December 2025 Summaries

DevOpsDays Tel Aviv, scheduled for December 11, 2025, at Expo Tel Aviv, Pavilion 10, will feature sessions aimed at enhancing cloud monitoring and cost management. A notable speaking session by Aviv Zohari, Field CTO at groundcover, will address the issue of cross-availability zone (AZ) traffic that can inflate cloud bills by using eBPF for real-time traffic analysis without sidecars or packet drops. This session will provide insights on tracing network flows back to specific services, nodes, and zones, offering platform teams the visibility needed to manage cloud costs effectively. Additionally, a demo theater session led by Shahar Azulay, Co-founder & CEO at groundcover, will explore full-stack observability for complex AI systems, such as large language models (LLMs) and autonomous agents, emphasizing the importance of visibility and control in these environments.

Security context is a crucial concept in IT security that defines access rights and privileges for resources within applications, operating systems, and container orchestration platforms like Kubernetes. It allows organizations to establish granular access controls, helping to mitigate security risks by ensuring that IT resources only have the permissions necessary for their specific roles, akin to giving different keys to different people in an office building based on their needs. Implementing security context involves configuring rules that govern each resource's access capabilities, which are then automatically enforced by controllers to prevent unauthorized actions. Misconfigurations, such as allowing containers to run with root privileges or neglecting to set filesystems as read-only, can undermine the effectiveness of security context, highlighting the importance of proper configuration and adherence to best practices like enforcing least privilege and robust authentication. Emerging trends include the use of AI to automate the generation and management of security contexts, enhancing efficiency and adaptability in environments with dynamic access needs. Additionally, observability solutions like groundcover complement security contexts by providing insights into resource activities, enabling organizations to detect anomalies and ensure that security policies are enforced properly, thereby enhancing the overall security posture.

Groundcover addresses the challenges of monitoring Large Language Models (LLMs) in production environments by providing comprehensive observability tools that offer insights into aspects like request volume, latency, errors, and costs. Traditional monitoring tools fail to provide the necessary visibility into LLMs, which often function as black boxes in the technology stack. Groundcover's solution leverages eBPF technology, enabling developers to monitor LLM activity without the need for additional instrumentation or SDKs, thus eliminating blind spots. The platform supports AWS Bedrock alongside OpenAI and Anthropic, providing a unified view of LLM performance across different providers, and ensures data residency and security within an AWS instance. This observability is crucial for understanding and controlling costs, as LLMs can quickly become expensive if not monitored properly. Moreover, the integration of LLM observability with other monitoring metrics like CPU, memory, and network allows teams to identify and address issues efficiently, preventing costly outages and ensuring data safety by flagging sensitive information. As the AI landscape rapidly evolves, having such visibility is essential for teams to manage AI systems effectively and maintain operational integrity from the onset of LLM adoption.