Exercise Your Right to Vote in OpenStack Australia: Nested Containers, OpenStack Storage and Machine Learning

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Voting Just Opened for OpenStack Australia

The 2017 Openstack Summit just opened up voting for presentations to be given Nov. 6-8, Sydney, Australia. Mellanox has a long history of supporting OpenStack with technology and product solutions. Mellanox has submitted a number of technical papers and would like to urge readers to vote, vote, vote! The OpenStack Foundation receives more than 1,500 submissions and of these, they only select 25-35 percent for participation so your votes count.

In this blog, we will cover the topic and content of three of our submissions. There is only one short week to vote so please review the content and vote for your favorites. Voting begins July 25, 2017 and ends August 1, 2017.

First paper topic: Achieving The Best of Both Worlds: Running Highly Efficient Containers Inside High Performance VMs

Overview: Running containers within VMs (a.k.a. nested container) is a topic for debate. There are pros and cons associated with such a deployment model. Nested containers alleviate two major challenges; security/isolation and lack of popular orchestration tools. However, they solve these problems by degrading network performance drastically.

Traditionally, open vswitches running in a hypervisor have a poor network I/O performance. With nested containers, this performance degradation problem gets compounded even further. In addition to the software switch in hypervisor handling packets to various VMs, there is another software switch that is running in each VM that dispatches packets between the containers within VMs.

Vote here: Achieving The Best of Both Worlds: Running Highly Efficient Containers Inside High Performance VMs


In this presentation, we will present ways to accelerate packet switching at the hypervisor and VM level to improve performance of nested containers by an order of magnitude.

Second paper topic: Openstack Storage – Born to be fast!

Overview: OpenStack automates storage provisioning, but what about storage performance? As servers and drives get faster, how can cutting edge storage solutions remain flexible and deliver high throughput, low latency and high IO operations per second to demanding cloud applications?

In this presentation, Mellanox will explore three ways to accelerate OpenStack storage. All three utilize a standard, advanced network transport called Remote Direct Memory Access (RDMA), which increases storage performance and lowers CPU utilization. Highlights include:

  • The first is iSER (iSCSI Extensions for RDMA), which has been supported by Cinder since Kilo, and runs up to 5x faster than regular iSCSI.
  • The second is adding RDMA to Ceph. Ceph supports both block and object storage and can use RDMA on just the cluster network or on the client network.
  • The newest way to use RDMA is via NVMe over Fabrics (NVMe-oF).

Vote here: Openstack Storage – Born to be fast!


Third paper topic: Brain in the cloud: Machine Learning On OpenStack Done Right!

Overview: Machine Learning is, no doubt, the hottest trend in information technology these days. Deep Neural Network (DNN), a subfield of Machine Learning with structure and mode of operation loosely inspired by the brain, allows technologists to solve complex problems such as image recognition that has been very difficult or even impossible to solve using standard programming paradigms. Mellanox therefore believes that DNN will grow in popularity to become a standard tool for many applications.

DNN concepts are not new. However, and until recently, applying them in practice could not be realized due to their high computational demands. With the recent development in parallel computing, especially around GPU acceleration and high speed and efficient networking, DNN has become a reality in modern data centers.

In this presentation, Mellanox will describe the system requirements to effectively run a machine learning cluster with popular frameworks such as TensorFlow. This will include a discussion regarding how such a system can be deployed in an OpenStack-based cloud without compromises, enjoying high-performance DNN programming paradigm as well as the benefits of cloud and software-defined data centers. Finally, Mellanox will highlight a case-study from Monash University.

Vote here: Brain in the cloud: Machine Learning On OpenStack Done Right!

Mellanox has contributed to the open source community in all three areas and supports these solutions.

Thanks for voting and see you in Sydney!

Supporting Resources:

About Ash Bhalgat

Ash is Senior Director of Cloud Marketing at Mellanox. He leads market strategy, product/solutions marketing and ecosystem engagements for cloud service provider and telco cloud markets. Ash is an accomplished hi-tech industry leader focused on the intersection of technology, products/solutions and markets. He has deep experience in building and marketing high impact, fast revenue growth products/solutions at large, mid-size and startups including companies such as Cisco, Mellanox, Polycom, Luxoft and Hapoose. His professional experience spans across diverse technology domains including Cloud Services, Software Defined Networking, Server and Network Virtualization, Routing, Switching, Wi-Fi, Unified Communication and Collaboration, Network Management, Mobile Apps and End User Devices. Ash graduated summa cum laude with a B.E. is Electrical Engineering from University of Pune (India), M.S. in Computer Engineering from University of Cincinnati and M.B.A. from Santa Clara University. Connect with Ash on LinkedIn or Twitter.

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