Discussing "Web Scalability for Startup Engineers" by Artur Ejsmont (Part 1)

Carter Morgan and Nathan Tupes discuss the importance of leveraging cloud technology and avoiding unnecessary reinvention in software engineering on their podcast, Book Overflow. Carter shares his strong preference for using existing cloud solutions like AWS S3 over building custom services. Nathan recounts a surprising encounter with Neil Ford in Germany and highlights the value of learning from industry experts. They delve into the book "Web Scalability for Startup Engineers" by Artur Ejsmont, emphasizing the significance of scalability, statelessness, load balancing, and the evolving landscape of databases. They also touch on the practical applications of these concepts in real-world scenarios and system design interviews.

• Scalability is defined as the ability to adjust the capacity of a system to cost-efficiently fulfill demands.
• It generally means handling more users, clients, data, transactions, or requests without affecting user experience.
• Scalability should allow for both scaling up and scaling down, and this process should be relatively cheap and quick to execute.
• In a startup context, scalability can make or break the company, particularly when dealing with sudden high traffic volumes.

"Scalability is an ability to adjust the capacity of the system to cost-efficiently fulfill the demands. Scalability usually means an ability to handle more users, clients, data, transactions, or requests without affecting the user experience."

• This quote emphasizes the dual aspects of scalability: handling increased demand while maintaining user experience.

"It is important to remember that scalability should allow us to scale down as much as scale up and that scaling should be relatively cheap and quick to do."

• This quote highlights the necessity for scalability to be flexible and cost-effective in both directions.

"If you are at a startup, scalability can make or break your company."

• This quote underscores the critical importance of scalability in a startup environment, where rapid growth and viral traffic can occur unexpectedly.

• Cloud technology allows for dynamic scaling, eliminating the need for physical servers that can be costly and difficult to manage.
• Leveraging cloud services like AWS, Google Cloud, and Microsoft Azure can prevent the pitfalls of managing your own infrastructure.
• Using cloud services ensures that you can handle sudden traffic spikes without needing to invest in physical hardware.

"I always joke that I'm like the anti-engineer because I will go to any lengths not to build something. I am such a huge proponent of cloud technology. I can't stand reinventing the wheel in any way, shape, or form."

• This quote emphasizes the speaker's strong preference for using existing cloud solutions to avoid unnecessary effort and complexity.

"Why on Earth would you build your own file hosting service? Just use S3."

• This quote illustrates the practicality of using established cloud services like AWS S3 for file hosting, highlighting the efficiency and reliability of such solutions.

• Scalability ties directly into business needs, translating market demand into technical requirements.
• Understanding the business implications of scalability can help engineers make better decisions that align with company goals.
• The ability to scale dynamically ensures that businesses can capitalize on viral moments and high traffic periods without losing potential customers.

"At the end of the day, the business is just translating market demand into requirements, and market demand is just a manifestation of the real needs of real people."

• This quote connects the technical concept of scalability to its business impact, emphasizing the importance of aligning technical capabilities with market needs.

"If you have a lot of people visit you all of a sudden, your machine doesn't catch on fire, or you don't have to buy tons of more machines to handle peak capacity. You can scale up and scale down dynamically."

• This quote highlights the practical benefits of cloud technology in handling variable traffic loads efficiently.

• Good scalability is downstream of good software design principles like modularity, readability, and maintainability.
• While the book covers these principles, it acknowledges that they have been better addressed in other literature.
• Emphasizing good software design ensures that scalability is easier to achieve and maintain.

"Good scalability is downstream of good software design in general."

• This quote underscores the foundational role that solid software design principles play in achieving effective scalability.

"The whole kind of first chunk of this book is kind of about just good software design in general... good scalability is downstream of good software design in general."

• This quote reiterates the importance of good software design as a prerequisite for achieving scalability.

• The book serves as a time capsule, capturing the state of technology and best practices from a decade ago.
• It highlights the rapid evolution of tools and technologies, such as the absence of Docker and Kubernetes in the book.
• Despite these changes, the core principles of scalability and good design remain relevant.

"It's kind of funny there's not a mention of Docker or React when these have become such important technologies in the modern landscape."

• This quote points out the rapid evolution of technology and the changing landscape of best practices in software engineering.

"Principles still ring true; some of the trendy things like AngularJS is mentioned in the book, but React didn't exist yet."

• This quote emphasizes that while specific technologies may change, the underlying principles of scalability and good design remain constant.

• The book provides practical examples and case studies to illustrate key concepts.
• It discusses real-world scenarios, such as the viral success of an interview or the challenges faced by companies like Stripe in scaling their infrastructure.
• These examples help ground the theoretical concepts in practical, real-world applications.

"Our interview with Brian Kernighan went viral on Hacker News... thank goodness we just use YouTube, which can handle huge amounts of traffic."

• This quote provides a real-world example of the importance of using scalable platforms to handle unexpected traffic spikes.

"Stripe scaled MongoDB to 5 million queries per second... they built this at a time in which they had to build their own tools to meet their scale needs in the early 2010s."

• This quote highlights a case study of how a major company like Stripe addressed scalability challenges, showcasing the practical application of the book's principles.

• Embarrassingly parallel refers to tasks that can be easily divided into smaller tasks that can be processed simultaneously without dependency on each other.
• This approach helps in structuring work to avoid cross-process dependencies, making the problem easier to solve.

"There's an old term called embarrassingly parallel... it's a way of structuring work so that you don't have dependencies across the processes that you're dealing with."

• Parallel processing can help in faster load times and reduce the load on servers by distributing tasks.

• Scalability involves not just the raw throughput but also the development process, teams, and code structure.
• Different strategies are required for different types of businesses, such as startups versus highly regulated companies.
• Startups often need to grow aggressively, requiring unique scalability strategies compared to more predictable environments like public transportation systems.

"To fully appreciate how scalability affects startups, try to assume more business-oriented perspectives: what are the constraints that could prevent our business from growing?"

• Scalability should be planned from the beginning to avoid costly rewrites and inefficiencies later.

"Keep in mind that many of the scalability evolution stages presented here only work if you plan for them in the beginning."

"Avoid full application rewrites at all costs, especially if you work in a startup. Rewrites always take much longer than you initially expect and are much more difficult than initially anticipated."

• Modern internet users have high expectations for performance; slow load times can lead to user drop-off.
• Startups must compete with established companies not just in product but also in performance and user experience.

"If a web page doesn't load in 5 seconds, we click away. We just assume it's broken."

• Internal performance thresholds, like aiming for a page load time of 1.8 seconds, are critical in meeting user expectations.

"Our internal threshold is 1.8 seconds, which I think 2 seconds is what we try to aim for."

• Open source projects from tech giants like Google and Facebook help train the public in effective design patterns.
• Tools like Kubernetes and React are examples of industry standards that originated as internal projects.

"By releasing these things as open source, you're actually training the public in design patterns that have helped these companies reach the scale that they have."

• Stateless services are fully interchangeable, allowing any instance to handle requests without side effects.
• This is crucial for scalability as it allows for easy horizontal scaling by adding more instances of the application.

"The key difference between stateful and stateless services is that instances of a stateless service are fully interchangeable, and clients can use any of the instances without seeing any difference in behavior."

• Statelessness is achieved by moving state out of the front-end application to an independent store, usually a database.

"When we talk about statelessness in services, we're not talking about having no state anywhere in the application; it's about moving that state out of the front-end application itself to some sort of independent store."

• Load balancers distribute incoming traffic across multiple instances of an application to ensure no single instance is overwhelmed.
• Modern load balancers operate across multiple availability zones to avoid single points of failure.

"A load balancer dynamically sends your traffic to one of the many instances that it's sitting in front of."

• High availability is achieved by running load balancers in multiple availability zones, ensuring reliability even if one zone fails.

"By default, you'll actually run an elastic load balancer in three availability zones... if any one of them goes out, you're not dead in the water."

• Full application rewrites are often more complex and time-consuming than initially expected.
• Rewrites can lead to similar issues as the original codebase over time and should be avoided if possible.

"Avoid full application rewrites at all costs... rewrites always take much longer than you initially expect and are much more difficult than initially anticipated."

• Instead of rewrites, consider decoupling pieces of the application and refactoring incrementally.

"With the rise of things like microservices... there are ways that you can sidestep a full rewrite, such as decoupling pieces and pulling out specific functionalities."

• Functional partitioning involves breaking down an application into smaller, independent services, often referred to as microservices.
• This approach allows for more manageable scaling and easier maintenance.

"Functional partitioning, which he's really just talking about microservices... breaking services out by their functionality."

• Analogies like grocery store checkout lanes help illustrate complex concepts like statelessness and load balancing.
• These analogies make it easier to understand how multiple instances of an application can process tasks in parallel.

"Imagine you have a shopping cart and that the state of keeping track of all the items that you have is handled externally... you could put a million cash registers in parallel, and those can handle any number of customers."

The podcast transcript covers various aspects of scalability in web applications, focusing on strategies for startups. Key themes include embarrassingly parallel work, the importance of performance, open source contributions, statelessness in web applications, load balancing, avoiding full rewrites, functional partitioning, and practical analogies to explain complex concepts. The discussion emphasizes planning for scalability from the beginning, using industry-standard tools, and understanding the unique challenges faced by startups in a highly competitive environment.

• Network Load Balancer (NLB): Routes TCP or UDP traffic without handling SSL/TLS termination.
• Purpose: Encapsulates complexity by routing traffic to multiple servers, making the backend architecture invisible to the outside world.
• Stateless Infrastructure: Front-end load balancers are often stateless, simplifying scaling and management.

"I'm sorry load balancers one's called Network load balancer it doesn't actually handle things like SSL termination or TLS termination all it does is Route TCP or UDP traffic so it's like what much lower in the tcpip stack"

• NLB operates at a lower level in the TCP/IP stack, focusing purely on routing traffic.

"However complicated it is whether I have one server or 7,000 servers behind that load balancer you don't know or care like you just send me traffic and I will respond to that traffic and that's the whole purpose of a load balancer"

• The load balancer abstracts the complexity of the backend infrastructure from the outside world.

• Definition: SPAs are web applications that load a single HTML page and dynamically update the content.
• Challenges: Initially, web crawlers couldn't index SPAs properly, causing issues with search engine optimization (SEO).
• Evolution: Server-Side Rendering (SSR) and hydration techniques have improved SPA performance and SEO compatibility.

"Single page applications are applications that largely live in JavaScript on the client... it felt fast in your hand like it felt like a mobile app almost like on in the web browser"

• SPAs provide a fast, mobile-app-like experience by dynamically updating content without reloading the page.

"Webcrawlers were designed to to scrape those individual pages that are served up by servers and they they couldn't do that anymore"

• Early SPAs posed challenges for web crawlers, affecting their ability to index content properly.

• Purpose: CDNs cache static assets like images, videos, and JavaScript files, distributing them closer to the user to reduce latency.
• Benefits: Offloads traffic from the backend, reduces load on the load balancer, and improves user experience by serving content quickly from the nearest edge location.

"You basically a lot of people use it for static assets that would be expensive to load video files images JavaScript... and this will just load really quickly off of this content distribution Network"

• CDNs are used to efficiently serve static assets, reducing load times and server strain.

"It's also physically close to you so there's ways that the providers can say like okay we'll use this Edge Network The Edge Network meaning we'll store it physically close to the person requesting it"

• CDNs leverage edge networks to store and serve content from locations physically close to users, minimizing latency.

• Definition: Extends the concept of CDNs by moving some computational tasks closer to the user.
• Examples: Cloudflare Workers, AWS Lambda@Edge, Fly.io, Vercel.
• Benefits: Enables faster processing and reduced latency by executing code near the user's location.

"They actually have moved a lot of the logic all the way to the edge to the CDN so that if it's appropriate you can actually load your static assets and do a little bit of compute really close to the customer"

• Edge compute allows for executing code and serving content near the user, further reducing latency.

• Microservices: Isolate specific functionalities into independent services that can be scaled and managed separately.
• Functional Partitioning: Similar to microservices, it involves isolating functionality and encapsulating it into independent services.
• Team Structure: Aligning microservices with small, autonomous teams (e.g., two-pizza teams) enhances development efficiency and ownership.

"He talks about microservices but he doesn't really call them that he I think he calls them functional partitioning... isolate a piece of functionality that requires a globally available State remove it from the application and create a new independent service"

• Functional partitioning involves creating independent services for specific functionalities, similar to microservices.

"You should probably structure your services around what can be independently maintained by a two Pizza team right so it's a rule of thumb"

• The two-pizza team concept suggests that services should be manageable by small, autonomous teams.

• Monolith: Single, large codebase where all functionalities are tightly coupled.
• Microservices: Decoupled services that communicate over the network, allowing for independent development and scaling.
• Trade-offs: While microservices offer flexibility and scalability, they can introduce complexity in terms of service communication and management.

"You know the it really has to do with the fact that like you know if let's say there's a bunch of like philosophy on you know Amazon does this a bunch of other companies done this so they call the two Pizza teams try to keep your teams small enough that two pizzas could feed well you should probably structure your services around what can be independently maintained by a two Pizza team right so it's a rule of thumb"

• Microservices should align with team structures that can independently manage and maintain them.

• SOAP: An older protocol for RPCs, heavily reliant on XML.
• REST: A more modern, resource-centric approach using HTTP and JSON.
• gRPC: A modern RPC framework that uses binary serialization for efficient communication.

"Soap was this very XML heavy way of doing remote procedure calls or rpcs... most Services try to do like a restful API it's like very very common even though the idea is you know 20 years old a little over 20 25 years old really"

• SOAP was an early method for RPCs, now largely replaced by REST and gRPC.

"Json one or if you're doing uh what they call like a binary serialization which is what grpc does which is like it actually has its own uh encoding format that is very efficiently sends data and it's typed and does all this like cool stuff"

• gRPC offers efficient, typed communication using binary serialization, suitable for complex business logic.

• Ownership Model: Encourages teams to take responsibility for specific services or components.
• Challenges in Monoliths: Large, shared codebases can lead to conflicts and reduced ownership, making it harder to manage and scale.

"I feel like if strong ownership over the product you create is a really guiding belief of your team I would I would really Place some heavy weight on on using microservices I think it rein forces that Paradigm much better"

• Microservices support a strong ownership model, enhancing team responsibility and control over their code.

"If there is no owner that's really all it is it's like ah you I have to get through this PR you know some bug happened and I'm just goingon to like fix it real real quick when I'm me get out of here"

• Without ownership, code quality and responsibility can diminish, leading to quick fixes and lack of pride in the codebase.

• SQL: Traditional relational databases, strong consistency, and ACID properties.
• NoSQL: Non-relational databases, designed for horizontal scalability and flexibility.
• Hybrid Approaches: Combining SQL and NoSQL to leverage the strengths of both for different use cases.

"So you know I guess uh Nathan let's talk about the data layer and what are your initial thoughts on how we the advice he gives on on designing a scalable data layer"

• The data layer's design involves choosing between SQL and NoSQL based on the application's scalability and consistency requirements.

These notes provide a comprehensive overview of the key themes and ideas discussed in the transcript, along with relevant verbatim quotes and explanations.

• SQL Databases:

  • Use ACID (Atomicity, Consistency, Isolation, Durability) properties.
  • Examples include MySQL, PostgreSQL, Microsoft SQL Server.
  • Powerful but challenging to scale, especially for write-heavy applications.

• NoSQL Databases:

  • Do not use traditional relational models or ACID properties.
  • Designed for horizontal scaling and handling large amounts of data.
  • Examples include MongoDB, DynamoDB, Redis, Cassandra.
  • Allow for flexible data schemas, such as JSON.

"Here's what SQL does and here's why it's so cool and here's why it's so powerful but it's actually hard to scale."

• SQL databases are powerful but come with scalability challenges.

"NoSQL takes a horizontal scaling approach where it can just kind of infinitely add more clones of itself to itself, which allows you to handle tons and tons of data."

• NoSQL databases excel in horizontal scaling, making them suitable for large data volumes.

• Master-Slave to Boss-Worker:
  • Historical context: Master-Slave terminology has fallen out of fashion.
  • Modern terminology: Boss-Worker or other alternatives.
  • Acknowledgment of historical terms for consistency with older texts.

"This book actually uses the term master and slave a lot. That's fallen out of fashion."

• The book uses outdated terminology, and modern alternatives are recommended.

"We should give a historical nod that this is the same period of time in which we stopped using Master branch and get and it switched to Maine over at GitHub."

• Terminology changes reflect broader societal shifts in language use.

• Read Replicas and Functional Partitioning:

  • Read replicas: Useful for read-heavy applications.
  • Functional partitioning: Different databases for different tasks (e.g., users, shopping cart).

• Sharding:

  • Divides data into smaller, manageable pieces.
  • Useful for both read-heavy and write-heavy applications.
  • Complex to implement due to data repartitioning and query routing challenges.

"You can have a bunch of read replicas, actually, and this is interesting too, we've changed our terminology a lot over the last 10 years."

• Read replicas are a common technique for scaling read-heavy applications.

"Sharding is not easy though because you can't just like it's not as simple as just adding more copies of the database because when you Shard again well now you have to repartition all of that data."

• Sharding requires careful planning and management.

• Cloud Services:

  • Managed databases like Amazon RDS, Google Bigtable.
  • Aurora: MySQL/PostgreSQL compatible with automatic scaling.

• Open Source Projects:

  • Vitess: Distributed database technology used by YouTube.
  • PlanetScale: Commercial version of Vitess for scalable database solutions.

"They now also have Aurora which is this really amazing technology that is MySQL compatible or PostgreSQL compatible but actually does a bunch of scaling like automatically scal storage up to terabytes."

• Aurora offers automatic scaling and is compatible with popular SQL databases.

"There's a new database or there's a database that actually the team that built so YouTube runs on MySQL server."

• Vitess is a distributed database technology developed for YouTube's scalability needs.

• CAP Theorem:

  • Consistency, Availability, Partition Tolerance: Pick two.
  • Drives the design of distributed systems and databases.

• NoSQL Databases and CAP Theorem:

  • MongoDB, DynamoDB, Redis: Examples of databases designed with CAP theorem trade-offs.
  • Purpose-built databases for specific needs (e.g., high availability, partition tolerance).

"The CAP theorem stated that you get there's three characteristics of these distributed systems there's consistency availability and partition tolerance and that you have to pick two."

• CAP theorem highlights the trade-offs in designing distributed systems.

"MongoDB is a probably a really big one that again I think kind of hit the hype machine, people realize that it's not this like perfect does everything database but for what it does do it's pretty amazing."

• MongoDB is a widely used NoSQL database with specific strengths and trade-offs.

• System Design Interviews:

  • Understanding the underlying technology is crucial.
  • Familiarity with terms like sharding, replication, and CAP theorem can impress interviewers.

• Emerging Database Technologies:

  • Importance of staying updated with new technologies and their implementations.
  • Deep dives into specific technologies can enhance practical knowledge and career growth.

"If you say you know actually, I learned this concept from web scalability for startup Engineers by Ur Edgmont, that's a I'd find you impressive if you said that."

• Demonstrating knowledge from reputable sources can be impressive in interviews.

"I want to make sure I spend more time doing deep dives into various emerging database Technologies just because the daily are so fascinating."

• Continuous learning and exploring new technologies are essential for career development.

• For Founding Engineers:

  • Dive deeper into the philosophy of decision-making around building scalable startups.
  • Recommended reading: "Fundamentals of Software Architecture" for modern thinking.

• For System Design Enthusiasts:

  • Gain a deeper understanding of why sharding, replication, and other techniques are important.
  • Explore newsletters and blogs for practical examples and up-to-date information.

"I would recommend this to founding Engineers who want to dive deeper into the philosophy of like decision making around building scalable startups."

• The book is highly recommended for engineers focused on building scalable systems.

"I'm gonna go a little deeper and and figure out kind of the nuts and bolts of our database strategy at my current company."

• Understanding the database strategy at your workplace can provide valuable insights.

"This is a great way to get a deeper dive on exactly why sharding is important on why replication is important on the advantages between SQL and no SQL statelessness everything we've really talked about here."

• The book provides a comprehensive understanding of key concepts in database scalability.