Kvm – Kernel Based Virtual Machine
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Security Assurance Requirements for Linux Application Container Deployments
NISTIR 8176 Security Assurance Requirements for Linux Application Container Deployments Ramaswamy Chandramouli This publication is available free of charge from: https://doi.org/10.6028/NIST.IR.8176 NISTIR 8176 Security Assurance Requirements for Linux Application Container Deployments Ramaswamy Chandramouli Computer Security Division Information Technology Laboratory This publication is available free of charge from: https://doi.org/10.6028/NIST.IR.8176 October 2017 U.S. Department of Commerce Wilbur L. Ross, Jr., Secretary National Institute of Standards and Technology Walter Copan, NIST Director and Under Secretary of Commerce for Standards and Technology NISTIR 8176 SECURITY ASSURANCE FOR LINUX CONTAINERS National Institute of Standards and Technology Internal Report 8176 37 pages (October 2017) This publication is available free of charge from: https://doi.org/10.6028/NIST.IR.8176 Certain commercial entities, equipment, or materials may be identified in this document in order to describe an experimental procedure or concept adequately. Such identification is not intended to imply recommendation or endorsement by NIST, nor is it intended to imply that the entities, materials, or equipment are necessarily the best available for the purpose. This p There may be references in this publication to other publications currently under development by NIST in accordance with its assigned statutory responsibilities. The information in this publication, including concepts and methodologies, may be used by federal agencies even before the completion of such companion publications. Thus, until each ublication is available free of charge from: http publication is completed, current requirements, guidelines, and procedures, where they exist, remain operative. For planning and transition purposes, federal agencies may wish to closely follow the development of these new publications by NIST. -
Virtual Machine Technologies and Their Application in the Delivery of ICT
Virtual Machine Technologies and Their Application In The Delivery Of ICT William McEwan accq.ac.nz n Christchurch Polytechnic Institute of Technology Christchurch, New Zealand [email protected] ABSTRACT related areas - a virtual machine or network of virtual machines can be specially configured, allowing an Virtual Machine (VM) technology was first ordinary user supervisor rights, and it can be tested implemented and developed by IBM to destruction without any adverse effect on the corporation in the early 1960's as a underlying host system. mechanism for providing multi-user facilities This paper hopes to also illustrate how VM in a secure mainframe computing configurations can greatly reduce our dependency on environment. In recent years the power of special purpose, complex, and expensive laboratory personal computers has resulted in renewed setups. It also suggests the important additional role interest in the technology. This paper begins that VM and VNL is likely to play in offering hands-on by describing the development of VM. It practical experience to students in a distance e- discusses the different approaches by which learning environment. a VM can be implemented, and it briefly considers the advantages and disadvantages Keywords: Virtual Machines, operating systems, of each approach. VM technology has proven networks, e-learning, infrastructure, server hosting. to be extremely useful in facilitating the Annual NACCQ, Hamilton New Zealand July, 2002 www. Annual NACCQ, Hamilton New Zealand July, teaching of multiple operating systems. It th offers an alternative to the traditional 1. INTRODUCTION approaches of using complex combinations Virtual Machine (VM) technology is not new. It was of specially prepared and configured OS implemented on mainframe computing systems by the images installed via the network or installed IBM Corporation in the early 1960’s (Varian 1997 pp permanently on multiple partitions or on 3-25, Gribben 1989 p.2, Thornton 2000 p.3, Sugarman multiple physical hard drives. -
OLD PRETENDER Lovrenc Gasparin, Fotolia
COVER STORY Bochs Emulator Legacy emulator OLD PRETENDER Lovrenc Gasparin, Fotolia Gasparin, Lovrenc Bochs, the granddaddy of all emulators, is alive and kicking; thanks to regular vitamin jabs, the lively old pretender can even handle Windows XP. BY TIM SCHÜRMANN he PC emulator Bochs first saw the 2.2.6 version in the Universe reposi- box). This also applies if you want to the light of day in 1994. Bochs’ tory; you will additionally need to install run Bochs on a pre-Pentium CPU, such Tinventor, Kevin Lawton, distrib- the Bximage program. (Bximage is al- as a 486. uted the emulator under a commercial li- ready part of the Bochs RPM for open- After installation, the program will cense before selling to French Linux ven- SUSE.) If worst comes to worst, you can simulate a complete PC, including CPU, dor Mandriva (which was then known always build your own Bochs from the graphics, sound card, and network inter- as MandrakeSoft). Mandriva freed the source code (see the “Building Bochs” face. The virtual PC in a PC works so emulator from its commercial chains, re- leasing Bochs under the LGPL license. Building Bochs If you prefer to build your own Bochs, or an additional --enable-ne2000 parameter Installation if you have no alternative, you will first to configure. The extremely long list of Bochs has now found a new home at need to install the C++ compiler and de- parameters in the user manual [2] gives SourceForge.net [1] (Figure 1). You can veloper packages for the X11 system. you a list of available options. -
Introduction to Virtualization Virtualization
Introduction to Virtualization Prashant Shenoy Computer Science CS691D: Hot-OS Lecture 2, page 1 Virtualization • Virtualization: extend or replace an existing interface to mimic the behavior of another system. – Introduced in 1970s: run legacy software on newer mainframe hardware • Handle platform diversity by running apps in VMs – Portability and flexibility Computer Science CS691D: Hot-OS Lecture 2, page 2 Types of Interfaces • Different types of interfaces – Assembly instructions – System calls – APIs • Depending on what is replaced /mimiced, we obtain different forms of virtualization Computer Science CS691D: Hot-OS Lecture 2, page 3 Types of Virtualization • Emulation – VM emulates/simulates complete hardware – Unmodified guest OS for a different PC can be run • Bochs, VirtualPC for Mac, QEMU • Full/native Virtualization – VM simulates “enough” hardware to allow an unmodified guest OS to be run in isolation • Same hardware CPU – IBM VM family, VMWare Workstation, Parallels,… Computer Science CS691D: Hot-OS Lecture 2, page 4 Types of virtualization • Para-virtualization – VM does not simulate hardware – Use special API that a modified guest OS must use – Hypercalls trapped by the Hypervisor and serviced – Xen, VMWare ESX Server • OS-level virtualization – OS allows multiple secure virtual servers to be run – Guest OS is the same as the host OS, but appears isolated • apps see an isolated OS – Solaris Containers, BSD Jails, Linux Vserver • Application level virtualization – Application is gives its own copy of components that are not shared • (E.g., own registry files, global objects) - VE prevents conflicts – JVM Computer Science CS691D: Hot-OS Lecture 2, page 5 Examples • Application-level virtualization: “process virtual machine” • VMM /hypervisor Computer Science CS691D: Hot-OS Lecture 2, page 6 The Architecture of Virtual Machines J Smith and R. -
Multicore Operating-System Support for Mixed Criticality∗
Multicore Operating-System Support for Mixed Criticality∗ James H. Anderson, Sanjoy K. Baruah, and Bjorn¨ B. Brandenburg The University of North Carolina at Chapel Hill Abstract Different criticality levels provide different levels of assurance against failure. In current avionics designs, Ongoing research is discussed on the development of highly-critical software is kept physically separate from operating-system support for enabling mixed-criticality less-critical software. Moreover, no currently deployed air- workloads to be supported on multicore platforms. This craft uses multicore processors to host highly-critical tasks work is motivated by avionics systems in which such work- (more precisely, if multicore processors are used, and if loads occur. In the mixed-criticality workload model that is such a processor hosts highly-critical applications, then all considered, task execution costs may be determined using but one of its cores are turned off). These design decisions more-stringent methods at high criticality levels, and less- are largely driven by certification issues. For example, cer- stringent methods at low criticality levels. The main focus tifying highly-critical components becomes easier if poten- of this research effort is devising mechanisms for providing tially adverse interactions among components executing on “temporal isolation” across criticality levels: lower levels different cores through shared hardware such as caches are should not adversely “interfere” with higher levels. simply “defined” not to occur. Unfortunately, hosting an overall workload as described here clearly wastes process- ing resources. 1 Introduction In this paper, we propose operating-system infrastruc- ture that allows applications of different criticalities to be The evolution of computational frameworks for avionics co-hosted on a multicore platform. -
Virtualizing Servers with Xen
Virtualization Xen Features Escalabilidade Performance QoS Implementation Future Virtualizing servers with Xen Evaldo Gardenali VI International Conference of Unix at UNINET Virtualization Xen Features Escalabilidade Performance QoS Implementation Future Outline Virtualization Xen Features Scalability Performance Quality of Service Implementation Future of Xen Virtualization Xen Features Escalabilidade Performance QoS Implementation Future Overview Why? Support heterogeneous environments: Linux r 2.4 e 2.6, NetBSD r , Plan9 r FreeBSD r , OpenSolaris r Consolidate work Legacy Systems Gradual Upgrade Service Isolation Quality of Service Isolated testing and development Ease of administration Ease of relocation and migration Virtualization Xen Features Escalabilidade Performance QoS Implementation Future Virtualization Techniques Single System Image: Ensim r , Vservers, CKRM, VirtuozzoTM, BSD r jail(), Solaris r Zones √ Groups processes in “resource containers” Hard to get isolation × Emulation: QEMU, Bochs √ Portable Extremely slow × Virtualization: VMware r , VirtualPC r √ Runs unmodified Operating Systems Virtualizing x86 is inefficient × User Mode Kernel: User Mode Linux, CoLinux Guest runs as a process on the host OS × Low performance (I/O, context switches) × Paravirtualization: Xen r , Denali √ Excellent performance Requires port to special architecture × Virtualization Xen Features Escalabilidade Performance QoS Implementation Future Virtualization Techniques Single System Image: Ensim r , Vservers, CKRM, VirtuozzoTM, BSD r jail(), Solaris -
Container and Kernel-Based Virtual Machine (KVM) Virtualization for Network Function Virtualization (NFV)
Container and Kernel-Based Virtual Machine (KVM) Virtualization for Network Function Virtualization (NFV) White Paper August 2015 Order Number: 332860-001US YouLegal Lines andmay Disclaimers not use or facilitate the use of this document in connection with any infringement or other legal analysis concerning Intel products described herein. You agree to grant Intel a non-exclusive, royalty-free license to any patent claim thereafter drafted which includes subject matter disclosed herein. No license (express or implied, by estoppel or otherwise) to any intellectual property rights is granted by this document. All information provided here is subject to change without notice. Contact your Intel representative to obtain the latest Intel product specifications and roadmaps. The products described may contain design defects or errors known as errata which may cause the product to deviate from published specifications. Current characterized errata are available on request. Copies of documents which have an order number and are referenced in this document may be obtained by calling 1-800-548-4725 or by visiting: http://www.intel.com/ design/literature.htm. Intel technologies’ features and benefits depend on system configuration and may require enabled hardware, software or service activation. Learn more at http:// www.intel.com/ or from the OEM or retailer. Results have been estimated or simulated using internal Intel analysis or architecture simulation or modeling, and provided to you for informational purposes. Any differences in your system hardware, software or configuration may affect your actual performance. For more complete information about performance and benchmark results, visit www.intel.com/benchmarks. Tests document performance of components on a particular test, in specific systems. -
Containerization Introduction to Containers, Docker and Kubernetes
Containerization Introduction to Containers, Docker and Kubernetes EECS 768 Apoorv Ingle [email protected] Containers • Containers – lightweight VM or chroot on steroids • Feels like a virtual machine • Get a shell • Install packages • Run applications • Run services • But not really • Uses host kernel • Cannot boot OS • Does not need PID 1 • Process visible to host machine Containers • VM vs Containers Containers • Container Anatomy • cgroup: limit the use of resources • namespace: limit what processes can see (hence use) Containers • cgroup • Resource metering and limiting • CPU • IO • Network • etc.. • $ ls /sys/fs/cgroup Containers • Separate Hierarchies for each resource subsystem (CPU, IO, etc.) • Each process belongs to exactly 1 node • Node is a group of processes • Share resource Containers • CPU cgroup • Keeps track • user/system CPU • Usage per CPU • Can set weights • CPUset cgroup • Reserve to CPU to specific applications • Avoids context switch overheads • Useful for non uniform memory access (NUMA) Containers • Memory cgroup • Tracks pages used by each group • Pages can be shared across groups • Pages “charged” to a group • Shared pages “split the cost” • Set limits on usage Containers • Namespaces • Provides a view of the system to process • Controls what a process can see • Multiple namespaces • pid • net • mnt • uts • ipc • usr Containers • PID namespace • Processes within a PID namespace see only process in the same namespace • Each PID namespace has its own numbering staring from 1 • Namespace is killed when PID 1 goes away -
Virtualization of Linux Based Computers: the Linux-Vserver Project
VirtualizationVirtualization ofof LinuxLinux basedbased computers:computers: thethe LinuxLinux--VServerVServer projectproject BenoBenoîîtt desdes Ligneris,Ligneris, Ph.Ph. D.D. [email protected] Objectives:Objectives: Objectives:Objectives: 1)1) PresentPresent thethe availableavailable programsprograms thatthat cancan provideprovide aa virtualizationvirtualization ofof LinuxLinux computerscomputers withwith differentdifferent technologies.technologies. Objectives:Objectives: 1)1) PresentPresent thethe availableavailable programsprograms thatthat cancan provideprovide aa virtualizationvirtualization ofof LinuxLinux computerscomputers withwith differentdifferent technologies.technologies. 2)2) FocusFocus onon LinuxLinux--VServers:VServers: aa veryvery lightweightlightweight andand effectiveeffective technologytechnology forfor thethe regularregular LinuxLinux useruser notnot interstedintersted inin KernelKernel hacking.hacking. PlanPlan PlanPlan ● IntroductionIntroduction PlanPlan ● IntroductionIntroduction ● OverviewOverview ofof thethe availableavailable technologytechnology PlanPlan ● IntroductionIntroduction ● OverviewOverview ofof thethe availableavailable technologytechnology ● ClassificationClassification ofof thethe problems:problems: usageusage criteriacriteria PlanPlan ● IntroductionIntroduction ● OverviewOverview ofof thethe availableavailable technologytechnology ● ClassificationClassification ofof thethe problems:problems: usageusage criteriacriteria ● ComparativeComparative studystudy ofof thethe existingexisting -
Control Groups (Cgroups)
System Programming for Linux Containers Control Groups (cgroups) Michael Kerrisk, man7.org © 2020 [email protected] February 2020 Outline 19 Cgroups 19-1 19.1 Introduction to cgroups v1 and v2 19-3 19.2 Cgroups v1: hierarchies and controllers 19-17 19.3 Cgroups v1: populating a cgroup 19-24 19.4 Cgroups v1: release notification 19-33 19.5 Cgroups v1: a survey of the controllers 19-43 19.6 Cgroups /procfiles 19-65 19.7 Cgroup namespaces 19-68 Outline 19 Cgroups 19-1 19.1 Introduction to cgroups v1 and v2 19-3 19.2 Cgroups v1: hierarchies and controllers 19-17 19.3 Cgroups v1: populating a cgroup 19-24 19.4 Cgroups v1: release notification 19-33 19.5 Cgroups v1: a survey of the controllers 19-43 19.6 Cgroups /procfiles 19-65 19.7 Cgroup namespaces 19-68 Goals Cgroups is a big topic Many controllers V1 versus V2 interfaces Our goal: understand fundamental semantics of cgroup filesystem and interfaces Useful from a programming perspective How do I build container frameworks? What else can I build with cgroups? And useful from a system engineering perspective What’s going on underneath my container’s hood? System Programming for Linux Containers ©2020, Michael Kerrisk Cgroups 19-4 §19.1 Focus We’ll focus on: General principles of operation; goals of cgroups The cgroup filesystem Interacting with the cgroup filesystem using shell commands Problems with cgroups v1, motivations for cgroups v2 Differences between cgroups v1 and v2 We’ll look briefly at some of the controllers System Programming for Linux Containers ©2020, Michael Kerrisk Cgroups 19-5 §19.1 -
A Container-Based Approach to OS Specialization for Exascale Computing
A Container-Based Approach to OS Specialization for Exascale Computing Judicael A. Zounmevo∗, Swann Perarnau∗, Kamil Iskra∗, Kazutomo Yoshii∗, Roberto Gioiosay, Brian C. Van Essenz, Maya B. Gokhalez, Edgar A. Leonz ∗Argonne National Laboratory fjzounmevo@, perarnau@mcs., iskra@mcs., [email protected] yPacific Northwest National Laboratory. [email protected] zLawrence Livermore National Laboratory. fvanessen1, maya, [email protected] Abstract—Future exascale systems will impose several con- view is essential for scalability, enabling compute nodes to flicting challenges on the operating system (OS) running on manage and optimize massive intranode thread and task par- the compute nodes of such machines. On the one hand, the allelism and adapt to new memory technologies. In addition, targeted extreme scale requires the kind of high resource usage efficiency that is best provided by lightweight OSes. At the Argo introduces the idea of “enclaves,” a set of resources same time, substantial changes in hardware are expected for dedicated to a particular service and capable of introspection exascale systems. Compute nodes are expected to host a mix of and autonomic response. Enclaves will be able to change the general-purpose and special-purpose processors or accelerators system configuration of nodes and the allocation of power tailored for serial, parallel, compute-intensive, or I/O-intensive to different nodes or to migrate data or computations from workloads. Similarly, the deeper and more complex memory hierarchy will expose multiple coherence domains and NUMA one node to another. They will be used to demonstrate nodes in addition to incorporating nonvolatile RAM. That the support of different levels of fault tolerance—a key expected workload and hardware heterogeneity and complexity concern of exascale systems—with some enclaves handling is not compatible with the simplicity that characterizes high node failures by means of global restart and other enclaves performance lightweight kernels. -
Cgroups Py: Using Linux Control Groups and Systemd to Manage CPU Time and Memory
cgroups py: Using Linux Control Groups and Systemd to Manage CPU Time and Memory Curtis Maves Jason St. John Research Computing Research Computing Purdue University Purdue University West Lafayette, Indiana, USA West Lafayette, Indiana, USA [email protected] [email protected] Abstract—cgroups provide a mechanism to limit user and individual resource. 1 Each directory in a cgroupsfs hierarchy process resource consumption on Linux systems. This paper represents a cgroup. Subdirectories of a directory represent discusses cgroups py, a Python script that runs as a systemd child cgroups of a parent cgroup. Within each directory of service that dynamically throttles users on shared resource systems, such as HPC cluster front-ends. This is done using the the cgroups tree, various files are exposed that allow for cgroups kernel API and systemd. the control of the cgroup from userspace via writes, and the Index Terms—throttling, cgroups, systemd obtainment of statistics about the cgroup via reads [1]. B. Systemd and cgroups I. INTRODUCTION systemd A frequent problem on any shared resource with many users Systemd uses a named cgroup tree (called )—that is that a few users may over consume memory and CPU time. does not impose any resource limits—to manage processes When these resources are exhausted, other users have degraded because it provides a convenient way to organize processes in access to the system. A mechanism is needed to prevent this. a hierarchical structure. At the top of the hierarchy, systemd creates three cgroups By placing throttles on physical memory consumption and [2]: CPU time for each individual user, cgroups py prevents re- source exhaustion on a shared system and ensures continued • system.slice: This contains every non-user systemd access for other users.