What's Going on with Cloudabi
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Unix Protection
View access control as a matrix Protection Ali Mashtizadeh Stanford University Subjects (processes/users) access objects (e.g., files) • Each cell of matrix has allowed permissions • 1 / 39 2 / 39 Specifying policy Two ways to slice the matrix Manually filling out matrix would be tedious • Use tools such as groups or role-based access control: • Along columns: • - Kernel stores list of who can access object along with object - Most systems you’ve used probably do this dir 1 - Examples: Unix file permissions, Access Control Lists (ACLs) Along rows: • dir 2 - Capability systems do this - More on these later. dir 3 3 / 39 4 / 39 Outline Example: Unix protection Each process has a User ID & one or more group IDs • System stores with each file: • 1 Unix protection - User who owns the file and group file is in - Permissions for user, any one in file group, and other Shown by output of ls -l command: 2 Unix security holes • user group other owner group - rw- rw- r-- dm cs140 ... index.html 3 Capability-based protection - Eachz}|{ groupz}|{ z}|{ of threez}|{ lettersz }| { specifies a subset of read, write, and execute permissions - User permissions apply to processes with same user ID - Else, group permissions apply to processes in same group - Else, other permissions apply 5 / 39 6 / 39 Unix continued Non-file permissions in Unix Directories have permission bits, too • Many devices show up in file system • - Need write permission on a directory to create or delete a file - E.g., /dev/tty1 permissions just like for files Special user root (UID 0) has all -
What If What I Need Is Not in Powerai (Yet)? What You Need to Know to Build from Scratch?
IBM Systems What if what I need is not in PowerAI (yet)? What you need to know to build from scratch? Jean-Armand Broyelle June 2018 IBM Systems – Cognitive Era Things to consider when you have to rebuild a framework © 2017 International Business Machines Corporation 2 IBM Systems – Cognitive Era CUDA Downloads © 2017 International Business Machines Corporation 3 IBM Systems – Cognitive Era CUDA 8 – under Legacy Releases © 2017 International Business Machines Corporation 4 IBM Systems – Cognitive Era CUDA 8 Install Steps © 2017 International Business Machines Corporation 5 IBM Systems – Cognitive Era cuDNN and NVIDIA drivers © 2017 International Business Machines Corporation 6 IBM Systems – Cognitive Era cuDNN v6.0 for CUDA 8.0 © 2017 International Business Machines Corporation 7 IBM Systems – Cognitive Era cuDNN and NVIDIA drivers © 2017 International Business Machines Corporation 8 IBM Systems – Cognitive Era © 2017 International Business Machines Corporation 9 IBM Systems – Cognitive Era © 2017 International Business Machines Corporation 10 IBM Systems – Cognitive Era cuDNN and NVIDIA drivers © 2017 International Business Machines Corporation 11 IBM Systems – Cognitive Era Prepare your environment • When something goes wrong it’s better to Remove local anaconda installation $ cd ~; rm –rf anaconda2 .conda • Reinstall anaconda $ cd /tmp; wget https://repo.anaconda.com/archive/Anaconda2-5.1.0-Linux- ppc64le.sh $ bash /tmp/Anaconda2-5.1.0-Linux-ppc64le.sh • Activate PowerAI $ source /opt/DL/tensorflow/bin/tensorflow-activate • When you -
A Practical UNIX Capability System
A Practical UNIX Capability System Adam Langley <[email protected]> 22nd June 2005 ii Abstract This report seeks to document the development of a capability security system based on a Linux kernel and to follow through the implications of such a system. After defining terms, several other capability systems are discussed and found to be excellent, but to have too high a barrier to entry. This motivates the development of the above system. The capability system decomposes traditionally monolithic applications into a number of communicating actors, each of which is a separate process. Actors may only communicate using the capabilities given to them and so the impact of a vulnerability in a given actor can be reasoned about. This design pattern is demonstrated to be advantageous in terms of security, comprehensibility and mod- ularity and with an acceptable performance penality. From this, following through a few of the further avenues which present themselves is the two hours traffic of our stage. Acknowledgments I would like to thank my supervisor, Dr Kelly, for all the time he has put into cajoling and persuading me that the rest of the world might have a trick or two worth learning. Also, I’d like to thank Bryce Wilcox-O’Hearn for introducing me to capabilities many years ago. Contents 1 Introduction 1 2 Terms 3 2.1 POSIX ‘Capabilities’ . 3 2.2 Password Capabilities . 4 3 Motivations 7 3.1 Ambient Authority . 7 3.2 Confused Deputy . 8 3.3 Pervasive Testing . 8 3.4 Clear Auditing of Vulnerabilities . 9 3.5 Easy Configurability . -
System Calls System Calls
System calls We will investigate several issues related to system calls. Read chapter 12 of the book Linux system call categories file management process management error handling note that these categories are loosely defined and much is behind included, e.g. communication. Why? 1 System calls File management system call hierarchy you may not see some topics as part of “file management”, e.g., sockets 2 System calls Process management system call hierarchy 3 System calls Error handling hierarchy 4 Error Handling Anything can fail! System calls are no exception Try to read a file that does not exist! Error number: errno every process contains a global variable errno errno is set to 0 when process is created when error occurs errno is set to a specific code associated with the error cause trying to open file that does not exist sets errno to 2 5 Error Handling error constants are defined in errno.h here are the first few of errno.h on OS X 10.6.4 #define EPERM 1 /* Operation not permitted */ #define ENOENT 2 /* No such file or directory */ #define ESRCH 3 /* No such process */ #define EINTR 4 /* Interrupted system call */ #define EIO 5 /* Input/output error */ #define ENXIO 6 /* Device not configured */ #define E2BIG 7 /* Argument list too long */ #define ENOEXEC 8 /* Exec format error */ #define EBADF 9 /* Bad file descriptor */ #define ECHILD 10 /* No child processes */ #define EDEADLK 11 /* Resource deadlock avoided */ 6 Error Handling common mistake for displaying errno from Linux errno man page: 7 Error Handling Description of the perror () system call. -
Advanced Components on Top of a Microkernel
Faculty of Computer Science Institute for System Architecture, Operating Systems Group Advanced Components on Top of A Microkernel Björn Döbel What we talked about so far • Microkernels are cool! • Fiasco.OC provides fundamental mechanisms: – Tasks (address spaces) • Container of resources – Threads • Units of execution – Inter-Process Communication • Exchange Data • Timeouts • Mapping of resources TU Dresden, 2012-07-24 L4Re: Advanced Components Slide 2 / 54 Lecture Outline • Building a real system on top of Fiasco.OC • Reusing legacy libraries – POSIX C library • Device Drivers in user space – Accessing hardware resources – Reusing Linux device drivers • OS virtualization on top of L4Re TU Dresden, 2012-07-24 L4Re: Advanced Components Slide 3 / 54 Reusing Existing Software • Often used term: legacy software • Why? – Convenience: • Users get their “favorite” application on the new OS – Effort: • Rewriting everything from scratch takes a lot of time • But: maintaining ported software and adaptions also does not come for free TU Dresden, 2012-07-24 L4Re: Advanced Components Slide 4 / 54 Reusing Existing Software • How? – Porting: • Adapt existing software to use L4Re/Fiasco.OC features instead of Linux • Efficient execution, large maintenance effort – Library-level interception • Port convenience libraries to L4Re and link legacy applications without modification – POSIX C libraries, libstdc++ – OS-level interception • Wine: implement Windows OS interface on top of new OS – Hardware-level: • Virtual Machines TU Dresden, 2012-07-24 L4Re: -
Download File
Annex 2: List of tested and analyzed data sharing tools (non-exhaustive) Below are the specifications of the tools surveyed, as to February 2015, with some updates from April 2016. The tools selected in the context of EU BON are available in the main text of the publication and are described in more details. This list is also available on the EU BON Helpdesk website, where it will be regularly updated as needed. Additional lists are available through the GBIF resources page, the DataONE software tools catalogue, the BioVel BiodiversityCatalogue and the BDTracker A.1 GBIF Integrated Publishing Toolkit (IPT) Main usage, purpose, selected examples The Integrated Publishing Toolkit is a free open source software tool written in Java which is used to publish and share biodiversity data sets and metadata through the GBIF network. Designed for interoperability, it enables the publishing of content in databases or text files using open standards, namely, the Darwin Core and the Ecological Metadata Language. It also provides a 'one-click' service to convert data set metadata into a draft data paper manuscript for submission to a peer-reviewed journal. Currently, the IPT supports three core types of data: checklists, occurrence datasets and sample based data (plus datasets at metadata level only). The IPT is a community-driven tool. Core development happens at the GBIF Secretariat but the coding, documentation, and internationalization are a community effort. New versions incorporate the feedback from the people who actually use the IPT. In this way, users can help get the features they want by becoming involved. The user interface of the IPT has so far been translated into six languages: English, French, Spanish, Traditional Chinese, Brazilian Portuguese, Japanese (Robertson et al, 2014). -
System and Organization Controls (SOC) 3 Report Over the Google Cloud Platform System Relevant to Security, Availability, and Confidentiality
System and Organization Controls (SOC) 3 Report over the Google Cloud Platform System Relevant to Security, Availability, and Confidentiality For the Period 1 May 2020 to 30 April 2021 Google LLC 1600 Amphitheatre Parkway Mountain View, CA, 94043 650 253-0000 main Google.com Management’s Report of Its Assertions on the Effectiveness of Its Controls Over the Google Cloud Platform System Based on the Trust Services Criteria for Security, Availability, and Confidentiality We, as management of Google LLC ("Google" or "the Company") are responsible for: • Identifying the Google Cloud Platform System (System) and describing the boundaries of the System, which are presented in Attachment A • Identifying our service commitments and system requirements • Identifying the risks that would threaten the achievement of its service commitments and system requirements that are the objectives of our System, which are presented in Attachment B • Identifying, designing, implementing, operating, and monitoring effective controls over the Google Cloud Platform System (System) to mitigate risks that threaten the achievement of the service commitments and system requirements • Selecting the trust services categories that are the basis of our assertion We assert that the controls over the System were effective throughout the period 1 May 2020 to 30 April 2021, to provide reasonable assurance that the service commitments and system requirements were achieved based on the criteria relevant to security, availability, and confidentiality set forth in the AICPA’s -
Lecture Notes in Assembly Language
Lecture Notes in Assembly Language Short introduction to low-level programming Piotr Fulmański Łódź, 12 czerwca 2015 Spis treści Spis treści iii 1 Before we begin1 1.1 Simple assembler.................................... 1 1.1.1 Excercise 1 ................................... 2 1.1.2 Excercise 2 ................................... 3 1.1.3 Excercise 3 ................................... 3 1.1.4 Excercise 4 ................................... 5 1.1.5 Excercise 5 ................................... 6 1.2 Improvements, part I: addressing........................... 8 1.2.1 Excercise 6 ................................... 11 1.3 Improvements, part II: indirect addressing...................... 11 1.4 Improvements, part III: labels............................. 18 1.4.1 Excercise 7: find substring in a string .................... 19 1.4.2 Excercise 8: improved polynomial....................... 21 1.5 Improvements, part IV: flag register ......................... 23 1.6 Improvements, part V: the stack ........................... 24 1.6.1 Excercise 12................................... 26 1.7 Improvements, part VI – function stack frame.................... 29 1.8 Finall excercises..................................... 34 1.8.1 Excercise 13................................... 34 1.8.2 Excercise 14................................... 34 1.8.3 Excercise 15................................... 34 1.8.4 Excercise 16................................... 34 iii iv SPIS TREŚCI 1.8.5 Excercise 17................................... 34 2 First program 37 2.1 Compiling, -
F1 Query: Declarative Querying at Scale
F1 Query: Declarative Querying at Scale Bart Samwel John Cieslewicz Ben Handy Jason Govig Petros Venetis Chanjun Yang Keith Peters Jeff Shute Daniel Tenedorio Himani Apte Felix Weigel David Wilhite Jiacheng Yang Jun Xu Jiexing Li Zhan Yuan Craig Chasseur Qiang Zeng Ian Rae Anurag Biyani Andrew Harn Yang Xia Andrey Gubichev Amr El-Helw Orri Erling Zhepeng Yan Mohan Yang Yiqun Wei Thanh Do Colin Zheng Goetz Graefe Somayeh Sardashti Ahmed M. Aly Divy Agrawal Ashish Gupta Shiv Venkataraman Google LLC [email protected] ABSTRACT 1. INTRODUCTION F1 Query is a stand-alone, federated query processing platform The data processing and analysis use cases in large organiza- that executes SQL queries against data stored in different file- tions like Google exhibit diverse requirements in data sizes, la- based formats as well as different storage systems at Google (e.g., tency, data sources and sinks, freshness, and the need for custom Bigtable, Spanner, Google Spreadsheets, etc.). F1 Query elimi- business logic. As a result, many data processing systems focus on nates the need to maintain the traditional distinction between dif- a particular slice of this requirements space, for instance on either ferent types of data processing workloads by simultaneously sup- transactional-style queries, medium-sized OLAP queries, or huge porting: (i) OLTP-style point queries that affect only a few records; Extract-Transform-Load (ETL) pipelines. Some systems are highly (ii) low-latency OLAP querying of large amounts of data; and (iii) extensible, while others are not. Some systems function mostly as a large ETL pipelines. F1 Query has also significantly reduced the closed silo, while others can easily pull in data from other sources. -
Open Source Copyrights
Kuri App - Open Source Copyrights: 001_talker_listener-master_2015-03-02 ===================================== Source Code can be found at: https://github.com/awesomebytes/python_profiling_tutorial_with_ros 001_talker_listener-master_2016-03-22 ===================================== Source Code can be found at: https://github.com/ashfaqfarooqui/ROSTutorials acl_2.2.52-1_amd64.deb ====================== Licensed under GPL 2.0 License terms can be found at: http://savannah.nongnu.org/projects/acl/ acl_2.2.52-1_i386.deb ===================== Licensed under LGPL 2.1 License terms can be found at: http://metadata.ftp- master.debian.org/changelogs/main/a/acl/acl_2.2.51-8_copyright actionlib-1.11.2 ================ Licensed under BSD Source Code can be found at: https://github.com/ros/actionlib License terms can be found at: http://wiki.ros.org/actionlib actionlib-common-1.5.4 ====================== Licensed under BSD Source Code can be found at: https://github.com/ros-windows/actionlib License terms can be found at: http://wiki.ros.org/actionlib adduser_3.113+nmu3ubuntu3_all.deb ================================= Licensed under GPL 2.0 License terms can be found at: http://mirrors.kernel.org/ubuntu/pool/main/a/adduser/adduser_3.113+nmu3ubuntu3_all. deb alsa-base_1.0.25+dfsg-0ubuntu4_all.deb ====================================== Licensed under GPL 2.0 License terms can be found at: http://mirrors.kernel.org/ubuntu/pool/main/a/alsa- driver/alsa-base_1.0.25+dfsg-0ubuntu4_all.deb alsa-utils_1.0.27.2-1ubuntu2_amd64.deb ====================================== -
Containers at Google
Build What’s Next A Google Cloud Perspective Thomas Lichtenstein Customer Engineer, Google Cloud [email protected] 7 Cloud products with 1 billion users Google Cloud in DACH HAM BER ● New cloud region Germany Google Cloud Offices FRA Google Cloud Region (> 50% latency reduction) 3 Germany with 3 zones ● Commitment to GDPR MUC VIE compliance ZRH ● Partnership with MUC IoT platform connects nearly Manages “We found that Google Ads has the best system for 50 brands 250M+ precisely targeting customer segments in both the B2B with thousands of smart data sets per week and 3.5M and B2C spaces. It used to be hard to gain the right products searches per month via IoT platform insights to accurately measure our marketing spend and impacts. With Google Analytics, we can better connect the omnichannel customer journey.” Conrad is disrupting online retail with new Aleš Drábek, Chief Digital and Disruption Officer, Conrad Electronic services for mobility and IoT-enabled devices. Solution As Conrad transitions from a B2C retailer to an advanced B2B and Supports B2C platform for electronic products, it is using Google solutions to grow its customer base, develop on a reliable cloud infrastructure, Supports and digitize its workplaces and retail stores. Products Used 5x Mobile-First G Suite, Google Ads, Google Analytics, Google Chrome Enterprise, Google Chromebooks, Google Cloud Translation API, Google Cloud the IoT connections vs. strategy Vision API, Google Home, Apigee competitors Industry: Retail; Region: EMEA Number of Automate Everything running -
Beginning Java Google App Engine
apress.com Kyle Roche, Jeff Douglas Beginning Java Google App Engine A book on the popular Google App Engine that is focused specifically for the huge number of Java developers who are interested in it Kyle Roche is a practicing developer and user of Java technologies and the Google App Engine for building Java-based Cloud applications or Software as a Service (SaaS) Cloud Computing is a hot technology concept and growing marketplace that drives interest in this title as well Google App Engine is one of the key technologies to emerge in recent years to help you build scalable web applications even if you have limited previous experience. If you are a Java 1st ed., 264 p. programmer, this book offers you a Java approach to beginning Google App Engine. You will explore the runtime environment, front-end technologies like Google Web Toolkit, Adobe Flex, Printed book and the datastore behind App Engine. You'll also explore Java support on App Engine from end Softcover to end. The journey begins with a look at the Google Plugin for Eclipse and finishes with a 38,99 € | £35.49 | $44.99 working web application that uses Google Web Toolkit, Google Accounts, and Bigtable. Along [1]41,72 € (D) | 42,89 € (A) | CHF the way, you'll dig deeply into the services that are available to access the datastore with a 52,05 focus on Java Data Objects (JDO), JDOQL, and other aspects of Bigtable. With this solid foundation in place, you'll then be ready to tackle some of the more advanced topics like eBook integration with other cloud platforms such as Salesforce.com and Google Wave.