Anees Shaikh
Anees Shaikh is with the Global Networking team at Google where he works on software systems to support network management, cloud networking, and routing security in Google’s production networks. Prior to joining Google, he was the Chief SDN Architect in the System Networking product group at IBM, and a research lead at the T.J. Watson Research Center working in all three major divisions (software, services, and systems) of IBM Research.
Anees has published widely in the areas of networking, cloud computing, and system management, and has been an invited speaker in numerous industry forums. He has also been active in a number of open source and standards efforts, including ONF, OpenStack, and IETF, as well as helping to found the OpenDaylight and OpenConfig projects.
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Despite coming up on two decades of network verification research, verification tooling continues to see limited real-world adoption and outages continue to occur. Relying on interviews with network engineers and our own experience as a large network operator, we ask why. These conversations reveal that the culprit is traditional verification's reliance on hand-crafted network models, which leads to issues with coverage, correctness, maintainability, and fidelity, ultimately hindering practical applicability and adoption.
To address this, we call for the research community to embrace "model-free verification" through network emulation. Recent technology advancements – maturation of orchestration infrastructure and vendor-provided container images – make it possible to leverage emulation to obtain a high-fidelity converged dataplane from actual router control plane code, and then apply established dataplane verification techniques to this extracted state. We prototype such a system with open-source components, and present early results showing this approach can accurately verify configurations previously untestable, paving the way for more robust, practical network verification.
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We highlight a problem that the networking community has
largely overlooked: ensuring that the inputs to network controllers in software-
defined WANs are accurate. We we show that “incorrect” inputs are a common
cause of major outages in practice and propose new directions to address these.
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A Decentralized SDN Architecture for the WAN
Nitika Saran
Ashok Narayanan
Sylvia Ratnasamy
Ankit Singla
Hakim Weatherspoon
2024 ACM Special Interest Group on Data Communication (SIGCOMM) (2024)
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Motivated by our experiences operating a global WAN, we argue that SDN’s reliance on infrastructure external to the data plane has significantly complicated the challenge of maintaining high availability. We propose a new decentralized SDN (dSDN) architecture in which SDN control logic instead runs within routers, eliminating the control plane’s reliance on external infrastructure and restoring fate sharing between control and data planes.
We present dSDN as a simpler approach to realizing the benefits of SDN in the WAN. Despite its much simpler design, we show that dSDN is practical from an implementation viewpoint, and outperforms centralized SDN in terms of routing convergence and SLO impact.
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The Case for Validating Inputs in Software-Defined WANs
Rishabh Iyer
Isaac Keslassy
Sylvia Ratnasamy
The 23rd ACM Workshop on Hot Topics in Networks (HOTNETS ’24), ACM, Irvine, CA (2024) (to appear)
Preview abstract
We highlight a problem that the networking community has
largely overlooked: ensuring that the inputs to network controllers in software-
defined WANs are accurate. We we show that “incorrect” inputs are a common
cause of major outages in practice and propose new directions to address these.
View details
Invisinets: Removing Networking from Cloud Networks
Sarah McClure
Zeke Medley
Deepak Bansal
Karthick Jayaraman
Ashok Narayanan
Jitendra Padhye
Sylvia Ratnasamy
Rishabh Tewari
2023
Preview abstract
Cloud tenant networks are complex to provision, configure, and manage. Tenants must figure out how to assemble, configure, test, etc. a large set of low-level building blocks in order to achieve their high-level goals. As these networks are increasingly spanning multiple clouds and on-premises infrastructure, the complexity scales poorly. We argue that the current cloud abstractions place an unnecessary burden on the tenant to become a seasoned network operator. We thus propose an alternative interface to the cloud provider's network resources in which a tenant's connectivity needs are reduced to a set of parameters associated with compute endpoints. Our API removes the tenant networking layer of cloud deployments altogether, placing its former duties primarily upon the cloud provider. We demonstrate that this API reduces the complexity experienced by tenants by 80-90% while maintaining a scalable and secure architecture. We provide a prototype of the underlying infrastructure changes necessary to support new functionality introduced by our interface and implement our API on top of current cloud APIs.
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Experiences with Modeling Network Topologies at Multiple Levels of Abstraction
Martin Pool
Xiaoxue Zhao
17th Symposium on Networked Systems Design and Implementation (NSDI) (2020)
Preview abstract
Network management is becoming increasingly automated,
and automation depends on detailed, explicit representations
of data about both the state of a network, and about an operator’s intent for its networks. In particular, we must explicitly
represent the desired and actual topology of a network; almost all other network-management data either derives from
its topology, constrains how to use a topology, or associates
resources (e.g., addresses) with specific places in a topology.
We describe MALT, a Multi-Abstraction-Layer Topology
representation, which supports virtually all of our network
management phases: design, deployment, configuration, operation, measurement, and analysis. MALT provides interoperability across software systems, and its support for abstraction allows us to explicitly tie low-level network elements to high-level design intent. MALT supports a declarative style that simplifies what-if analysis and testbed support.
We also describe the software base that supports efficient use of MALT, as well as numerous, sometimes painful
lessons we have learned about curating the taxonomy for a
comprehensive, and evolving, representation for topology.
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Data Models for Optical Devices in Data Center Operator Networks
Nancy El-Sakkary
Vijay Vusirikala
OSA Technical Digest, OSA Publishing (2019)
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Standardized, vendor agnostic data models deliver major operational benefits. OpenConfig has been implemented on multiple platforms and is an ideal data model to take advantage of these benefits. This document provides an overview.
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Optical Zero Touch Networking - A Large Operator Perspective
Nancy El-Sakkary
Vijay Vusirikala
OSA Technical Digest, OSA Publishing (2019)
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A key area of innovation in optical networking has been enabling modern, vendoragnostic APIs on devices. We provide specifics of how these new capabilities enable deployment and operational efficiencies.
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Despite remarkable developments in open networking and SDN, a critical element of operating any network, the management plane, remains an afterthought. As the control and data planes open up, users are still firmly locked into a myriad of proprietary CLIs, APIs, and extensions to configure and monitor the network. In this talk, the presenters will describe a new way of managing, monitoring, and testing networking systems that is vendor-independent, comprehensive, and devised by a broad set of network operators collaborating with equipment and software vendors. The technologies in this ecosystem are designed for automated management systems and include open source data models, development tools, management protocols, and reference implementations. With these tools, the industry have an open, end-to-end open architecture that finally brings network management into the modern SDN era.
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Optical Network Control & Management Plane Evolution-A Large Datacenter Operator Perspective
Nancy El-Sakkary
Vijay Vusirikala
OSA Technical Digest, OSA Publishing (2019)
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Legacy management technologies and concepts are a major blocker to efficiently building and operating a large scale optical network. We provide an overview of new, modern device management technologies and discuss deployment and operational efficiencies that they enable.
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