Scalable Quotes

Metaphor is awkward, but emotion, by its nature, leaves you no more scalable approach.

If you do something to benefit one person, that is an absolute gain, and its relative insignificance in the wider scheme is irrelevant. Benefit two people without concomitant harm to others - or a village, tribe, city, class, nation, society or civilisation - and the benefits are scalable, arithmetic. There is no excuse beyond fatalistic self-indulgence and sheer laziness for doing nothing.

In distributed systems, suspicion, pessimism, and paranoia pay off.

The moral of the story is that a NoSQL system may find itself accidentally reinventing SQL, albeit in disguise.

data outlives code.

Without stories of progress, the world has become a terrifying place. The ruin glares at us with the horror of its abandonment. It’s not easy to know how to make a life, much less avert planetary destruction. Luckily there is still company, human and not human. We can still explore the overgrown verges of our blasted landscapes - the edges of capitalist discipline, scalability, and abandoned resource plantations. We can still catch the scent of the latent commons - and the elusive autumn aroma.

You get what you design for. Chester, your peer in Development, is spending all his cycles on features, instead of stability, security, scalability, manageability, operability, continuity, and all those other beautiful ’itties.

how do you get, maintain, and multiply attention in a scalable and efficient way?

The faster you run high quality experiments, the more likely you’ll find scalable, effective growth tactics. Determining the success of a customer acquisition idea is dependent on an effective tracking and reporting system, so don’t start testing until your tracking/reporting system has been implemented.

Learn the language you need. Learn the language of business (accounting) Learn the language of scalability (programming) Learn the language of entrepreneurship (influence)

Concepts and patterns that your brain is sorting through and making sense of are much more scalable and universal than any specific vendor’s technology

Scalability becomes supercharged with “network effects.” A network effect exists when assets become more valuable the more of them exist.

A growth hacker is someone who has thrown out the playbook of traditional marketing and replaced it with only what is testable, trackable, and scalable. Their tools are e-mails, pay-per-click ads, blogs, and platform APIs instead of commercials, publicity, and money.

It is one thing when prices drift downward over time due to innovation, scalability or other efficiencies. This might be considered “good” deflation and is familiar to any contemporary consumer who has seen prices of computers or wide-screen TVs fall year after year. It is another matter when prices are forced down by unnecessary monetary contraction, credit constraints, deleveraging, business failures, bankruptcies and mass unemployment. This may be considered “bad” deflation. This bad deflation was exactly what was required in order to return the most important currencies to their prewar parity with gold.

A database is just a tool: how you use it is up to you.

We spend this life looking for a center, a place where we can suspend without a wobble. The specific coordinates are elusive, scalable only by the heart. _Population: 485_, p 202

Reactive applications are characteristically interactive, fault tolerant, scalable, and event driven.

Self-service is a scalable, cost-effective way to make customers happy.

When a team must allocate a disproportionate amount of time to resolving tickets at the cost of spending time improving the service, scalability and reliability suffer.

Next, name your scalable product or service. Naming your offering gives you ownership of it and helps you differentiate it from those of potential competitors.

A second key to deep decarbonization brings up an inconvenient truth for the traditional Green movement: nuclear power is the world’s most abundant and scalable carbon-free energy source.

Whenever you hear a snotty (and frustrated) European middlebrow presenting his stereotypes about Americans, he will often describe them as “uncultured,” “unintellectual,” and “poor in math” because, unlike his peers, Americans are not into equation drills and the constructions middlebrows call “high culture”—like knowledge of Goethe’s inspirational (and central) trip to Italy, or familiarity with the Delft school of painting. Yet the person making these statements is likely to be addicted to his iPod, wear blue jeans, and use Microsoft Word to jot down his “cultural” statements on his PC, with some Google searches here and there interrupting his composition. Well, it so happens that America is currently far, far more creative than these nations of museumgoers and equation solvers. It is also far more tolerant of bottom-up tinkering and undirected trial and error. And globalization has allowed the United States to specialize in the creative aspect of things, the production of concepts and ideas, that is, the scalable part of the products, and, increasingly, by exporting jobs, separate the less scalable components and assign them to those happy to be paid by the hour. There

Defining the sales methodology enables the sales training formula to be scalable and predictable. The three elements of the sales methodology are the buyer journey, the sales process, and the qualifying matrix.

As the Big Shift takes hold, companies are no longer places that exist to drive down costs by getting increasingly bigger. They’re places that support and organize talented individuals to get better faster by working with others. The rationale of the firm shifts from scalable efficiency to scalable learning—the ability to improve performance more rapidly and learn faster by effectively integrating more and more participants distributed across traditional institutional boundaries.

the success of creation spaces can be traced back to careful design at the outset by a small group of people who were very thoughtful about the conditions required to foster or “scaffold” scalable collaboration, learning, and performance improvement.

The Global Learning XPRIZE competition, which started in 2014, offered $15 million for “open-source, scalable software that will enable children in developing countries to teach themselves basic reading, writing and arithmetic within 15 months.” Results from the winners, Kitkit School and onebillion, suggest that the goal has largely been achieved.

First make it possible. Then make it beautiful. Then make it fast.

The need for data integration often only becomes apparent if you zoom out and consider the dataflows across an entire organization.

The fastest and most reliable network request is no network request at all!

it is poor civic hygiene to install technologies that could someday facilitate a police state

The Google File System

Martin Kleppmann: “Rethinking Caching in Web Apps,

To Schema on Read or to Schema on Write, That Is the Hadoop Data Lake Question

Lawrence Page, Sergey Brin, Rajeev Motwani, and Terry Winograd: “The PageRank Citation Ranking: Bringing Order to the Web,” Stanford InfoLab Technical Report 422, 1999.

If we want the future to be better than the past, moral imagination is required, and that’s something only humans can provide [87]. Data and models should be our tools, not our masters.

Direct democracy, prefigurative politics and direct action are not, we hasten to add, intrinsically flawed.19 Rather than being denounced in themselves, their utility needs to be judged relative to particular historical situations and particular strategic objectives – in terms of their ability to exert real power to create genuine lasting transformation. The reality of complex, globalised capitalism is that small interventions consisting of relatively non-scalable actions are highly unlikely to ever be able to reorganise our socioeconomic system. As we suggest in the second half of this book, the tactical repertoire of horizontalism can have some use, but only when coupled with other more mediated forms of political organisation and action.

The cost-effectiveness of energy has four dimensions: Affordability: How much money does it cost relative to how much money people have? Reliability: To what extent can it be produced “on demand”—when needed, in as large a quantity as needed? Versatility: How wide a variety of machines can it power? Scalability: How many people can it produce energy for and in how many places?

Starting a successful business is not tricky. Starting a successful business does not require above average intelligence. Starting a successful business does require having a pig-headed, purpose-driven tenacity about achieving your life goals and fulfilling your life's vision through providing products and services that offer uncompromising quality in a scalable and duplicatable way.

PEACETIME CEO/WARTIME CEO Peacetime CEO knows that proper protocol leads to winning. Wartime CEO violates protocol in order to win. Peacetime CEO focuses on the big picture and empowers her people to make detailed decisions. Wartime CEO cares about a speck of dust on a gnat’s ass if it interferes with the prime directive. Peacetime CEO builds scalable, high-volume recruiting machines. Wartime CEO does that, but also builds HR organizations that can execute layoffs. Peacetime CEO spends time defining the culture. Wartime CEO lets the war define the culture. Peacetime CEO always has a contingency plan. Wartime CEO knows that sometimes you gotta roll a hard six. Peacetime CEO knows what to do with a big advantage. Wartime CEO is paranoid. Peacetime CEO strives not to use profanity. Wartime CEO sometimes uses profanity purposefully. Peacetime CEO thinks of the competition as other ships in a big ocean that may never engage. Wartime CEO thinks the competition is sneaking into her house and trying to kidnap her children. Peacetime CEO aims to expand the market. Wartime CEO aims to win the market. Peacetime CEO strives to tolerate deviations from the plan when coupled with effort and creativity. Wartime CEO is completely intolerant. Peacetime CEO does not raise her voice. Wartime CEO rarely speaks in a normal tone. Peacetime CEO works to minimize conflict. Wartime CEO heightens the contradictions. Peacetime CEO strives for broad-based buy-in. Wartime CEO neither indulges consensus building nor tolerates disagreements. Peacetime CEO sets big, hairy, audacious goals. Wartime CEO is too busy fighting the enemy to read management books written by consultants who have never managed a fruit stand. Peacetime CEO trains her employees to ensure satisfaction and career development. Wartime CEO trains her employees so they don’t get their asses shot off in the battle. Peacetime CEO has rules like “We’re going to exit all businesses where we’re not number one or two.” Wartime CEO often has no businesses that are number one or two and therefore does not have the luxury of following that rule.

Interruption Marketing was easy. Build a few ads, run them everywhere. Interruption Marketing was scalable. If you need more sales, buy more ads. Interruption Marketing was predictable. With experience, a mass marketer could tell how many dollars in revenue one more dollar in ad spending would generate. Interruption Marketing fit the command and control bias of big companies. It was totally controlled by the advertiser, with no weird side effects.

Pop culture is all about identity and feeling like you’re participating. It has nothing to do with cooperation, the past or the future — it’s living in the present. I think the same is true of most people who write code for money.

Similarly, product managers must be problem solvers as well. They are not trying to design the user experience, or architect a scalable, fault‐tolerant solution. Rather, they solve for constraints aligned around their customer's business, their industry, and especially their own business. Is this something their customers need? Is it substantially better than the alternatives? Is it something the company can effectively market and sell, that they can afford to build, that they can service and support, and that complies with legal and regulatory constraints?

Don’t know if there even is such a thing as “worse” when it comes to grief. I’ve kind of come to think of grief the same way you might think about drowning. Drowning is drowning, some people might be drowning for longer than others, some drowning might put you on a whole new path once you’re through it, sometimes it might change how your brain works if you’re cut off from oxygen for long enough, could even cost you your life—the severity of the drowning incident might be scalable but the drowning itself, the grief itself, it’s all water you can’t breathe in.

The appropriate milestones measuring a startup’s progress answer these questions: How well do we understand what problems customers have? How much will they pay to solve those problems? Do our product features solve these problems? Do we understand our customers’ business? Do we understand the hierarchy of customer needs? Have we found visionary customers, ones who will buy our product early? Is our product a must-have for these customers? Do we understand the sales roadmap well enough to consistently sell the product? Do we understand what we need to be profitable? Are the sales and business plans realistic, scalable, and achievable? What do we do if our model turns out to be wrong?

Scalable Social Network Analysis. The SSNA would monitor telephone calls, conference calls, and ATM withdrawals, but it also sought to develop a far more invasive surveillance technology, one that could “capture human activities in surveillance environments.” The Activity Recognition and Monitoring program, or ARM, was modeled after England’s CCTV camera. Surveillance cameras would be set up across the nation, and through the ARM program, they would capture images of people as they went about their daily lives, then save these images to massive data storage banks for computers to examine. Using state-of-the-art facial recognition software, ARM would seek to identify who was behaving outside the computer’s pre-programmed threshold for “ordinary.” The parameters for “ordinary” remain classified.

Technology is a powerful force in our society. Data, software, and communication can be used for bad: to entrench unfair power structures, to undermine human rights, and to protect vested interests. But they can also be used for good: to make underrepresented people’s voices heard, to create opportunities for everyone, and to avert disasters. This book is dedicated to everyone working toward the good.

The Industrial Revolution has bequeathed us the production-line theory of education. In the middle of town there is a large concrete building divided into many identical rooms, each room equipped with rows of desks and chairs. At the sound of a bell, you go to one of these rooms together with thirty other kids who were all born the same year as you. Every hour a different grown-up walks in and starts talking. The grown-ups are all paid to do so by the government. One of them tells you about the shape of the earth, another tells you about the human past, and a third tells you about the human body. It is easy to laugh at this model, and almost everybody agrees that no matter its past achievements, it is now bankrupt. But so far we haven’t created a viable alternative. Certainly not a scalable alternative that can be implemented in rural Mexico rather than just in wealthy California suburbs.

TechCrunch, Fast Company, Mashable, Inc., Entrepreneur, and countless other publications. LinkedIn and Hacker News abound with job postings: Growth Hacker Needed. Their job isn’t to “do” marketing as I had always known it; it’s to grow companies really fast—to take something from nothing and make it something enormous within an incredibly tight window. And it says something about what marketing has become that these are no longer considered synonymous tasks. The term “growth hacker” has many different meanings for different people, but I’ll define it as I have come to understand it: A growth hacker is someone who has thrown out the playbook of traditional marketing and replaced it with only what is testable, trackable, and scalable. Their tools are e-mails, pay-per-click ads, blogs, and platform APIs instead of commercials, publicity, and money. While their marketing brethren chase vague notions like “branding” and “mind share,” growth hackers relentlessly pursue users and growth—and when they do it right, those users beget more users, who beget more users. They are the inventors, operators, and mechanics of their own self-sustaining and self-propagating growth machine that can take a start-up from nothing to something.

a young Goldman Sachs banker named Joseph Park was sitting in his apartment, frustrated at the effort required to get access to entertainment. Why should he trek all the way to Blockbuster to rent a movie? He should just be able to open a website, pick out a movie, and have it delivered to his door. Despite raising around $250 million, Kozmo, the company Park founded, went bankrupt in 2001. His biggest mistake was making a brash promise for one-hour delivery of virtually anything, and investing in building national operations to support growth that never happened. One study of over three thousand startups indicates that roughly three out of every four fail because of premature scaling—making investments that the market isn’t yet ready to support. Had Park proceeded more slowly, he might have noticed that with the current technology available, one-hour delivery was an impractical and low-margin business. There was, however, a tremendous demand for online movie rentals. Netflix was just then getting off the ground, and Kozmo might have been able to compete in the area of mail-order rentals and then online movie streaming. Later, he might have been able to capitalize on technological changes that made it possible for Instacart to build a logistics operation that made one-hour grocery delivery scalable and profitable. Since the market is more defined when settlers enter, they can focus on providing superior quality instead of deliberating about what to offer in the first place. “Wouldn’t you rather be second or third and see how the guy in first did, and then . . . improve it?” Malcolm Gladwell asked in an interview. “When ideas get really complicated, and when the world gets complicated, it’s foolish to think the person who’s first can work it all out,” Gladwell remarked. “Most good things, it takes a long time to figure them out.”* Second, there’s reason to believe that the kinds of people who choose to be late movers may be better suited to succeed. Risk seekers are drawn to being first, and they’re prone to making impulsive decisions. Meanwhile, more risk-averse entrepreneurs watch from the sidelines, waiting for the right opportunity and balancing their risk portfolios before entering. In a study of software startups, strategy researchers Elizabeth Pontikes and William Barnett find that when entrepreneurs rush to follow the crowd into hyped markets, their startups are less likely to survive and grow. When entrepreneurs wait for the market to cool down, they have higher odds of success: “Nonconformists . . . that buck the trend are most likely to stay in the market, receive funding, and ultimately go public.” Third, along with being less recklessly ambitious, settlers can improve upon competitors’ technology to make products better. When you’re the first to market, you have to make all the mistakes yourself. Meanwhile, settlers can watch and learn from your errors. “Moving first is a tactic, not a goal,” Peter Thiel writes in Zero to One; “being the first mover doesn’t do you any good if someone else comes along and unseats you.” Fourth, whereas pioneers tend to get stuck in their early offerings, settlers can observe market changes and shifting consumer tastes and adjust accordingly. In a study of the U.S. automobile industry over nearly a century, pioneers had lower survival rates because they struggled to establish legitimacy, developed routines that didn’t fit the market, and became obsolete as consumer needs clarified. Settlers also have the luxury of waiting for the market to be ready. When Warby Parker launched, e-commerce companies had been thriving for more than a decade, though other companies had tried selling glasses online with little success. “There’s no way it would have worked before,” Neil Blumenthal tells me. “We had to wait for Amazon, Zappos, and Blue Nile to get people comfortable buying products they typically wouldn’t order online.

what exactly is a startup? A startup is not a smaller version of a large company. A startup is a temporary organization in search of a scalable, repeatable, profitable business model

A startup is a temporary organization in search of a scalable, repeatable, profitable business model.

Management means measurement, and a failure to measure is a failure to manage.

A growth hacker is someone who has thrown out the playbook of traditional marketing and replaced it with only what is testable, trackable, and scalable. Their tools are e-mails, pay-per-click ads, blogs, and platform APIs instead of commercials, publicity, and money. While their marketing brethren chase vague notions like “branding” and “mind share,” growth hackers relentlessly pursue users and growth—and when they do it right, those users beget more users, who beget more users. They are the inventors, operators, and mechanics of their own self-sustaining and self-propagating growth machine.

The goal of Customer Development is not to avoid spending money but to preserve cash while searching for the repeatable and scalable business model. Once found, then spend like there’s no tomorrow.

non-functional tests such as performance, security, reliability, inter-operability, scalability, etc.

They will be moisture sensors, valve controls, “smart dust,” parking meters, home appliances, and so on. These types of end devices almost never contain the processors, memory, hard drives, and other features needed to run a protocol stack.

Cassandra is now 5 years old. It is an active open source project in the Apache Software Foundation and therefore it is known as Apache Cassandra as well. Cassandra can manage huge volume of structured, semi-structured, and unstructured data in a large distributed cluster across multiple data centers. It provides linear scalability, high performance, fault tolerance, and supports a very flexible data model.

Cassandra tokens are signed 64-bit integers, so the minimum possible hash is -263 or -9223372036854775808 and the maximum possible hash is 263-1 or 9223372036854775807.

Features of Cassandra In order to keep this chapter short, the following bullet list covers the great features provided by Cassandra: Written in Java and hence providing native Java support Blend of Google BigTable and Amazon Dynamo Flexible schemaless column-family data model Support for structured and unstructured data Decentralized, distributed peer-to-peer architecture Multi-data center and rack-aware data replication Location transparent Cloud enabled Fault-tolerant with no single point of failure An automatic and transparent failover Elastic, massively, and linearly scalable Online node addition or removal High Performance Built-in data compression Built-in caching layer Write-optimized Tunable consistency providing choices from very strong consistency to different levels of eventual consistency Provision of Cassandra Query Language (CQL), a SQL-like language imitating INSERT, UPDATE, DELETE, SELECT syntax of SQL Open source and community-driven

process of reading from multiple nodes and collating the results is performed by a coordinator node and is entirely transparent to the application.

In fact, Cassandra is even more robust when a node is unavailable to receive a write. Through a process called hinted handoff, other nodes in the cluster will store information about the write request, and then replay that request to the missing node when it becomes available again.

Note that master-follower databases are not distributed: every machine has a full copy of the dataset. Master-follower replication is great for scaling up the processing power available for handling read requests, but does nothing to accommodate arbitrarily large datasets. Master-follower replication also provides some resilience against machine failure: in particular, failure of a machine will not result in data loss, since other machines have a full copy of the same dataset.

We saw that counter columns can coexist in a table only with other counter columns; they can't be in the same table as other data columns or collection columns.

Cassandra's tunable consistency allows us to specify, for each query, how many replicas must be involved for the request to be considered a success.

Cassandra doesn't only send the request to one replica; instead, it sends the request to all the interested replicas, and then fulfills the request as soon as the first one responds successfully.

If the data is different on different replicas, Cassandra will return the copy with the most recent timestamp, ensuring that we are getting the most recently written copy of the row.

Using the ALL consistency for both reading and writing, however, is an overkill in virtually all cases. If we write the data at the ALL consistency, then we can subsequently read it with ONE consistency because we know all of the replicas have the most recent copy of the data. Conversely, if we are reading with the ALL consistency, we will have immediate consistency even if the profile was updated with ONE consistency. At least one of the replicas has the most recent version of the data, and since we're reading all the copies, we're guaranteed to get the latest version back in one of them.

Describing architectures through implementation is akin to constructing a picture of your current or desired soulmate from pictures cut out of US Magazine; the result may paint a good picture of what you have or want, but it in no way describes how it is that the soulmate will meet your current or future needs.

A startup is an organization formed to search for a scalable and repeatable business model.

A growth hacker is someone who has thrown out the playbook of traditional marketing and replaced it with only what is testable, trackable, and scalable. Their tools are e-mails, pay-per-click ads, blogs, and platform APIs instead of commercials, publicity, and money. While their marketing brethren chase vague notions like “branding” and “mind share,” growth hackers relentlessly pursue users and growth—and when they do it right, those users beget more users, who beget more users. They are the inventors, operators, and mechanics of their own self-sustaining and self-propagating growth machine that can take a start-up from nothing to something.

the build-up of reliable information from a very large number of individually unreliable sources.

Before he became the most brilliant and famous man in the ad business, David Ogilvy sold ovens door-to-door. Because of that, he never forgot that advertising is just a slightly more scalable form of creating demand than door-to-door sales.

This shows that even a slight spatial or casual dependency between data entries or operations could kill scalability, so separation of data into independent shards and careful data modeling is extremely important for scalability.

how do you get, maintain, and multiply attention in a scalable and efficient way?

Over the course of my coverage of this topic, I am convinced that CAP falls far short of giving a complete picture of the engineering tradeoffs behind building scalable, distributed systems.

scripting language is a programming language that provides you with the ability to write scripts that are evaluated (or interpreted) by a runtime environment called a script engine (or an interpreter). A script is a sequence of characters that is written using the syntax of a scripting language and used as the source for a program executed by an interpreter. The interpreter parses the scripts, produces intermediate code, which is an internal representation of the program, and executes the intermediate code. The interpreter stores the variables used in a script in data structures called symbol tables. Typically, unlike in a compiled programming language, the source code (called a script) in a scripting language is not compiled but is interpreted at runtime. However, scripts written in some scripting languages may be compiled into Java bytecode that can be run by the JVM. Java 6 added scripting support to the Java platform that lets a Java application execute scripts written in scripting languages such as Rhino JavaScript, Groovy, Jython, JRuby, Nashorn JavaScript, and so on. Two-way communication is supported. It also lets scripts access Java objects created by the host application. The Java runtime and a scripting language runtime can communicate and make use of each other’s features. Support for scripting languages in Java comes through the Java Scripting API. All classes and interfaces in the Java Scripting API are in the javax.script package. Using a scripting language in a Java application provides several advantages: Most scripting languages are dynamically typed, which makes it simpler to write programs. They provide a quicker way to develop and test small applications. Customization by end users is possible. A scripting language may provide domain-specific features that are not available in Java. Scripting languages have some disadvantages as well. For example, dynamic typing is good to write simpler code; however, it turns into a disadvantage when a type is interpreted incorrectly and you have to spend a lot of time debugging it. Scripting support in Java lets you take advantage of both worlds: it allows you to use the Java programming language for developing statically typed, scalable, and high-performance parts of the application and use a scripting language that fits the domain-specific needs for other parts. I will use the term script engine frequently in this book. A script engine is a software component that executes programs written in a particular scripting language. Typically, but not necessarily, a script engine is an implementation of an interpreter for a scripting language. Interpreters for several scripting languages have been implemented in Java. They expose programming interfaces so a Java program may interact with them.

Thankfully, over time, I have come to realize those skills initially dismissed as “soft”—communicating a vision, providing feedback, or leading a team—are fundamental to everything we try to do in business. You don't create a successful, sustainable, and scalable organization unless you can engage the people within the organization to work together. The “best friend at work” from the

startups need to operate in a “search” mode as they test and prove every one of their initial hypotheses. They learn from the results of each test, refine the hypothesis and test again, all in search of a repeatable, scalable and profitable business model.

If the application is event-driven, it can be decoupled into multiple self-contained components. This helps us become more scalable, because we can always add new components or remove old ones without stopping or breaking the system. If errors and failures are passed to the right component, which can handle them as notifications, the application can become more fault-tolerant or resilient. So if we build our system to be event-driven, we can more easily achieve scalability and failure tolerance, and a scalable, decoupled, and error-proof application is fast and responsive to users.

Microservices are important simply because they add unique value in a way of simplification of complexity in systems.  By breaking apart your system or application into many smaller parts, you show ways of reducing duplication, increasing cohesion and lowering your coupling between parts, thus making your overall system parts easier to understand, more scalable, and easier to change. The downside of a distributed system is that it is always more complex from a systems standpoint. The overhead of many small services to manage is another factor to consider. 

classic example is Google’s AdWords, which is now a multi-billion dollar business within Google. A key to its scalability is self-provisioning—that is, the interface for an AdWords customer has been completely automated such that there is no manual involvement.

Rule 28—Don’t Rely on QA to Find Mistakes

Don’t accept that the application is too complex or that you release code too often as excuses that you can’t roll back. No sane pilot would take off in an airplane without the ability to land, and no sane engineer would roll code that they could not pull back off in an emergency.

To grow your business you need cash, either generated from operations or raised as capital (equity or debt). The more cash your operations generate, the less capital you need to raise. Scalability means the ability of your business to generate increasing cash—cash flow from operations—for each additional dollar of capital invested (

A successful product may not be scalable, a successful process always is.

Scalability, availability, and performance are the top three concerns for an enterprise architect

The book takes a holistic view of three quality attributes—scalability, availability, and performance—

A really nice deep dive on Scalability Techniques for Practical Synchronization Primitives. 

The key is to combine new technologies with effective distribution to potential customers, a scalable and high-margin revenue model, and an approach that allows you to serve those customers given your probable resource constraints.

The purpose of hiring a management team is to solve the organization’s problems in a more scalable way. The CEO should be the hub, and the executive team the spokes that connect the CEO to the frontline managers and employees operating where the rubber hits the road.

In conclusion, smaller companies with a limited budget might opt for open source platforms. Larger, more established, and more demanding companies would typically go with a commercial platform, enabling them to connect their different applications under the same roof. Companies with high growth objectives should leverage scalable cloud-based platforms.

The second growth factor needed for a strong, scalable business is distribution.

How did Facebook successfully overcome the growth limiter of operational scalability? On the technology side, one of the philosophies that helped Facebook become successful was its famous motto “Move fast and break things.” This emphasis on speed, which came directly from Mark Zuckerberg, allowed Facebook to achieve rapid product development and continuous product improvement. Even today, every new software engineer who joins Facebook is asked to make a revision to the Facebook codebase (potentially affecting millions or even billions of users) on his or her first day of work. However, as Facebook’s user base and engineering team grew to a massive size, Mark had to change the philosophy to “Move fast and break things with stable infrastructure.

In contrast, a growth team’s engineers can move far faster because building scalable and extensible testing infrastructure is a core part of their jobs.

Beetsol provides businesses with robust and scalable solutions for their online meeting, event and training needs.

Engineers hate doing throwaway work. Not only is it wasteful, it offends their sense of efficiency. They are firm believers in the conventional wisdom that says it’s better to build your product right the first time, so you only have to build it once. But when you’re blitzscaling, inefficiency is the rule, not the exception. To prioritize speed, you might invest less in security, write code that isn’t scalable, and wait for things to start breaking before you build QA tools and processes. It’s true that all of these decisions will lead to problems later on, but you might not have a later on if you take too long to build the product. A hack that takes a tenth of the time may be more useful than an elegantly engineered solution, even if it has to be thrown away later.

A namespace is just a JavaScript object that we can use to hold the parts of our application.

create their own OKRs for their own organization. For example, the design department might have objectives related to moving to a responsive design; the engineering department might have objectives related to improving the scalability and performance of the architecture; and the quality department might have objectives relating to the test and release automation. The problem is that the individual members of each of these functional departments are the actual members of a cross‐functional product team. The product team has business‐related objectives (for example, to reduce the customer acquisition cost, to increase the number of daily active users, or to reduce the time to onboard a new customer), but each person on the team may have their own set of objectives that cascade down through their functional manager. Imagine if the engineers were told to spend their time on re‐platforming, the designers on moving to a responsive design, and QA on retooling. While each of these may be worthy activities, the chances of solving the business problems that the cross‐functional teams were created to solve are not high.

Startups are about focusing and executing on a single, scalable idea rather than jumping on every good one which crosses your desk.

True engineers love simple solutions. Avoid adding features that are not needed by the business. Avoid modifying the Data Vault 2.0 model by system attributes if there is no actual need. Whenever complexity is added to the solution, there must be a good reason for it. This makes it easier to maintain the final solution.