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

openstack-libvirt-images

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Integrating classic IT with cloud-native

This is the fifth and final in a series of posts that delves deeper into the questions that IDC’s Mary Johnston Turner and Gary Chen considered in a recent IDC Analyst Connection. The fifth question asked:

What types of technologies are available to facilitate the integration of multiple generations of infrastructure and applications as hybrid cloud-native and conventional architectures evolve?

Mary and Gary write that “We expect that as these next-generation environments evolve, conventional and cloud-native infrastructure and development platforms will extend support for each other. As an example, OpenStack was built as a next-generation cloud-native solution, but it is now adding support for some enterprise features.”

This is the one aspect of integration. Today, it’s useful to draw a distinction between conventional and cloud-native infrastructures in part because they often use different technologies and those technologies are changing at different rates. However, as projects/products that are important for many enterprise cloud-native deployments–such as OpenStack–mature, they’re starting to adopt features associated with enterprise virtualization and enterprise management.

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Highly available virtual machines in RHEL OpenStack Platform 7

OpenStack provides scale and redundancy at the infrastructure layer to provide high availability for applications built for operation in a horizontally scaling cloud computing environment. It has been designed for applications that are “designed for failure” and voluntarily excluded features that would enable traditional enterprise applications, in fear of limiting its’ scalability and corrupting its initial goals. These traditional enterprise applications demand continuous operation, and fast, automatic recovery in the event of an infrastructure level failure. While an increasing number of enterprises look to OpenStack as providing the infrastructure platform for their forward-looking applications they are also looking  to simplify operations by consolidating their legacy application workloads on it as well.

As part of the On-Ramp to Enterprise OpenStack program, Red Hat, in collaboration with Intel, Cisco and Dell, have been working on delivering a high availability solution for such enterprise workloads running on top of OpenStack. This work provides an initial implementation of the instance high availability proposal that we put forward in the past and is included in the recently released Red Hat Enterprise Linux OpenStack Platform 7.

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Analyzing the performance of Red Hat Enterprise Linux OpenStack Platform using Rally

 In our recent blog post, we’ve discussed the steps involved in determining the performance and scalability of a Red Hat Enterprise Linux OpenStack Platform environment. To recap, we’ve recommended the following:

  1. Validate the underlying hardware performance using AHC
  2. Deploy Red Hat Enterprise Linux OpenStack Platform
  3. Validate the newly deployed infrastructure using Tempest
  4. Run Rally with specific scenarios that stress the control plane of OpenStack environment
  5. Run CloudBench (cbtool) experiments that stress applications running in virtual machines within OpenStack environment

In this post, we would like to focus on step 4: Running Rally with a specific scenario to stress the control plane of the OpenStack environment. The main objectives are:

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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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An ecosystem of integrated cloud products

In my prior post, I described how OpenStack from Red Hat frees  you to pursue your business with the peace of mind that your cloud is secure and stable. Red Hat has several products that enhance OpenStack to provide cloud management, virtualization, a developer platform, and scalable cloud storage.

Cloud Management with Red Hat CloudForms            

CloudForms contains three main components

  • Insight – Inventory, Reporting, Metrics red-hat-cloudforms-logo
  • Control – Eventing, Compliance, and State Management
  • Automate – Provisioning, Reconfiguration, Retirement, and Optimization

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IBM and Red Hat Join Forces to Power Enterprise Virtualization

Adam Jollans is the Program Director  for Cross-IBM Linux and Open Virtualization Strategy
IBM Systems & Technology Group

IBM and Red Hat have been teaming up for years. Today, Red Hat and IBM are announcing a new collaboration to bring Red Hat Enterprise Virtualization to IBM’s next-generation Power Systems through Red Hat Enterprise Virtualization for Power.

A little more than a year ago, IBM announced a commitment to invest $1 billion in new Linux and open source technologies for Power Systems. IBM has delivered on that commitment with the next-generation Power Systems servers incorporating the POWER8 processor which is available for license and open for development through the OpenPOWER Foundation. Designed for Big Data, the new Power Systems can move data around very efficiently and cost-effectively. POWER8’s symmetric multi-threading provides up to 8 threads per core, enabling workloads to exploit the hardware for the highest level of performance.

Red Hat Enterprise Virtualization combines hypervisor technology with a centralized management platform for enterprise virtualization. Red Hat Enterprise Virtualization Hypervisor, built on the KVM hypervisor, inherits the performance, scalability, and ecosystem of the Red Hat Enterprise Linux kernel for virtualization. As a result, your virtual machines are powered by the same high-performance kernel that supports your most challenging Linux workloads.

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Co-Existence of Containers and Virtualization Technologies

By, Federico Simoncelli, Principal Software Engineer, Red Hat

As a software engineer working on the Red Hat Enterprise Virtualization (RHEV), my team and I are driven by innovation; we are always looking for cutting edge technologies to integrate into our product.

Lately there has been a growing interest in Linux containers solutions such as Docker. Docker provides an open and standardized platform for developers and sysadmins to build, ship, and run distributed applications. The application images can be safely held in your organization registry or they can be shared publicly in the docker hub portal (http://registry.hub.docker.com) for everyone to use and to contribute to.

Linux containers are a well-known technology that runs isolated Linux systems on the same host sharing the same kernel and resources as cpu time and memory. Containers are more lightweight, perform better and allow more density of instances compared to full virtualization where virtual machines run dedicated full kernels and operating systems on top of virtualized hardware. On the other hand virtual machines are still the preferred solution when it comes to running highly isolated workloads or different operating systems than the host.

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