Cloud platforms, services, and infrastructure
Found 61 articles
Effective cloud security architecture demands ongoing adaptation to align design with operational reality, ensuring security doesn't lapse over time.
Effective telemetry and observability are essential for maintaining system performance, especially at high scale, yet they pose significant challenges in implementation.
Different teams often adopt varying approaches to Kubernetes deployment, creating inefficiencies. Standardizing practices can streamline delivery and onboarding.
Observability in enterprises requires a nuanced approach that accounts for diverse systems and operational realities rather than just cloud-native models.
CloudBolt's new StormForge feature enables better GPU usage tracking in Kubernetes, offering insights for resource optimization and cost management.
Karmada, now CNCF-certified, enhances Kubernetes with centralized control for multi-cluster operations and AI workloads.
Groundcover's acquisition of Wand integrates automated Kubernetes resource optimization into its observability platform, enhancing efficiency for users.
Dependency mocking tools must evolve to meet the demands of cloud native architectures, ensuring test accuracy amidst rapid deployment changes.
Key-value databases enhance enterprise applications by simplifying data access, improving performance, and reducing infrastructure costs in cloud-native environments.
To ensure reliability in data-intensive apps, it's crucial to integrate data freshness into health checks, moving beyond traditional availability metrics.
Discover how to improve autoscaling for Rails applications by focusing on queue latency rather than CPU, leading to better responsiveness and user experience.
Production-safe security testing is crucial for identifying ongoing vulnerabilities in cloud-native applications, ensuring safety post-deployment.
Kubernetes is adapting to the demands of AI workloads, enhancing its capabilities without requiring a complete infrastructure overhaul.
DataAgent exits stealth with $10 million in pre-seed funding, offering an AI-driven platform designed to autonomously resolve Kubernetes production issues.
Effective cloud migration in regulated sectors hinges on managing compliance and risk, rather than merely choosing the right technology stack.
Continuous assurance is reshaping governance, risk, and compliance practices to keep pace with the rapid evolution of cloud-native technology.
Prompt injection in AI poses new security challenges; it's crucial to shift focus towards robust access control in cloud-native environments.
KEDA enhances autoscaling for AI workloads in Kubernetes by prioritizing workload demands over resource usage, improving efficiency and responsiveness.
Explore effective strategies for migrating legacy systems to cloud-native architectures, enabling responsive real-time AI capabilities.
Examine the hidden operational costs of cloud-native architecture and learn to evaluate platform components for better efficiency and value.