Public vs Private, Amazon compared to OpenStack

Public vs Private, Amazon Web Services EC2 compared to OpenStack®

How to choose a cloud platform and when to use both

The public vs private cloud debate is a path well trodden. While technologies and offerings abound, there is still confusion among organizations as to which platform is suited for their agile needs. One of the key benefits to a cloud platform is the ability to spin up compute, networking and storage quickly when users request these resources and similarly decommission when no longer required. Among public cloud providers, Amazon has a market share ahead of Google, Microsoft and others. Among private cloud providers, OpenStack® presents a viable alternative to Microsoft or VMware.

This article compares Amazon Web Services EC2 and OpenStack® as follows:

  • What technical features do the two platforms provide?
  • How do the business characteristics of the two platforms compare?
  • How do the costs compare?
  • How to decide which platform to use and how to use both

OpenStack® and Amazon Web Services (AWS) EC2 defined

From  OpenStack.org “OpenStack software controls large pools of compute, storage, and networking resources throughout a datacenter, managed through a dashboard or via the OpenStack API. OpenStack works with popular enterprise and open source technologies making it ideal for heterogeneous infrastructure.”

From AWS “Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers..”

Technical comparison of OpenStack® and AWS EC2

The tables below name and briefly describe the feature in OpenStack® and AWS. 

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The Age of Cloud File Services

The new OpenStack Kilo upstream release that became available on April 30, 2015 marks a significant milestone for the Manila project for shared file system service for OpenStack with an increase in development capacity and extensive vendors adoption. This project was kicked off 3 years ago and became incubated during 2014 and now moves to the front of the stage at the upcoming OpenStack Vancouver Conference taking place this month with customer stories of Manila deployments in Enterprise and Telco environments.

storage-roomThe project was originally sponsored and accelerated by NetApp and Red Hat and has established a very rich community that includes code contribution fromcompanies such as EMC, Deutsche Telekom, HP, Hitachi, Huawei, IBM, Intel, Mirantis and SUSE.

The momentum of cloud shared file services is not limited to the OpenStack open source world. In fact, last month at the AWS Summit in San Francisco, Amazon announced it new Shared File Storage for Amazon EC2, The Amazon Elastic File System also known for EFS. This new storage service is an addition to the existing AWS storage portfolio, Amazon Simple Storage Service (S3) for object storage, Amazon Elastic Block Store (EBS) for block storage, and Amazon Glacier for archival, cold storage.

The Amazon EFS provides a standard file system semantics and is based on NFS v4 that allows the EC2 instances to access file system at the same time, providing a common data source for a wide variety of workloads and applications that are shared across thousands of instances. It is designed for broad range of use cases, such as Home directories, Content repositories, Development environments and big data applications. Data uploaded to EFS is automatically replicated to different availability zones, and because EFS file systems are SSD-based, there should be few latency and throughput related problems with the service. The Amazon EFS file system as a service allows users to create and configure file systems quickly with no minimum fee or setup cost, and customers pay only for the storage used by the file system based on elastic storage capacity that automatically grows and shrinks when adding and removing files on demand.

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What’s Coming in OpenStack Networking for the Kilo Release

KiloOpenStack  Kilo, the 11th release of the open source project, was officially released in April, and now is a good time to review some of the changes we saw in the OpenStack Networking (Neutron) community during this cycle, as well as some of the key new networking features introduced in the project.

Scaling the Neutron development community

The Kilo cycle brings two major efforts which are meant to better expand and scale the Neutron development community: core plugin decomposition and advanced services split. These changes should not directly impact OpenStack users but are expected to reduce code footprint, improve feature velocity, and ultimately bring faster innovation speed. Let’s take a look at each individually:

Neutron core plugin decomposition

Neutron, by design, has a pluggable architecture which offers a custom backend implementation of the Networking API. The plugin is a core piece of the deployment and acts as the “glue” between the logical API and the actual implementation. As the project evolves, more and more plugins were introduced, coming from open-source projects and communities (such as Open vSwitch and OpenDaylight), as well as from various vendors in the networking industry (like Cisco, Nuage, Midokura and others). At the beginning of the Kilo cycle, Neutron had dozens of plugins and drivers span from core plugins, ML2 mechanism drivers, L3 service plugins, and L4-L7 service plugins for FWaaS, LBaaS and VPNaaS – the majority of those included directly within the Neutron project repository. The amount of code required to review across those drivers and plugins was growing to the point where it was no longer scaling. The expectation that core Neutron reviewers review code which they had no knowledge of, or could not test due to lack of proper hardware or software setup, was not realistic. This also caused some frustration among the vendors themselves, who sometimes failed to get their plugin code merged on time.

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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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