LXCF: Tools for Dividing Host OS Into Container with Libvirt-LXC
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Effective Virtual CPU Configuration with QEMU and Libvirt
Effective Virtual CPU Configuration with QEMU and libvirt Kashyap Chamarthy <[email protected]> Open Source Summit Edinburgh, 2018 1 / 38 Timeline of recent CPU flaws, 2018 (a) Jan 03 • Spectre v1: Bounds Check Bypass Jan 03 • Spectre v2: Branch Target Injection Jan 03 • Meltdown: Rogue Data Cache Load May 21 • Spectre-NG: Speculative Store Bypass Jun 21 • TLBleed: Side-channel attack over shared TLBs 2 / 38 Timeline of recent CPU flaws, 2018 (b) Jun 29 • NetSpectre: Side-channel attack over local network Jul 10 • Spectre-NG: Bounds Check Bypass Store Aug 14 • L1TF: "L1 Terminal Fault" ... • ? 3 / 38 Related talks in the ‘References’ section Out of scope: Internals of various side-channel attacks How to exploit Meltdown & Spectre variants Details of performance implications What this talk is not about 4 / 38 Related talks in the ‘References’ section What this talk is not about Out of scope: Internals of various side-channel attacks How to exploit Meltdown & Spectre variants Details of performance implications 4 / 38 What this talk is not about Out of scope: Internals of various side-channel attacks How to exploit Meltdown & Spectre variants Details of performance implications Related talks in the ‘References’ section 4 / 38 OpenStack, et al. libguestfs Virt Driver (guestfish) libvirtd QMP QMP QEMU QEMU VM1 VM2 Custom Disk1 Disk2 Appliance ioctl() KVM-based virtualization components Linux with KVM 5 / 38 OpenStack, et al. libguestfs Virt Driver (guestfish) libvirtd QMP QMP Custom Appliance KVM-based virtualization components QEMU QEMU VM1 VM2 Disk1 Disk2 ioctl() Linux with KVM 5 / 38 OpenStack, et al. libguestfs Virt Driver (guestfish) Custom Appliance KVM-based virtualization components libvirtd QMP QMP QEMU QEMU VM1 VM2 Disk1 Disk2 ioctl() Linux with KVM 5 / 38 libguestfs (guestfish) Custom Appliance KVM-based virtualization components OpenStack, et al. -
Systematic Evaluation of Sandboxed Software Deployment for Real-Time Software on the Example of a Self-Driving Heavy Vehicle
Systematic Evaluation of Sandboxed Software Deployment for Real-time Software on the Example of a Self-Driving Heavy Vehicle Philip Masek1, Magnus Thulin1, Hugo Andrade1, Christian Berger2, and Ola Benderius3 Abstract— Companies developing and maintaining software-only products like web shops aim for establishing persistent links to their software running in the field. Monitoring data from real usage scenarios allows for a number of improvements in the software life-cycle, such as quick identification and solution of issues, and elicitation of requirements from previously unexpected usage. While the processes of continuous integra- tion, continuous deployment, and continuous experimentation using sandboxing technologies are becoming well established in said software-only products, adopting similar practices for the automotive domain is more complex mainly due to real-time and safety constraints. In this paper, we systematically evaluate sandboxed software deployment in the context of a self-driving heavy vehicle that participated in the 2016 Grand Cooperative Driving Challenge (GCDC) in The Netherlands. We measured the system’s scheduling precision after deploying applications in four different execution environments. Our results indicate that there is no significant difference in performance and overhead when sandboxed environments are used compared to natively deployed software. Thus, recent trends in software architecting, packaging, and maintenance using microservices encapsulated in sandboxes will help to realize similar software and system Fig. 1. Volvo FH16 truck from Chalmers Resource for Vehicle Research engineering for cyber-physical systems. (Revere) laboratory that participated in the 2016 Grand Cooperative Driving Challenge in Helmond, NL. I. INTRODUCTION Companies that produce and maintain software-only prod- ucts, i.e. -
An Empirical Study of Virtualization Versus Lightweight Containers
On Exploiting Page Sharing in a Virtualized Environment - an Empirical Study of Virtualization Versus Lightweight Containers Ashish Sonone, Anand Soni, Senthil Nathan, Umesh Bellur Department of Computer Science and Engineering IIT Bombay Mumbai, India ashishsonone, anandsoni, cendhu, [email protected] Abstract—While virtualized solutions are firmly entrenched faulty application can result in the failure of all applications in cloud data centers to provide isolated execution environ- executing on that machine. On the other hand, each virtual ments, the chief overhead it suffers from is that of memory machine runs its own OS and hence, a faulty application consumption. Even pages that are common in multiple virtual machines (VMs) on the same physical machine (PM) are not cannot crash the host OS. Further, each application can shared and multiple copies exist thereby draining valuable run on any customized and optimized guest OS which is memory resources and capping the number of VMs that can be different from the host OS. For example, each guest OS can instantiated on a PM. Lightweight containers (LWCs) on the run its own I/O scheduler which is optimized for the hosted other hand does not suffer from this situation since virtually application. In addition to this, the hypervisor provides many everything is shared via Copy on Write semantics. As a result the capacity of a PM to host LWCs is far higher than hosting other features such as live migration of virtual machines, equivalent VMs. In this paper, we evaluate a solution using high availability using periodic checkpointing and storage uKSM to exploit memory page redundancy amongst multiple migration. -
KVM Based Virtualization and Remote Management Srinath Reddy Pasunuru St
St. Cloud State University theRepository at St. Cloud State Culminating Projects in Information Assurance Department of Information Systems 5-2018 KVM Based Virtualization and Remote Management Srinath Reddy Pasunuru St. Cloud State University, [email protected] Follow this and additional works at: https://repository.stcloudstate.edu/msia_etds Recommended Citation Pasunuru, Srinath Reddy, "KVM Based Virtualization and Remote Management" (2018). Culminating Projects in Information Assurance. 53. https://repository.stcloudstate.edu/msia_etds/53 This Starred Paper is brought to you for free and open access by the Department of Information Systems at theRepository at St. Cloud State. It has been accepted for inclusion in Culminating Projects in Information Assurance by an authorized administrator of theRepository at St. Cloud State. For more information, please contact [email protected]. 1 KVM Based Virtualization and Remote Management by Srinath Reddy Pasunuru A Starred Paper Submitted to the Graduate Faculty of St. Cloud State University in Partial Fulfillment of the Requirements for the Degree Master of Science in Information Assurance May, 2018 Starred Paper Committee Susantha Herath, Chairperson Ezzat Kirmani Sneh Kalia 2 Abstract In the recent past, cloud computing is the most significant shifts and Kernel Virtual Machine (KVM) is the most commonly deployed hypervisor which are used in the IaaS layer of the cloud computing systems. The Hypervisor is the one which provides the complete virtualization environment which will intend to virtualize as much as hardware and systems which will include the CPUs, Memory, network interfaces and so on. Because of the virtualization technologies such as the KVM and others such as ESXi, there has been a significant decrease in the usage if the resources and decrease in the costs involved. -
Adding Generic Process Containers to the Linux Kernel
Adding Generic Process Containers to the Linux Kernel Paul B. Menage∗ Google, Inc. [email protected] Abstract Technically resource control and isolation are related; both prevent a process from having unrestricted access to even the standard abstraction of resources provided by the Unix kernel. For the purposes of this paper, we While Linux provides copious monitoring and control use the following defintions: options for individual processes, it has less support for applying the same operations efficiently to related Resource control is any mechanism which can do either groups of processes. This has led to multiple proposals or both of: for subtly different mechanisms for process aggregation for resource control and isolation. Even though some of these efforts could conceptually operate well together, • tracking how much of a resource is being com- merging each of them in their current states would lead sumed by a set of processes to duplication in core kernel data structures/routines. • imposing quantative limits on that consumption, ei- The Containers framework, based on the existing ther absolutely, or just in times of contention. cpusets mechanism, provides the generic process group- ing features required by the various different resource Typically resource control is visible to the processes be- controllers and other process-affecting subsystems. The ing controlled. result is to reduce the code (and kernel impact) required for such subsystems, and provide a common interface Namespace isolation1 is a mechanism which adds an with greater scope for co-operation. additional indirection or translation layer to the nam- ing/visibility of some unix resource space (such as pro- This paper looks at the challenges in meeting the needs cess ids, or network interfaces) for a specific set of pro- of all the stakeholders, which include low overhead, cesses. -
Large-Scale Cluster Management at Google with Borg Abhishek Verma† Luis Pedrosa‡ Madhukar Korupolu David Oppenheimer Eric Tune John Wilkes Google Inc
Large-scale cluster management at Google with Borg Abhishek Vermay Luis Pedrosaz Madhukar Korupolu David Oppenheimer Eric Tune John Wilkes Google Inc. Abstract config file command-line Google’s Borg system is a cluster manager that runs hun- borgcfg webweb browsers tools dreds of thousands of jobs, from many thousands of differ- ent applications, across a number of clusters each with up to Cell BorgMaster tens of thousands of machines. BorgMasterBorgMaster UIUI shard shard BorgMasterBorgMaster read/UIUIUI shard shard It achieves high utilization by combining admission con- shard Scheduler persistent store trol, efficient task-packing, over-commitment, and machine scheduler (Paxos) link shard linklink shard shard sharing with process-level performance isolation. It supports linklink shard shard high-availability applications with runtime features that min- imize fault-recovery time, and scheduling policies that re- duce the probability of correlated failures. Borg simplifies life for its users by offering a declarative job specification Borglet Borglet Borglet Borglet language, name service integration, real-time job monitor- ing, and tools to analyze and simulate system behavior. We present a summary of the Borg system architecture and features, important design decisions, a quantitative anal- Figure 1: The high-level architecture of Borg. Only a tiny fraction ysis of some of its policy decisions, and a qualitative ex- of the thousands of worker nodes are shown. amination of lessons learned from a decade of operational experience with it. cluding with a set of qualitative observations we have made from operating Borg in production for more than a decade. 1. Introduction The cluster management system we internally call Borg ad- 2. -
Containers Demystified DOAG 2019
Containers Demystified DOAG 2019 Daniel Westermann - Jan Karremans AGENDA Intro History of containers What happened to Docker?? History k8s WHY Automation of the stuff Demo Intro …boring About me Daniel Westermann Principal Consultant Open Infrastructure Technology Leader +41 79 927 24 46 daniel.westermann[at]dbi-services.com EDB containers in Red Hat OpenShift 19.11.2019 Page 4 Who we are The Company Founded in 2010 More than 70 specialists Specialized in the Middleware Infrastructure The invisible part of IT Customers in Switzerland and all over Europe Our Offer Consulting Service Level Agreements (SLA) Trainings License Management dbi services Template - DOAG 2019 19.11.2019 Page 5 Jan Karremans @Johnnyq72 BACKGROUND 25 years of database technology 15 years of consulting 15 years of management 10 years of software development 10 years of technology sales 5 years of community advocacy 5 years of international public speaking EXPERTISE Oracle ACE Alumni EDB Postgres Advanced Server Professional Leader in the PostgreSQL community To Postgres what RedHat is to Linux EnterpriseDB Enterprise-grade Postgres The Most Complete Open Source Database Platform Freeing companies from vendor lock-in • Bruce Momjian • PostgreSQL, Global Development Group, Founding member • PostgreSQL, Core Team member • EnterpriseDB, Senior Database Architect • Mr. Postgres History of containers In the beginning • It was 1960… Bill Joy Co-founder of Sun Microsystems • Sharing 1 single computer with many users • It was then 1979… • Introducing chroot • Bill -
Ovirt Architecture
oVirt Architecture Itamar Heim Presented here by Dan Kenigsberg [email protected] oVirt Overview 1 Agenda ● oVirt Components ● Engine ● Clients ● Host ● Engine Agent - VDSM ● Guest ● Storage Concepts ● Data Warehouse & Reports ● User flows oVirt Overview 2 Architecture From 30,000 Feet Servers Engine Client oVirt Overview 3 The Real World Web Clients Python SDK DB Python CLI Engine R LDAP E Server S T Guest agent Spice Guest client Shared Storage VDSM Host Local Storage oVirt Overview 4 oVirt Engine VM & Template Life Cycle Load HA create, schedule, snapshot Balancing Storage Configuration & Monitoring Network Configuration & Monitoring Host Host Host Host Register/Install Monitoring Maintenance Fencing Authentication, Authorization Inventory Audit oVirt Overview 5 oVirt Engine Postgres DB Active Directory Engine RHDS R E S IDM T oVirt Overview 6 The Real World Web Clients Python SDK DB Python CLI Engine R LDAP E Server S T Guest agent Spice Guest client Shared Storage VDSM Host Local Storage oVirt Overview 7 The Clients Admin Portal User Portal R Python SDK Engine E S T Python CLI oVirt Overview 8 Admin Portal oVirt Overview 9 User Portal oVirt Overview 10 Power User Portal oVirt Overview 11 REST API oVirt Overview 12 SDK oVirt Overview 13 CLI oVirt Overview 14 The Real World Web Clients Python SDK DB Python CLI Engine R LDAP E Server S T Guest agent Spice Guest client Shared Storage VDSM Host Local Storage oVirt Overview 15 The Host QEMU/KVM Fedora Engine MOM libvirt oVirt Node VDSM KSM Configuration Monitoring : Network, Storage, Host, -
Vnfs in a CNF Environment
VNFs in a CNF environment Monika Antoniak, Piotr Skamruk CodiLime Agenda ● Who are we? ● Business use case - use existing VNFs in a containerized set-up ● Technical solution to the problem ● Q&A Who we are? Who we are ● CodiLime has been providing networking engineering services since 2011 ● As part of our R&D efforts and based on our expertise with CNFs and VNFs, we have decided to explore this topic further ● Today we are presenting the working example Business use case Business case What if… ● You love the lightness of containers and use them on a daily basis ● You value the flexibility and resilience of the overall solution ● You want a simple way to deploy things ● You enjoy using kubernetes to manage your resources ● ...and you use a business critical network function as a blackbox VM What can you do to get all of that? A step back: VNFs and CNFs VNF (Virtual Network Function): a well- CNF (Containerized Network Function): a known way to realize network functions in new way of providing required network virtualized or cloud environments functionality with the help of containers Software is provided as a VM image that Software is distributed as a container cannot be changed into a container image, image and can be managed using or is based on an operating system other container-management tools (like docker than Linux images in kubernetes env) VNF examples: vFW, vBNG, vEPC CNF examples: vCPE/cCPE, LDAP, DHCP Back to business Goal: a converged setup for running containerized and VM-based network functions ● using a single user interface -
Ubuntu Server Guide Basic Installation Preparing to Install
Ubuntu Server Guide Welcome to the Ubuntu Server Guide! This site includes information on using Ubuntu Server for the latest LTS release, Ubuntu 20.04 LTS (Focal Fossa). For an offline version as well as versions for previous releases see below. Improving the Documentation If you find any errors or have suggestions for improvements to pages, please use the link at thebottomof each topic titled: “Help improve this document in the forum.” This link will take you to the Server Discourse forum for the specific page you are viewing. There you can share your comments or let us know aboutbugs with any page. PDFs and Previous Releases Below are links to the previous Ubuntu Server release server guides as well as an offline copy of the current version of this site: Ubuntu 20.04 LTS (Focal Fossa): PDF Ubuntu 18.04 LTS (Bionic Beaver): Web and PDF Ubuntu 16.04 LTS (Xenial Xerus): Web and PDF Support There are a couple of different ways that the Ubuntu Server edition is supported: commercial support and community support. The main commercial support (and development funding) is available from Canonical, Ltd. They supply reasonably- priced support contracts on a per desktop or per-server basis. For more information see the Ubuntu Advantage page. Community support is also provided by dedicated individuals and companies that wish to make Ubuntu the best distribution possible. Support is provided through multiple mailing lists, IRC channels, forums, blogs, wikis, etc. The large amount of information available can be overwhelming, but a good search engine query can usually provide an answer to your questions. -
The Evolution of Linux Containers and Integration of Docker with SLES® 12
The Evolution of Linux Containers and Integration of Docker with SLES® 12 Michal Svec Flavio Castelli Senior Product Manager Senior Software Engineer [email protected] [email protected] Agenda • Linux Containers • Docker • Demo 2 Linux Containers Traditional virtualization App App App App A A' B B' Bins/Libs Bins/Libs Bins/Libs Bins/Libs Virtual Machine Virtual Guest OS Guest OS Guest OS Guest OS Hypervisor (Type 2) Host OS Server 4 Linux Containers App App App App A A' B B' Bins/Libs Bins/Libs Bins/Libs Bins/Libs Guest OS Guest OS System container Application container Guest OS Guest OS Kernel Kernel Hypervisor (Type 2) Host OS Server 5 What is a Linux Container? Apps Kernel Server 6 Why Use Linux Containers? • Lightweight virtualization solution ‒ Isolated from the other processes ‒ 1 kernel to rule them all ‒ Normal I/O ‒ Dynamic changes possible without reboot ‒ Nested virtualization is not a problem ‒ No boot time or very short one • Isolate services (e.g. web server, ftp, ...) • Provide root read-only access ‒ Mount host / as read-only ‒ Add only needed resources read-write 7 Linux Containers Use Cases • Deploy everywhere quickly ‒ Deploy application and their dependencies together. • Enterprise Data Center ‒ Limit applications which have a tendency to grab all resources on a system: ‒ Memory (databases) ‒ CPU cycles/scheduling (compute intensive applications) • Outsourcing business ‒ Guarantee a specific amount of resources (SLAs!) to a set of applications for a specific customer without more heavy virtualization technologies 8 Linux -
Xen to KVM Migration Guide
SUSE Linux Enterprise Server 12 SP4 Xen to KVM Migration Guide SUSE Linux Enterprise Server 12 SP4 As the KVM virtualization solution is becoming more and more popular among server administrators, many of them need a path to migrate their existing Xen based environments to KVM. As of now, there are no mature tools to automatically convert Xen VMs to KVM. There is, however, a technical solution that helps convert Xen virtual machines to KVM. The following information and procedures help you to perform such a migration. Publication Date: September 24, 2021 Contents 1 Migration to KVM Using virt-v2v 2 2 Xen to KVM Manual Migration 9 3 For More Information 18 4 Documentation Updates 18 5 Legal Notice 18 6 GNU Free Documentation License 18 1 SLES 12 SP4 Important: Migration Procedure Not Supported The migration procedure described in this document is not fully supported by SUSE. We provide it as a guidance only. 1 Migration to KVM Using virt-v2v This section contains information to help you import virtual machines from foreign hypervisors (such as Xen) to KVM managed by libvirt . Tip: Microsoft Windows Guests This section is focused on converting Linux guests. Converting Microsoft Windows guests using virt-v2v is the same as converting Linux guests, except in regards to handling the Virtual Machine Driver Pack (VMDP). Additional details on converting Windows guests with the VMDP can be found in the separate Virtual Machine Driver Pack documentation at https://www.suse.com/documentation/sle-vmdp-22/ . 1.1 Introduction to virt-v2v virt-v2v is a command line tool to convert VM Guests from a foreign hypervisor to run on KVM managed by libvirt .