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Release It!: Design and Deploy Production-Ready Software 2nd Edition
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A single dramatic software failure can cost a company millions of dollars - but can be avoided with simple changes to design and architecture. This new edition of the best-selling industry standard shows you how to create systems that run longer, with fewer failures, and recover better when bad things happen. New coverage includes DevOps, microservices, and cloud-native architecture. Stability antipatterns have grown to include systemic problems in large-scale systems. This is a must-have pragmatic guide to engineering for production systems.
If you're a software developer, and you don't want to get alerts every night for the rest of your life, help is here. With a combination of case studies about huge losses - lost revenue, lost reputation, lost time, lost opportunity - and practical, down-to-earth advice that was all gained through painful experience, this book helps you avoid the pitfalls that cost companies millions of dollars in downtime and reputation. Eighty percent of project life-cycle cost is in production, yet few books address this topic.
This updated edition deals with the production of today's systems - larger, more complex, and heavily virtualized - and includes information on chaos engineering, the discipline of applying randomness and deliberate stress to reveal systematic problems. Build systems that survive the real world, avoid downtime, implement zero-downtime upgrades and continuous delivery, and make cloud-native applications resilient. Examine ways to architect, design, and build software - particularly distributed systems - that stands up to the typhoon winds of a flash mob, a Slashdotting, or a link on Reddit. Take a hard look at software that failed the test and find ways to make sure your software survives.
To skip the pain and get the experience...get this book.
About the Author
- ISBN-109781680502398
- ISBN-13978-1680502398
- Edition2nd
- PublisherPragmatic Bookshelf
- Publication dateFebruary 13, 2018
- LanguageEnglish
- Dimensions7.5 x 0.78 x 9.25 inches
- Print length378 pages
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The Pragmatic Programmers publishes hands-on, practical books on classic and cutting-edge software development and engineering management topics. We help professionals solve real-world problems, hone their skills, and advance their careers.
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From the Preface
In this book, you will examine ways to architect, design, and build software —particularly distributed systems—for the muck and mire of the real world. You will prepare for the armies of illogical users who do crazy, unpredictable things. Your software will be under attack from the moment you release it. It needs to stand up to the typhoon winds of flash mobs or the crushing pressure of a DDoS attack by poorly secured IoT toaster ovens. You’ll take a hard look at software that failed the test and find ways to make sure your software survives contact with the real world.
Who Should Read This Book
I’ve targeted this book to architects, designers, and developers of distributed software systems, including websites, web services, and EAI projects, among others. These must be available or the company loses money. Maybe they’re commerce systems that generate revenue directly through sales or critical internal systems that employees use to do their jobs. If anybody has to go home for the day because your software stops working, then this book is for you.
Product details
- ASIN : 1680502395
- Publisher : Pragmatic Bookshelf; 2nd edition (February 13, 2018)
- Language : English
- Paperback : 378 pages
- ISBN-10 : 9781680502398
- ISBN-13 : 978-1680502398
- Item Weight : 1.27 pounds
- Dimensions : 7.5 x 0.78 x 9.25 inches
- Best Sellers Rank: #121,884 in Books (See Top 100 in Books)
- #9 in Client-Server Networking Systems
- #131 in Software Development (Books)
- #2,280 in Unknown
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Overall, I found the material well written although suited more to the newcomer than to seasoned pros...indeed, there are a few passages that aren't wrong, but will make the little hairs on the back of salty old IT operations staff stand up. Plus, many large organizations will be taking the release automation journey hand-in-hand with a set of vendor-written products that are usually optimized to work a certain way, and of course that will have a big impact on how you proceed. But, as a starting point for a person or team just trying to get their head around streamlining the release process, this book will definitely give the reader lots of good ideas.
Definitely recommended if you're in the early stages of DevOps and release automation.
An absolute master class in software engineering.
One, boring but important - typically *before* software is shipped - merge conflict, writing good commit message, writing unit tests (hopefully, before writing code), bring your voice to sprint grooming etc.
Two, exciting and critical - typically *after* software is shipped - performance bottlenecks, scalability concerns, "byzantine" failures (if no one knows why it happened, it is likely this!), fault-propagation (google "data center squirrel") etc.
Release It, 2nd edition deals with the latter and lays out a foundational roadmap on how to tackle those, drawn from author's experience. To the best of my knowledge, this is the only book where you can learn "it". I had the 1st edition for years and spending after 2nd edition was a smart decision.
Some notes and insights from the book are listed below. I call them "Scalability First Principles" --
-- distributed systems exhibit default availability more like “two eights” rather than the coveted “five nines"
-- Software design as taught today is terribly incomplete. It only talks about what systems should do. It doesn’t address the converse—what systems should not do.
-- Team assignments are the first draft of the architecture.
-- The postmortem can actually be harder to solve than a murder, because the body goes away.
-- An impulse is a rapid shock to the system. An impulse to the system is when something whacks it with a hammer. In contrast, stress to the system is a force applied to the system over an extended period. A celebrity tweet about your site is an impulse.
-- If all else fails, production becomes your longevity testing environment by default.
-- Just as auto engineers create crumple zones—software areas designed to protect passengers by failing first are called "crackstoppers".
-- Tight coupling accelerates cracks.
-- Two camps of software stability - Two camps - fault tolerant vs. let it crash
-- Traditional statistics is not applicable today. Six Sigma quality on Facebook would create 768,000 angry users per day
-- “technology frontier” -- where the twin specters of high interactive complexity and tight coupling conspire to turn rapidly moving cracks into full-blown failures
-- it can take a long time to discover that you can’t connect.
-- Speculative retries also allow failures to jump the gap.
-- Blocked Threads antipattern is the proximate cause of most failures.
-- Beware the code you cannot see.
-- Good marketing can kill you at any time
-- Anytime you have a “many-to-one” or “many-to-few” relationship, you can be hit by scaling effects when one side increases.
-- Start machines quickly, but shut them down slowly.
-- Slow responses tend to propagate upward from layer to layer in a gradual form of cascading failure.
-- Antipatterns - things that wake you up; Patterns - Things that let you enjoy normal life
-- App - things happen more and happen faster; DB - things happen less and happen slower
-- Hope is not a design method.
-- half your code is usually devoted to error handling instead of providing features
-- We’re usually more interested in the fault density than the total count.
-- Fiddling is often followed by the “ohnosecond”—that very short moment in time during which you realize that you have pressed the wrong key and brought down a server, deleted vital data, or otherwise damaged the peace and harmony of stable operations
-- Log files on production systems have a terrible signal-to-noise ratio.
-- Sometimes the best thing you can do to create system-level stability is to abandon component-level stability.
-- Handshaking is ubiquitous in low-level communications protocols but is almost nonexistent at the application level. Use health checks in clustered or load-balanced services as a way for instances to handshake with the load balancer.
-- A good test harness should be devious. It should be as nasty and vicious as real-world systems will be. The test harness should leave scars on the system under test.
-- Every performance problem starts with a queue backing up somewhere.
-- Automation has no judgment. When it goes wrong, it tends to go wrong really quickly.
-- A priori prediction of all failure modes is not possible. Human action is a major source of system failures.
-- Containers promise to deliver the process isolation and packaging of a virtual machine together with a developer-friendly build process.
-- Kubernetes, Mesos, and Docker Swarm are attacking both the networking and allocation problem. Whichever one solves this problem first will be able to truly claim the title of “operating system for the data center.”
-- Using containers pushes some complexity out of the boxes and into the control plane.
-- Code, Config, Connection - Fuel, Fire, Air
-- “Configuration” suffers from hidden linkages and high complexity—two of the biggest factors leading to operator error. This puts the system at risk because configuration is part of the system’s user interface
-- Netflix is a monitoring system that streams movies as a side effect.
-- best thing to do under high load is turn away work we can’t complete in time. This is called “load shedding,” and it’s the most important way to control incoming demand.
-- Services should also have relatively short listen queues.
-- Reject work as close to the edge as possible. The further it penetrates into your system, the more resources it ties up.
-- Start rejecting work when your response time is going to provoke retries. Rejection is much better than Retry at scale
-- GUIs make terrible administrative interfaces for longterm production operation. The best interface for long-term operation is the command line
-- We talk about pets and cattle, but given their ephemeral lifespans, we should call some of them “mayflies.”
-- We treat deployment as a feature.
-- The idea of continuous deployment is to reduce that delay as much as possible to minimize the liability of undeployed code. “If it hurts, do it more often.”
-- Static assets should always have far-future cache expiration headers.
-- Use traffic shaping at your load balancer to gradually ramp up traffic to the canary group while watching monitoring for anomalies in metrics.
-- The boundary between operations and development has become fractal.
-- Postel’s law: “Be conservative in what you do, be liberal in what you accept from others.”
-- i.e., We can always accept more than we accepted before, but we cannot accept less or require more. We can always return more than we returned before, but we cannot return less
-- The net suffering in your organization is minimized if everyone thinks globally and acts locally.
-- thrashing happens when the feedback from the environment is slower than the rate of control changes.
-- To avoid thrashing, try to create a steady cadence of delivery and feedback.
-- A closed feedback loop is essential to improvement. The faster that feedback loop operates, the more accurate those improvements will be. This demands frequent releases. Frequent releases with incremental functionality also allow your company to outpace its competitors and set the agenda in the marketplace.
-- “Form follows failure.” That is, changes in the design of such commonplace things as forks and paper clips are motivated more by the things early designs do poorly than those things they do well. Each new attempt differs from its predecessor mainly in its attempts to correct flaws.
-- Layers enforce vertical isolation, but they encourage horizontal coupling.
-- Microservices are a technological solution to an organizational problem. As an organization grows, the number of communication pathways grows exponentially. Similarly, as a piece of software grows, the number of possible dependencies within the software grows exponentially.
-- Classes tend toward a power-law distribution. Most classes have one or a few dependencies, while a very small number have hundreds or thousands. That means any particular change is likely to encounter one of those and incur a large risk of “action at a distance.” This makes developers hesitant to touch the problem classes, so necessary refactoring pressure is ignored and the problem gets worse. Eventually, the software degrades to a Big Ball of Mud.
-- It turns out that like concurrency, safety is not a composable property.
-- Drift into failure - systems exist within boundaries of Limits of capacity, economy & safety.
-- The task of a regulator is to eliminate variation, but this variation is the ultimate source of information about the quality of its work. Therefore, the better job a regulator does, the less information it gets about how to improve.
-- A related paradox is the “Volkswagen microbus” paradox: You learn how to fix the things that often break. You don’t learn how to fix the things that rarely break. But that means when they do break, the situation is likely to be more dire. We want a continuous low level of breakage to make sure our system can handle the big things.
-- At Netflix, chaos is an opt-out process.
-- “If you have a wall full of green dashboards, that means your monitoring tools aren’t good enough.” There’s always something weird going on.
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The book was immediately applicable to my day job. Every software developer who wants to put products in production should read this book.
Es un libro de 2017. Hoy en día se usan tecnologías distintas, los que lo compren para estar al día que lo tengan en cuenta.








