Cloud Events & Education

SAP TechEd

Esri IMGIS

Every dashboard, every alert, every 3 a.m. page begins as a few hundred bits of truth emitted by your code. In this hands-on hour we follow one OpenTelemetry metric observation end to end: the moment an app records it, its OTLP journey into the new CloudWatch OTel metric store, querying it back with PromQL, and — when an incident strikes — handing it to the Amazon DevOps Agent to pinpoint root cause. You'll take away a repeatable pattern for OTel-native observability on AWS.

Learning Objectives:

• Configure and enable AWS Transform
• Configure an AWS Transform workspace for VMware
• Assess VMware workloads for migration
• Create and execute transformation plans
• Validate migrated resources

Target audience:

Developers, architects, and cloud engineers who intend to apply AWS Transform transformation capabilities in real-life situations to accelerate migration and modernization goals.

Prerequisites:

• Amazon Virtual Private Cloud (Amazon VPC) and Networking
• AWS Identity and Access Management (IAM)
• AWS Application Migration Service (MGN)
• VMware environments (RVTools)

This workshop is level 300. Basic knowledge of Windows and Linux operating systems, VMware RVTools structure, data ingestion, network migration and wave plan leveraging AWS Application Migration Service is required.

Align your data foundation to power practical, real-time AI outcomes.

Discover AI capabilities that work, scale and deliver real growth for every business. Online

AI isn't coming to education, it's already reshaping how institutions teach, research, and operate. The question isn't whether to act, but how to move from scattered experiments to institutional transformation. 

Imagine Education: Intelligence in Action brings together Australia's most senior higher-education, TAFE, K–12 and EdTech leaders for an exclusive half-day of real-world case studies, strategic conversation, and hands-on methodology — all hosted at AWS Sydney by Kim Majerus, Vice-President, Global Education and Local Government, AWS. 

Be among the first in ANZ to witness the official launch of Kiro for Students — our AI-powered development environment designed to help the next generation of builders learn by doing. This is your first look at how we're putting AI directly into the hands of the students who will shape what comes next. 

It's also where the institutions already deploying AI at scale share the playbook — the architecture decisions, the governance models, the culture shifts — so you can compress years of trial-and-error into an afternoon. 

Who Should Attend 

• Senior Academic & Digital Leaders — DVCs Academic, PVCs Teaching & Learning, PVCs Digital Futures, CIOs/CTOs 
• Research Leaders — Research Directors, Research Computing leads, HDR supervisors, and academics leading large-scale data/AI research 
• Learning & Teaching Innovators — Directors of Learning & Teaching, Learning Designers, Academic Developers, Heads of School, and K–12 teachers experimenting with AI in curriculum, assessment, and student support 
• EdTech Founders & Leaders — CEOs, CTOs, and Product leaders at education technology companies building AI-powered tools for teaching, learning, and student success

"Design smarter AI workflows with visual orchestration, token optimization and extensible agent capabilities.

Cybersecurity threats are evolving faster than ever — and the cost of falling behind is growing. Whether you're just starting your cloud journey or looking to strengthen your existing security posture, this webinar gives you a practical, no-fluff look at what's happening in today's threat landscape, what risks to prioritize, and how AWS can help you stay one step ahead.

You'll walk away with a clearer understanding of the security foundations every organization needs, hands-on exposure to tools that can identify vulnerabilities before attackers do, and a first look at how AI-powered security agents are changing the way teams detect and respond to threats — in real time, and across any environment.

Who should attend?:

This session is for anyone responsible for protecting their organization's digital infrastructure — from CISOs and security leaders shaping cloud security strategy, to security engineers and analysts on the front lines of threat detection, to cloud architects and DevOps engineers building and securing infrastructure day to day. Finance & IT decision-makers evaluating IT security strategies will also find this session highly valuable.

Not on AWS yet? The AWS Security Agent is designed to help organizations detect and respond to threats across their environments — even if your workloads are not running on AWS. Whether you're on-premises, multi-cloud, or hybrid, this session will show you how AWS security intelligence can work for you.

What we'll cover:

• Security on the Cloud — understand the shared responsibility model and the foundations of building a secure cloud environment on AWS.
• AWS Security Assessment Tool — discover how to proactively identify security gaps, misconfigurations, and compliance risks across your AWS workloads.
• AWS Security Agent — see how intelligent, automated agents can help detect threats in real time and streamline incident response.

Seats are limited — register now.

LLMは次々と新しいものが登場し、最適な選択をするために世の中の動向をキャッチアップするだけでも一苦労です。また、性能だけでなく推論場所や推論内容の保存場所などの要件も関係するため、最適なLLMの選択は専門性が要求される高度なタスクとなっています。

本セッションでは、Amazon Bedrock経由でのLLM利用に関する基本としてのデータの処理や保存に関して解説し、技術的要件に応じてどのように最適なLLMを選択すればいいのかを紹介します。技術的要件の整理や公開情報に基づくモデル選択のアプローチについて深掘りします。ぜひこの機会にAmazon Bedrockが提供する豊富な選択肢から最適なLLMを選ぶ方法論について理解を深めていただければ幸いです。

【このような方におすすめ】

・数あるLLMの中から最適なものを選ぶ方法論を理解したい方

・LLM選定に関して重要になる観点について理解したい方

・Amazon BedrockにおけるLLMの処理について興味がある方

GenAI is transforming how teams operate in the Media & Entertainment (M&E) industry. Join AWS SMEs for a full-day hybrid event exploring AI-driven operations on AWS for M&E workloads — live in-person at our Del-24 office in Gurugram, with a parallel virtual track for teams across India and APJC.

We'll open with the AWS Support vision for AI-enabled M&E operations and explore the AI revolution in MEGS — including a behind-the-scenes look at how Prime Video reinvented live operations with AI (“The Invisible Orchestra”). This is followed by three hands-on workshops: (1) AI-Powered Troubleshooting for Media Workflows leveraging AWS DevOps Agent — turning manual troubleshooting across MediaLive, MediaPackage, and CloudFront into AI-powered autonomous investigation; (2) AI-Powered Live Video for Social and Mobile with AWS Elemental Inference; and (3) FAST Channel Personalization — a serverless, event-driven platform delivering personalized linear streaming with targeted ad insertion using Amazon Bedrock, AWS MediaTailor, and AWS MediaConvert. 

 💻 Bring your laptop! The afternoon hands-on sessions are fully interactive — you will need your own laptop to participate.

Key Takeaways

•     A clear understanding of how agentic AI is reshaping operations for Media & Entertainment workloads on AWS
•     Practical knowledge of the AWS DevOps Agent and Frontier Agents — from capabilities to enterprise deployment
•     Hands-on experience applying agentic operations through interactive workshops and real-world MNE scenarios
•     Direct access to AWS experts and principal technologists for discussions about your operational challenges

Who Should Attend

This event is designed for:

•     Practitioners & Architects — SRE, DevOps, Platform, and Cloud engineers and architects who build and operate systems for MNE workflows
•     Technical Leaders — VPs, Directors, and Managers driving operational strategy and AI adoption across their organizations for MNE Customers

Whether you are hands-on-keyboard or setting the roadmap, you will leave with practical approaches for adopting agentic operations.

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

"**세션 소개** AI 에이전트가 점점 더 큰 코드베이스와 복잡한 시스템에서 활용되면서, 비주얼 오케스트레이션과 효율적인 컨텍스트 관리는 현대적인 개발 환경에서 더욱 중요해지고 있습니다. 이 세션에서는 GitHub Copilot 앱의 Canvases, 컨텍스트 엔지니어링, 확장 가능한 에이전트 기능을 활용해 토큰을 최적화한 더욱 스마트한 A

Get started with GenAI observability – Set up foundational observability for your GenAI workloads by understanding what telemetry is automatically available for your Bedrock and AgentCore applications and how to access it without manual instrumentation.

Learn how to visualize evaluation metrics – Track and visualize evaluation metrics so you can confidently assess whether your agents are meeting production standards.

Learn how to integrate CloudWatch Application Signals – Gain end-to-end visibility across your application stack by integrating with CloudWatch Application Signals for Application Performance Monitoring.

Related Services

• Amazon Bedrock
• Amazon Bedrock AgentCore
• Amazon CloudWatch GenAI observability (Model/agent observability, evaluations)
• Amazon CloudWatch Application Signals

A Halloween night of code, canapés & good company — in honour of our builder community

Builders, this one's for you. 🕹️

Crawl out of your IDE and join us this Halloween for a devilishly good evening celebrating the tech community that keeps things shipping. Come see spec-driven, agentic development in action with Kiro — and see how it's changing the way software actually gets built. No tricks, all treats. 🍬

On the cards:

• 👻 Live Kiro demos — real code, built in front of you, no smoke and mirrors
• 🧑‍💻 A panel of financial services builders sharing how they're using Kiro for AI-DLC inside their orgs
• 🍕 Food & drinks in a spooky setting — fuel for the night (costumes optional, enthusiasm mandatory)
• 🎁 Door gifts — because every good party has loot
• 🎤 Guest speakers who've been in the trenches doing the work you do
• 🚀 The launch of the Melbourne Kiro User Group — meet your people 

Meet the builders doing the same work you are, swap war stories over a drink, and have a genuinely good time.

No tricks. All treats. All builders welcome. 🧛

Create a dashboard in just one day and learn the art of analyzing your data in a rich and compelling manner.

"セッションの紹介 AIエージェントの活用が大規模化・高度化する中、効率的なコンテキスト管理とビジュアルオーケストレーションは、次世代のAI開発を支える重要な要素となっています。 本セッションでは、GitHub CopilotのCanvases、コンテキストエンジニアリング、拡張可能なエージェント機能を活用し、よりスマートで効率的なAIワークフローを構築する方法をご紹介します。

"AI Agent 需要處理的程式碼庫規模愈來愈大、系統也日益複雜，因此視覺化編排與高效率的情境管理，已成為現代開發不可或缺的一環。 在本場次中，您將了解如何運用 GitHub Copilot app 中的 Canvases、情境工程與可擴充的 Agent 功能，設計更聰明且經過 Token 最佳化的 AI 工作流程。透過實際示範，您將看到開發者如何協調 multi-agent 協

"**课程介绍** 随着 AI Agent 开始处理更大规模的代码库和日益复杂的系统，可视化编排和高效的上下文管理正成为现代开发过程中不可或缺的能力。 在本场课程中，你将了解如何利用 GitHub Copilot app 中的 Canvases、上下文工程以及可扩展的 Agent 能力，设计更智能且经过 Token 优化的 AI 工作流。 通过实际演示，你将看到开发者如何协

Erstellen Sie ein Dashboard an nur einem Tag, und erfahren Sie, wie Sie Ihre Daten auf umfassende und überzeugende Weise analysieren.

Dieses praxisnahe Training richtet sich an erf. Power BI Data Analysts die erstmals mit Microsoft Fabric arbeiten und vermittelt Grundlagen zur Datenkonsolidierung und wertvollen Erkenntnissen.

Denne praktiske workshop, der er skræddersyet til Power BI-dataanalytikere, lærer dig at gøre modeller klar til chat, låse op for indsigt med naturligt sprog og optimere data til Copilot.

Novidades do FabCon, agora em Portugal!

Create a dashboard in just one day and learn the art of analyzing your data in a rich and compelling manner.

A look at how AI is changing the two most friction heavy stages of the workflow.

Tailored for Power BI Data Analysts, this hands-on workshop teaches you to make models chat-ready, unlock insights with natural language, and optimize data for Copilot.

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

Join us for an immersive technical workshop: Implement a Lakehouse with Microsoft Fabric to gain hands-on experience implementing a modern data lakehouse architecture using Microsoft Fabric.

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

Cree un panel de información en tan solo un día y aprenda el arte de analizar sus datos de forma enriquecida y atractiva.

Learn practical prompt engineering techniques and discover how to work effectively with Microsoft Copilot. This session features real-world examples that will help participants achieve more accu

Tailored for Power BI Data Analysts, this hands-on workshop teaches you to make models chat-ready, unlock insights with natural language, and optimize data for Copilot.

"Go hands-on with WorkIQ Developer Tools as we walk through building your first Copilot plugin, from setup to a working extension.

"What does it take to build a cloud-native platform foundation for modern applications and AI workloads? Join us to explore Azure Red Hat OpenShift (ARO) and the role of open-source Kubernetes

Aprende técnicas prácticas de ingeniería de prompts y descubre cómo trabajar eficazmente con Microsoft Copilot.

Tailored for Power BI Data Analysts, this hands-on workshop teaches you to make models chat-ready, unlock insights with natural language, and optimize data for Copilot.

AI agents are moving into production, and the applications they run alongside are more distributed than ever. Traditional monitoring wasn't built for either. Amazon CloudWatch Omni, the next generation of Amazon CloudWatch, is an AI-first observability experience that gives you unified observability for your AI agents and applications in one place. Built on open standards and delivered outside the AWS Management Console as a standalone web experience and an IDE extension, Omni brings the interoperability of open standards together with the trusted foundation and scale of AWS.

Join this technical session for a walkthrough of how Omni helps you observe, troubleshoot, and improve agents and applications together, from a single trace to root cause across your full stack.

In this introductory webinar, you will get a high-level overview of:

• Observing applications and AI agents in one place: replacing fragmented tooling with a unified experience across logs, traces, and agent telemetry
• Evaluating and iterating on AI agents: from diagnosing issues to comparing models and prompts, in your IDE or the web UI
• Querying and investigating with AI: using natural language to explore your telemetry and AI-assisted investigations to troubleshoot faster
• Getting started with CloudWatch Omni: setting up your space and enabling access for your teams

Red Hat Summit Connect- Tokyo

What is Partner Central Agent Day (PCAD)?

The Partner Central Agents Day (PCAD) is a one-day, in-person enablement event designed to help AWS Partners unlock the full potential of Partner Central Agents for co-selling. Hosted across key APJ markets, PCAD brings together partner sales, alliance, and technical teams for hands-on learning, live demos, and guided implementation so you walk away with agents running in your environment and a clear plan to accelerate your co-sell motion with AWS. 

Why Attend?

Partner Central Agents are transforming how partners co-sell with AWS. PCAD gives you the dedicated time and expert support to activate these capabilities against your real pipeline, not hypothetical scenarios. 

Enhance Your Sales Team with Agents

• Partner Central agents available to manage joint pipeline where your team works 
• Account intelligence is designed to surface at the right moment to accelerate the sales cycle 
• Automated sales play generation customized by account 

Same-Day Integration

• Complete MCP integration 
• Validate data flows 
• Activate agents in your sandbox environment 
• No CRM integration required 

Walk Away with Your Adoption Plan

• Early access to the Partner Central AI roadmap 
• Self-service activation kits to activate your use cases 
• 90-day adoption plan to help you scale agentic adoption across your teams 

Who Should Attend?

PCAD is open to partner organizations who have completed their Partner Central 3.0 migration. This is a mandatory pre-requisite, as Agent capabilities are only accessible after migration. If your organization hasn't migrated yet, please complete migration before registering. To ensure your organization can capitalize on this event and achieves same-day implementation, please ensure the following individuals from your organization attend: 

[Required] Business Persona with Partner Central Administrator access (e.g. Alliance Lead)— This individual will configure workflow automation and activate agentic integrations within your workflows. 

[Required] Technical Persona with access to manage and deploy in your Partner Central Sandbox environment and your AWS Account — This individual will work directly with AWS engineers to complete agent deployment and validate data flows in real time. 

[Optional] Technical Persona(s) with access to manage in-house tools – If you want to integrate internal tools (e.g. CRM, Slack, Marketo etc) with Partner Central agents and tools, this individual will work with our AWS team to configure and deploy these integrations. 

Every team is building AI agents. Far fewer can answer the questions that come right after the demo: What is the agent allowed to do? Who did it act for? Where does the code it writes actually run, and what can that code reach? This workshop is about closing that gap on Kubernetes, using the same open standards and open-source projects you can take home: an AI gateway in front of LLM models, an MCP gateway for tools, end-to-end tracing, microVMs for sandboxing, and identity-aware authorization at every hop.

What You'll Learn:

• Build agents with an open-source agent SDK and run them as standard Kubernetes workloads
• Route model traffic through an AI gateway, so agents get model access without ever holding credentials
• Run coding agents such as Claude Code as workloads on your cluster
• Trace every prompt, tool call, token, and dollar with observability tooling hosted on EKS
• Give agents tools safely through an MCP gateway instead of direct connections
• Execute untrusted, model-written code in air-gapped microVM sandboxes, vended in seconds from warm pools
• Establish agent identity: propagate the user's identity to every tool call and enforce per-tool authorization at the gateway

By the end, you will know how to take an agent from a promising prototype to a governed, observable, production-ready workload, and you will have a reference architecture built entirely from open source and AWS services you already run.

Drive breakthrough impact with the latest AI tools for work. Get the practical strategies you need to create, deploy, govern, and manage AI agents.  This webinar is ideal for: business leader, strategist, or IT professional focused on turning AI potential into tangible workplace results.

Learn how AI-assisted assessments automate cloud TCO modeling, eliminate mapping errors, and generate CFO-ready business cases in minutes.  This webinar is ideal for: anyone involved in IT infrastructure, architecture or operations planning. *Special learning offer: receive 300 free credits to access Google Skills labs and earn Skills Badges upon completion.

For CDOs, CTOs and CIOs: unify and govern your data estate to scale AI with trust and control.

「似たエージェントを別の部署でも作っていた」「使い方は作った人に聞かないとわからない」。各部署で AI 活用が進む一方、エージェントの存在や用途が共有されず、重複開発や利用の属人化が起きていませんか。

本セッションでは、AWS Agent Registry を題材に、エージェントや MCP サーバー、スキルを一元管理し、検索を通じて組織内での発見・再利用につなげる考え方をご紹介します。管理者・開発者・利用者それぞれの役割と、登録した情報を公開する前に管理者の承認を組み込むフローを解説します。さらに、アクセス制御の基本にも触れ、組織としてエージェントの共有と管理を進めるためのポイントを整理します。

Join us for a 60-minute live session exploring how AWS DevOps Agent and CloudWatch Database Insights can work together to fundamentally shift your database operations from reactive incident response to proactive, automated management.

Through real-time demonstrations against various RDS and Aurora workloads, you'll walk away with practical knowledge for detecting performance anomalies early, diagnosing root causes faster, and automating common remediation steps.

What you'll learn:

• Build custom DevOps Agent skills that can detect and offer remediation for database issues such as runaway queries, connection saturation, and query degradation.
• Use Database Insights to trace performance issues down to individual queries, execution plans, and lock contention patterns with DevOps Agent.
• Use CloudWatch alarms to automatically trigger DevOps Agent skills in order to decrease MTTR

Session Highlights:

• Live incident simulation: Watch a real Aurora PostgreSQL performance degradation unfold, get diagnosed, and get resolved end-to-end
• Custom skill demo: See DevOps Agent execute and diagnose RDS/Aurora database issues in real time

Target Audience:

DBAs, SREs, DevOps engineers, and platform teams who manage production databases on AWS. Basic familiarity with Amazon RDS or Aurora is helpful but not required.

Join the Microsoft Fabric Roadshow in Bengaluru to discover the latest innovations, hear from Data & AI experts, connect with peers, and accelerate your journey toward AI transformation.

イベント概要:

AIコーディングツールの進化により、「業務改善」はもう情シスやエンジニアに依頼するだけのものではなくなりました。 

本ワークショップでは、AI コーディングツール初学者向けに、Claude Cowork を実際に触りながら、エクセル集計、見積もり作成、リサーチ、パワーポイント作成といった日常業務を自分の手で効率化する体験をしていただきます。後半では、自社の課題をAIで調査し、解決のためのアプリを実際に作って発表するところまで行います。

※複数名でご来場の場合は、お一人ずつお申込みをお願いします。

※定員制となりますので、満員になりましたら申し込みを終了させていただきます。

こんな方におすすめです:

営業・企画・経理・総務・人事など、日々の業務を効率化したい方

経営層・マネジメント層（AI活用の可能性を自ら体感したい方）

IT部門・情報システム部門の担当者（開発者以外も含む）

事業部門の業務改善・DX推進担当者

AI Coding（Claude Cowork）を導入済み、または検討中のお客様

当ワークショップで得られること:

AIコーディングツール（Claude Cowork）の実践的な使い方をハンズオン形式で体験できる

業務レベルのお悩みを持ち込み、当日AIに依頼してアプリを開発する体験ができる

開発部門だけでなく事業部門の課題解決にAIコーディングをどう活かすか学べる

AWSの社員による直接サポートを受けながら取り組める

アジェンダ:

2026年 10月 29日 (木) 13:40- 17:00 ※開場は13:00-（お早目のご来場をお願いいたします） 

13:40 - 13:45 オープニング

13:45 - 14:10 座学

14:10 - 15:00 ハンズオン

15:00 - 15:15 休憩

15:15 - 16:15 アプリ作成〜発表

16:15 - 17:00 懇親会

お願い:

ワークショップはハンズオン形式となっており、ご自身のPCをお持ち込みいただいてのご参加となります。

Claude Coworkが利用可能な状態にセットアップを完了いただいたうえでお越しください。

恐れ入りますが、セットアップが完了していない場合はハンズオンにご参加いただけませんので、あらかじめご了承ください。

セットアップは以下のブログ記事をご参考いただけますと幸いです。

Claude Cowork セットアップガイド  

A Halloween night of code, canapés & good company — in honour of our builder community

Builders, this one's for you. 🕹️

Crawl out of your IDE and join us this Halloween for a devilishly good evening celebrating the tech community that keeps things shipping. Come see spec-driven, agentic development in action with Kiro — and see how it's changing the way software actually gets built. No tricks, all treats. 🍬

On the cards:

• 👻 Live Kiro demos — real code, built in front of you, no smoke and mirrors
• 🧑‍💻 A panel of financial services builders sharing how they're using Kiro for AI-DLC inside their orgs
• 🍕 Food & Drinks in a spooky setting — fuel for the night (costumes optional, enthusiasm mandatory)
• 🎁 Door gifts — because every good party has loot
• 🎤 Guest speakers who've been in the trenches doing the work you do
• 🚀 The launch of the Melbourne Kiro User Group — meet your people 

Meet the builders doing the same work you are, swap war stories over a drink, and have a genuinely good time.

No tricks. All treats. All builders welcome. 🧛

Erstellen Sie ein Dashboard an nur einem Tag, und erfahren Sie, wie Sie Ihre Daten auf umfassende und überzeugende Weise analysieren.

Pensato per analisti Power BI esperti senza conoscenza di Microsoft Fabric, questo corso pratico presenta gli elementi essenziali per consolidare i dati e scoprire informazioni utili chiave bas.

Tailored for SQL developers and DBAs, this hands-on workshop teaches how to build secure AI-powered apps using T‑SQL and trusted SQL data.

Tailored for Power BI Data Analysts, this hands-on workshop teaches you to make models chat-ready, unlock insights with natural language, and optimize data for Copilot.

Join us to explore how Microsoft Fabric, SQL, and AI innovations can help you unify your data estate, accelerate insights, and build an AI-ready enterprise.

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

Create a dashboard in just one day and learn the art of analyzing your data in a rich and compelling manner.

Red Hat Summit Connect- Mexico City

This free workshop will guide you through the end-to-end process of migrating Microsoft SQL Server databases to Azure SQL.

Explore the next evolution of AI through intelligent agents capable of reasoning, planning, automating, and collaborating with users. Participants will discover emerging use cases and opportunit

Technical Workshop: Unify a Trusted Data Estate for Your AI

"Learn how to create the semantic foundation that powers business-aware agents. In this session, we'll explore how ontologies in Fabric IQ model the entities, relationships, and concepts

What can you build with .NET and Microsoft Foundry? Let’s find out together! Join us for a series of practical explorations featuring new SDK capabilities, cool projects, and the latest Foundry

Explora la próxima evolución de la IA a través de agentes inteligentes capaces de razonar, planificar, automatizar y colaborar con los usuarios. L

只需一天时间即可创建仪表板，并学习如何以丰富、引人注目的方式分析数据。

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

Create a dashboard in just one day and learn the art of analyzing your data in a rich and compelling manner.

クラウドに移行したものの中身はリフトしたまま、あるいは、オンプレミスで長年のシステムをそのまま運用し続けている企業の皆さまに向けて、「移行のその後」を考えるイベントを 2026年10月30日（金）に AWS 大阪オフィスで開催いたします。 

システム企画から設計、開発、テストへと進む流れは、AI の時代になっても変わりません。変わったのは各工程の進め方です。既存コードの読み解きや実装は AI の支援で速くなりました。一方で、その変更を本番環境に出してよいかを判断する根拠、つまりテストは、今も多くを人の手に頼っています。 

全員共通のセッションでは、工程ごとに AI をどう組み合わせるかという全体像と、AI を活用したテスト効率化の一例をご紹介します。続いて役割別の 3 つのブレイクアウトセッションから 1 つをお選びいただき、ご自身の業務に持ち帰れる形で体験していただきます。 

■ こんな方におすすめです 

・クラウドに移行したけれど、アーキテクチャや運用は以前のまま手を入れられていない 

・オンプレミスの既存システムを長年そのまま使い続けている 

・テストの工数を理由に、パッチやバージョンアップを止めている 

・移行やモダナイゼーションでAI を活用したいが、最初の一歩が決まらない 

■注意事項

・ご参加いただくアジェンダによって、開始、終了時間が異なりますのでご注意ください

・ランチセッションにご参加の方全員に、お弁当をご用意します（アレルギー等に関するリクエストには恐縮ながら対応しておりません。ご了承お願いいたします）

・アジェンダは変更になる場合がございますので、あらかじめご了承ください

AI が応対するセルフサービスを作ろうとすると、思った以上に悩みどころがあります。AI に自由に話させると、意図しない回答をしないか心配になります。一方で、決められた手順だけで組むと、お客様のさまざまな言い回しに柔軟に応えられません。業務システムとの連携やテストまで考えると、最初の一歩をなかなか踏み出せない方も多いのではないでしょうか。 

Amazon Connect Customer の最新機能である agentic CX designer を使うと、AI ネイティブな顧客体験を画面上で簡単に設計できます。AI に任せる部分と決められた手順で確実に進める部分を組み合わせ、その場でテストしてから公開できます。

本セッションでは、agentic CX designer で AI が応対するセルフサービスを設計し、動かすまでの流れを、デモを交えてご紹介します。AI との通話内容に応じてお客様の画面が切り替わる最新機能 Live Sync もお見せします。「自社の窓口なら、ここから AI に任せられそう」と感じていただけるヒントを、30 分でお届けします。

コンタクトセンターやお問い合わせ窓口の改善に取り組んでいる方や、生成 AI を顧客接点で活用したいものの、何から始めればよいか迷っている方におすすめです。

Running ECS on EC2 but tired of managing the underlying infrastructure? In this hands-on workshop, you will deploy a containerized application using Amazon ECS Managed Instances, a compute option that gives you access to EC2 instance types while AWS handles provisioning, scaling, and patching. You will create a Managed Instances capacity provider, configure memory-optimized compute, attach persistent storage, and set up intelligent resource optimization with auto-scaling and workload consolidation. You get your own AWS account for two hours, with AWS container experts available to help throughout.

Create a dashboard in just one day and learn the art of analyzing your data in a rich and compelling manner.

Tailored for Power BI Data Analysts, this hands-on workshop teaches you to make models chat-ready, unlock insights with natural language, and optimize data for Copilot.

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

Tailored for Power BI Data Analysts, this hands-on workshop teaches you to make models chat-ready, unlock insights with natural language, and optimize data for Copilot.

Discover how Real-Time Intelligence can revolutionize your data, transforming it into a dynamic and actionable resource that drives value throughout your entire organization.

Tailored for Power BI Data Analysts, this hands-on workshop teaches you to make models chat-ready, unlock insights with natural language, and optimize data for Copilot.

Join this hands-on workshop to learn how to build a lakehouse with Microsoft Fabric and modernize data engineering, analytics, AI, and business intelligence on one unified platform.

Tailored for SQL developers and DBAs, this hands-on workshop teaches how to build secure AI-powered apps using T‑SQL and trusted SQL data.

Apache Iceberg is now the #1 open table format across enterprises. 58% of organizations use it for business-critical analytics, and 95% are deploying it for AI/ML workloads.

Meanwhile, the agentic AI market is surging past $10B in 2026 (43% YoY growth) — reshaping how organizations turn data into decisions, faster and at lower cost.

Join us for a focused business session in the first half, followed by hands on lab in the afternoon. Learn how leading companies are combining open data architectures with AI agents to reduce platform costs, eliminate vendor lock-in, and put real-time insights directly into the hands of business leaders

What Awaits You:

Vision & Strategy – Learn how AWS with Apache Iceberg is helping customers harness their data for competitive differentiation

Under the hood – Understand the power of Iceberg to build lakehouse architectures, deploy interoperable data patterns, follow industry best practices, and migration strategies.

Hands-On Labs – We’ll have a hands-on lab to learn how to build production-ready architectures that deliver cost savings and performance gains.

Transform from AWS + Iceberg-aware to AWS + Iceberg-unstoppable!

This session is ideal for CDOs, CIOs, CTOs, data & analytics leaders, architects, BI teams, engineers, and decision-makers driving modernization and AI adoption.

* Breakfast, lunch, and networking included

**Seats are limited—secure your spot today and take the first step toward building your analytics and AI-ready future.

Note: Bring your own laptops, AWS Labs Sandbox will be provided

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

「不具合が起きたら？ 設定で迷ったら？ どこに相談すればいいのだろう」

Amazon EC2 で Linux を使ううえで、こんな疑問をお持ちではないでしょうか。

本セッションでは、Amazon EC2 で Linux を使ううえで知っておきたい「サポート」の範囲を、現役のクラウドサポートエンジニアが、ディストリビューションごとの違いとあわせて整理します。

【こんな内容をお話しします】

・Linux の「サポート」とは何か

・ディストリビューションや利用形態、質問内容による相談先の違い

・AWS サポートの活用のしかた

【こんな方におすすめ】

・Amazon EC2 で Linux を使っている、またはこれから使う方

・Linux ディストリビューションごとのサポートの違いを知りたい方

・Linux について AWS サポートをどう活用できるのかを知りたい方

Stop watching demos. Start building.

In one day, you'll design, test, and deploy a working conversational AI application using Amazon Connect's agentic CX designer. No code. No prerequisites. We provide a fully provisioned AWS environment and a real-world use case - you build it end-to-end with expert guidance, then walk away knowing how to do it again with your own.

Who Should Attend

• CX and contact center leaders exploring AI-powered self-service
• Business leaders who want to see what their team can ship in a day
• Developers and architects building conversational experiences
• IT leaders evaluating Amazon Connect

Agenda

Arrival

8:30 – 9:00 | Arrival + Coffee

9:00 – 9:15 | Opening Remarks

9:15 – 10:00 | Be the 5%: Why 95% of AI Pilots Fail — Your Playbook to Production

10:00 – 10:15 | Break

Build

10:15 – 12:15 | Build Your First Agent: Hands-on with agentic CX designer

12:15 – 1:15 | Lunch (served)

1:15 – 3:15 | Expand & Operationalize: Take Your Agent to Production

3:15 – 3:30 | Break

Wrap-Up

3:30 – 4:15 | Customer Story + Q&A

4:15 – 4:35 | The Art of the Possible: What Else Can You Build?

4:35 – 5:00 | Wrap-Up + Next Steps

What You Leave With

• Hands-on experience building an agentic self-service application from scratch
• A clear understanding of how to apply this to your own use cases
• A path to expand across your organization
• Direct access to AWS specialists to talk through your specific scenarios

How It Works

• We provide a fully provisioned AWS environment and guided use case - nothing to set up
• Instructor-led labs with hands-on support throughout
• Bring your questions and your own use cases to discuss with AWS experts
• All you need is a laptop with browser access

SAP ASUG Tech Connect

Cree un panel de información en tan solo un día y aprenda el arte de analizar sus datos de forma enriquecida y atractiva.

Diseñada para analistas de datos de Power BI expertos y nuevos en Microsoft Fabric esta formación práctica enseña fundamentos de consolidación de datos y descubrimiento de información valiosa.

AIOps is where observability is headed - but getting there starts with the right foundations. Observability Day 2026 in Wellington is a full-day, in-person event for operators, engineers, architects, and leaders who want to build those foundations and stay ahead of the curve. From unified telemetry and Gen-AI observability to AI-powered operations agents, we'll show you how the pieces fit together; and give you hands-on experience with the capabilities that are reshaping how teams build, monitor, and operate at scale.

What to Expect

• Future of Agentic Operations: Operations is moving from reactive firefighting to proactive, AI-led prevention. Hear how AI agents are changing the way teams detect, investigate, and resolve issues, and what this means for your operating model, your people, and your path from human-led to autonomous operations.
• Observability for the AI era: A re-imagined agentic first Observability experience that is AI-powered, built on open standards, and delivered outside the AWS Console.
• Unified Data Store: One foundation for all signals. Stop stitching together metrics, logs, and traces from disconnected sources. Learn how a converged observability data platform with a single ingestion model across all signal types gives you correlated insights from day one.
• Unified Application and Agentic Observability: Learn how to monitor, trace, and optimize your Generative AI applications and agents - from model performance and token usage to latency and evaluation workflows.
• DevOps Agent: AI that operates alongside your team. DevOps Agent doesn't just alert you; it investigates. It correlates signals across data stores, performs root cause analysis, and suggests remediation. Experience how AI-led operations can reduce your Mean Time to Resolution from hours to minutes.
• Hands-on Workshop: Don't just hear about it - build with it. In this guided, hands-on session, you'll roll up your sleeves and get hands-on with everything you've learned earlier in the day. Apply the concepts, tools, and capabilities in practice. and walk away with real, ready-to-use skills to leverage in your day to day operations.

Why Attend?

• Hear directly from Tech Leaders about the latest innovations and roadmap
• Get hands-on with cutting-edge observability tools
• Connect with peers solving similar operational challenges across industries
• Learn practical strategies to evolve from reactive monitoring to AI-led autonomous operations

Who Should Attend?

• DevOps Engineers, SREs, Platform Engineers, ML Engineers - who build and operate
• Engineering Managers, Architects, Technical Leads - who design and decide
• IT Directors, CTOs, VP Engineering - who drive transformation, particularly the session from 9:00am to 11:00am.

As enterprises move agents from experimentation into production, teams hit the same problems: agent sprawl with no reuse, shadow AI, no cost attribution, no unified tracing, non-standard integration, and unclear ownership after go-live. Scaling across business units also means deciding who can access enterprise data, which tools agents can use, how their behaviour is evaluated, and who is accountable when something goes wrong.

The answer is a shared agentic AI platform: an enterprise foundation for building, governing, observing and scaling agents safely, reusing enterprise controls instead of rebuilding them for every agent. This workshop shows how to stand that platform up on AWS with Amazon Bedrock AgentCore, then operate real workloads on it, with consistent platform controls and the flexibility for business units to build agents for their own needs.

What participants leave with:

• A working mental model of agent = model + harness, and the foundation vs domain split 
• A reproducible platform foundation pattern (multi-tenant design, identity, governance, gateways, model access, registry, etc.)  
• A hands-on understanding of multi-layered governance from org SCP to platform/domain gateway to project CI/CD gates 
• The governed workload pattern with different types of user journey  
• A view of operating models and a maturity-based next step for their own organisation 

Who should attend: AI engineers, platform engineers and architects, solution and cloud architects, and technical leads and engineering managers. The session is hands-on and code-focused, familiarity with Python helps. 

The data platform for the AI frontier. Local experts, real customer stories, and the Fabric solutions and innovations that matter to your business.

AWS 토큰 이코노믹스 프레임워크로 토큰 비용은 낮추고, 가치는 높이고

행사 개요

AI 적용이 확산되면서, 치솟는 AI 청구서(AI bill shock)는 이제 대부분의 기업이 마주한 공통된 현실이 되었습니다. 토큰 단가는 계속 내려가는데도 조직 전체의 AI 지출은 오히려 가파르게 늘어나고, 정작 그 비용이 어디서·왜 발생하는지조차 보이지 않는 상황에 많은 팀이 부딪히고 있습니다. 사용량을 틀어막자니 혁신이 멈추고, 그대로 두자니 비용을 감당하기 어려운 딜레마입니다.

이 문제의 본질은 '지출이 많다'가 아니라 '지출한 만큼 무엇을 얻고 있는지 모른다'는 데 있습니다. 그래서 지금 필요한 것은 단순한 '예산 삭감'이 아니라, AI 투자를 비즈니스 가치와 연결하고 토큰의 생산성(지출 대비 얻는 가치)을 끌어올리는 체계적인 프레임워크입니다. 이번 세미나에서는 AWS 토큰 이코노믹스 프레임워크를 기반으로 토큰을 더 저렴하게 생산하고, 그 비용과 가치를 측정 가능하게 하는 실질적인 방법을 다룹니다.

이런 질문을 하고 계신다면, 이 세미나는 당신을 위한 것입니다

• 토큰 비용을 줄이라는 부담이 큰데, 어떻게 하면 성능을 유지하면서도 토큰 비용을 줄일 수 있을까요?

• 모델을 서빙하려는데 토큰 기반 API 서비스를 이용하는 게 좋을까요, GPU 기반으로 셀프 호스트하는 게 좋을까요?

• GPU를 최대한 효율적으로 이용하고 싶은데 어떻게 최적화할 수 있을까요?

• GPU 비용이 너무 과다하고 구하기도 어려운데, 대안이 없을까요?

• Bedrock, OpenAI, 그리고 자체 호스팅(self-hosted) vLLM 엔드포인트에 걸쳐, 요청 단위로 토큰 소비를 어떻게 추적할 수 있을까요?

• 우리 플랫폼에서 발생하는 AI 비용을 특정 팀·서비스·use case로 어떻게 귀속시킬 수 있을까요?

• 에이전트 루프가 폭주하기 전에, 에이전트별 토큰 예산과 서킷 브레이커를 어떻게 설정할 수 있을까요?

• 비용·지연·품질을 기준으로, 매니지드 API와 self-hosted 모델 사이에서 요청을 어떻게 라우팅할 수 있을까요?

추천 참석 대상

• LLM, 에이전트, RAG 파이프라인을 프로덕션에 배포하는 AI/ML 엔지니어

• 멀티 모델 서빙 인프라를 구축·운영하는 플랫폼 엔지니어 및 AI Ops

• AI 워크로드의 안정성·비용·관측성을 책임지는 DevOps 및 SRE 팀

• LLM 호출(Amazon Bedrock, 3rd party API, self-hosted)을 애플리케이션에 통합하는 백엔드 엔지니어

• 모델 서빙·라우팅·관측성에 대해 build-vs-buy 의사결정을 내리는 엔지니어링 리드

안내 사항

• 방문 시 대중교통 이용을 권장드립니다. (자차 이용 시 센터필드 주차장 이용 가능하나, 주차권은 미지원됩니다)

• 참가비는 무료이며, 점심식사가 제공됩니다.

• 더 많은 고객분들을 모시기 위해 회사당 참석 인원이 제한될 수 있음을 양해 부탁드립니다.

• 문의사항이 있으신 경우 flexible-ai-korea@amazon.com 으로 연락주시기 바랍니다.

Tailored for Power BI Data Analysts, this hands-on workshop teaches you to make models chat-ready, unlock insights with natural language, and optimize data for Copilot.

About the Event:

You will learn how to implement token tracking, monitoring, and attribution across your entire AI estate — whether consumption runs through Amazon Bedrock, self-hosted models on your own compute, or third-party APIs such as Anthropic or OpenAI. You will leave with a production-ready implementation pattern that gives you a single pane of glass across every consumption environment.

AWS AI Infrastructure — the foundation layer and native tools for agent cost optimization

AWS AI infrastructure is the layer every AI service runs on: Amazon Bedrock for managed model access, Amazon EKS for self-hosted model serving, and the underlying GPU and CPU compute. Where does each one make economic sense, and how to implement and instrument the choices. Introduction to AWS native tools for token cost optimization available in AWS AgentCore and Bedrock.

Kong AI Gateway — routing, budgets, and guardrails

A single governed entry point in front of every model provider: semantic and cost-aware routing, token-based rate limiting, per-team spend quotas, semantic caching, and prompt guarding, across managed APIs and self-hosted vLLM endpoints alike.

Arize AI / Phoenix — observability and evaluation

Per-request tracing of tokens, cost, and latency alongside output quality: dataset evaluation, drift detection, and quality alerting, so a cost decision is never made blind to its effect on the answer.

If you are asking any of these questions, this workshop is for you

✓ How do I trace token consumption per request across Bedrock, OpenAI, and my self-hosted vLLM endpoints?

✓ How do I set per-agent token budgets and circuit breakers before agentic loops run away?

✓ How do I route requests between managed APIs and self-hosted models based on cost, latency, or quality?

✓ How do I attribute AI costs back to specific teams, services, and use cases in my platform?

What You Will Learn

▶ Consumption and cost attribution — trace every token back to a team, service, and use case across Bedrock, self-hosted models, and third-party APIs

▶ Routing — direct requests across multiple models and providers based on cost, latency, or availability

▶ Governance and monitoring — enforce per-team token budgets, evaluate model datasets, and set up drift detection and quality alerts

What You Will Build

A token tracking and observability stack using Kong AI Gateway and the Arize AI observability stack on Amazon EKS. By the end of the day you will have a working pipeline capturing per-request token counts, cost, latency, model quality, and team attribution — across Amazon Bedrock, foundation model providers accessed directly, and self-hosted vLLM endpoints.

Who Should Attend

■ AI/ML engineers deploying LLMs, agents, and RAG pipelines to production

■ Platform engineers & AI Ops building and operating multi-model serving infrastructure

■ DevOps & SRE teams responsible for AI workload reliability, cost, and observability

■ Backend engineers integrating LLM calls (Bedrock, OpenAI, self-hosted) into applications

■ Engineering leads making build-vs-buy decisions on model serving, routing, and observability

Please bring your own laptop. A lab environment is provided — no local setup is required. Working familiarity with Kubernetes and with calling an LLM API is assumed.

Full Agenda:

Start End Duration Session

9.00 9.30 0.30 Registration & Networking

9.30 10.15 0.45 Token Economics Framework

10.15 10.45 0.30 AWS Services for Token Economics - AgentCore Gateway

10.45 11.00 0.15 B R E A K

11.00 12.00 1.00 Kong AI Gateway — Overview

12.00 13.00 1.00 Arize AI / Phoenix — Overview

13.00 14.00 1.00 L U N C H

14.00 14.30 0.30 Live Demo : Integrated / Unified Token Economics Solution

14.30 15.30 1.00 Hands-On Lab : Integration Workshop — Kong + Arize + AWS End-to-End

15.30 15.45 0.15 B R E A K

15.45 16.45 1.00 Continuation - Hands-On Lab : Integration Workshop — Kong + Arize + AWS End-to-End

16.45 16.55 0.10 Recap and Quiz

16.55 17.00 0.05 W R A P - U P

About the Event:

You will learn how to implement token tracking, monitoring, and attribution across your entire AI estate — whether consumption runs through Amazon Bedrock, self-hosted models on your own compute, or third-party APIs such as Anthropic or OpenAI. You will leave with a production-ready implementation pattern that gives you a single pane of glass across every consumption environment.

AWS AI Infrastructure — the foundation layer and native tools for agent cost optimization

AWS AI infrastructure is the layer every AI service runs on: Amazon Bedrock for managed model access, Amazon EKS for self-hosted model serving, and the underlying GPU and CPU compute. Where does each one make economic sense, and how to implement and instrument the choices. Introduction to AWS native tools for token cost optimization available in AWS AgentCore and Bedrock.

Kong AI Gateway — routing, budgets, and guardrails

A single governed entry point in front of every model provider: semantic and cost-aware routing, token-based rate limiting, per-team spend quotas, semantic caching, and prompt guarding, across managed APIs and self-hosted vLLM endpoints alike.

Arize AI / Phoenix — observability and evaluation

Per-request tracing of tokens, cost, and latency alongside output quality: dataset evaluation, drift detection, and quality alerting, so a cost decision is never made blind to its effect on the answer.

If you are asking any of these questions, this workshop is for you

✓ How do I trace token consumption per request across Bedrock, OpenAI, and my self-hosted vLLM endpoints?

✓ How do I set per-agent token budgets and circuit breakers before agentic loops run away?

✓ How do I route requests between managed APIs and self-hosted models based on cost, latency, or quality?

✓ How do I attribute AI costs back to specific teams, services, and use cases in my platform?

What You Will Learn

▶ Consumption and cost attribution — trace every token back to a team, service, and use case across Bedrock, self-hosted models, and third-party APIs

▶ Routing — direct requests across multiple models and providers based on cost, latency, or availability

▶ Governance and monitoring — enforce per-team token budgets, evaluate model datasets, and set up drift detection and quality alerts

What You Will Build

A token tracking and observability stack using Kong AI Gateway and the Arize AI observability stack on Amazon EKS. By the end of the day you will have a working pipeline capturing per-request token counts, cost, latency, model quality, and team attribution — across Amazon Bedrock, foundation model providers accessed directly, and self-hosted vLLM endpoints.

Who Should Attend

■ AI/ML engineers deploying LLMs, agents, and RAG pipelines to production

■ Platform engineers & AI Ops building and operating multi-model serving infrastructure

■ DevOps & SRE teams responsible for AI workload reliability, cost, and observability

■ Backend engineers integrating LLM calls (Bedrock, OpenAI, self-hosted) into applications

■ Engineering leads making build-vs-buy decisions on model serving, routing, and observability

Please bring your own laptop. A lab environment is provided — no local setup is required. Working familiarity with Kubernetes and with calling an LLM API is assumed.

Full Agenda:

Start End Duration Session

9.00 9.30 0.30 Registration & Networking

9.30 10.15 0.45 Token Economics Framework

10.15 10.45 0.30 AWS Services for Token Economics - AgentCore Gateway

10.45 11.00 0.15 B R E A K

11.00 12.00 1.00 Kong AI Gateway — Overview

12.00 13.00 1.00 Arize AI / Phoenix — Overview

13.00 14.00 1.00 L U N C H

14.00 14.30 0.30 Live Demo : Integrated / Unified Token Economics Solution

14.30 15.30 1.00 Hands-On Lab : Integration Workshop — Kong + Arize + AWS End-to-End

15.30 15.45 0.15 B R E A K

15.45 16.45 1.00 Continuation - Hands-On Lab : Integration Workshop — Kong + Arize + AWS End-to-End

16.45 16.55 0.10 Recap and Quiz

16.55 17.00 0.05 W R A P - U P

In this hands-on workshop, you'll build sandboxed execution environments for AI agents using AWS Lambda MicroVMs — Lambda's newest compute primitive that combines Firecracker VM-level isolation with serverless scaling and zero infrastructure management.

You'll start in Module 1 with the fundamentals every other module builds on: create a custom MicroVM image with a Dockerfile, launch your first MicroVM, and interact with it over HTTP. From there, the use-case modules are independent - pick the ones that interest you and skip the rest:

• Module 2 - Event-Driven Coding Agents: a pull request triggers an ephemeral MicroVM that runs an AI coding agent over the diff and posts a review back.
• Module 3 - Ephemeral CI/CD Runners: a per-job runner launches on a push, runs the pipeline in a clean MicroVM, reports the result, and disappears.
• Module 4 - Multi-tenant SaaS: each customer gets their own MicroVM behind a control plane that launches, caches, and routes to per-tenant instances.

Along the way you'll work with the core building blocks: MicroVM images, snapshots for fast startup, network connectors, and the launch/suspend/resume/terminate lifecycle.

Prerequisites: Basic AWS familiarity, serverless concepts, CLI experience. AWS account provisioned by the workshop.

Duration: ~2.5–3 hours (3 modules, 30–45 minutes each).

Microsoft Fabric Roadshow Oslo. A local experience. A global vision. Join us for the Microsoft Fabric Roadshow

Diseñada para analistas de datos de Power BI expertos y nuevos en Microsoft Fabric esta formación práctica enseña fundamentos de consolidación de datos y descubrimiento de información valiosa.

Create a dashboard in just one day and learn the art of analyzing your data in a rich and compelling manner.

GitHub Copilot Hands-on Lab

Red Hat Summit Connect- Bogota

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

Tailored for Power BI Data Analysts, this hands-on workshop teaches you to make models chat-ready, unlock insights with natural language, and optimize data for Copilot.

Join us in the Microsoft Technical Workshop: Build Agentic AI solutions with Microsoft Foundry.

Google Public Sector Summit On-Demand bridges the gap between ambitious innovation and secure, scaled execution. Tailored for leaders, creators, coders, and builders, the event focuses on moving organizations beyond AI pilots and experimentation into fully deployed, mission-ready realities. Register early to access the on-demand sessions which will be available following the in-person event.

클라우드 전환 과정에서 비용 최적화에 대한 고민을 가지신 분들을 위해 AWS에서는 Amazon EKS 기반에서 Graviton 인스턴스를 활용하여 현대화 및 비용 최적화 두 목표를 달성하는 내용에 대한 워크숍을 11월 4일 (수)에 개최합니다.

본 "그라비톤으로 EKS 시작하기" 행사는 EKS를 처음 시작하시는 분들과 컨테이너 기술에 익숙하지 않으신 분들을 위한 입문 과정입니다. Kubernetes 핵심 개념(Pod, Labels, Replica/Deployments)과 함께 AWS Graviton 프로세서의 아키텍처와 성능 특징까지 실습 중심으로 배우실 수 있습니다.

워크숍 하이라이트:

• Kubernetes & Amazon EKS 핵심 개념: Pod, Labels, Deployments 등 필수 개념과 EKS 개요, Karpenter 소개
• ARM/AWS Graviton 소개: 비용 효율적인 Graviton 프로세서의 특징과 마이그레이션 고려사항
• 핸즈온 워크숍: Intel/Graviton 멀티 아키텍처 환경에서 실제 웹 애플리케이션 배포 실습

EKS를 활용한 현대화와 Graviton 기반 비용 최적화를 동시에 경험할 수 있는 "그라비톤으로 EKS 시작하기" 워크숍에 지금 바로 등록하세요!

행사 문의: yechoi@amazon.com

Microsoft Fabric を初めて利用する、経験豊富な Power BI データ アナリスト向けに設計されたこの実践的トレーニングでは、データ統合の基礎と、価値あるインサイトを引き出す方法について学びます。

• Introduction to agentic development — the AWS point of view on agentic software development; the breadth of the approach and spec-driven development as the foundation
• Wireframing & rapid prototyping — accelerated time-to-value; going from idea to working prototype fast, without sacrificing structure.
• The operational assistant — agentic tooling as a force-multiplier for existing teams: enhancing security posture and automating patching, documentation, legacy code comprehension, testing.
• Security & governance — the "control plane": guardrails, auditability, and how spec-driven development makes AI-generated code reviewable and defensible.

技術情報を解説動画にするには、内容の調査から台本作成、映像制作、ナレーション収録、公開まで、多くの工程が必要です。本セッションでは、これらを AWS 上の AI エージェントに任せる、自動解説動画制作ワークフローを紹介します。

AWS What's New の RSS を起点に、Amazon Bedrock AgentCore 上で動く AI エージェントが公式ドキュメントを調査し、台本と映像を制作します。HyperFrames による映像生成と、Qwen3-TTS による本人の声を再現したナレーションを組み合わせ、映像・音声を確認しながら修正。完成した動画を YouTube へ公開し、X への紹介投稿までつなげます。

デモを交えながら、AWS Step Functions による処理の連携、GPU ワーカーの起動・停止、公開対象の記事選別、失敗時の再実行と重複投稿の防止など、継続運用に必要な設計を解説します。コンテンツ制作を効率化したい方や、複数のツールを使って成果物を仕上げる AI エージェントを AWS 上で構築したい方におすすめです。

Join us for Emerging Partner Leaders (EPL) Hub India— a half-day, invitation-only event where emerging AWS partners connect directly with AWS leadership, hear from Rising Star partners who've achieved standout results, and leave with a clear 90-day plan to grow their AWS practice. Expect strategic insights, peer networking, and actionable collaboration opportunities.

Erstellen Sie ein Dashboard an nur einem Tag, und erfahren Sie, wie Sie Ihre Daten auf umfassende und überzeugende Weise analysieren.

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

Tento praktický kurz je určen pro zkušené datové analytiky Power BI, kteří začínají s platformou Microsoft Fabric. Naučíte se v něm základy konsolidace dat a získávání cenných přehledů.

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

Tailored for Power BI Data Analysts, this hands-on workshop teaches you to make models chat-ready, unlock insights with natural language, and optimize data for Copilot.

Red Hat Summit Connect- Austin

Make coding page-focused scenarios more efficient and productive. Join us to discover how to build an ASP.NET Core web app using the Razor Pages feature to consume APIs.

Join us at a free technical workshop to explore the innovative capabilities of AI agents—and find out how to transform your applications

This hands-on lab is designed to give developers practical experience using GitHub Copilot as an AI-powered assistant throughout the Software Development Life Cycle (SDLC).

What is Partner Central Agent Day (PCAD)?

The Partner Central Agents Day (PAD) is a one-day, in-person enablement event designed to help AWS Partners unlock the full potential of Partner Central Agents for co-selling. Hosted across key APJ markets, PAD brings together partner sales, alliance, and technical teams for hands-on learning, live demos, and guided implementation — so you walk away with agents running in your environment and a clear plan to accelerate your co-sell motion with AWS.

Why Attend?

Partner Central Agents are transforming how partners co-sell with AWS. PCAD gives you the dedicated time and expert support to activate these capabilities against your real pipeline, not hypothetical scenarios. 

Enhance Your Sales Team with Agents

• Partner Central agents available to manage joint pipeline where your team works 
• Account intelligence is designed to surface at the right moment to accelerate the sales cycle 
• Automated sales play generation customized by account 

Same-Day Integration

• Complete MCP integration 
• Validate data flows 
• Activate agents in your sandbox environment 
• No CRM integration required 

Walk Away with Your Adoption Plan

• Early access to the Partner Central AI roadmap 
• Self-service activation kits to activate your use cases 
• 90-day adoption plan to help you scale agentic adoption across your teams 

Who Should Attend?

PAD is open to partner organizations who have completed their Partner Central in Console migration. This is a mandatory pre-requisite — Agent capabilities are only accessible after migration. If your organization hasn't migrated yet, please complete migration before registering. To get the most out of this event, we strongly recommend sending two people from your organization: one Business persona and one Technical persona. Here's why:

• [Required] Business Persona with Partner Central Administrator access (e.g. Alliance Lead): This individual will configure workflow automation and activate agentic integrations within your workflows. The morning session covers strategy, use cases, and live demos that are essential for understanding how Agents fit into your co-sell motion.
• [Required] Technical Persona with access to manage and deploy in your Partner Central Sandbox environment and your AWS Account — This individual will work directly with AWS engineers to complete agent deployment and validate data flows in real time. The afternoon hands-on lab is where your team actually deploys and activates Agents, and this session cannot be completed without a technical person present.
• [Optional] Technical Persona(s) with access to manage in-house tools: If you want to integrate internal tools (e.g. CRM, Slack, Marketo etc.) with Partner Central agents and tools, this individual will work with our AWS team to configure and deploy these integrations.

⚡Important note on session attendance:

• Morning session (Strategy & Demos): Valuable for all personas — both Business and Tech should attend.
• Afternoon session (Hands-on Lab & Deployment): Your Technical persona must attend this session. If your Tech person has limited availability, joining the afternoon session alone is acceptable — but attending the full day is strongly recommended for best results.

💡 From our experience running PAD across multiple cities: teams that attended with only a Business persona were unable to complete the afternoon hands-on deployment. Please ensure your Technical person is confirmed before registering.

Pre-Requisites — What to Prepare Before the Event

This is an activation workshop, not a setup workshop. To make the most of your day, please ensure the following are completed before you arrive:

1. Partner Central in Console Migration — COMPLETED Your organization must have fully migrated to Partner Central in the Console. If you can log in at partnercentral.aws and see the new interface, you're ready. Not migrated yet? Please complete your migration first — you will not be able to participate in the hands-on lab without it.
2. IAM User with Admin Access — READY Your Technical persona must have an IAM user with full admin permissions in your AWS sandbox or development account. Please confirm this access before event day — setting up IAM on-site takes valuable time away from the lab.
3. Partner Central Sandbox Access — VERIFIED Your Technical persona should be able to log into and operate within your Partner Central Sandbox environment. Please test this login in advance.
4. MCP Client Installed — WORKING Your Technical persona should have an MCP-compatible client (e.g. Claude Desktop, Cursor, or equivalent) installed and working on their laptop before arriving. This is required for the hands-on integration lab.

⚠️ Please do not arrive without completing these steps. In past editions, partners who came unprepared spent 1–2 hours on setup instead of activation — missing out on the core learning experience. If any of the above are not ready, please resolve them before event day or reach out to us for guidance.

What to Bring on Event Day

• Laptop (fully charged, with charger)
• IAM credentials saved and accessible
• Partner Central Sandbox login tested and working
• MCP Client installed and verified
• Business cards for networking

 

As enterprises move agents from experimentation into production, teams hit the same problems: agent sprawl with no reuse, shadow AI, no cost attribution, no unified tracing, non-standard integration, and unclear ownership after go-live. Scaling across business units also means deciding who can access enterprise data, which tools agents can use, how their behaviour is evaluated, and who is accountable when something goes wrong.

The answer is a shared agentic AI platform: an enterprise foundation for building, governing, observing and scaling agents safely, reusing enterprise controls instead of rebuilding them for every agent. This workshop shows how to stand that platform up on AWS with Amazon Bedrock AgentCore, then operate real workloads on it, with consistent platform controls and the flexibility for business units to build agents for their own needs.

What participants leave with:

• A working mental model of agent = model + harness, and the foundation vs domain split 
• A reproducible platform foundation pattern (multi-tenant design, identity, governance, gateways, model access, registry, etc.)  
• A hands-on understanding of multi-layered governance from org SCP to platform/domain gateway to project CI/CD gates 
• The governed workload pattern with different types of user journey  
• A view of operating models and a maturity-based next step for their own organisation 

Who should attend: AI engineers, platform engineers and architects, solution and cloud architects, and technical leads and engineering managers. The session is hands-on and code-focused, familiarity with Python helps. 

Build with confidence. Secure and defend at scale.  As AI keeps reshaping the enterprise, security must move faster than ever. Join security experts from Google Cloud, Mandiant, and Wiz to learn how to securely build and govern AI agents, safeguard applications from the ground up, protect your systems against new AI-driven attacks, and respond quickly when risks appear. View the sessions in your preferred language with subtitles in 한국어, Bahasa Indonesia, 繁體中文, 简体中文, 日本語, ภาษาไทย and English. Plus, check out the Japan Digital Summit.

Red Hat Summit Connect- Taipei

Create a dashboard in just one day and learn the art of analyzing your data in a rich and compelling manner.

Microsoft Cloud & AI Innovation Day Malaysia.

Join AWS for a morning tea created for business leaders who value real-world experience over promises. We will introduce Amazon Quick Desktop, the AI platform that connects securely to the data and applications your teams already use and turns everyday questions into finished work. Then we will sit down with a customer to hear how their organizations are putting Amazon Quick Desktop to work.

In a panel discussion, leaders from two prominent Australian enterprises will join an AWS Solutions Architect to share their recent experiences implementing Amazon Quick. They will unpack how they moved from proof of concept to production, who they involved and why, how they brought both executives and business users along, and how they proved the value that unlocked the next phase.

What you will learn

• How business teams use Amazon Quick to get answers and complete work across their existing systems
• The approaches two organisations used to move from pilot to production
• How to engage executive and business audiences on separate but complementary tracks
• How to equip non-technical teams to evaluate and build with confidence
• How to measure business value and build the case to scale

同一の Agent や MCP Server、Knowledge Base を複数のユーザーで共有する場合、ユーザーごとに検索対象を制御しなければ、閲覧権限のない文書が Agent 経由で漏洩するリスクがあります。本セッションでは、Amazon Bedrock Managed Knowledge Base と AgentCore Gateway で構成する Agentic RAG を題材に、Fine-grained Access Control（FGAC）の実現方法を深掘りします。

認可を担うユーザー属性（userContext）を LLM に生成させず、Request Interceptor で検証済み JWT から決定的に注入し、Managed KB の ACL awareness で検索対象の文書を制御する設計を解説します。さらに、AgentCore Policy と Resource-based policy を組み合わせた多層防御と、CDK による実装・検証のポイントを紹介します。「AIエージェントの権限管理」シリーズ第3弾です。

実装・検証記事：https://zenn.dev/aws_japan/articles/007-bedrock-agentcore-gateway-managed-kb-mcp

Stop watching demos. Start building.

In one day, you'll design, test, and deploy a working conversational AI application using Amazon Connect's agentic CX designer. No code. No prerequisites. We provide a fully provisioned AWS environment and a real-world use case - you build it end-to-end with expert guidance, then walk away knowing how to do it again with your own.

Who Should Attend

• CX and contact center leaders exploring AI-powered self-service
• Business leaders who want to see what their team can ship in a day
• Developers and architects building conversational experiences
• IT leaders evaluating Amazon Connect

Agenda

Arrival

8:30 – 9:00 | Arrival + Coffee

9:00 – 9:15 | Opening Remarks

9:15 – 10:00 | Be the 5%: Why 95% of AI Pilots Fail — Your Playbook to Production

10:00 – 10:15 | Break

Build

10:15 – 12:15 | Build Your First Agent: Hands-on with agentic CX designer

12:15 – 1:15 | Lunch (served)

1:15 – 3:15 | Expand & Operationalize: Take Your Agent to Production

3:15 – 3:30 | Break

Wrap-Up

3:30 – 4:15 | Customer Story + Q&A

4:15 – 4:35 | The Art of the Possible: What Else Can You Build?

4:35 – 5:00 | Wrap-Up + Next Steps

What You Leave With

• Hands-on experience building an agentic self-service application from scratch
• A clear understanding of how to apply this to your own use cases
• A path to expand across your organization
• Direct access to AWS specialists to talk through your specific scenarios

How It Works

• We provide a fully provisioned AWS environment and guided use case - nothing to set up
• Instructor-led labs with hands-on support throughout
• Bring your questions and your own use cases to discuss with AWS experts
• All you need is a laptop with browser access

Create a dashboard in just one day and learn the art of analyzing your data in a rich and compelling manner.

The Fundamentals of Amazon EKS workshop provides hands-on experience with Amazon EKS. This workshop demonstrates how Amazon EKS automates cluster operations from the control plane through compute resources, eliminating infrastructure management overhead while reducing costs and improving application performance. Participants work through guided exercises in real AWS environments to build practical skills for production workloads.

You'll learn how to

• Create clusters and deploy applications
• Expose your applications over the internet
• Utilise storage for stateful workloads
• Implement autoscaling to meet the compute demands of your workload

This workshop is designed for DevOps engineers, platform engineers, and cloud architects who manage Kubernetes workloads on AWS and have basic knowledge of Kubernetes and AWS services.

New to Amazon ECS? In this free, hands-on workshop you will build a multi-tier web application on Amazon Elastic Container Service (Amazon ECS) and AWS Fargate from scratch. Start by deploying your first container, then progressively add microservices with ECS Service Connect, handle traffic spikes with auto-scaling, and release changes safely using Blue/Green deployments. You will also set up monitoring with CloudWatch Container Insights so you can observe your application in real time. You get your own AWS account for two hours, with AWS container experts available to help throughout.

コンテナワークロードのセキュリティは、単一の対策ではなく、開発ライフサイクル全体を通じた多層的な取り組みが求められます。本ワークショップでは前半の座学で、コンテナのビルド、サプライチェーンを経た Amazon ECR への格納、Amazon ECS によるデプロイ、そしてランタイムでの稼働という各段階において、セキュリティをどう担保するかを順を追って網羅的に解説します。コンテナ技術アーキテクチャの階層とコンポーネントを俯瞰しながら、レジストリ、オーケストレーター、ホストといった各レイヤーに、予防的統制（最小権限、AWS Fargate の採用、ディストロレスイメージ、Immutable タグなど）と発見的統制（AWS CloudTrail、Amazon Inspector、Amazon GuardDuty Runtime Monitoring など）を対応づけ、後半のハンズオンが全体のどこを守るものかを明確にします。

本ワークショップでは、主に以下のトピックを扱います。

• コンテナセキュリティの全体像：開発ライフサイクル（ビルド → Amazon ECR への格納 → Amazon ECS によるデプロイ → ランタイム稼働）に沿った俯瞰
• 予防的統制と発見的統制の体系的な整理と、各レイヤー（レジストリ・オーケストレーター・ホスト）へのマッピング
• 生成 AI ワークロード時代に重要性が増す「できることを減らす」設計（AWS Fargate による隔離、Linux Capabilities の削除、root 権限の排除）
• Amazon Inspector の拡張スキャンによる言語ライブラリの脆弱性（CVE）検知と対応【ハンズオン】
• マルチステージビルドやタスク定義の見直しによるアタックサーフェスの削減【ハンズオン】
• Amazon GuardDuty Runtime Monitoring による不審通信の検知と、対象ワークロードの切り離し【ハンズオン】

また、生成 AI を活用したエージェントなどのワークロードが増える中で、AWS Fargate のような隔離された実行環境や、Linux Capabilities の削除・root 権限の排除といった「できることを減らす」設計の重要性にも触れます。後半のハンズオンでは、AWS Fargate 上の Amazon ECS ワークロードを対象に、Amazon Inspector の拡張スキャンで言語ライブラリの脆弱性（CVE）を検知し、マルチステージビルドやタスク定義の見直しによってアタックサーフェスを削減します。さらに、意図的に発生させた不正な通信を Amazon GuardDuty Runtime Monitoring で検知し、対象ワークロードを切り離すまでの一連の流れを体験します。検知から対応までを手を動かして学ぶことで、実務に活かせるコンテナセキュリティの勘所を習得できます。

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

Red Hat Summit Connect- Paris

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

Microsoft Fabric Roadshow Herzliya

N/A

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Deze workshop is op maat gemaakt voor Power BI-gegevensanalisten. U leert modellen chatklaar te maken, inzichten te verkrijgen met natuurlijke taal en gegevens te optimaliseren voor Copilot.

-

Dieses praxisnahe Training richtet sich an erf. Power BI Data Analysts die erstmals mit Microsoft Fabric arbeiten und vermittelt Grundlagen zur Datenkonsolidierung und wertvollen Erkenntnissen.

Microsoft Fabric Roadshow Stockholm - Digital

Adaptado para programadores de SQL e DBAs, este workshop prático ensina a criar aplicações seguras baseadas em IA utilizando T-SQL e dados SQL fidedignos.

Create a dashboard in just one day and learn the art of analyzing your data in a rich and compelling manner.

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

This free workshop will guide you through the end-to-end process of migrating Microsoft SQL Server databases to Azure SQL.

Technical Workshop: Build Agents and Software Faster with AI That Knows Your Business

AI is moving from experimentation into production, making financial visibility, cost control, and measurable business value more important than ever.

Discover how Real-Time Intelligence can revolutionize your data, transforming it into a dynamic and actionable resource that drives value throughout your entire organization.

Automate a Day in Your Organisation with Amazon Quick

A hands-on executive workshop | 3 hours | 24 seats only

Routine work is quietly taxing your teams. They pull data from CRMs, analytics tools, and documents. They lose focus to repetitive tasks, they waste time switching between apps and complex analysis slows every decision down. The result? 40+ hours a month lost, hours your organisation can't afford to keep giving away.

Amazon Quick changes that. It's a set of agentic AI teammates that quickly answer your questions at work and help you turn those answers into actions, unifying your data sources into clear, context-rich answers, taking action alongside you, and delivering an intuitive AI experience your organisation will love.

This workshop is best suited for executives who want to automate repeated processes across their organisation and free their teams to focus on what matters. In three hands-on hours, you'll:

Automate a day in your work - experience real, end-to-end workflows across Legal, Finance, Sales, and HR, simulating real applications and data.

See it unify your data - turn disparate sources and curated knowledge into clear, trustworthy answers.

Trust it at enterprise scale - understand how Amazon Quick meets Amazon's rigorous security standards, navigates global privacy and work-council requirements, and scales for company-wide adoption.

Hear real customer stories - from organisations already automating their workflows with Amazon Quick.

Learn from AWS Partners - who have helped customers deploy Amazon Quick in as little as 5 days.

Walk away ready to bring this back to your own teams: after the session, your AWS account team can run this same workshop in your offices, with your data.

📅 Friday, 6 November 2026 | 🕙 09:30 AM – 1:00 PM | 📍 AWS Office, Level 12, 555 Collins St, Melbourne (Register on Level 1)

🔥 Seats are strictly limited to 24 and allocated on a first-come, first-served basis. Register now to lock in your place.

By completing your registration, you acknowledge and agree that your name and email address will be shared with the AWS Partners involved in facilitating this workshop for the purposes of event delivery and follow-up.

Workshop Overview

Join us for an intensive, hands-on workshop where you'll gain advanced practical experience with AI-powered operations (AIOps) using AWS observability services. This session is designed for experienced Operations teams, Site Reliability Engineers (SREs), DevOps engineers, platform engineers, and solutions architects who want to master intelligent automation and machine learning-driven operational insights on AWS.

What You'll Learn

• CloudWatch Investigations: Master CloudWatch Investigations to automatically correlate metrics, logs, and traces for faster root cause analysis and incident resolution
• Troubleshooting with CloudWatch Investigations: Learn advanced troubleshooting techniques using AI-driven insights to identify anomalies, dependencies, and failure patterns across distributed systems
• MCP Servers Configuration: Set up and configure Model Context Protocol (MCP) servers to enable AI agents to interact with your observability data and infrastructure
• SLO Alarm Investigation: Investigate Service Level Objective (SLO) breaches using AI-powered analysis to understand impact, identify contributing factors, and recommend remediation actions
• DynamoDB Throttling Investigation: Deep dive into DynamoDB throttling scenarios using CloudWatch Investigations to analyze capacity patterns, identify hot partitions, and optimize throughput

Hands-On Labs

Through pre-built workloads and guided exercises, you'll:

• Deploy and configure CloudWatch Investigations for multi-tier applications with complex dependencies
• Use CloudWatch Investigations to troubleshoot real-world production scenarios including latency spikes, error rate increases, and resource exhaustion
• Generate automated incident reports with AI-synthesized root cause analysis and remediation recommendations
• Configure MCP server environments to enable AI agents to query observability data and execute operational tasks
• Investigate SLO alarm breaches using AI-driven correlation of metrics, logs, and distributed traces
• Analyze and resolve DynamoDB throttling issues using CloudWatch Investigations to identify capacity bottlenecks and optimization opportunities

Who Should Attend

This workshop is ideal for technical professionals with solid AWS experience and existing observability knowledge who want to build production-ready, AI-powered operational solutions. Participants should be comfortable with AWS services, basic scripting, monitoring concepts, and have interest in applying machine learning to operations.

開発組織における生成 AI の活用は 2026 年が導入としたら 2027 年は評価の年となり、AI エージェントの稼働に対する会社や事業への価値貢献が厳しく見られることになります。AI BPR は他の手法が「ボトルネック」や「問題」に注目するところ、価値の特定と差別優位化に焦点を当て AI エージェントと人間の役割分担の決定と実装を行うこれまでと異なる方法論です。AI BPR が開始 4 カ月で 30 社以上のお客様で実践され、海外の AWS でも活用が始まっている背景にはこのアプローチの根本的な違いがあります。AI エージェントが導入された開発組織は当然人間だけでなく AI エージェントのコストも負担するようになり、消費したトークンがサービス価値を高め、結果として売上に貢献できなければどれだけ「生産性」が上がっても経営としては赤字になります。AI BPR は「開発プロセス」単体ではなくあらかじめ「ビジネスモデル」をスコープにすることで価値の生産から提供までの一連全体を見たうえで会社の生存に不可欠な点から AI エージェントによる強化を行っていくことをコンセプトにした方法論です。本セッションでは手法の詳細と実績についてお話しします。

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

大阪開催 ガバメントクラウドワークショップ

テーマ

AI時代におけるクラウド活用をセキュリティやコスト対策、実際の自治体での活用事例などをご紹介。

後半には実際のAWS環境を使ったハンズオンや事業者間のネットワーキングの場などもご用意しておりますのでぜひご参加ください。

【タイムスケジュール】

13:00 - 13:30 : 開場・受付

13:30 - 13:45 : オープニング

13:45 - 14:15 : AWSの考えるセキュリティ対策

14:15 - 14:45 : 株式会社マイクロ二ティ様

・【srest】 ガバメントクラウドにおけるFinOpsの実践・定着

14:45 - 15:15 : Polimill 株式会社 様

・1,200自治体向けアプリストア「Qommons ONE」

～事業者のサービスを全国の自治体に提供する仕組みと参加方法～

15:15 - 15:30 : 休憩

15:30 - 18:00 : ハンズオンワークショップセミナー

この時間は４つのハンズオン/セミナーから１つを選択して参加する形式になります。ご希望のものを選び、それぞれのリンクから申し込みをお願いします。

・コーディングエージェントを利用したソフトウェア開発ライフサイクルハンズオン

https://aws-experience.com/apj/smb/event/45d20774-249d-419d-9ff2-8b11a39bd617

・AWS Transformを利用したVMware環境のAWS移行体験ワークショップ

https://aws-experience.com/apj/smb/event/efe3f384-5fe6-4343-99b1-32a97ddc9e48

・生成AIを用いたAWS環境の運用保守効率化ワークショップ

https://aws-experience.com/apj/smb/event/ab1c4244-9373-4fa1-accb-6c793703671e

・自治体におけるAI利活用の事例紹介/ディスカッション

https://aws-experience.com/apj/smb/event/c17f7594-7d05-4de3-9e35-853697c715ff

18:00 - 19:00 : 懇親会

19:00 - 21:00 : Gov-JAWS

こちらのイベントは下記の「大阪開催 ガバメントクラウドワークショップ」内で行うハンズオンセミナーになります。

ご参加される方は下記にも申し込みをお願いします。

https://aws-experience.com/apj/smb/event/b75379db-c0f5-41af-af88-970fd7eaa16a

こちらのイベントは下記の「大阪開催 ガバメントクラウドワークショップ」内で行うハンズオンセミナーになります。

ご参加される方は下記にも申し込みをお願いします。

https://aws-experience.com/apj/smb/event/b75379db-c0f5-41af-af88-970fd7eaa16a

こちらのイベントは下記の「大阪開催 ガバメントクラウドワークショップ」内で行うハンズオンセミナーになります。

ご参加される方は下記にも申し込みをお願いします。

https://aws-experience.com/apj/smb/event/b75379db-c0f5-41af-af88-970fd7eaa16a

こちらのイベントは下記の「大阪開催 ガバメントクラウドワークショップ」内で行うハンズオンセミナーになります。

ご参加される方は下記にも申し込みをお願いします。

https://aws-experience.com/apj/smb/event/b75379db-c0f5-41af-af88-970fd7eaa16a

こちらのイベントは下記の「大阪開催 ガバメントクラウドワークショップ」内で行うハンズオンセミナーになります。

ご参加される方は下記にも申し込みをお願いします。

https://aws-experience.com/apj/smb/event/b75379db-c0f5-41af-af88-970fd7eaa16a

こちらのイベントは下記の「大阪開催 ガバメントクラウドワークショップ」内で行うハンズオンセミナーになります。

ご参加される方は下記にも申し込みをお願いします。

https://aws-experience.com/apj/smb/event/b75379db-c0f5-41af-af88-970fd7eaa16a

こちらのイベントは下記の「大阪開催 ガバメントクラウドワークショップ」内で行うハンズオンセミナーになります。

ご参加される方は下記にも申し込みをお願いします。

https://aws-experience.com/apj/smb/event/b75379db-c0f5-41af-af88-970fd7eaa16a

こちらのイベントは下記の「大阪開催 ガバメントクラウドワークショップ」内で行うハンズオンセミナーになります。

ご参加される方は下記にも申し込みをお願いします。

https://aws-experience.com/apj/smb/event/b75379db-c0f5-41af-af88-970fd7eaa16a

こちらのイベントは下記の「大阪開催 ガバメントクラウドワークショップ」内で行うハンズオンセミナーになります。

ご参加される方は下記にも申し込みをお願いします。

https://aws-experience.com/apj/smb/event/b75379db-c0f5-41af-af88-970fd7eaa16a

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

Tailored for SQL developers and DBAs, this hands-on workshop teaches how to build secure AI-powered apps using T‑SQL and trusted SQL data.

Create a dashboard in just one day and learn the art of analyzing your data in a rich and compelling manner.

Apache Iceberg is now the #1 open table format across enterprises. 58% of organizations use it for business-critical analytics, and 95% are deploying it for AI/ML workloads.

Meanwhile, the agentic AI market is surging past $10B in 2026 (43% YoY growth) — reshaping how organizations turn data into decisions, faster and at lower cost.

Join us for a focused business session in the first half, followed by hands on lab in the afternoon. Learn how leading companies are combining open data architectures with AI agents to reduce platform costs, eliminate vendor lock-in, and put real-time insights directly into the hands of business leaders

What Awaits You

Vision & Strategy – Learn how AWS with Apache Iceberg is helping customers harness their data for competitive differentiation

Under the hood – Understand the power of Iceberg to build lakehouse architectures, deploy interoperable data patterns, follow industry best practices, and migration strategies.

Hands-On Labs – We’ll have a hands-on lab to learn how to build production-ready architectures that deliver cost savings and performance gains.

Transform from AWS + Iceberg-aware to AWS + Iceberg-unstoppable!

This session is ideal for CDOs, CIOs, CTOs, data & analytics leaders, architects, BI teams, engineers, and decision-makers driving modernization and AI adoption.

* Breakfast, lunch, and networking included

**Seats are limited—secure your spot today and take the first step toward building your analytics and AI-ready future.

Note: Bring your own laptops, AWS Labs Sandbox will be provided

This workshop teaches AWS DevOps Agent, a frontier agent that resolves and proactively prevents incidents, continuously improving reliability and performance of your applications.

Adaptado a analistas de dados do Power BI sem experiência no Microsoft Fabric, esta formação prática ensina princípios da consolidação de dados e revela insights valiosos de forma clara e útil.

As enterprises move agents from experimentation into production, teams hit the same problems: agent sprawl with no reuse, shadow AI, no cost attribution, no unified tracing, non-standard integration, and unclear ownership after go-live. Scaling across business units also means deciding who can access enterprise data, which tools agents can use, how their behaviour is evaluated, and who is accountable when something goes wrong.

The answer is a shared agentic AI platform: an enterprise foundation for building, governing, observing and scaling agents safely, reusing enterprise controls instead of rebuilding them for every agent. This workshop shows how to stand that platform up on AWS with Amazon Bedrock AgentCore, then operate real workloads on it, with consistent platform controls and the flexibility for business units to build agents for their own needs.

What participants leave with:

• A working mental model of agent = model + harness, and the foundation vs domain split 
• A reproducible platform foundation pattern (multi-tenant design, identity, governance, gateways, model access, registry, etc.)  
• A hands-on understanding of multi-layered governance from org SCP to platform/domain gateway to project CI/CD gates 
• The governed workload pattern with different types of user journey  
• A view of operating models and a maturity-based next step for their own organisation 

Who should attend: AI engineers, platform engineers and architects, solution and cloud architects, and technical leads and engineering managers. The session is hands-on and code-focused, familiarity with Python helps. 

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

모델은 선택할 수 있지만, 보안·운영·관측성·비용의 책임은 인프라에 남습니다. OpenAI·Claude·Amazon Bedrock 등 어떤 모델을 쓰든, 멀티모델·Agentic 워크로드를 프로덕션에서 실제로 운영하는 기반으로서의 Amazon EKS를 하루 만에 경험하세요.

GenAI는 training → inference → agentic AI로 빠르게 옮겨가고 있습니다. 이 전환의 단계에서 실제 효율과 경제성, 그리고 인프라 비용을 측정하고 관리하는 역량이 점점 더 중요해지고 있습니다.

모델 API를 사용하든, 자체 모델(self-hosted)을 직접 운영하든 — LLM Gateway, Agent와 Tool, RAG, 인증, 네트워크, 확장, 관측(telemetry) 은 결국 여러분의 환경에서 운영됩니다. 특히 모델을 직접 서빙하는 경우에는 모델 추론 런타임 자체의 배포·확장·가속기 활용·비용까지 고객이 책임지게 됩니다. 그리고 어떤 기능·어떤 Agent loop·어떤 Pod가 비용과 리스크를 만드는지 설명할 수 있는 역량이 프로덕션 운영의 핵심이 됩니다.

본 행사는 단순한 특정 모델의 기능 소개를 넘어, GenAI를 새로운 형태의 분산 애플리케이션으로 바라보고 Amazon EKS를 멀티모델·Agentic 애플리케이션의 공통 런타임으로 다루고자 합니다. 배포·권한·확장·정책·관측을 하나의 플랫폼에서 표준화하는 방법을, 오전 세미나와 오후 핸즈온 랩을 통해 함께 살펴보시길 바랍니다.

🗓️ 행사 일정: 2026. 11. 10(화) 09:30–16:30

🏢 행사 장소: 센터필드 EAST 12층 (서울시 강남구 테헤란로 231)

👥 참석 추천 대상: GenAI·Agentic 워크로드를 더 잘 운영하고 싶은 분들을 환영하며, 특히 아래와 같은 고민을 해 오신 분들께 본 행사 참석을 추천드립니다.

• 멀티모델·Agent·RAG를 프로덕션에서 운영하며 공통 보안·운영·비용 표준이 필요한 Platform Engineering / AI Platform 팀
• EKS·Kubernetes 기반으로 운영하는 플랫폼 엔지니어 및 AI Ops
• AI 워크로드의 안정성·비용·관측성을 책임지는 SRE · Observability · DevOps 팀
• Cloud Security · FinOps 및 비용 귀속·공통 보안/운영 표준이 필요한 조직
• Amazon Bedrock·3rd party API·self-hosted 등 여러 LLM 호출을 통합하는 백엔드 엔지니어 및 엔지니어링 리드

안내 사항

- 방문 시 대중교통 이용을 권장드립니다. (자차 이용 시 센터필드 주차장 이용 가능하나, 주차권은 지원되지 않습니다)

- 참가비는 무료이며, 점심식사가 제공됩니다.

- 더 많은 고객분들을 모시기 위해 회사당 최대 참석 인원을 제한할 수 있음을 양해 부탁드립니다. 

- 핸즈온 실습을 위해 개인 노트북 개별 지참이 필요합니다.

- 문의사항이 있으신 경우 flexible-ai-korea@amazon.com 으로 연락주시기 바랍니다. 

Modern Data and AI Strategy for Agentic AI: Explore how organizations leverage agentic AI to create sustainable business value, examining real-world applications, implementation strategies, and measurable outcomes across industries. 

Demo of Amazon Quick Suite & Agentic AI: Experience firsthand how Quick Suite empowers organizations to rapidly deploy agentic AI solutions — from natural language querying to custom AI agents that automate complex workflows and unlock insights from enterprise data. 

One-on-One Engagement: Connect directly with AWS Data & AI strategists and/or partner specialists to discuss specific business needs, build a personalized roadmap, and explore funding options. 

This roundtable brings together data and AI strategy with Amazon Quick Suite's cutting-edge capabilities: 

• AI-Powered Analytics: Quick Research for deep-dive analysis and comprehensive reporting 
• Intelligent Automation: Quick Flows and Quick Automate to streamline workflows 
• Custom AI Agents: Build tailored solutions for specific business needs 
• Advanced Collaboration: Spaces for secure knowledge sharing and team productivity 

Tailored for Power BI Data Analysts, this hands-on workshop teaches you to make models chat-ready, unlock insights with natural language, and optimize data for Copilot.

About the event

Implement token tracking, monitoring and attribution across your entire AI estate — Amazon Bedrock, self-hosted models, and third-party APIs like Anthropic or OpenAI — and leave with a production-ready pattern that gives you a single pane of glass across every consumption environment.

If you’re asking any of these questions, this workshop is for you:

• “How do I trace token consumption per-request across Bedrock, OpenAI and my self-hosted vLLM endpoints?”
• “How do I set per-agent token budgets and circuit breakers before agentic loops run away?”
• “How do I route requests between managed APIs and self-hosted models based on cost / latency / quality?”
• “How do I attribute AI costs back to specific teams, services and use cases in my platform?”

Register Now

Seats are limited. Register now to secure your spot and accelerate your kubernetes platform engineering with AI

Join us for a 60-minute live session exploring how AWS DevOps Agent and CloudWatch Database Insights can work together to fundamentally shift your database operations from reactive incident response to proactive, automated management.

Through real-time demonstrations against various RDS and Aurora workloads, you'll walk away with practical knowledge for detecting performance anomalies early, diagnosing root causes faster, and automating common remediation steps.

What you'll learn:

• Build custom DevOps Agent skills that can detect and offer remediation for database issues such as runaway queries, connection saturation, and query degradation.
• Use Database Insights to trace performance issues down to individual queries, execution plans, and lock contention patterns with DevOps Agent.
• Use CloudWatch alarms to automatically trigger DevOps Agent skills in order to decrease MTTR

Session Highlights:

• Live incident simulation: Watch a real Aurora PostgreSQL performance degradation unfold, get diagnosed, and get resolved end-to-end
• Custom skill demo: See DevOps Agent execute and diagnose RDS/Aurora database issues in real time

Target Audience:

DBAs, SREs, DevOps engineers, and platform teams who manage production databases on AWS. Basic familiarity with Amazon RDS or Aurora is helpful but not required.

Build a complete Agentic AI platform on Amazon EKS. Deploy LLMs on AWS Neuron, set up a unified API gateway (Lite LLM) with observability (Langfuse), and create intelligent agents using LangGraph and MCP. Through a credit underwriting app, implement LLM-as-a-Judge evaluation, A/B routing, RAG with Milvus, and production security via Pod Identity, External Secrets, and Bedrock Guardrails. Full AI platform lifecycle from model serving to secure, scalable applications.

このワークショップでは、GitHub Copilot を単なるコード補完ツールとしてではなく、レガシーアプリケーションの理解、設計復元、移行計画、実装、検証、レビューをつなぐ AI エージェントとして活用し、モダナイゼーションを前に進める実践的な進め方を学びます。

Red Hat Summit Connect- Riyadh

第 9 回 AWS ジャパン 生成 AI Frontier Meetup を開催します。本イベントは生成 AI 実用化推進プログラム参加者の皆様、GENIAC関係者の皆様、生成 AI に興味をお持ちのお客様に対し、AWSスピーカーによる生成AIの最新トレンドやテクノロジーアップデートに関するセッションを通じて学びを深めていただくとともに、プログラム参加者間での成功事例や課題の共有、情報交換の場を設けます。また、生成 AI 開発モデルのプレゼンテーションや相談コーナーを設置します。これにより、潜在的なビジネスパートナーや顧客が直接対話し、技術やアイデアに触れる場を創出します。全体交流会を実施し、参加者間での情報交換や協業の可能性を含めた幅広いネットワーキングを促進します。このイベントを通じて、生成 AI 技術の実用化を加速し、新たなビジネス機会の創出と業界全体の発展に貢献することを目指します。 

2024 年11 月15 日に開催した第 1 回の様子はこちら から、2025 年 2 月 7 日に開催した第 2 回はこちら から、2025 年 4 月 16 日に開催した第 3 回はこちら から、2025 年 8 月 26 日に開催した第 4 回はこちら から、2025 年 11 月 17 日に開催した第 5 回はこちら から、2026 年 2 月 17 日に開催した第 6 回はこちら、2026 年 5 月 27 日に開催した第 7 回はこちら から、 2026 年 8 月 27 日に開催した第 8 回はこちら からご確認ください。

法人での参加となりますので勤務先メールアドレスでご登録ください。(フリーアドレスではご登録いただけません)
アジェンダは変更の可能性がございます。

Create a dashboard in just one day and learn the art of analyzing your data in a rich and compelling manner.

Challenge 0: Setup Challenge1: Cart feature Challenge2: Backlog feature Challenge3: Test and review Challenge4: Deploy to Azure Challenge5: Monitor and SRE Challenge6: Agentic workflows

Join us for a practical, hands-on technical event on applying agentic AI across the software development lifecycle.

Erstellen Sie ein Dashboard an nur einem Tag, und erfahren Sie, wie Sie Ihre Daten auf umfassende und überzeugende Weise analysieren.

Pensato per analisti Power BI esperti senza conoscenza di Microsoft Fabric, questo corso pratico presenta gli elementi essenziali per consolidare i dati e scoprire informazioni utili chiave bas.

Dieses praxisnahe Training richtet sich an erf. Power BI Data Analysts die erstmals mit Microsoft Fabric arbeiten und vermittelt Grundlagen zur Datenkonsolidierung und wertvollen Erkenntnissen.

Create a dashboard in just one day and learn the art of analyzing your data in a rich and compelling manner.

Microsoft Modernization & Sovereignty Hackathon | Tag 1

In this advanced 400-level workshop, you will learn how to optimize Amazon EKS and Karpenter for cost performance when running Apache Spark jobs and visualize job-level costs to inform decisions around migration, expansion, and ongoing optimization. Throughout the workshop, you will run the same Spark job five times. Before each run, you will apply different infrastructure configurations, including Spot instances, NVMe storage, and Graviton, and compare how quickly the job completes. In the final section, you will monitor and analyze cost per job. By the end of the workshop, you will be able to optimize analytics workloads on Spark on Amazon EKS, compare infrastructure options, and make informed cost-performance decisions.

GitHub Copilot Hands-on Lab

Red Hat Summit Connect- Sao Paolo

Red Hat Summit Connect- Montreal

Adobe MAX (Flagship - Creative)

Join this hands-on workshop to learn how to build a lakehouse with Azure Databricks and enhance data science, machine learning, data engineering, warehousing, and analytics.

Tailored for experienced Power BI Data Analysts new to Microsoft Fabric, this hands-on training will teach you the essentials of data consolidation and uncovering valuable insights.

Learn how to transform your infrastructure, applications, and data into an AI‑ready foundation that supports today’s workloads and enables future innovation.

Learning Objectives:

• Configure and enable AWS Transform
• Configure an AWS Transform workspace for VMware
• Assess VMware workloads for migration
• Create and execute transformation plans
• Validate migrated resources

Target audience:

Developers, architects, and cloud engineers who intend to apply AWS Transform transformation capabilities in real-life situations to accelerate migration and modernization goals.

Prerequisites:

• Amazon Virtual Private Cloud (Amazon VPC) and Networking
• AWS Identity and Access Management (IAM)
• AWS Application Migration Service (MGN)
• VMware environments (RVTools)

This workshop is level 300. Basic knowledge of Windows and Linux operating systems, VMware RVTools structure, data ingestion, network migration and wave plan leveraging AWS Application Migration Service is required.

Partners are invited to join the AWS Public Sector Team ahead of New Zealand Public Sector Cloud Day to meet the team and hear about our programs and region updates. 

Partner Central Agents Day（PCAD）とは？

Partner Central Agents Day（PAD）は、AWS パートナーが共同販売における Partner Central エージェントの可能性を最大限に引き出すための、対面型イネーブルメントイベントです。APJ の主要国で開催される PADでは、パートナーのセールス、アライアンス、技術チームが一堂に会し、ハンズオン学習、ライブデモ、ガイド付き実装を通じて、パートナーの環境でエージェントを稼働させ、AWS との共同販売活動を加速するための明確な計画作りのヒントを持ち帰ることができます。

参加すべき理由

Partner Central エージェントは、パートナーが AWS と共同販売する方法を変革しています。PADでは、仮想のシナリオではなく、実際のパイプラインに対してこれらの機能を有効化するために専門家のサポートを提供します。

エージェントでセールスチームを強化

• Partner Central エージェントが、チームの業務環境で共同パイプラインを管理

• アカウントインテリジェンスが、セールスサイクルを加速する適切なタイミングで表示されるよう設計

• アカウントごとにカスタマイズされたセールスプレイを自動生成

当日中のインテグレーション

• MCP インテグレーションの完了

• データフローの検証

• サンドボックス環境でのエージェント有効化

• CRM インテグレーション不要

導入プランを持ち帰る

• Partner Central AI ロードマップへの早期アクセス

• ユースケースを有効化するためのセルフサービスアクティベーションキット

• チーム全体でエージェント導入を拡大するための90日間導入プラン

参加前提条件

PADは、すでに Partner Central 3.0 へ移行済みのパートナーを対象としています。エージェント機能は移行後にのみアクセス可能なため、 Partner Central 3.0 移行を完了していることが必須の前提条件となります。まだ移行が完了していないパートナーは、登録前に移行を完了してください。また、本イベントを最大限に活用し、当日中の実装を実現するために、イベント当日までに下記の環境準備を行っていただく必要があります。

1. AWS マネジメントコンソールでの AWS Partner Central へのアクセスと必要な IAM ロール

2. Amazon Quick デスクトップおよび AWS CLI や Python など各種ツール

お申込みいただいた皆様には後日、詳細を記載したチェックリストを配布いたします。チェックリストを参照して事前の環境設定をお願いいたします。

参加対象者

【必須】Partner Central 管理者アクセス権を持つビジネス担当者（例：アライアンスリード）— ワークフローの自動化を設定し、ワークフロー内でエージェントインテグレーションを有効化します。

【必須】Partner Central サンドボックス環境および AWS アカウントでの管理・デプロイアクセス権を持つ技術担当者 — AWS エンジニアと直接連携し、エージェントのデプロイを完了し、リアルタイムでデータフローを検証します。

【任意】社内ツールの管理アクセス権を持つ技術担当者 — 社内ツール（CRM、Slack、Marketo など）を Partner Central エージェントおよびツールと連携させたい場合、AWS チームと協力してこれらのインテグレーションを設定・デプロイします。

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