '0.35rem 0.7rem', background: 'var(--pts-card-bg)' }}
+              >
+                {item.label}
+              </Link>
+            ))}
+          </div>
+          <div style={{ marginTop: '1rem', fontSize: '0.85rem' }}>
+            <Link href="/aws-ai-ml-job-support/" style={{ color: 'var(--pts-accent)', fontWeight: 600 }}>
+              AWS AI/ML job support hub →
+            </Link>
+          </div>
+        </section>
+
         <div style={{ display: 'flex', flexDirection: 'column', gap: '1.5rem' }}>
           {posts.map((post) => {
             const href = getPostUrl(post);

app/globals.css

@@ -444,3 +444,31 @@ a:hover {
   color: var(--pts-text-muted);
   padding: 0;
 }
+
+.post-content table {
+  width: 100%;
+  border-collapse: collapse;
+  margin: 1.25rem 0;
+  font-size: 0.9rem;
+  display: block;
+  overflow-x: auto;
+}
+
+.post-content th,
+.post-content td {
+  border: 1px solid var(--pts-border);
+  padding: 0.55rem 0.7rem;
+  text-align: left;
+  vertical-align: top;
+  color: var(--pts-text-muted);
+}
+
+.post-content th {
+  background: var(--pts-tech-header);
+  color: var(--pts-text);
+  font-weight: 700;
+}
+
+.post-content tbody tr:nth-child(even) td {
+  background: rgba(0, 223, 130, 0.04);
+}