The Lttng Tracer: a Low Impact Performance and Behavior Monitor for GNU/Linux
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Lttng and the Love of Development Without Printf() [email protected]
Fosdem 2014 + LTTng and the love of development without printf() [email protected] 1 whoami David Goulet, Software Developer, EfficiOS, Maintainer of LTTng-tools project ● https://git.lttng.org//lttng-tools.git 2 Content Quick overview of LTTng 2.x Everything else you need to know! Recent features & future work. 3 What is tracing? ● Recording runtime information without stopping the process – Enable/Disable event(s) at runtime ● Usually used during development to solve problems like performance, races, etc... ● Lots of possibilities on Linux: LTTng, Perf, ftrace, SystemTap, strace, ... 4 OverviewOverview ofof LTTngLTTng 2.x2.x 5 Overview of LTTng 2.x Unified user interface, kernel and user space tracers combined. (No need to recompile kernel) Trace output in a unified format (CTF) – https://git.efficios.com/ctf.git Low overhead, Shipped in distros: Ubuntu, Debian, Suse, Fedora, Linaro, Wind River, etc. 6 Tracers ● lttng-modules: kernel tracer module, compatible with kernels from 2.6.38* to 3.13.x, ● lttng-ust: user-space tracer, in-process library. * Kernel tracing is now possible on 2.6.32 to 2.6.37 by backport of 3 Linux Kernel patches. 7 Utilities ● lttng-tools: cli utilities and daemons for trace control, – lttng: cli utility for tracing control, – lttng-ctl: tracing control API, – lttng-sessiond: tracing registry daemon, – lttng-consumerd: extract trace data, – lttng-relayd: network streaming daemon. 8 Viewers ● babeltrace: cli text viewer, trace converter, plugin system, ● lttngtop: ncurse top-like viewer, ● Eclipse lttng plugin: front-end for lttng, collect, visualize and analyze traces, highly extensible. 9 LTTng-UST – How does it work? Users instrument their applications with static tracepoints, liblttng-ust, in-process library, dynamically linked with application, Session setup, etc., Run app, collect traces, Post analysis with viewers. -
A Comprehensive Review for Central Processing Unit Scheduling Algorithm
IJCSI International Journal of Computer Science Issues, Vol. 10, Issue 1, No 2, January 2013 ISSN (Print): 1694-0784 | ISSN (Online): 1694-0814 www.IJCSI.org 353 A Comprehensive Review for Central Processing Unit Scheduling Algorithm Ryan Richard Guadaña1, Maria Rona Perez2 and Larry Rutaquio Jr.3 1 Computer Studies and System Department, University of the East Caloocan City, 1400, Philippines 2 Computer Studies and System Department, University of the East Caloocan City, 1400, Philippines 3 Computer Studies and System Department, University of the East Caloocan City, 1400, Philippines Abstract when an attempt is made to execute a program, its This paper describe how does CPU facilitates tasks given by a admission to the set of currently executing processes is user through a Scheduling Algorithm. CPU carries out each either authorized or delayed by the long-term scheduler. instruction of the program in sequence then performs the basic Second is the Mid-term Scheduler that temporarily arithmetical, logical, and input/output operations of the system removes processes from main memory and places them on while a scheduling algorithm is used by the CPU to handle every process. The authors also tackled different scheduling disciplines secondary memory (such as a disk drive) or vice versa. and examples were provided in each algorithm in order to know Last is the Short Term Scheduler that decides which of the which algorithm is appropriate for various CPU goals. ready, in-memory processes are to be executed. Keywords: Kernel, Process State, Schedulers, Scheduling Algorithm, Utilization. 2. CPU Utilization 1. Introduction In order for a computer to be able to handle multiple applications simultaneously there must be an effective way The central processing unit (CPU) is a component of a of using the CPU. -
The Different Unix Contexts
The different Unix contexts • User-level • Kernel “top half” - System call, page fault handler, kernel-only process, etc. • Software interrupt • Device interrupt • Timer interrupt (hardclock) • Context switch code Transitions between contexts • User ! top half: syscall, page fault • User/top half ! device/timer interrupt: hardware • Top half ! user/context switch: return • Top half ! context switch: sleep • Context switch ! user/top half Top/bottom half synchronization • Top half kernel procedures can mask interrupts int x = splhigh (); /* ... */ splx (x); • splhigh disables all interrupts, but also splnet, splbio, splsoftnet, . • Masking interrupts in hardware can be expensive - Optimistic implementation – set mask flag on splhigh, check interrupted flag on splx Kernel Synchronization • Need to relinquish CPU when waiting for events - Disk read, network packet arrival, pipe write, signal, etc. • int tsleep(void *ident, int priority, ...); - Switches to another process - ident is arbitrary pointer—e.g., buffer address - priority is priority at which to run when woken up - PCATCH, if ORed into priority, means wake up on signal - Returns 0 if awakened, or ERESTART/EINTR on signal • int wakeup(void *ident); - Awakens all processes sleeping on ident - Restores SPL a time they went to sleep (so fine to sleep at splhigh) Process scheduling • Goal: High throughput - Minimize context switches to avoid wasting CPU, TLB misses, cache misses, even page faults. • Goal: Low latency - People typing at editors want fast response - Network services can be latency-bound, not CPU-bound • BSD time quantum: 1=10 sec (since ∼1980) - Empirically longest tolerable latency - Computers now faster, but job queues also shorter Scheduling algorithms • Round-robin • Priority scheduling • Shortest process next (if you can estimate it) • Fair-Share Schedule (try to be fair at level of users, not processes) Multilevel feeedback queues (BSD) • Every runnable proc. -
Flame Graphs Freebsd
FreeBSD Developer and Vendor Summit, Nov, 2014 Flame Graphs on FreeBSD Brendan Gregg Senior Performance Architect Performance Engineering Team [email protected] @brendangregg Agenda 1. Genesis 2. Generaon 3. CPU 4. Memory 5. Disk I/O 6. Off-CPU 7. Chain 1. Genesis The Problem • The same MySQL load on one host runs at 30% higher CPU than another. Why? • CPU profiling should answer this easily # dtrace -x ustackframes=100 -n 'profile-997 /execname == "mysqld"/ {! @[ustack()] = count(); } tick-60s { exit(0); }'! dtrace: description 'profile-997 ' matched 2 probes! CPU ID FUNCTION:NAME! 1 75195 :tick-60s! [...]! libc.so.1`__priocntlset+0xa! libc.so.1`getparam+0x83! libc.so.1`pthread_getschedparam+0x3c! libc.so.1`pthread_setschedprio+0x1f! mysqld`_Z16dispatch_command19enum_server_commandP3THDPcj+0x9ab! mysqld`_Z10do_commandP3THD+0x198! mysqld`handle_one_connection+0x1a6! libc.so.1`_thrp_setup+0x8d! libc.so.1`_lwp_start! 4884! ! mysqld`_Z13add_to_statusP17system_status_varS0_+0x47! mysqld`_Z22calc_sum_of_all_statusP17system_status_var+0x67! mysqld`_Z16dispatch_command19enum_server_commandP3THDPcj+0x1222! mysqld`_Z10do_commandP3THD+0x198! mysqld`handle_one_connection+0x1a6! libc.so.1`_thrp_setup+0x8d! libc.so.1`_lwp_start! 5530! # dtrace -x ustackframes=100 -n 'profile-997 /execname == "mysqld"/ {! @[ustack()] = count(); } tick-60s { exit(0); }'! dtrace: description 'profile-997 ' matched 2 probes! CPU ID FUNCTION:NAME! 1 75195 :tick-60s! [...]! libc.so.1`__priocntlset+0xa! libc.so.1`getparam+0x83! this stack libc.so.1`pthread_getschedparam+0x3c! -
Comparing Systems Using Sample Data
Operating System and Process Monitoring Tools Arik Brooks, [email protected] Abstract: Monitoring the performance of operating systems and processes is essential to debug processes and systems, effectively manage system resources, making system decisions, and evaluating and examining systems. These tools are primarily divided into two main categories: real time and log-based. Real time monitoring tools are concerned with measuring the current system state and provide up to date information about the system performance. Log-based monitoring tools record system performance information for post-processing and analysis and to find trends in the system performance. This paper presents a survey of the most commonly used tools for monitoring operating system and process performance in Windows- and Unix-based systems and describes the unique challenges of real time and log-based performance monitoring. See Also: Table of Contents: 1. Introduction 2. Real Time Performance Monitoring Tools 2.1 Windows-Based Tools 2.1.1 Task Manager (taskmgr) 2.1.2 Performance Monitor (perfmon) 2.1.3 Process Monitor (pmon) 2.1.4 Process Explode (pview) 2.1.5 Process Viewer (pviewer) 2.2 Unix-Based Tools 2.2.1 Process Status (ps) 2.2.2 Top 2.2.3 Xosview 2.2.4 Treeps 2.3 Summary of Real Time Monitoring Tools 3. Log-Based Performance Monitoring Tools 3.1 Windows-Based Tools 3.1.1 Event Log Service and Event Viewer 3.1.2 Performance Logs and Alerts 3.1.3 Performance Data Log Service 3.2 Unix-Based Tools 3.2.1 System Activity Reporter (sar) 3.2.2 Cpustat 3.3 Summary of Log-Based Monitoring Tools 4. -
A Simple Chargeback System for SAS® Applications Running on UNIX and Linux Servers
SAS Global Forum 2007 Systems Architecture Paper: 194-2007 A Simple Chargeback System For SAS® Applications Running on UNIX and Linux Servers Michael A. Raithel, Westat, Rockville, MD Abstract Organizations that run SAS on UNIX and Linux servers often have a need to measure overall SAS usage and to charge the projects and users who utilize the servers. This allows an organization to pay for the hardware, software, and labor necessary to maintain and run these types of shared servers. However, performance management and accounting software is normally expensive. Purchasing such software, configuring it, and managing it may be prohibitive in terms of cost and in terms of having staff with the right skill sets to do so. Consequently, many organizations with UNIX or Linux servers do not have a reliable way to measure the overall use of SAS software and to charge individuals and projects for its use. This paper presents a simple methodology for creating a chargeback system on UNIX and Linux servers. It uses basic accounting programs found in the UNIX and Linux operating systems, and exploits them using SAS software. The paper presents an overview of the UNIX/Linux “sa” command and the basic accounting system. Then, it provides a SAS program that utilizes this command to capture and store monthly SAS usage statistics. The paper presents a second SAS program that reads the monthly SAS usage SAS data set and creates both a chargeback report and a general usage report. After reading this paper, you should be able to easily adapt the sample SAS programs to run on servers in your own environment. -
Linuxcon North America 2012
LinuxCon North America 2012 LTTng 2.0 : Tracing, Analysis and Views for Performance and Debugging. E-mail: [email protected] Mathieu Desnoyers August 29th, 2012 1 > Presenter ● Mathieu Desnoyers ● EfficiOS Inc. ● http://www.efficios.com ● Author/Maintainer of ● LTTng, LTTng-UST, Babeltrace, Userspace RCU Mathieu Desnoyers August 29th, 2012 2 > Content ● Tracing benefits, ● LTTng 2.0 Linux kernel and user-space tracers, ● LTTng 2.0 usage scenarios & viewers, ● New features ready for LTTng 2.1, ● Conclusion Mathieu Desnoyers August 29th, 2012 3 > Benefits of low-impact tracing in a multi-core world ● Understanding interaction between ● Kernel ● Libraries ● Applications ● Virtual Machines ● Debugging ● Performance tuning ● Monitoring Mathieu Desnoyers August 29th, 2012 4 > Tracing use-cases ● Telecom ● Operator, engineer tracing systems concurrently with different instrumentation sets. ● In development and production phases. ● High-availability, high-throughput servers ● Development and production: ensure high performance, low-latency in production. ● Embedded ● System development and production stages. Mathieu Desnoyers August 29th, 2012 5 > LTTng 2.0 ● Rich ecosystem of projects, ● Key characteristics of LTTng 2.0: – Small impact on the traced system, fast, user- oriented features. ● Interfacing with: Common Trace Format (CTF) Interoperability Between Tracing Tools Tracing Well With Others: Integration with the Common Trace Format (CTF), of GDB Tracepoints Into Trace Tools, Mathieu Desnoyers, EfficiOS, Stan Shebs, Mentor Graphics, -
Linux Performance Tools
Linux Performance Tools Brendan Gregg Senior Performance Architect Performance Engineering Team [email protected] @brendangregg This Tutorial • A tour of many Linux performance tools – To show you what can be done – With guidance for how to do it • This includes objectives, discussion, live demos – See the video of this tutorial Observability Benchmarking Tuning Stac Tuning • Massive AWS EC2 Linux cloud – 10s of thousands of cloud instances • FreeBSD for content delivery – ~33% of US Internet traffic at night • Over 50M subscribers – Recently launched in ANZ • Use Linux server tools as needed – After cloud monitoring (Atlas, etc.) and instance monitoring (Vector) tools Agenda • Methodologies • Tools • Tool Types: – Observability – Benchmarking – Tuning – Static • Profiling • Tracing Methodologies Methodologies • Objectives: – Recognize the Streetlight Anti-Method – Perform the Workload Characterization Method – Perform the USE Method – Learn how to start with the questions, before using tools – Be aware of other methodologies My system is slow… DEMO & DISCUSSION Methodologies • There are dozens of performance tools for Linux – Packages: sysstat, procps, coreutils, … – Commercial products • Methodologies can provide guidance for choosing and using tools effectively • A starting point, a process, and an ending point An#-Methodologies • The lack of a deliberate methodology… Street Light An<-Method 1. Pick observability tools that are: – Familiar – Found on the Internet – Found at random 2. Run tools 3. Look for obvious issues Drunk Man An<-Method • Tune things at random until the problem goes away Blame Someone Else An<-Method 1. Find a system or environment component you are not responsible for 2. Hypothesize that the issue is with that component 3. Redirect the issue to the responsible team 4. -
Advanced Linux Tracing Technologies for Online Surveillance of Software Systems
Advanced Linux tracing technologies for Online Surveillance of Software Systems M. Couture DRDC – Valcartier Research Centre Defence Research and Development Canada Scientific Report DRDC-RDDC-2015-R211 October 2015 © Her Majesty the Queen in Right of Canada, as represented by the Minister of National Defence, 2015 © Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2015 Abstract This scientific report provides a description of the concepts and technologies that were developed in the Poly-Tracing Project. The main product that was made available at the end of this four-year project is a new software tracer called Linux Trace Toolkit next generation (LTTng). LTTng actually represents the centre of gravity around which much more applied research and development took place in the project. As shown in this document, the technologies that were produced allow the exploitation of the LTTng tracer and its output for two main purposes: a- solving today’s increasingly complex software bugs and b- improving the detection of anomalies within live information systems. This new technology will enable the development of a set of new tools to help detect the presence of malware and malicious activity within information systems during operations. Significance to defence and security All the technologies described in this document result from collaborative R&D efforts (the Poly-Tracing project), which involved the participation of NSERC, Ericsson Canada, DRDC – Valcartier Research Centre, and the following Canadian universities: Montreal Polytechnique, Laval University, Concordia University, and the University of Ottawa. This scientific report should be considered as one of the Platform-to-Assembly Secured Systems (PASS) deliverables. -
CS414 SP 2007 Assignment 1
CS414 SP 2007 Assignment 1 Due Feb. 07 at 11:59pm Submit your assignment using CMS 1. Which of the following should NOT be allowed in user mode? Briefly explain. a) Disable all interrupts. b) Read the time-of-day clock c) Set the time-of-day clock d) Perform a trap e) TSL (test-and-set instruction used for synchronization) Answer: (a), (c) should not be allowed. Which of the following components of a program state are shared across threads in a multi-threaded process ? Briefly explain. a) Register Values b) Heap memory c) Global variables d) Stack memory Answer: (b) and (c) are shared 2. After an interrupt occurs, hardware needs to save its current state (content of registers etc.) before starting the interrupt service routine. One issue is where to save this information. Here are two options: a) Put them in some special purpose internal registers which are exclusively used by interrupt service routine. b) Put them on the stack of the interrupted process. Briefly discuss the problems with above two options. Answer: (a) The problem is that second interrupt might occur while OS is in the middle of handling the first one. OS must prevent the second interrupt from overwriting the internal registers. This strategy leads to long dead times when interrupts are disabled and possibly lost interrupts and lost data. (b) The stack of the interrupted process might be a user stack. The stack pointer may not be legal which would cause a fatal error when the hardware tried to write some word at it. -
Building Embedded Linux Systems ,Roadmap.18084 Page Ii Wednesday, August 6, 2008 9:05 AM
Building Embedded Linux Systems ,roadmap.18084 Page ii Wednesday, August 6, 2008 9:05 AM Other Linux resources from O’Reilly Related titles Designing Embedded Programming Embedded Hardware Systems Linux Device Drivers Running Linux Linux in a Nutshell Understanding the Linux Linux Network Adminis- Kernel trator’s Guide Linux Books linux.oreilly.com is a complete catalog of O’Reilly’s books on Resource Center Linux and Unix and related technologies, including sample chapters and code examples. ONLamp.com is the premier site for the open source web plat- form: Linux, Apache, MySQL, and either Perl, Python, or PHP. Conferences O’Reilly brings diverse innovators together to nurture the ideas that spark revolutionary industries. We specialize in document- ing the latest tools and systems, translating the innovator’s knowledge into useful skills for those in the trenches. Visit con- ferences.oreilly.com for our upcoming events. Safari Bookshelf (safari.oreilly.com) is the premier online refer- ence library for programmers and IT professionals. Conduct searches across more than 1,000 books. Subscribers can zero in on answers to time-critical questions in a matter of seconds. Read the books on your Bookshelf from cover to cover or sim- ply flip to the page you need. Try it today for free. main.title Page iii Monday, May 19, 2008 11:21 AM SECOND EDITION Building Embedded Linux SystemsTomcat ™ The Definitive Guide Karim Yaghmour, JonJason Masters, Brittain Gilad and Ben-Yossef, Ian F. Darwin and Philippe Gerum Beijing • Cambridge • Farnham • Köln • Sebastopol • Taipei • Tokyo Building Embedded Linux Systems, Second Edition by Karim Yaghmour, Jon Masters, Gilad Ben-Yossef, and Philippe Gerum Copyright © 2008 Karim Yaghmour and Jon Masters. -
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.