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How to store and secure sensitive data in web applications
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.
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Master API security: Securing your entire API ecosystem with Beagle Security’s API discovery
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.
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How much does pen testing cost (2025)
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.
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FinOps in 2025: The 6 Phases of FinOps Evolution
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.
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Understanding Cost Seasonality in Kubernetes
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.
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Simplify Database Management with the MariaDB Enterprise Kubernetes Operator
The MariaDB Enterprise Kubernetes Operator simplifies managing MariaDB Enterprise Platform on Kubernetes. Acting as an embedded DBA, it leverages Kubernetes Custom Resource Definitions (CRDs) to automate deployment and operation of complex MariaDB topologies, including high-availability Galera clusters and MaxScale setups, using simple YAML files. Key features include effortless deployment, seamless rolling upgrades with minimal downtime, automated backups and recovery, and enhanced security. This operator enables advanced high availability with Galera and integrated load balancing with MaxScale, unlocking enterprise-grade features. Certified for Red Hat OpenShift, it reduces operational complexity, ensures data availability and security, and is available with a MariaDB Enterprise Platform Plus subscription.
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Quick Start Environments: Simplifying AI Development for Practitioners
Say Goodbye to Setup Headaches: Anaconda Unleashes Quick Start Environments! Every data scientist, ML engineer, and developer knows the agony of environment setup – hours lost to dependency conflicts instead of actual analysis. Anaconda is revolutionizing this pain point with its new Quick Start Environments for Jupyter Notebooks within the Anaconda AI Platform! Imagine expert-assembled toolkits, meticulously pre-configured with the optimal mix of tested, compatible packages, ready to launch with a single click. From a Python Starter for beginners to a comprehensive Anaconda Distribution, specialized Finance, and focused AI/ML Starter Environments, these solutions eliminate frustration and supercharge productivity. Discover how these game-changing environments standardize workflows, accelerate onboarding, and free you to focus on innovation, not infrastructure!
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Navigating the Evolving AI Landscape How Anaconda is Reshaping Data Science and Machine Learning Platforms
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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Enterprise Open Source AI: Navigating Risk, Securing Innovation, and Owning Your Destiny
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.
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Integrated password security with Bitwarden SSO
Enhance your organization’s security and simplify user access with Bitwarden Login with SSO. This feature integrates identity-based single sign-on (SSO) with Bitwarden’s zero-knowledge encrypted password manager, supporting SAML 2.0 and OpenID Connect. Ideal for enterprises, it enables seamless authentication through existing identity providers while extending protection to all apps—even those without native SSO support.
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Bitwarden and the passwordless security revolution
Passwordless authentication is the future. Although multifactor authentication (MFA) is still viable, it's not as strong and reliable as the authentication factor found in passwordless authentication.
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DevOps tool sprawl: is ‘tool tax’ just the tip of the iceberg
DevOps tools streamline automation, but tool overload causes chaos. Discover why tool simplicity, seamless integration, and usability matter—and how tool sprawl is becoming a major DevOps challenge.