AWS re:Invent 2025 marked a major shift in Agentic AI, with tangible solutions like Bedrock AgentCore, AWS Security Agent, and DevOps Agent transforming how AI agents are orchestrated and deployed. Security Hub went GA, multimodal AI capabilities advanced, and hands-on workshops highlighted real-world applications. This recap covers the key announcements, innovations, and human connections that made re:Invent 2025 a landmark event for AWS builders and partners.
AWS re:Invent 2025 delivered one of the most transformative years of innovation yet, signalling a major shift toward AI-native cloud platforms, frontier-scale infrastructure and streamlined developer experiences. From AgentCore and Nova 2 to Trainium3 UltraServers, S3 Vectors and multicloud networking with Google Cloud, AWS introduced capabilities that will fundamentally change how engineering teams build, automate and scale. In this blog, we break down the biggest announcements and what they mean for organisations looking to modernise, innovate and move faster with confidence.
AI coding assistants are changing how developers work. In this blog, Ian Ng shares how Amazon Q Developer became a powerful coding partner, helping automate routine tasks so developers can focus on architecture, problem-solving, and building better solutions faster.
A winning data strategy combines strong governance, reliable quality, and scalable architecture to drive measurable outcomes. With AWS and Cevo’s Data Strategy Diagnostic, organisations can build the foundation for AI-driven innovation and long-term growth.
CSV files are simple, flexible, and everywhere but they’re also one of the easiest ways for sensitive customer data to leak. In this guide, we show you how to use AWS Glue Studio’s no-code, ML-powered transforms to automatically detect and redact PII in CSV files. With step-by-step instructions, you’ll learn how to protect data at ingestion, ensure compliance, and build pipelines that keep analytics both powerful and privacy-first.
Data is everywhere but without a clear strategy, it can hold your business back instead of moving it forward. In this blog, we share how the AWS Data Strategy Diagnostic helps organisations assess their data maturity, uncover gaps, and build a practical roadmap to turn data into real business value.
Unit testing JSONata in AWS Step Functions doesn’t have to be painful. By separating JSONata templates into their own files, introducing a simple template manager, and running fast local unit tests, you can validate transformations in milliseconds, without deploying to AWS. This framework makes debugging easier, feedback loops faster, and Step Functions more maintainable.
Prompt engineering for AWS has transformed the way I work in cloud consulting. By learning to give AI tools like Amazon Q and Amazon Bedrock the right context, constraints, and roles, I’ve gone from getting generic answers to receiving tailored, cost-saving solutions. In this post, I share the practical techniques that turn AI into a true partner for solving complex AWS challenges.
Many teams treat Infrastructure as Code maintenance as a “nice to have” until outdated tools bring productivity to a standstill. This blog explores the hidden costs of standing still, why small, continuous updates matter, and how smarter maintenance leads to real cost optimisation and long-term resilience.
As data breaches surge across Australia, protecting Personally Identifiable Information (PII) has never been more urgent. In this practical guide, I share why PII redaction in the cloud is essential for both compliance and resilience and how AWS-native tools can help you detect, redact, and govern sensitive data at scale. Whether you’re just starting out or refining an existing approach, this article offers real-world strategies to reduce breach impact and build customer trust.
