--- title: TCC 2025 Digest venue: TCC year: 2025 date: '2025-01-01' tags: [] paper_count: 12 draft: false --- 12 papers selected. --- ### DRKC: Deep Reinforcement Learning Enhanced Microservice Scheduling on Kubernetes Clusters in Cloud-Edge Environment *Jian Jiang, Qianmu Li, Pengchuan Wang, Yunhuai Liu* **TL;DR** — DRKC uses deep reinforcement learning to schedule microservices across Kubernetes clusters spanning cloud and edge nodes, optimizing latency and resource utilization. **Why notable** — One of the few papers to tackle DRL-based microservice placement at the Kubernetes level in a real cloud-edge topology, making it directly actionable for practitioners. --- ### DesFaaS: Cross-Layer Joint Dynamic Deployment System for Serverless Stateful Functions *Yuquan Jing, Binbin Feng, Zhijun Ding* **TL;DR** — DesFaaS jointly optimizes the placement and lifecycle of stateful serverless functions across compute, network, and storage layers to reduce latency and cost. **Why notable** — Addresses the hard problem of state management in FaaS by co-designing across layers, opening a new direction for stateful serverless architectures. --- ### CARL: Cost-Optimized Online Container Placement on VMs Using Adversarial Reinforcement Learning *Prathamesh Saraf Vinayak, Saswat Subhajyoti Mallick, Lakshmi Jagarlamudi, Anirban Chakraborty 0001 *et al.** **TL;DR** — CARL applies adversarial reinforcement learning to online container bin-packing on cloud VMs, minimizing cost while handling adversarial workload patterns. **Why notable** — The adversarial training objective makes the scheduler robust to worst-case workload shifts, a significant advance over standard RL-based placement. --- ### CADER: Cost-Efficient Cloud Application Deployment With Tenant Requirement Guarantee in Multi-Clouds *Huaqing Tu, Ziqiang Hua, Qianpiao Ma, Hanguang Luo *et al.** **TL;DR** — CADER places cloud application components across multiple providers to minimize cost while enforcing per-tenant SLA and data-locality constraints. **Why notable** — Provides a rigorous multi-cloud placement framework that balances cost and tenant requirements, directly addressing a key challenge in multi-cloud SaaS/PaaS deployments. --- ### Cloud Load Balancers Need to Stay Off the Data Path *Yuchen Zhang, Shuai Jin, Zhenyu Wen, Shibo He *et al.** **TL;DR** — Based on large-scale production experience, this paper argues and demonstrates that cloud load balancers should operate out-of-band to eliminate throughput bottlenecks at scale. **Why notable** — A rare production-grounded architectural insight from a major cloud provider that challenges conventional in-path load balancer designs. --- ### PHOENIX: Misconfiguration Detection for AWS Serverless Computing *Jinfeng Wen, Haodi Ping* **TL;DR** — PHOENIX automatically detects security and correctness misconfigurations in AWS Lambda deployments by analyzing IAM policies, triggers, and function configurations. **Why notable** — Serverless misconfiguration is a leading cause of cloud security incidents; PHOENIX provides an automated, deployable detection tool for AWS environments. --- ### FaaSScout: Fast and Full Lifecycle RCA for FaaS Applications Using Salient Feature Mining *Min Li 0065, Jin Huang, Pengfei Chen 0002, Chongkang Tan* **TL;DR** — FaaSScout performs root cause analysis across the full FaaS invocation lifecycle by mining salient features from traces and logs to localize faults quickly. **Why notable** — Fills a critical operational gap for serverless: fast, automated fault diagnosis that covers cold starts, platform issues, and application errors in a unified framework. --- ### Hybrid Serverless Platform for Smart Deployment of Service Function Chains *Sheshadri K. R, J. Lakshmi* **TL;DR** — A hybrid serverless platform that intelligently places NFV service function chains on serverless infrastructure, reducing provisioning overhead while meeting latency targets. **Why notable** — Bridges serverless computing and NFV, demonstrating that serverless abstractions can be applied to network function deployment with competitive performance. --- ### PiCoP: Service Mesh for Sharing Microservices in Multiple Environments Using Protocol-Independent Context Propagation *Hiroya Onoe, Daisuke Kotani, Yasuo Okabe* **TL;DR** — PiCoP extends service mesh capabilities to span heterogeneous protocol environments by providing protocol-independent context propagation for distributed microservice tracing and control. **Why notable** — Solves a practical multi-cloud and hybrid deployment challenge where microservices communicate over different protocols, enabling unified observability and policy enforcement. --- ### A Reference Architecture for Governance of Cloud Native Applications *William Pourmajidi, Lei Zhang 0078, John Steinbacher, Tony Erwin *et al.** **TL;DR** — Proposes and validates a reference architecture that unifies policy enforcement, compliance, and lifecycle governance for cloud-native applications across deployment environments. **Why notable** — Provides a vendor-neutral governance blueprint grounded in industry practice, filling a gap between DevOps tooling and organizational cloud compliance requirements. --- ### Observability and Incident Response in Managed Serverless Environments Using Ontology-Based Log Monitoring *Lavi Ben-Shimol, Edita Grolman, Aviad Elyashar, Inbar Maimon *et al.** **TL;DR** — Uses an ontology-based approach to monitor serverless function logs, enabling structured incident detection and response in managed FaaS environments. **Why notable** — Brings structured knowledge representation to serverless observability, enabling richer incident correlation than rule-based or purely ML-based log monitors. --- ### A Run-Time Framework for Ensuring Zero-Trust State of Client's Machines in Cloud Environment *Devki Nandan Jha, Graham Lenton, James Asker, David Blundell *et al.** **TL;DR** — A runtime attestation framework continuously verifies the security posture of client machines accessing cloud resources, enforcing zero-trust policies based on live system state. **Why notable** — Moves zero-trust enforcement from static policy configuration to continuous runtime verification, addressing a key gap in current cloud access control models.