DOCSLIB.ORG

Reliability: Software Software Vs

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Reliability Theory SENG 521 Re lia bility th eory d evel oped apart f rom th e mainstream of probability and statistics, and Software Reliability & was usedid primar ily as a tool to h hlelp Software Quality nineteenth century maritime and life iifiblinsurance companies compute profitable rates Chapter 5: Overview of Software to charge their customers. Even today, the Reliability Engineering terms “failure rate” and “hazard rate” are often used interchangeably. Department of Electrical & Computer Engineering, University of Calgary Probability of survival of merchandize after B.H. Far （[email protected]） 1 http://www. enel.ucalgary . ca/People/far/Lectures/SENG521/ ooene MTTF is R e 0.37 From Engineering Statistics Handbook [email protected] 1 [email protected] 2 Reliability: Natural System Reliability: Hardware Natural system Hardware life life cycle. cycle. Aging effect: Useful life span Life span of a of a hardware natural system is system is limited limited by the by the age (wear maximum out) of the system. reproduction rate of the cells. Figure from Pressman’s book Figure from Pressman’s book [email protected] 3 [email protected] 4 Reliability: Software Software vs. Hardware So ftware life cyc le. Software reliability doesn’t decrease with Software systems time, i.e., software doesn’t wear out. are changed (updated) many Hardware faults are mostly physical faults, times during their e. g., fatigue. life cycle. Each update adds to Software faults are mostly design faults the structural which are harder to measure, model, detect deterioration of the and correct. software system. Figure from Pressman’s book [email protected] 5 [email protected] 6 Software vs. Hardware Reliability: Science HdHardware filfailure can b“fid”bbe “fixed” by repl liacing a Exploring ways of implementing “reliability” faulty component with an identical one, therefore no reliability growth . in software products. Software problems can be “fixed” by changing the Reliability Science’s goals: code in order to have the failure not happen again , Dli“dl”(Developing “models” (regressi on and therefore reliability growth is present. aggregation models) and “techniques” to build Software does not go through production phase the relia ble soft ware. same way as hardware does. Testing such models and techniques for adequacy, Conclusion: hardware reliability models may not sounddldness and completeness. be used identically for software. [email protected] 7 [email protected] 8 What is Engineering? Reliability: Engineering /1 Engineering = What is the problem to be solved? Engineer ing of “reli abili ty” i n sof tware What characters of the entity are products. Analysis + used to solve the problem? Design + How will the entity be realized? Reliability Engineering’s goal: How is it constructed? Construction + developing software to reach the market What approach is used to uncover Verification + errors in design and construction? With “minimum” development time How w ill th e en tittity b e suppor te d i n With “ mi ni mum” d evel opment cost Management the long term? With “maximum” reliability With “minimum” expertise needed With “minimum” available technology [email protected] 9 [email protected] 10 Reliability: Engineering /2 What is SRE? /1 Software quality means getting the right So ftware Re lia bility Engi neeri ng (S RE) i s a mul ti - faceted discipline covering the software product balance among development cost , development lifecyc le. time, people, technology and reliability. It involves both technical and management Min imum & Max imum activities in three basic areas: Cost, Time, People, SRE Software Development and Maintenance Technology, Reliability Optimum Measurement and Analysis of reliability data Pick quantitative representations for the 5 factors (cost , Feedback of reliability information into the software time, people, technology and reliability) and measure lifecycle activities. them! [email protected] 11 [email protected] 12 What is SRE ? /2 SRE i s a practi ce f or quantit a tivel y pl anni ng and guiding software development and test, with emphasis on reliability and availability. SRE simultaneously does three things: It ensures that product reliability and availability meet user needs. Software Reliability It delivers the product to market faster. It increases productivity, lowering product life-cycle cost. Engineering (SRE) Process In applying SRE, one can vary relative emphasis placed on these three factors. [email protected] 14 [email protected] 13 Reference SRE: Process /1 Dr. Musa’s Software There are 5 s teps i n Reliability SRE process (for Engiiineering, 2 E d each system to test): Chapter 1 Define necessary reliability Develop operational profiles Prepare for test Execute test Apply failure data to guide decisions [email protected] 15 [email protected] 16 SRE: Process /2 SRE: Process /2 Modified version of the SRE Process The DlODevelop Opera tilPfiltional Profiles, and PfPrepare for Test activities all start during the Requirements (and perhaps architectural analysis) phase of the software development process. They all extend to varying degrees into the Design and Implementation phase, as they can be affected by it. The Execute Test and Guide Test activities coincide with the Test phase. Ref: Musa’s book 2nd Ed [email protected] 17 [email protected] 18 SRE: Necessary Reliability Failure Intensity Objective (FIO) DfiDefine w hat “fil“failure ” means f or th e so ftware prod uct. Failure intens ity ( λ)i) is de fined as fa ilure per natural Choose a common measure for all failure intensities, either units (or time), e.g. failures per some natural unit or failures per hour . 3 alarms per 100 hours of operation. Set the total system failure intensity objective (FIO) for the 5 failures per 1000 transactions, etc. software/hardware system. Failure intensity of a cascade (serial) system is the Compute a developed software FIO by subtracting the total of the FIOs of all hardware and acquired software sum of failure intensities for all of the components components from the system FIOs. of the system. Use the developpyed software FIOs to track the reliability For exponential model: growth during system test (later on). n ztsystem12 n i i1 [email protected] 19 [email protected] 20 How to Set FIO? Reliability vs. Failure Intensity Se tting FIO in terms o f sys tem re lia bility ( R) or ava ila bility (A): Reliability for 1 hour Failure intensity mission time ln R 1 R or for R 0.95 0.36800 1 failure / hour tt 0.90000 105 failure / 1000 hours 1 A 0. 95900 1f1 fail ure /d/ day 0.99000 10 failure / 1000 hours tAm 0. 99400 1 failure / week λ λ R is failure intensity 0.99860 1 failure / month R is reliability A 0.99900 1 failure / 1000 hours t is natural unit (time, etc.) 0.99989 1 failure / year tm is downtime per failure [email protected] 21 [email protected] 22 SRE: Operation SRE: Operational Mode An operation ijtliltkhihis a major system logical task, which OtildOperational mode idititttfis a distinct pattern of syst em returns control to the system when complete. use and/or set of environmental conditions that may An operation iittfftthis an input event affects the course of need separate testing due to likelihood of behavior of software. stimulating different failures. ElExample: operations for a We b proxy server Example: Connect internal users to external Web Time (time of year, day of week, time of day) EilitlEmail internal users t o ext ernal users Different user types (customer or user) Email external users to internal users Users experiences (novice or expert) DNS request by internal users The same operation may appear in different Etc. operational mode with different probabilities. [email protected] 23 [email protected] 24 SRE: Operational Profile SRE: System Operational Profile An operational profile is a complete set of operations with their StSystem opera tiltional profil e mustbt be deve lope dfd for a ll of fit its probabilities of occurrence (during the operational use of the software). important operational modes. An operational profile is a description of the distribution of input events There are four principal steps in developing an operational that is expected to occur in actual software operation. profile: The operational profile of the software reflects how it will be used in Identify the operation initiators (i.e., user types, external systems, and practice. Probability the sys tem itse lf) of occurrence List the operations invoked by each initiator Operational mode Determine the occurrence rates Determine the occurrence probabilities by dividing the occurrence rates by the total occurrence rate Operation [email protected] 25 [email protected] 26 SRE: Prepare for Test SRE: Execute Test The PfTtPrepare for Test activ ity uses th e operati onal Allocate test ti me among t he assoc iated systems an d profiles to prepare test cases and test procedures. types of test (feature, load, regression, etc.). Test cases are a llocat ed i n accord ance with th e Invoke the test cases at random times, choosing operational profile. operations randomly in accordance with the TtTest cases are ass igned dtth to the operati tibons by operational profile. selecting from all the possible intra-operation choices with equal probability. Identifyy,g failures, along with when they occur. The test procedure is the controller that invokes test This information will be used in Apply Failure Data cases during execution. and Guide Test . [email protected] 27 [email protected] 28 Types of Test SRE: Apply Failure Data Certification Test: Accept or reject (binary Plot each new failure as it occurs on a decision) an acquired component for a given target failure intensity. reliability demonstration chart. Feature (Unit) TestTest:: A single execution of an Accept or reject software (operations) using operation with interaction between operations miiinim ize d.
Recommended publications
  • An Architect's Guide to Site Reliability Engineering Nathaniel T

    An Architect's Guide to Site Reliability Engineering Nathaniel T

    An Architect's Guide to Site Reliability Engineering Nathaniel T. Schutta @ntschutta ntschutta.io https://content.pivotal.io/ ebooks/thinking-architecturally Sofware development practices evolve. Feature not a bug. It is the agile thing to do! We’ve gone from devs and ops separated by a large wall… To DevOps all the things. We’ve gone from monoliths to service oriented to microserivces. And it isn’t all puppies and rainbows. Shoot. A new role is emerging - the site reliability engineer. Why? What does that mean to our teams? What principles and practices should we adopt? How do we work together? What is SRE? Important to understand the history. Not a new concept but a catchy name! Arguably goes back to the Apollo program. Margaret Hamilton. Crashed a simulator by inadvertently running a prelaunch program. That wipes out the navigation data. Recalculating… Hamilton wanted to add error-checking code to the Apollo system that would prevent this from messing up the systems. But that seemed excessive to her higher- ups. “Everyone said, ‘That would never happen,’” Hamilton remembers. But it did. Right around Christmas 1968. — ROBERT MCMILLAN https://www.wired.com/2015/10/margaret-hamilton-nasa-apollo/ Luckily she did manage to update the documentation. Allowed them to recover the data. Doubt that would have turned into a Hollywood blockbuster… Hope is not a strategy. But it is what rebellions are built on. Failures, uh find a way. Traditionally, systems were run by sys admins. AKA Prod Ops. Or something similar. And that worked OK. For a while. But look around your world today.
  • Chapter 6 Structural Reliability

    Chapter 6 Structural Reliability

    MIL-HDBK-17-3E, Working Draft CHAPTER 6 STRUCTURAL RELIABILITY Page 6.1 INTRODUCTION ....................................................................................................................... 2 6.2 FACTORS AFFECTING STRUCTURAL RELIABILITY............................................................. 2 6.2.1 Static strength.................................................................................................................... 2 6.2.2 Environmental effects ........................................................................................................ 3 6.2.3 Fatigue............................................................................................................................... 3 6.2.4 Damage tolerance ............................................................................................................. 4 6.3 RELIABILITY ENGINEERING ................................................................................................... 4 6.4 RELIABILITY DESIGN CONSIDERATIONS ............................................................................. 5 6.5 RELIABILITY ASSESSMENT AND DESIGN............................................................................. 6 6.5.1 Background........................................................................................................................ 6 6.5.2 Deterministic vs. Probabilistic Design Approach ............................................................... 7 6.5.3 Probabilistic Design Methodology.....................................................................................
  • Writing Quality Software

    Writing Quality Software

    Writing Quality Software About this white paper: This whitepaper was written by David C. Young, an employee of General Dynamics Information Technology (GDIT). Dr. Young is part of a team of GDIT employees who maintain, and support high performance computing systems at the Alabama Supercomputer Center (ASC). This was written in 2020. This paper is written for people who want to write good software, but don’t have a master’s degree in software architecture (or someone managing the project who does). Much of what is here would be covered in a software development practices class, often taught at the master’s degree level. Writing quality software is not only about the satisfaction of a job well done. It is also reflects on you and your professional reputation amongst your peers. In some cases writing quality software can be a factor in getting a job, losing a job, or even life or death. Furthermore, writing quality software should be considered an implicit requirement in every software development project. If the intended useful life of the software is many years, that is yet another reason to do a good job writing it. Introduction Consider this situation, which is all too common. You have written a really neat piece of software. You put it out on github, then tell your colleagues about it. Soon you are bombarded with a series of complaints from people who tried to install, and use your software. Some of those complaints might be; • It won’t install on their version of Linux. • They did the same thing you reported, but got a different answer.
  • Studying the Feasibility and Importance of Software Testing: an Analysis

    Studying the Feasibility and Importance of Software Testing: an Analysis

    Dr. S.S.Riaz Ahamed / Internatinal Journal of Engineering Science and Technology Vol.1(3), 2009, 119-128 STUDYING THE FEASIBILITY AND IMPORTANCE OF SOFTWARE TESTING: AN ANALYSIS Dr.S.S.Riaz Ahamed Principal, Sathak Institute of Technology, Ramanathapuram,India. Email:[email protected], [email protected] ABSTRACT Software testing is a critical element of software quality assurance and represents the ultimate review of specification, design and coding. Software testing is the process of testing the functionality and correctness of software by running it. Software testing is usually performed for one of two reasons: defect detection, and reliability estimation. The problem of applying software testing to defect detection is that software can only suggest the presence of flaws, not their absence (unless the testing is exhaustive). The problem of applying software testing to reliability estimation is that the input distribution used for selecting test cases may be flawed. The key to software testing is trying to find the modes of failure - something that requires exhaustively testing the code on all possible inputs. Software Testing, depending on the testing method employed, can be implemented at any time in the development process. Keywords: verification and validation (V & V) 1 INTRODUCTION Testing is a set of activities that could be planned ahead and conducted systematically. The main objective of testing is to find an error by executing a program. The objective of testing is to check whether the designed software meets the customer specification. The Testing should fulfill the following criteria: ¾ Test should begin at the module level and work “outward” toward the integration of the entire computer based system.
  • Training-Sre.Pdf

    Training-Sre.Pdf

    C om p lim e nt s of Training Site Reliability Engineers What Your Organization Needs to Create a Learning Program Jennifer Petoff, JC van Winkel & Preston Yoshioka with Jessie Yang, Jesus Climent Collado & Myk Taylor REPORT Want to know more about SRE? To learn more, visit google.com/sre Training Site Reliability Engineers What Your Organization Needs to Create a Learning Program Jennifer Petoff, JC van Winkel, and Preston Yoshioka, with Jessie Yang, Jesus Climent Collado, and Myk Taylor Beijing Boston Farnham Sebastopol Tokyo Training Site Reliability Engineers by Jennifer Petoff, JC van Winkel, and Preston Yoshioka, with Jessie Yang, Jesus Climent Collado, and Myk Taylor Copyright © 2020 O’Reilly Media. All rights reserved. Printed in the United States of America. Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472. O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (http://oreilly.com). For more infor‐ mation, contact our corporate/institutional sales department: 800-998-9938 or [email protected]. Acquistions Editor: John Devins Proofreader: Charles Roumeliotis Development Editor: Virginia Wilson Interior Designer: David Futato Production Editor: Beth Kelly Cover Designer: Karen Montgomery Copyeditor: Octal Publishing, Inc. Illustrator: Rebecca Demarest November 2019: First Edition Revision History for the First Edition 2019-11-15: First Release See http://oreilly.com/catalog/errata.csp?isbn=9781492076001 for release details. The O’Reilly logo is a registered trademark of O’Reilly Media, Inc. Training Site Reli‐ ability Engineers, the cover image, and related trade dress are trademarks of O’Reilly Media, Inc.
  • Software Reliability and Dependability: a Roadmap Bev Littlewood & Lorenzo Strigini

    Software Reliability and Dependability: a Roadmap Bev Littlewood & Lorenzo Strigini

    Software Reliability and Dependability: a Roadmap Bev Littlewood & Lorenzo Strigini Key Research Pointers Shifting the focus from software reliability to user-centred measures of dependability in complete software-based systems. Influencing design practice to facilitate dependability assessment. Propagating awareness of dependability issues and the use of existing, useful methods. Injecting some rigour in the use of process-related evidence for dependability assessment. Better understanding issues of diversity and variation as drivers of dependability. The Authors Bev Littlewood is founder-Director of the Centre for Software Reliability, and Professor of Software Engineering at City University, London. Prof Littlewood has worked for many years on problems associated with the modelling and evaluation of the dependability of software-based systems; he has published many papers in international journals and conference proceedings and has edited several books. Much of this work has been carried out in collaborative projects, including the successful EC-funded projects SHIP, PDCS, PDCS2, DeVa. He has been employed as a consultant to industrial companies in France, Germany, Italy, the USA and the UK. He is a member of the UK Nuclear Safety Advisory Committee, of IFIPWorking Group 10.4 on Dependable Computing and Fault Tolerance, and of the BCS Safety-Critical Systems Task Force. He is on the editorial boards of several international scientific journals. 175 Lorenzo Strigini is Professor of Systems Engineering in the Centre for Software Reliability at City University, London, which he joined in 1995. In 1985-1995 he was a researcher with the Institute for Information Processing of the National Research Council of Italy (IEI-CNR), Pisa, Italy, and spent several periods as a research visitor with the Computer Science Department at the University of California, Los Angeles, and the Bell Communication Research laboratories in Morristown, New Jersey.
  • Manual on Quality Assurance for Computer Software Related to the Safety of Nuclear Power Plants

    Manual on Quality Assurance for Computer Software Related to the Safety of Nuclear Power Plants

    SIMPLIFIED SOFTWARE LIFE-CYCLE DIAGRAM FEASIBILITY STUDY PROJECT TIME I SOFTWARE P FUNCTIONAL I SPECIFICATION! SOFTWARE SYSTEM DESIGN DETAILED MODULES CECIFICATION MODULES DESIGN SOFTWARE INTEGRATION AND TESTING SYSTEM TESTING ••COMMISSIONING I AND HANDOVER | DECOMMISSION DESIGN DESIGN SPECIFICATION VERIFICATION OPERATION AND MAINTENANCE SOFTWARE LIFE-CYCLE PHASES TECHNICAL REPORTS SERIES No. 282 Manual on Quality Assurance for Computer Software Related to the Safety of Nuclear Power Plants f INTERNATIONAL ATOMIC ENERGY AGENCY, VIENNA, 1988 MANUAL ON QUALITY ASSURANCE FOR COMPUTER SOFTWARE RELATED TO THE SAFETY OF NUCLEAR POWER PLANTS The following States are Members of the International Atomic Energy Agency: AFGHANISTAN GUATEMALA PARAGUAY ALBANIA HAITI PERU ALGERIA HOLY SEE PHILIPPINES ARGENTINA HUNGARY POLAND AUSTRALIA ICELAND PORTUGAL AUSTRIA INDIA QATAR BANGLADESH INDONESIA ROMANIA BELGIUM IRAN, ISLAMIC REPUBLIC OF SAUDI ARABIA BOLIVIA IRAQ SENEGAL BRAZIL IRELAND SIERRA LEONE BULGARIA ISRAEL SINGAPORE BURMA ITALY SOUTH AFRICA BYELORUSSIAN SOVIET JAMAICA SPAIN SOCIALIST REPUBLIC JAPAN SRI LANKA CAMEROON JORDAN SUDAN CANADA KENYA SWEDEN CHILE KOREA, REPUBLIC OF SWITZERLAND CHINA KUWAIT SYRIAN ARAB REPUBLIC COLOMBIA LEBANON THAILAND COSTA RICA LIBERIA TUNISIA COTE D'lVOIRE LIBYAN ARAB JAMAHIRIYA TURKEY CUBA LIECHTENSTEIN UGANDA CYPRUS LUXEMBOURG UKRAINIAN SOVIET SOCIALIST CZECHOSLOVAKIA MADAGASCAR REPUBLIC DEMOCRATIC KAMPUCHEA MALAYSIA UNION OF SOVIET SOCIALIST DEMOCRATIC PEOPLE'S MALI REPUBLICS REPUBLIC OF KOREA MAURITIUS UNITED ARAB
  • Software Quality Assurance Activities in Software Testing

    Software Quality Assurance Activities in Software Testing

    Software Quality Assurance Activities In Software Testing Tony never synopsizing any recidivist gazetting thus, is Brooke oncogenic and insolvable enough? Monogenous Chadd externalises, his disciplinarians denudes spring-clean Germanically. Spindliest Antoni never humors so edgewise or attain any shells lyingly. Each module performs one or two tasks, and thenpasses control to another module. Perform test automation for web application using Cucumber. Identify and describe safety software procurement methods, including supplier evaluation and source inspection processes. He previously worked at IBM SWS Toronto Lab. The information maintained in status accounting should enable the rebuild of any previous baseline. Beta Breakers supports all industry sectors. Thank you save time for all the lack of that includes test software assurance and must often. Focus on demonstrating pos next column containing algorithms, activities in software quality assurance testing activities of testing programs for their findings from his piece of skills, validate features to refresh teh page object. XML data sets to simulate production, using LLdap and ALTOVA. Schedule information should be expressed as absolute dates, as dates relative to either SCM or project milestones, or as a simple sequence of events. Its scope of software quality assurance and the correct email list all testshave been completely correct, in software quality assurance activities to be precisely known about its process on a familiarity level. These exercises are performed at every step along the way in the workshop. However, you have to balance driving out quality with production value. The second step is the validation of the computer system implementation against the computer system requirements. Software development tools, whose output becomes part of the program implementation and which can therefore introduce errors.
  • Big Data for Reliability Engineering: Threat and Opportunity

    Big Data for Reliability Engineering: Threat and Opportunity

    Reliability, February 2016 Big Data for Reliability Engineering: Threat and Opportunity Vitali Volovoi Independent Consultant [email protected] more recently, analytics). It shares with the rest of the fields Abstract - The confluence of several technologies promises under this umbrella the need to abstract away most stormy waters ahead for reliability engineering. News reports domain-specific information, and to use tools that are mainly are full of buzzwords relevant to the future of the field—Big domain-independent1. As a result, it increasingly shares the Data, the Internet of Things, predictive and prescriptive lingua franca of modern systems engineering—probability and analytics—the sexier sisters of reliability engineering, both statistics that are required to balance the otherwise orderly and exciting and threatening. Can we reliability engineers join the deterministic engineering world. party and suddenly become popular (and better paid), or are And yet, reliability engineering does not wear the fancy we at risk of being superseded and driven into obsolescence? clothes of its sisters. There is nothing privileged about it. It is This article argues that“big-picture” thinking, which is at the rarely studied in engineering schools, and it is definitely not core of the concept of the System of Systems, is key for a studied in business schools! Instead, it is perceived as a bright future for reliability engineering. necessary evil (especially if the reliability issues in question are safety-related). The community of reliability engineers Keywords - System of Systems, complex systems, Big Data, consists of engineers from other fields who were mainly Internet of Things, industrial internet, predictive analytics, trained on the job (instead of receiving formal degrees in the prescriptive analytics field).
  • Reducing Product Development Risk with Reliability Engineering Methods

    Reducing Product Development Risk with Reliability Engineering Methods

    Reducing Product Development Risk with Reliability Engineering Methods Mike McCarthy Reliability Specialist Who am I? • Mike McCarthy, Principal Reliability Engineer – BSc Physics, MSc Industrial Engineering – MSaRS (council member), MCMI, – 18+ years as a reliability practitioner – Extensive experience in root cause analysis of product and process issues and their corrective action. • Identifying failure modes, predicting failure rates and cost of ‘unreliability’ – I use reliability tools to gain insight into business issues - ‘Risk’ based decision making 2 Agenda ‘Probable’ Duration 1. Risk 2 min 2. Reliability Tools to Manage Risk 4 min 3. FMECA 6 min 4. Design of Experiments (DoE) 5 min 5. Accelerated Testing 5 min 6. Summary 3 min 7. Questions 5 min Total: 30 min 3 Managing Risk? Design Installation Terry Harris © GreenHunter Bio Fuels Inc. Maintenance Operation Chernobyl 4 Likelihood-Consequence Curve Consequence Catastrophic Prohibited ‘Acceptable’ Negligible Likelihood Impossible Certain (frequency) to occur 5 Reliability Tools to Manage Risk 6 Tools to Manage Risk • Design Reviews • FRACAS/DRACAS Review & • Subcontractor Review Control • Part Selection & Control (including de-rating) • Computer Aided Engineering Tools (FEA/CFD) • FME(C)A / FTA Design & • System Prediction & Allocation (RBDs) • Quality Function Deployment (QFD) Analysis • Critical Item Analysis • Thermal/Vibration Analysis & Management • Predicting Effects of Storage, Handling etc • Life Data Analysis (eg Weibull) • Reliability Qualification Testing Test & • Maintainability
  • Renesas' Synergy Software Quality Handbook

    Renesas' Synergy Software Quality Handbook

    User’s Manual Synergy Software Quality Handbook Notice 1. Renesas Synergy™ Platform User’s Manual Synergy Software Software Quality Assurance All information contained in these materials, including products and product specifications, represents information on the product at the time of publication and is subject to change by Renesas Electronics Corp. without notice. Please review the latest information published by Renesas Electronics Corp. through various means, including the Renesas Electronics Corp. website (http://www.renesas.com). www.renesas.com Rev. 4.0 April 2019 Synergy Software Quality Handbook Descriptions of circuits, software and other related information in this document are provided only to illustrate the operation of semiconductor products and application examples. You are fully responsible for the incorporation or any other use of the circuits, software, and information in the design of your product or system. Renesas Electronics disclaims any and all liability for any losses and damages incurred by you or third parties arising from the use of these circuits, software, or information. 2. Renesas Electronics hereby expressly disclaims any warranties against and liability for infringement or any other disputes involving patents, copyrights, or other intellectual property rights of third parties, by or arising from the use of Renesas Electronics products or technical information described in this document, including but not limited to, the product data, drawing, chart, program, algorithm, application examples. 3. No license, express, implied or otherwise, is granted hereby under any patents, copyrights or other intellectual property rights of Renesas Electronics or others. 4. You shall not alter, modify, copy, or otherwise misappropriate any Renesas Electronics product, whether in whole or in part.
  • Site Reliability Engineering HOW GOOGLE RUNS PRODUCTION SYSTEMS

    Site Reliability Engineering HOW GOOGLE RUNS PRODUCTION SYSTEMS

    Site Reliability Engineering HOW GOOGLE RUNS PRODUCTION SYSTEMS Edited by Betsy Beyer, Chris Jones, Jennifer Petof & Niall Richard Murphy Praise for Site Reliability Engineering Google’s SREs have done our industry an enormous service by writing up the principles, practices and patterns—architectural and cultural—that enable their teams to combine continuous delivery with world-class reliability at ludicrous scale. You owe it to yourself and your organization to read this book and try out these ideas for yourself. —Jez Humble, coauthor of Continuous Delivery and Lean Enterprise I remember when Google first started speaking at systems administration conferences. It was like hearing a talk at a reptile show by a Gila monster expert. Sure, it was entertaining to hear about a very different world, but in the end the audience would go back to their geckos. Now we live in a changed universe where the operational practices of Google are not so removed from those who work on a smaller scale. All of a sudden, the best practices of SRE that have been honed over the years are now of keen interest to the rest of us. For those of us facing challenges around scale, reliability and operations, this book comes none too soon. —David N. Blank-Edelman, Director, USENIX Board of Directors, and founding co-organizer of SREcon I have been waiting for this book ever since I left Google’s enchanted castle. It is the gospel I am preaching to my peers at work. —Björn Rabenstein, Team Lead of Production Engineering at SoundCloud, Prometheus developer, and Google SRE until 2013 A thorough discussion of Site Reliability Engineering from the company that invented the concept.