Enhance Kubernetes Cluster Performance and Optimise Cost with Karpenter – Part 3
Discover how Karpenter enhances Kubernetes cluster performance and optimises costs in EKS. Learn how to monitor Karpenter using logs, metrics, and dashboards to gain full observability, identify scaling bottlenecks, and fine-tune your workloads for reliable, cost-efficient operations.
Enhance Kubernetes Cluster Performance and Optimise Cost with Karpenter – Part 2
Learn how to migrate from Kubernetes Cluster Autoscaler to Karpenter on Amazon EKS to improve scaling speed, reduce infrastructure costs, and increase resource efficiency. This deep dive also explores EKS Auto Mode, showing how cloud-managed autoscaling can further reduce operational overhead while improving security and reliability.
Kafka ZooKeeper to KRaft: The Next Chapter in Apache Kafka (MSK and Kafka 3.9 Support)
Apache Kafka’s move from ZooKeeper to KRaft simplifies metadata management, boosts scalability, and accelerates failover. Learn how Kafka 3.9 on Amazon MSK leverages Raft consensus to streamline operations and support large-scale event streaming.
AWS re:Invent 2025 Recap
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 Key Announcements
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.
Continuous Evolution: Building Adaptability in the Age Of AI
In the age of AI, standing still is not an option. Continuous evolution and adaptability are essential for organisations to thrive, harness technology, and turn rapid change into a competitive advantage.
Transforming Data Engineering with DevOps on the Databricks Platform
The role of the Data Engineer is rapidly changing, from writing ETL scripts to engineering production-grade data products. On the Databricks Lakehouse Platform, this shift demands more than technical know-how; it requires a DevOps mindset. By embracing software engineering best practices, automated testing, and CI/CD pipelines, data teams can deliver scalable, reliable, and secure solutions. This blog explores how DevOps principles and tools like Git Folders and Databricks Asset Bundles are transforming data engineering into a discipline of continuous innovation and delivery.
Measuring Agentic AI ROI: Introducing The Triad ROI Framework
Agentic AI is redefining how enterprises measure success — not just in innovation, but in real financial returns. In this second step toward Agentic AI excellence, we introduce the Triad ROI Framework, a practical model for quantifying value across cost savings, revenue growth, and risk reduction. Learn how to assess impact over time, track the right metrics, and build the foundations for sustainable AI-driven performance.
Agentic AI: From Hidden Tool to Trusted Partner
Agentic AI is transforming the way we work, evolving from hidden tools in the shadows to trusted collaborators. In this blog, we explore the four stages of agentic AI, the key risks of data, hallucination, and context drift, and why human-in-the-loop governance is essential for building trust and maximising productivity.
How AI Became My Coding Assistant (And Why It Should Be Yours Too)
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.