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CPS110: Wrapping up memory (virtual machines) Landon Cox March 18, 2009 Traditional OS structure App App App Operating System Host Machine App OS abstractions Threads Instructions CPU Last month of class Applications Virtual Memory OS Virtual addrs Physical mem Hardware What are the interfaces and the resources? What is being virtualized? “Kernel library” Syst calls I/O devices Courser abstraction: virtual machine We’ve already seen a kind of virtual machine OS gives processes virtual memory Each process runs on a virtualized CPU Virtual machine An execution environment May or may not correspond to physical reality Virtual machine options How to implement a virtual machine? 1. Interpreted virtual machines Translate every VM instruction Kind of like on-the-fly compilation VM instruction HW instruction(s) 2. Direct execution Execute instructions directly Emulate the hard ones Interpreted virtual machines Implement the machine in software Must translate emulated to physical Java: byte codes x86, PPC, ARM, etc Software fetches/executes instructions Program (foo.class) Byte code Interpreter (java) x86 What does this picture look like? Dynamic virtual memory translator Java virtual machine What is the interface? Java byte-code instructions What is the abstraction? Stack-machine architecture What are the resources? CPU, physical memory, disk, network The Java programming language High-level language compiled into byte code Library of services (kind of like a kernel) Like C++/STL, C# Direct execution What is the interface? Hardware ISA (e.g. x86 instructions) What is the abstraction? Physical machine (e.g. x86 processor) What are the resources? CPU, physical memory, disk, network Program (XP kernel) x86 Monitor (VMware) Different techniques Emulation Bochs, QEMU Full virtualization VMware Paravirtualization Xen Dynamic recompilation Virtual PC Virtual machines are hot VMware IPO: $19.1 billion Xen sale: $500 million Views of the CPU How is a process’s view of the CPU different than the OS’s? Kernel mode Access to physical memory Manipulation of page tables Other “privileged instructions” Turn off interrupts Traps Keep these in mind when thinking about virtual machines Virtual machine structure Guest App Guest App Guest App Guest OS Guest OS Guest OS Virtual Machine Monitor (Hypervisor) Host Machine Why are hypervisors useful? Code reuse Can run old operating systems + apps on new hardware Original purpose of VMs by IBM in the 60s Encapsulation Can put entire state of an “application” in one thing Move it, restore it, copy it, etc Isolation, security All interactions with hardware are mediated Hypervisor can keep one VM from affecting another Hypervisor cannot be corrupted by guest operating systems Encapsulation Say I want to suspend/restore an application I decide to write the process mem + PCB to disk I reboot my kernel and restart the process Will this work? No, application state is spread out in many places Application might involve multiple processes Applications have state in the kernel (lost on reboot) (e.g. open files, locks, process ids, driver states, etc) Encapsulation Virtual machines capture all of this state Can suspend/restore an application On same machine between boots On different machines Very useful in server farms We’ll talk more about this with Xen Security Can user processes corrupt the kernel? Can overwrite logs Overwrite kernel file Can boot a new kernel Exploit a bug in the system call interface Ok, so I’ll use a hypervisor. Is my data any less vulnerable? All the state in the guest is still vulnerable (file systems, etc) So what’s the point? Hypervisors can observe the guest OS Security services in hypervisor are safe, makes detection easier Security Hypervisors buggy too, why trust them more than kernels? Narrower interface to malicious code (no system calls) No way for kernel to call into hypervisor Smaller, (hopefully) less complex codebase Should be fewer bugs Anything wrong with this argument? Hypervisors are still complex May be able to take over hypervisor via non-syscall interfaces E.g. what if hypervisor is running IP-accessible services? Paravirtualization (in Xen) may compromise this VMware architecture Host World VMM World Target App Host App VM App Host OSVM Driver Host Machine Target App Target OS Virtual Machine Monitor SimOS (proto-VMware) arch. Target App Target App Target OS Host App SimOS Host OS Host Machine Host App SimOS memory SimOS SimOS VMemory SimOS code, data Target OS TargOS code, data Target App TargApp code, data Target App Virtual MMU SimDisk Host OS Host Machine SimDisk File Mem File SimOS page fault SimOS SimOS VMemory Target OS Target App Target App SimOS Fault handler What if I want to TargOS Fault handler suspend and Unmapped addr migrate the target OS? Virtual MMU SimDisk Host OS Host Machine SimDisk File Mem File Full vs interpreted Why would I use VMware instead of Java? Support for legacy applications Do not force users to use a particular language Do not force users to use a particular OS Why would I use Java instead of VMware? Lighter weight Nice properties of type-safe language Can prove safety at compile time Full vs interpreted What about protection? What does Java use for protection? VMware? Java relies on language features (cannot express unsafe computation) VMware relies on the hardware to enforce protection (like an OS) What are the trade-offs? Which protection model is better? Java gives you stronger (i.e. provable) safety guarantees Hardware protection doesn’t constrain programming expressiveness What about sharing (kind of the opposite of protection)? Sharing among components in Java is easy (call a function, compiler makes sure it is safe) Sharing between address spaces is more work, has higher overhead (use sockets, have to context switch, flush TLB, etc) Singularity (could try both) Virtual machine challenges Privilege modes Memory management Protection Performance Many more for every architecture… Course administration Multi-process test cases Autograder will test your pager with > 1 process But don’t submit any to the autograder How to write multi-process test cases Use vm_yield Can quickly open processes in different windows Can use sleep (unsigned int seconds) Could use fork Course administration Various Project 2 policies Free physical pages and disk blocks Easiest thing is to choose lowest page or block priority_queue<int, vector<int>, greater<int> > disk_free; Assigning disk blocks Allocate eagerly in vm_extend Fail vm_extend if there are no unassigned disk blocks left Do not want to overcommit disk space Course administration Extra office hours Ryan: Monday, 23rd, 12p-2p Landon: Tuesday, 24th, 10a-12p Matt: Tuesday, 24th, 415p-815p Niko: Wednesday, 25th, 10a-12p Other questions? Sharing machines among users PlanetLab (752 nodes at 361 sites) Platform for distributed applications Research testbed Why is this more useful than a cluster? See real Internet problems Latency, failures, etc Service fault tolerance Sharing machines among users Consolidate under-utilized servers to reduce CapEx and OpEx Avoid downtime with relocation Dynamically re-balance workload to guarantee application SLAs Enforce security policy What about the enterprise? Sharing machines among users When? PlanetLab (testbeds, distributed services) Data centers (three-tier web applications) Scientific computing (protein folding, etc) What should the interface be? Shared infrastructure interfaces Unmodified OS Each app gets a login username Access resources through system calls Users can see other users’ files, processes Drawbacks of this approach? Administration, configuration headaches (e.g. which libraries are installed?) No performance isolation (one process can dominate CPU, buffer cache, bandwidth) Shared infrastructure interfaces Unmodified OS Retrofit resource accounting into OS (V-Servers) Access resources through system calls Virtualize some resources (e.g. each app has own process table, file system) Drawbacks of this approach? How do you know that you’ve virtualized everything you need to Especially hard for software resources (e.g. what about entries in the file descriptor table?) (e.g. who gets charged on a page fault?) Shared infrastructure interfaces Unmodified OS Retrofit resource accounting into OS (V-Servers) Virtual machines (Xen, VMware) Virtualize hardware interface Each app gets to choose its own OS (e.g. apps have their own virt. CPU, physical memory, disk) Drawbacks of this approach? Heavy-weight (debatable) Redundant state (e.g. kernel, libraries, executables) Might not scale well (if you believe it is heavy-weight) Amazon EC2 Anyone know what EC2 uses? Xen Xen challenges Kind of the opposite approach of V-Servers V-Servers: start with OS, virtualize Xen: start with VM, “para-virtualize” Goals Performance isolation Support many operating systems Reduce performance overhead of virtualization Para-virtualization Full virtualization Fool OS into thinking it has access to hardware Para-virtualization Expose real and virtual resources to OS Why do we need para-virtualization? Mostly because x86 made full virtualization hard This is much less so now Unlikely to be an issue in the near future Why para-virtualize? Limitations of x86 Privileged instructions fail silently VMM must execute these instructions Cannot rely on traps to VMM How does VMware deal with this? At run-time rewrite guest kernel binary Insert traps into the VMM, when necessary Why para-virtualize? Limitations of x86 Timing issues May want to expose “real time” to OS TCP time outs, RTT estimates Support for performance optimizations Superpages Page coloring VMware architecture Host World VMM World Target App Host App VM App Host OSVM Driver Host Machine Target App Target OS Virtual Machine Monitor SimOS architecture Target App Target App Target OS Host App SimOS Host OS Host Machine Host App Xen architecture Guest App Guest App Guest OS Guest OS Host App Xen Domain 0 Host Machine X86_32 address space When are each set of virtual addresses are valid? 4GB 3GB Xen S Kernel S User All address spaces All of a VM’s address spaces U 0GB When does the hypervisor need to flush the TLB? When a new guest VM or guest app needs to be run. Each guest app Xen physical memory Allocated by hypervisor when VM is created Why can’t we allow guests to update PTBR? Might map virtual addrs to physical addrs they don’t own VMware and Xen used to handle this differently VMware maintained “shadow page tables” Xen used “hypercalls” (Xen and VMware support both mechanisms now) VMware guest page tables Virtual → Machine Update PTE Guest OS How does VMM grab control when PTE is updated? Marks PTE pages read-only, generates page fault. Shadow page table VMM Hardware MMU Xen physical memory Guest OSes allocate and manage own PTs “Hypercall” to change PT base Like a system call between guest OS and Xen Xen must validate PT updates before use What are the validation rules? 1. Guest may only map phys. pages it owns 2. PT pages may only be mapped RO Xen guest page tables Virtual → Machine Update PTE hypercall (like a syscall) Guest OS 1) Validation check 2) Perform update VMM Hardware MMU Para-virtualized CPU Hypervisor runs at higher privilege than guest OS Why is having only two levels a problem? Guest OSes must be protected from guest applications Hypervisor must be protected from guest OS What do we do if we only have two privilege levels? OS shares lower privilege level with guest applications Run guest apps and guest OS in different address spaces Why would this be slow? VMM must flush the TLB on system calls, page faults X86_32 address space 4GB 3GB Xen Kernel S S Ring 0 Ring 1 Ring 3 User U 0GB What does this assume? Guest OS doesn’t need ring 2 (e.g. OS/2). Para-virtualized CPU Hypervisor runs at higher privilege than guest OS Ring 0 hypervisor, ring 1 guest OS, ring 3 guest apps Handling exceptions Guest registers handlers with Xen (must modify guest) System calls Guests register "fast" handler with Xen Xen validates handler, inserts in CPU’s handler table No need to go to ring 0 to execute What handler cannot be executed directly and why? Page fault handler must read register CR2 (only allowed in ring 0) CR2 is where the fault-generating address is stored Para-virtualization Pros Better performance (maybe) Scales better than full virtualization Cons OS needs (minor) changes How well does it actually scale? Unclear at this point Impure abstractions Is it important to provide good abstractions? I say yes Bad interfaces lead to code complexity, maintainability issues