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  1. PostgreSQL® extensions you need to know in 2025

    Uncover the pivotal role of PostgreSQL's extensions ecosystem, its historical context, and why it remains indispensable for modern data needs, including AI and analytics. Dive into key extensions like TimescaleDB, PostGIS, and pgvector, and learn how a managed service, like Aiven, mitigates risks and enhances reliability.

  2. Practical AI security in multi-cloud environments

    As organizations rapidly adopt generative and agentic AI tools across multi-cloud environments, securing those systems has never been more critical. This article explores the key challenges of AI security—such as visibility gaps, runtime threats, and compliance pressures—and outlines best practices for building a strong AI security posture. From continuous monitoring with Falco to managing AI-specific risks with frameworks like MITRE ATLAS and OWASP AI, learn how to protect your AI infrastructure against evolving threats and regulatory demands.

  3. Private Tunnels: Benefits and Setup for Businesses

    Unmask the power of private tunnels! Discover how these secure passageways encrypt data, mask IPs, and leverage intrusion prevention for ultimate online privacy. Learn their benefits, setup essentials, and how solutions like Netmaker elevate network security for businesses.

  4. Prometheus data source update: Redefining our big tent philosophy

    Grafana is redefining its "big tent" philosophy! Discover how purpose-built data sources, like the new plugins for Amazon Managed Service for Prometheus and Azure Monitor Managed Service for Prometheus, enhance interoperability and cater to specific cloud use cases, empowering users to centralize observability without sacrificing vendor neutrality or functionality.

  5. Protecting Kubernetes environments with OX Security: A holistic approach to cloud-native security

    Learn how to secure your Kubernetes environments with OX Security and how it can help you manage the complexities of cloud-native architectures.

  6. Quick Start Environments: Simplifying AI Development for Practitioners

    Skip setup hassles—Anaconda’s Quick Start Environments let data pros launch pre-built, conflict-free workspaces instantly and start building faster.

  7. Rails debug mode enabled

    Uncover the critical security risks of running Ruby on Rails in development mode on a live server, from exposing internal workings and sensitive information to increasing the risk of remote code execution and DoS attacks. Learn practical steps to safeguard your application and prevent these vulnerabilities.

  8. Recruit Wizard scaled and moved to daily deployments with Octopus Cloud

    Recruit Wizard transformed its software delivery by adopting Octopus Deploy for full deployment automation across Kubernetes and virtual machines. Moving from quarterly to daily deployments, the team now uses Config as Code and Runbooks to streamline releases, reduce errors, and empower non-engineering staff to run operational tasks independently. With Octopus Cloud, they’ve modernized and scaled their deployments while staying focused on growth and innovation in recruitment software.

  9. Redefining Access: Teleport on Zero Trust, Infrastructure Identity, and the Future of Cloud Security

    Dave Sudia from Teleport shares expert insights on cloud-native security, Zero Trust, and task-based access control—reshaping infrastructure identity for today’s evolving access needs.

  10. Reducing MTTR with Grafana Cloud: Inside ASOS’ observability stack

    To deliver on that experience time and time again, the ASOS engineering team relies on Grafana Cloud for real-time observability.

  11. Revolutionizing Authorization: What’s Next for Cerbos

    Alex Olivier of Cerbos explores the future of authorization, KubeCon highlights, and how externalizing policy management simplifies scale and security for modern applications.

  12. Running LLMs on Kubernetes: From GPU Bottlenecks to Reliable, Production-Grade Inference

    Abdel Sghiouar explores Kubernetes’ evolution, from enterprise adoption to GenAI workloads, highlighting hardware challenges, operational hurdles, and community-driven innovations.

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