Enterprise End User Summit 2012
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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. -
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! -
Navigating the Next Evolution of Application Development Using Distributed Tracing
Navigating the Next Evolution of Application Development Using Distributed Tracing Navigating the Next Evolution of Application Development 1 Table of Contents Introduction ...........................................................................................................................................................................................3 How has software been built? Waterfall vs. DevOps ................................................................................. ............................. 4 The next evolution: Microservices ................................................................................................................................................5 What will you need to do differently to capitalizeon modern application development? ..........................................6 Get started with Epsagon on AWS ...............................................................................................................................................8 Case Study: Bastian Solutions .......................................................................................................................................................9 Learn More ..........................................................................................................................................................................................10 Navigating the Next Evolution of Application Development 2 Introduction Building and maintaining a competitive edge often requires you to evolve with your customers’ -
Traceability Establishment and Visualization of Software Artefacts in Devops Practice: a Survey
(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 10, No. 7, 2019 Traceability Establishment and Visualization of Software Artefacts in DevOps Practice: A Survey D. A. Meedeniya1, I. D. Rubasinghe2, I. Perera3 Dept. of Computer Science and Engineering, University of Moratuwa, Sri Lanka Abstract—DevOps based software process has become the artefacts in the SDLC [2][3]. There are different forms of popular with the vision of an effective collaboration between the relationships between the homogeneous and heterogeneous development and operations teams that continuously integrates software artefacts. Some artefacts may be highly coupled, and the frequent changes. Traceability manages the artefact some may depend on other artefacts in different degrees, consistency during a software process. This paper explores the unidirectionally or bidirectionally. Thus, software artefacts trace-link creation and visualization between software artefacts, consistency management helps to fine-tune the software existing tool support, quality aspects and the applicability in a process. The incomplete, outdated software artefacts and their DevOps environment. As the novelty of this study, we identify the inconsistencies mislead both the development and maintenance challenges that limit the traceability considerations in DevOps process. Thus, artefact management is essential such that the and suggest research directions. Our methodology consists of changes are accurately propagated to the impacted artefacts concept identification, state-of-practice exploration and analytical review. Despite the existing related work, there is a without creating inconsistencies. Traceability is the potential to lack of tool support for the traceability management between relate artefacts considering their relationships [4][5]; thus, a heterogeneous artefacts in software development with DevOps solution for artefact management. -
Elinos Product Overview
SYSGO Product Overview ELinOS 7 Industrial Grade Linux ELinOS is a SYSGO Linux distribution to help developers save time and effort by focusing on their application. Our Industrial Grade Linux with user-friendly IDE goes along with the best selection of software packages to meet our cog linux Qt LOCK customers needs, and with the comfort of world-class technical support. ELinOS now includes Docker support Feature LTS Qt Open SSH Configurator Kernel embedded Open VPN in order to isolate applications running on the same system. laptop Q Bug Shield-Virus Docker Eclipse-based QEMU-based Application Integrated Docker IDE HW Emulators Debugging Firewall Support ELINOS FEATURES MANAGING EMBEDDED LINUX VERSATILITY • Industrial Grade Creating an Embedded Linux based system is like solving a puzzle and putting • Eclipse-based IDE for embedded the right pieces together. This requires a deep knowledge of Linux’s versatility Systems (CODEO) and takes time for the selection of components, development of Board Support • Multiple Linux kernel versions Packages and drivers, and testing of the whole system – not only for newcomers. incl. Kernel 4.19 LTS with real-time enhancements With ELinOS, SYSGO offers an ‘out-of-the-box’ experience which allows to focus • Quick and easy target on the development of competitive applications itself. ELinOS incorporates the system configuration appropriate tools, such as a feature configurator to help you build the system and • Hardware Emulation (QEMU) boost your project success, including a graphical configuration front-end with a • Extensive file system support built-in integrity validation. • Application debugging • Target analysis APPLICATION & CONFIGURATION ENVIRONMENT • Runs out-of-the-box on PikeOS • Validated and tested for In addition to standard tools, remote debugging, target system monitoring and PowerPC, x86, ARM timing behaviour analyses are essential for application development. -
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. -
System Calls Instrumentation for Intrusion Detection In
System Calls Instrumentation for Intrusion Detection in Embedded Mixed-Criticality Systems Marine Kadar SYSGO GmbH, Klein-Winternheim, Germany [email protected] Sergey Tverdyshev SYSGO GmbH, Klein-Winternheim, Germany [email protected] Gerhard Fohler Technische Universität Kaiserslautern, Germany [email protected] Abstract System call relative information such as occurrences, type, parameters, and return values are well established metrics to reveal intrusions in a system software. Many Host Intrusion Detection Systems (HIDS) from research and industry analyze these data for continuous system monitoring at runtime. Despite a significant false alarm rate, this type of defense offers high detection precision for both known and zero-day attacks. Recent research focuses on HIDS deployment for desktop computers. Yet, the integration of such run-time monitoring solution in mixed-criticality embedded systems has not been discussed. Because of the cohabitation of potentially vulnerable non-critical software with critical software, securing mixed-criticality systems is a non trivial but essential issue. Thus, we propose a methodology to evaluate the impact of deploying system call instrumentation in such context. We analyze the impact in a concrete use-case with PikeOS real-time hypervisor. 2012 ACM Subject Classification Security and privacy → Embedded systems security; Security and privacy → Intrusion detection systems Keywords and phrases Instrumentation, Mixed-criticality, Real-Time, System Calls, Host Intrusion Detection Systems Digital Object Identifier 10.4230/OASIcs.CERTS.2019.2 Funding This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 764785, FORA—Fog Computing for Robotics and Industrial Automation. -
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. -
Powerful Software Analysis System-Wide Tracing Is Here
DATASHEET Powerful Software Analysis Benefits Software tracing is an efficient way to record information about a program’s execution. Programmers, TRACEexperienced system administrators, and technical supportCOMPASS personnel use • Faster resolution of complex problems it to diagnose problems, tune for performance, and improve • Clear understanding of system behaviour comprehension of system behavior. Trace Compass facilitates the visualization and analysis of traces and logs • System performance optimization from multiple sources; it enables diagnostic and monitoring • Adds value in many stages of a product’s operations from a simple device to an entire cloud. life cycle: development, test, production • Facilitates the addition of new parsers, analyses, and views to solve specific issues System-Wide Tracing is here • Scales to GBs of compact binary trace Trace Compass can take multiple traces and logs from • Correlate traces from different nodes in a different sources and formats, and merge them into a single cloud with trace synchronization event stream that allows system-wide tracing. It is possible to correlate application, virtual machine, operating systems, • Multi-platform: Linux, Windows, MacOSX. bare metal, and hardware traces and to display the results together, delivering unprecedented insight into your entire system. Overview • Can be integrated into Eclipse IDE or used as a standalone application. Eclipse plug-ins facilitates the addition of new analysis and views. • Provides an extensible framework written in Java that exposes a generic interface for integration of logs or trace data input. • Custom text or XML parsers can be added directly from the graphical interface by the user. • Extendable to support various proprietary log or trace files. -
System Wide Tracing and Profiling in Linux
SYSTEM WIDE TRACING AND PROFILING IN LINUX Nadav Amit Agenda • System counters inspection • Profiling with Linux perf tool • Tracing using ftrace Disclaimer • Introductory level presentation • We are not going to cover many tools • We are not going to get deep into the implementation of the tools • I am not an expert on many of the issues Collect Statistics • First step in analyzing the system behavior • Option 1: Resource statistics tools • iostat, vmstat, netstat, ifstat • dstat Examples: dstat --vm --aio • dstat • dstat --udp --tcp --socket • dstat --vm --aio dstat --udp --tcp --socket Watch system behavior online • Option 2: Sample the counter • top • Use –H switch for thread specific • Use ‘f’ to choose additional fields: page faults, last used processor • Use ‘1’ to turn off cumulative mode • iotop • Remember to run as sudoer top Inspect Raw Counters • Option 3: Go to the raw counters • General • /proc/stat • /proc/meminfo • /proc/interrupts • Process specific • /proc/[pid]/statm – process memory • /proc/[pid]/stat – process execution times • /proc/[pid]/status – human readable • Device specific • /sys/block/[dev]/stat • /proc/dev/net • Hardware • smartctl /proc/interrupts /sys/block/[dev]/stat Name units description ---- ----- ----------- read I/Os requests number of read I/Os processed read merges requests number of read I/Os merged with in-queue I/O read sectors sectors number of sectors read read ticks milliseconds total wait time for read requests write I/Os requests number of write I/Os processed write merges requests number -
Debian \ Amber \ Arco-Debian \ Arc-Live \ Aslinux \ Beatrix
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