Web application security testing is more critical than ever as enterprises face growing threats and regulatory demands. This article breaks down essential components of an effective testing program—defining scope, blending automated and manual tools, integrating into the SDLC, and prioritizing risk. Learn how modern approaches like ASPM, AI, and continuous monitoring can help security teams stay ahead of evolving vulnerabilities and protect enterprise applications.

PointFive introduces a new approach to cloud cost management with Cloud Efficiency Posture Management (CEPM) — a discipline focused on optimizing cloud resource configuration, scaling, and architecture. Unlike traditional FinOps tools that emphasize spend visibility and discounts, CEPM continuously identifies root causes of inefficiency, delivers actionable insights, and embeds optimization into engineering workflows. From misconfigured DynamoDB tables to inefficient Aurora storage settings, PointFive helps teams move beyond surface-level cost savings to drive sustained performance, reliability, and cloud efficiency at scale.

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.

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.

Given the surge in web application data breaches, learn how to effectively store and secure sensitive data in your web applications. This article explores critical data types, client-side and server-side storage mechanisms, common OWASP Top 10 vulnerabilities, and essential protective measures like robust authentication, access control, and encryption strategies.

Discover how unchecked API sprawl creates critical security blind spots for fast-growing fintech startups, leading to data breaches and operational inefficiencies. Learn how Beagle Security's API discovery feature automatically uncovers and tests all APIs within Kubernetes or Istio environments, ensuring complete visibility and proactive vulnerability management.

Explore the true costs of penetration testing in 2025, breaking down pricing by scope (web, mobile, API, cloud, network, IoT) and methodology (black box, grey box, white box). Discover key factors influencing costs and learn how AI-powered solutions like Beagle Security offer a faster, more affordable alternative to traditional pen tests.

Explore the six evolving phases of FinOps, from the initial "Observational" data collection to "Automated" and the future of "Integrated FinOps," revealing how organizations learn to manage cloud spend and optimize infrastructure efficiently over time.

Unpack the concept of cost seasonality in Kubernetes, explore the factors that drive its fluctuations, and discover effective strategies—including right-sizing, autoscaling optimization, and leveraging tools like PerfectScale—to manage and predict your cloud spend while maintaining performance.

As AI adoption surges across industries, organizations face critical decisions about how to manage innovation, risk, and control. Open source AI offers enterprises the ability to “own their destiny” — providing transparency, flexibility, and customization that proprietary models often lack. However, with these benefits come challenges: security vulnerabilities, model drift, and cultural shifts in AI literacy. To succeed, businesses must build secure infrastructure, foster cross-functional collaboration, and establish governance pathways that empower safe innovation. The future belongs to cybernetic businesses — and those that proactively shape their AI strategies today will lead tomorrow.

The data science and machine learning (DSML) landscape is exploding with innovation, but it's also bringing new complexities! Organizations are grappling with the critical need to manage intricate AI development lifecycles, ensure robust governance and security for open-source components, and scale deployments without a hitch. The article dives into how these escalating challenges demand more than just tools—they require comprehensive, secure, and flexible solutions to truly unleash AI's full potential! It's an exciting time, and the focus is squarely on building a trusted foundation for the future of AI.

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