Author: cima (page 2 of 2)

OpenStack Summit – Deep Dive into Day 2

CERN Openstack (super) User Story
CERN is looking for answers to the fundamental questions concerning creation of the Universe and true to its nature, its a a big data challenge. With the historical run of LHC in 2013, their archive now contains ~100PB (with additional 27PB/year) at ~11 000 servers with ~75000 disk drives and ~45 000 tapes and with the reopening of the LHC, they expect a significant increase of data in 2015. CERN recently opened up a new data center in Budapest connected to Geneve’s headquarters by T-Systems 100GbE line. 
CERN currently runs  four Openstack Icehouse clouds and expects these to run 150 000 cores by Q1 2015 in total. All the CERN‘s non-specific code is upstream and are available for anyone who would like to build at the top of it in the future.
CERN put great emphasis on collaboration. Openlab project is public-private partnership between CERN and major ICT companies (e.g. Rackspace) and its goal is to accelerate the development of cutting-edge cloud solutions.
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OpenShift on OpenStack
RedHat and Cisco gave a demo on deploying OpenShift on OpenStack using Heat, Docker & Kubernetes. OpenShift is a PaaS offering from RedHat with both the enterprise and open source versions. The thought process of deploying OpenShift on OpenStack is to maintain a high degree of flexibility and enable a faster deployment of applications. In the demo, Heat was made use of for orchestration. Docker’s pull and push methodology is used for getting a new Image or saving a modified version which could be pulled later on. Along with tagging of the images, diff operation can also be done. Docker containers are also used as daemons. However Docker cannot see beyond a single host and doesn’t have the capacity to manage mass configuration and deployment. That’s where the Kubernetes comes into picture. Here Pod resemble the Docker’s containers and the etc functionality is used to configure the master which would pass it along to the slaves and there by mass configuration is achieved.The link to the presentation can be found here.
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Openstack Summit 2014 Paris – First Impressions

The OpenStack Summit is a five-day conference for developers, users, and administrators of OpenStack Cloud Software. This time it takes place in Palais des congrès in Paris from November 2 to November 7. ICCLab is attending the Openstack Summit for the very first time.

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The impact of ephemeral VM disk usage on the performance of Live Migration in Openstack

In our previous work we presented the performance of live migration in Openstack Icehouse using various types of VM flavors, its memory load and also examined how it performs in network and CPU loaded environment (see our previous posts –performance of live migration, performance of block live migration, performance of both under varying cpu and network load). One factor which was not considered in our earlier work is the impact of VM ephemeral disk size on the performance of the live migration. That is the focus of this post. Continue reading

Performance of Live Migration in Openstack under CPU and network load

Previously, we analyzed the performance of virtual machine (VM) live migration in different scenarios under Openstack Icehouse. Until now, all our experiments were performed on essentially unloaded servers – clearly, this means that the results are not so widely applicable. Here, we analyze how the addition of load to the physical hosts and the network impacts the behaviour of both block live migration (BLM) and live migration (LM). (Note that the main difference is that BLM migrates the VM disk via the network while LM uses shared storage between source and destination hosts and the disk is not migrated at all). Continue reading

An analysis of the performance of live migration in Openstack

We continue our recent work regarding an analysis of the performance of live migration in Openstack Icehouse. Our previous results focused on block live migration in Openstack, without shared storage configured between computing nodes. In this post we focus on the performance of live migration in the system with a shared file system configured, compare it with block live migration and try to determine scenarios more suitable for each approach. Continue reading

An analysis of the performance of block live migration in Openstack

Since our servers have been set up for live migration with Openstack Icehouse, we wondered how live migration would perform. We measured the duration of the migration process, VM downtime duration and the amount of data transfered via the ethernet during a live migration. All tests were performed across 5 different VM flavors to examine the impact of the flavor. Another point we were curious about is how  higher memory load of VMs can impact migration performance. Here, we present the results of our experiments which show how live mgration works in these different scenarios.

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Setting up Live Migration in Openstack Icehouse [Juno]

[Update 8.12.2014] Since OpenStack’s Juno release hasn’t introduced any changes regarding live migration, Juno users should be able to follow this tutorial as well as the Icehouse users. If you experience any issues let us know. The same setup can be used for newer versions of QEMU and Libvirt as well. Currently we are using QEMU 2.1.5 with Libvirt 1.2.11.

The Green IT theme here in ICCLab is working on monitoring and reducing datacenter energy consumption by leveraging Openstack’s live migration feature. We’ve already experimented a little with live migration in the Havana release (mostly with no luck), but since live migration is touted as one of the new stable features in the Icehouse release, we decided to investigate how it has evolved. This blogpost, largely based on official Openstack documentation, provides step-by-step walkthrough of how to setup and perform virtual machine live migration with servers running the Openstack Icehouse release and KVM/QEMU hypervisor with libvirt.

Virtual machine (VM) live migration is a process, where a VM instance, comprising of its states, memory and emulated devices, is moved from one hypervisor to another with ideally no downtime. It can come handy in many situations such as basic system maintenance, VM consolidation and more complex load management systems designed to reduce data center energy consumption. Continue reading

Vojtech Cima

Vojtech joined the ICC lab through the IAESTE trainee programme.

He’s completed his  Masters study programme at the department of Computer science of the Technical University in Ostrava in Czech Republic. During his studies, he spent one year at Saimaa University of Applied Sciences in Finland participating in a double degree study program. His academic activities are mainly focused on computer vision and image segmentation.

Outside his studies, he has had diverse work experiences. He worked as a Web app Developer for Outotec Company during his stay in Finland. Afterwards he joined Verizon as a part-time Network Engineer for the period of time before he came to Switzerland.

ICCLab provides Vojtech a great opportunity to take  part in the fast moving  cloud computing industry and extend his horizons in this exciting field in a very international environment of young (and not so young!) technically talented people.

During his 10-month internship in ZHAW ICCLab he explored and compared different approaches for live virtual machine migration in an Openstack context. This work was done within the ICCLab’s energy aware cloud load management initiative.

Currently, he works on the ACeN KTI project focusing on network function virtualisation (NFV) in collaboration with two industry partners – Exoscale and Citrix.

Vojtech’s first day leads him to believe that besides the technical skills he will learn, he will also get unforgettable memories with new co-workers and friends.


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