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Home » Collections for April Joy Deang

About April Joy Deang

April is an 3x AWS Certified. A lifelong learner, she believes that knowledge is ever-evolving and is currently exploring the transformative potential of Artificial Intelligence (AI).

AWS Data and AI Journey: Building Agentic AI Systems

2026-05-22T18:05:08+00:00

Stage 5 of the AWS Data and AI Journey: Building Agentic AI Systems Building agentic AI systems is the next frontier for organizations that have already laid the groundwork with a modern data foundation, governed pipelines, and enterprise-wide generative AI. This is where agentic AI enters the picture. Generative AI systems can answer questions, summarize documents, and generate content. Agentic AI goes further by enabling systems to reason through tasks, interact with tools, make decisions, coordinate workflows, and complete multi-step objectives with limited human intervention. Instead of acting only as assistants, AI systems begin operating more like autonomous digital workers [...]

AWS Data and AI Journey: Building Agentic AI Systems2026-05-22T18:05:08+00:00

AWS Data and AI Journey: Applying Generative AI Across the Enterprise

2026-05-22T17:20:47+00:00

Stage 4 of the AWS Data and AI Journey: Applying Generative AI Across the Enterprise Applying generative AI across the enterprise is no longer just an experiment, it's a strategic priority for organizations ready to turn their data into real business intelligence. This is where generative AI enters the picture. With trusted, connected, and governed data in place, organizations can confidently apply large language models, retrieval systems, and AI agents to real business problems. Generative AI shifts data from being a record of what happened into an active driver of decisions, automation, and customer experience. Stage 4 of the AWS [...]

AWS Data and AI Journey: Applying Generative AI Across the Enterprise2026-05-22T17:20:47+00:00

AWS Data and AI Journey: Data Governance and Security

2026-04-27T15:18:02+00:00

Stage 3 of the AWS Data and AI Journey: Data Governance and Security As organizations establish a modern data foundation (Stage 1) and enable seamless data movement (Stage 2), the next critical step is ensuring that data remains trusted, secure, and compliant across the entire ecosystem. At this stage, data is no longer confined to a single platform. It flows across cloud services, SaaS applications, analytics environments, and AI systems. Without strong governance and security, this expanded data landscape introduces risks such as unauthorized access, data leakage, compliance violations, and loss of trust in data. Stage 3 focuses on building [...]

AWS Data and AI Journey: Data Governance and Security2026-04-27T15:18:02+00:00

AWS Data and AI Journey: Integrating and Moving Data Across Systems

2026-03-14T14:56:39+00:00

Stage 2 of the AWS Data and AI Journey: Integrating and Moving Data Across Systems As organizations build a modern data foundation, the next challenge is ensuring that data can move efficiently across systems, teams, and applications. Even with scalable storage and analytics platforms in place, data often remains fragmented across cloud services, SaaS tools, on-premises environments, and operational systems. Without reliable integration, data becomes delayed, siloed, or difficult to operationalize. This limits an organization’s ability to generate timely insights, automate workflows, and support AI-driven decision-making. Stage 2 of the AWS Data and AI journey focuses on integrating and moving [...]

AWS Data and AI Journey: Integrating and Moving Data Across Systems2026-03-14T14:56:39+00:00

AWS Data and AI Journey: Modernizing Your Data Foundation

2026-03-14T15:34:06+00:00

Stage 1 of the AWS Data and AI Journey: Modernizing Your Data Foundation Artificial intelligence systems are only as powerful as the data infrastructure supporting them. Many organizations want to adopt advanced AI capabilities, but they quickly discover that their data architecture is not ready. Data may be fragmented across systems, stored in legacy databases, or difficult to scale. Before machine learning, generative AI, or autonomous agents can deliver meaningful outcomes, organizations must first establish a modern data foundation. This first stage of the AWS data and AI maturity journey focuses on building a cloud-ready, scalable, and unified data platform [...]

AWS Data and AI Journey: Modernizing Your Data Foundation2026-03-14T15:34:06+00:00

The Economics of AI Infrastructure: Understanding AWS AI Factories

2026-03-05T16:37:43+00:00

Artificial intelligence has shifted from being a software innovation challenge to becoming an infrastructure challenge. Organizations no longer struggle primarily with model design. Instead, organizations are increasingly challenged by compute density, energy consumption, networking scale, and operational complexity when deploying modern AI systems. As large-scale generative AI systems become central to business strategy, infrastructure decisions now carry long-term economic consequences. This is the context in which AWS AI Factories emerged. First announced at AWS re:Invent, AWS AI Factories introduce a new economic model for enterprises that require large-scale AI infrastructure. Moreover, these organizations may struggle to rely entirely on public [...]

The Economics of AI Infrastructure: Understanding AWS AI Factories2026-03-05T16:37:43+00:00

Improving Application Security with AWS Security Agent

2026-03-05T14:39:52+00:00

Modern software teams are very fast today. Code is pushed daily. Pipelines deploy automatically. Features reach users quickly. This is the success of DevOps. But security often does not move at the same speed. In many organizations, security reviews are still scheduled monthly or quarterly. Penetration tests require coordination. Findings come late. When issues are discovered, teams must pause releases and fix problems under pressure. This gap between fast development and slow security creates risk. To solve this, companies are moving toward DevSecOps where security becomes part of the development process itself. This is where AWS Security Agent becomes important. [...]

Improving Application Security with AWS Security Agent2026-03-05T14:39:52+00:00

Reinforcement Fine-Tuning in Amazon Bedrock: A Practical Guide for Enterprise AI

2026-02-26T16:29:47+00:00

Large language models are powerful, but power alone is not enough for enterprise AI. A model may generate fluent responses, yet still miss your company’s tone, fail structured validation rules, or produce outputs that are technically correct but operationally unusable. The real challenge is not just making models smarter, it is teaching them what better means in your specific business context. This is exactly where Reinforcement Fine-Tuning (RFT) in Amazon Bedrock changes the game. The Problem with Traditional Fine-Tuning Most model customization strategies start with Supervised Fine-Tuning (SFT). In SFT, you provide input-output pairs that represent correct responses. The model [...]

Reinforcement Fine-Tuning in Amazon Bedrock: A Practical Guide for Enterprise AI2026-02-26T16:29:47+00:00

Defending Against AI-Powered Cyberattacks with AWS

2026-02-04T13:10:58+00:00

The cybersecurity landscape is evolving rapidly because AI-powered cyberattacks are becoming more advanced. In particular, attackers leverage artificial intelligence (AI) to automate phishing, bypass traditional defenses, and target machine learning models. Consequently, these AI-powered cyberattacks are faster, more sophisticated, and harder to detect than ever before. Fortunately, AWS provides a suite of AI-driven security services. Moreover, these services enable organizations to detect, prevent, and respond to modern threats, thereby keeping applications, data, and workloads safe in the cloud. Understanding AI-Powered Cyberattacks In practice, AI-powered cyberattacks are a new breed of cyberthreats that leverage machine learning and automation to outsmart defenders. [...]

Defending Against AI-Powered Cyberattacks with AWS2026-02-04T13:10:58+00:00

Understanding the Agentic AI Security Framework: Made Easy

2026-02-04T13:22:03+00:00

Agentic AI is changing how we think about artificial intelligence. Instead of waiting for prompts, these systems can plan tasks, make decisions, and act on their own. They behave more like digital teammates than static tools, completing multi-step work and coordinating across apps, data, and even other agents all without constant human supervision. But with this new power comes new responsibility. When AI agents can access tools, call APIs, store memory, and influence other agents, the risks are no longer limited to “bad prompts” or one-time outputs. Autonomy introduces new attack surfaces: reasoning can be manipulated, memory can be poisoned, [...]

Understanding the Agentic AI Security Framework: Made Easy2026-02-04T13:22:03+00:00

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