AWS Partner Network (APN) Blog

Tag: Intermediate (200)

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How Public AI delivers sovereign LLM inference on AWS and Intel

Open-weight large language models are being released by research institutions worldwide, but turning published weights into production inference services remains a challenge—especially under strict data residency requirements. This post shows how Public AI built a scalable inference platform on Amazon EKS and Intel-powered Amazon EC2 instances to serve Switzerland’s Apertus model family, and why this architecture provides a repeatable blueprint for sovereign LLM initiatives.

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Unified Secrets Security with GitGuardian and AWS Secrets Manager

AI coding assistants and MCP servers have made development faster, but they’ve also made secrets exposure harder to catch. Developers share credentials through config files, Git repos, and CI/CD logs without realizing it. This post walks through how GitGuardian integrates with AWS Secrets Manager to give security teams full visibility across the secrets lifecycle: detecting when vaulted credentials show up in code, finding duplicate secrets scattered across multi-account architectures, and putting continuous governance policies in place so secrets management becomes proactive rather than reactive. We cover a phased implementation roadmap, from initial deployment through automated monitoring, that helps you build a secrets security strategy that grows with your organization.

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Automate compliance session review with Teleport and Amazon Bedrock

Organizations accumulate thousands of hours of session recordings that satisfy compliance mandates but rarely get reviewed. Learn how Teleport and Amazon Bedrock replace manual playback with AI-powered summarization, risk classification, and SIEM-ready alerts—keeping session data within your AWS environment.

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Hybrid cloud from data gravity to business agility with Cloudera on AWS

Discover how hybrid elasticity introduces a zero-migration data access model that decouples data residency from compute elasticity, enabling enterprises to transform existing data centers into dynamic hybrid data hubs with on-demand cloud scale without moving data.

Generative AI using TiDB and Amazon Bedrock

Generative AI using TiDB and Amazon Bedrock

What if one database could handle transactions, analytics, and semantic vector search for your AI agents—all without managing separate systems? TiDB Cloud on AWS, integrated with Amazon Bedrock, delivers a unified, serverless architecture purpose-built for the demands of autonomous AI. In this post, PingCAP and AWS walk you through the reference architecture, real-world use cases, and the key design decisions to make your generative AI applications production ready using the TiDB console.

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Simplify multi-account log ingestion to Splunk

Amazon CloudWatch Logs centralization offers AWS partners and customers a streamlined alternative to complex, per-account log aggregation pipelines — consolidating logs from across multiple AWS accounts and regions into a single ingestion point for Splunk. By integrating natively with AWS Organizations, the solution automatically onboards new accounts and log groups, reducing operational overhead and total cost of ownership while preserving security boundaries and full data lineage.

Architecting agentic AI for scale and trust from the start

The race to deploy AI agents is accelerating — and the organizations pulling ahead are those that build trust from day one. In this joint blog, PwC Australia and AWS deliver a practical blueprint for deploying AI agents safely at scale, answering the three critical questions your board will ask. Governance, observability, and auditability aren’t constraints on speed — they’re your competitive advantage.

How SAS Viya Workbench on AWS accelerated analytics innovation

SAS Viya Workbench on AWS provides a unified cloud environment for Python, R, and SAS, letting teams focus on building models instead of managing infrastructure. Its split-plane architecture keeps your data securely within your AWS account while SAS handles orchestration. With elastic scalability, pre-configured environments, and built-in collaboration, teams can accelerate analytics innovation from day one.

Build a secure, scalable deployment pipeline with CircleCI’s AWS Deployment Pipeline Reference Architecture implementation

Modern software teams no longer need to choose between deployment speed and security. CircleCI’s implementation of the AWS Deployment Pipeline Reference Architecture demonstrates how to build enterprise-grade deployment pipelines that deliver 50% faster deployments while reducing security vulnerabilities by 85%. This reference implementation combines the robust cloud infrastructure of AWS with the flexible CI/CD platform of CircleCI, providing a ready-to-fork blueprint that organizations can customize and deploy in an afternoon.

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MoneySuperMarket’s AI leap with Firemind and AWS

MoneySuperMarket found that searching for the right credit card is often overwhelming for customers. In partnership with Firemind and AWS, they built Money Concierge, an AI-powered assistant that provides personalized suggestions in natural language, in only 6 months. The solution has helped over 55,000 customers in their credit card journey achieving 93% positive feedback.