Atos (France)

Kubernetes plays an important role nowadays in enabling cloud-native telecom and microservices management in 5G/6G networks. It provides a platform for deploying, scaling, and managing cloud-native micro-services but also 5G/6G core functionalities. In this work, we demonstrate the importance of misbehavior detection in Kubernetes clusters paired with suitable mitigation measures as a solid baseline to minimize disruption of 5G service delivery. We evidence the impact of two types of DoS attacks, blackholing and network DoS, and results of detection and mitigation in Kubernetes.

International audience

The global Stocktake, a fundamental component of the Paris Agreement tracking progress on national mitigation actions, collects the Nationally Determined Contributions (NDCs) generated through the means of annual national inventories. Carbon capture through the natural ecosystem is essential to reach the Paris Agreements and thus it is crucial to understand the interaction of the atmosphere/biosphere and its changes with global warming. We present the model performances of our regional inversion system over France for the year 2022, with a special focus on an extreme drought event that impacted southern Europe during the summer. Our inversion system optimizes CO2 fluxes from fossil fuel and biogenic fluxes at higher spatiotemporal resolutions over France (3km, hourly). The Lagrangian Particle Dispersion Model (LPDM) developed running in a backward-in-time model, driven by meteorological inputs from a 3-km run of the Weather Research Forecast Model (WRF-Chem), establishes the transport of CO2 molecules. Employing a Bayesian inversion technique, we optimize prior CO2 flux estimates by integrating tower footprints and ICOS atmospheric measurements into a newly developed inversion framework, combining block matrix decomposition and adaptive mesh refinement. We infer the prior flux estimates using the TNO high-resolution fossil fuel inventory and biogenic CO2 fluxes produced by the Vegetation Photosynthesis Respiration Model (VPRM). We start by evaluating the WRF-chem model performances at high resolution compared to low resolution simulations. Then we assess the meteorology and CO2 exchanges over continental France throughout the year 2022. With the Lagrangian Model, we can explore the actual ICOS network constraints by determining the share of biogenic and fossil fuel sources at each tower of the ICOS network. We discuss here how our inversion system could help constrain the regional distribution of CO2 fluxes, including sub-annual variations at seasonal and monthly timescales to track current climate change impacts (forest fires, droughts), and the effects of emission mitigation policies. Finally, we determine potential networks of surface stations (extension of the current ICOS network) to enable the monitoring of CO2 fluxes and emissions at policy-relevant scales over continental France.