Tuning for Zero Packet Loss in Red Hat OpenStack Platform – Part 3

In Part 1 of this series Federico Iezzi, EMEA Cloud Architect with Red Hat covered the architecture and planning requirements to begin the journey into achieving zero packet loss in Red Hat OpenStack Platform 10 for NFV deployments. In Part 2 he went into the details around the specific tuning and parameters required. Now, in Part 3, Federico concludes the series with an example of how all this planning and tuning comes together!

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Tuning for Zero Packet Loss in Red Hat OpenStack Platform – Part 2

Ready for more Fast Packets?!

In Part 1 we reviewed the fundamentals of achieving zero packet loss, covering the concepts behind the process. In his next instalment Federico Iezzi, EMEA Cloud Architect with Red Hat continues his series diving deep into the details behind the tuning.

Buckle in and join the fast lane of packet processing!

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Tuning for Zero Packet Loss in Red Hat OpenStack Platform – Part 1

For Telcos considering OpenStack, one of the major areas of focus can be around network performance. While the performance discussion may often begin with talk of throughput numbers expressed in Million-packets-per-second (Mpps) values across Gigabit-per-second (Gbps) hardware, it really is only the tip of the performance iceberg. The most common requirement is to have absolutely stable and deterministic network performance (Mpps and latency) over the absolutely fastest possible throughput. With that in mind, many applications in the Telco space require low latency that can only tolerate zero packet loss.

In this “Operationalizing OpenStack” blogpost Federico Iezzi, EMEA Cloud Architect with Red Hat, discusses some of the real-world deep tuning and process required to make zero packet loss a reality!

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Red Hat joins the DPDK Project

Today, the DPDK community announced during the Open Networking Summit that they are moving the project to the Linux Foundation, and creating a new governance structure to enable companies to engage with the project, and pool resources to promote the DPDK community. As a long-time contributor to DPDK, Red Hat is proud to be a founding Gold member of the new DPDK Project initiative under the Linux Foundation.

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SDN with Red Hat OpenStack Platform: OpenDaylight Integration

OpenDaylight is an open source project under the Linux Foundation with the goal of furthering the adoption and innovation of software-defined networking (SDN) through the creation of a common industry supported platform. Red Hat is a Platinum Founding member of OpenDaylight and part of the community alongside a list of participants that covers the gamut  from individual contributors to large network companies, making it a powerful and innovative engine that can cover many use-cases.

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OpenStack Use Cases – New Analyst Papers and Webinar Now Available

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As the OpenStack market continues to mature, some organizations have made the move and put OpenStack projects into production. They have done this in a variety of ways for a variety of reasons. However, other organizations have waited to see what these first-movers are doing with it and whether or not they are successful before exploring for themselves.

As such, we’re pleased to announce the availability of 4 new analyst white papers from 451 Research on how organizations are using OpenStack in production. The information in these papers is based on 451 Research’s own insights as well as interviews with customers who have put OpenStack into production.

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9 tips to properly configure your OpenStack Instance

In OpenStack jargon, an Instance is a Virtual Machine, the guest workload. It boots from an operating system image, and it is configured with a certain amount of CPU, RAM and disk space, amongst other parameters such as networking or security settings.

In this blog post kindly contributed by Marko Myllynen we’ll explore nine configuration and optimization options that will help you achieve the required performance, reliability and security that you need for your workloads.

Some of the optimizations can be done inside a guest regardless of what has the OpenStack Cloud Administrator enabled in your cloud. However, more advanced options require prior enablement and, possibly, special host capabilities. This means many of the options described here will depend on how the Administrator configured the cloud, or may not be available for some tenants as they are reserved for certain groups. More information about this subject can be found on the Red Hat Documentation Portal and its comprehensive guide on OpenStack Image Service. Similarly, the upstream OpenStack documentation has some extra guidelines available.

The following configurations should be evaluated for any VM running on any OpenStack environment. These changes have no side-effects and are typically safe to enable even if unused

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Boosting the NFV datapath with RHEL OpenStack Platform

With software-defined networking (SDN) and network functions virtualization (NFV) gaining traction, more cloud service providers are looking for open solutions, based on standardized hardware platforms and open source software. In particular, communication service providers (CSPs) are undergoing a major shift from specialized hardware-based network elements to a software based provisioning paradigm where virtualized network functions (VNFs) are deployed in private or hybrid clouds of network operators. Increasingly, OpenStack is seen as the virtual infrastructure platform of choice for NFV, with many of the world’s largest communications companies implementing solutions with OpenStack today.

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Driving in the Fast Lane – CPU Pinning and NUMA Topology Awareness in OpenStack Compute

The OpenStack Kilo release, extending upon efforts that commenced during the Juno cycle, includes a number of key enhancements aimed at improving guest performance. These enhancements allow OpenStack Compute (Nova) to have greater knowledge of compute host layout and as a result make smarter scheduling and placement decisions when launching instances. Administrators wishing to take advantage of these features can now create customized performance flavors to target specialized workloads including Network Function Virtualization (NFV) and High Performance Computing (HPC).

What is NUMA topology?

Historically, all memory on x86 systems was equally accessible to all CPUs in the system. This resulted in memory access times that were the same regardless of which CPU in the system was performing the operation and was referred to as Uniform Memory Access (UMA).

In modern multi-socket x86 systems system memory is divided into zones (called cells or nodes) and associated with particular CPUs. This type of division has been key to the increasing performance of modern systems as focus has shifted from increasing clock speeds to adding more CPU sockets, cores, and – where available – threads. An interconnect bus provides connections between nodes, so that all CPUs can still access all memory. While the memory bandwidth of the interconnect is typically faster than that of an individual node it can still be overwhelmed by concurrent cross node traffic from many nodes. The end result is that while NUMA facilitates faster memory access for CPUs local to the memory being accessed, memory access for remote CPUs is slower.

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Red Hat Enterprise Linux OpenStack Platform 6: SR-IOV Networking – Part I: Understanding the Basics

Red Hat Enterprise Linux OpenStack Platform 6: SR-IOV Networking – Part I: Understanding the Basics

Red Hat Enterprise Linux OpenStack Platform 6 introduces support for single root I/O virtualization (SR-IOV) networking. This is done through a new SR-IOV mechanism driver for the OpenStack Networking (Neutron) Modular Layer 2 (ML2) plugin, as well as necessary enhancements for PCI support in the Compute service (Nova).

In this blog post I would like to provide an overview of SR-IOV, and highlight why SR-IOV networking is an important addition to RHEL OpenStack Platform 6. We will also follow up with a second blog post going into the configuration details, describing the current implementation, and discussing some of the current known limitations and expected enhancements going forward.

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