Open-Source Web Servers: Performance on a Carrier-Class Linux Platform
ARIES started as a proof-of-concept project to study if we could build an internet server that has near telecom-grade characteristics using Linux and open-source software as the base technology. We have experimented with the various Linux distributions, web and streaming servers, traffic distribution and load-balancing schemes, distributed and journaling filesystems suitable for HA Linux clusters and redundancy solutions (NFS, Ethernet, Software RAID).
For the future, the work in ARIES will be directed toward augmenting the clustering capabilities of Linux to enable the system to accommodate more types of mobile internet services in addition to the already deployed web server applications looked at thus far. The focus will be to enable the system to reach the optimal utilization of the cluster's resources and to enhance the security aspects required within a mobile internet server. In addition, the project will augment the capabilities of the existing systems by supporting IPv6 technology.
We are keeping all three web servers on our experimental Linux cluster platform. The tested web servers did not scale linearly as we added more CPUs. However, they demonstrated very good performance and near-linear scalability (testing was limited to 12 CPUs). We are currently deploying the latest versions of Apache (2.0.15a), Jigsaw (2.2.0) and Tomcat (3.2).
Based on our tests, we believe that Apache has shown to be considerably faster and more stable than other web servers. We are looking forward to testing and experimenting with the 2.0 release version, which promises a clean code, a well-structured I/O layering and a much-enhanced scalability.
The author would like to acknowledge the Open Architecture Research Department at Ericsson Research for approving the publication of this article, as well as Marc Chatel and Evangeline Paquin, Ericsson Research Canada, for their help and contributions to the benchmarking activities.
Ibrahim F. Haddad (firstname.lastname@example.org) works for Ericsson Research, the Open Architecture Lab in Montréal, researching carrier-class server nodes in real-time all IP networks. He is currently a DSc candidate in Computer Science at Concordia University.
|Speed Up Your Web Site with Varnish||Jun 19, 2013|
|Non-Linux FOSS: libnotify, OS X Style||Jun 18, 2013|
|Containers—Not Virtual Machines—Are the Future Cloud||Jun 17, 2013|
|Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer||Jun 12, 2013|
|Weechat, Irssi's Little Brother||Jun 11, 2013|
|One Tail Just Isn't Enough||Jun 07, 2013|
- Speed Up Your Web Site with Varnish
- Containers—Not Virtual Machines—Are the Future Cloud
- Linux Systems Administrator
- Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer
- Non-Linux FOSS: libnotify, OS X Style
- Senior Perl Developer
- Technical Support Rep
- UX Designer
- RSS Feeds
- Reply to comment | Linux Journal
3 min 27 sec ago
- Reply to comment | Linux Journal
4 hours 3 min ago
- Yeah, user namespaces are
5 hours 19 min ago
- Cari Uang
8 hours 50 min ago
- user namespaces
11 hours 44 min ago
12 hours 10 min ago
- One advantage with VMs
14 hours 38 min ago
- about info
15 hours 11 min ago
15 hours 12 min ago
15 hours 13 min ago
Free Webinar: Hadoop
How to Build an Optimal Hadoop Cluster to Store and Maintain Unlimited Amounts of Data Using Microservers
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Some of key questions to be discussed are:
- What is the “typical” Hadoop cluster and what should be installed on the different machine types?
- Why should you consider the typical workload patterns when making your hardware decisions?
- Are all microservers created equal for Hadoop deployments?
- How do I plan for expansion if I require more compute, memory, storage or networking?