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pcrtisuyog · 2 months ago

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The Evolution of the Full Stack Web Developer: Then vs. Now

Technology is moving at lightning speed, and so are the people who build it. One such pivotal role in the digital space is that of the full stack developer—a professional who juggles both the front-end and back-end of web applications. But like all things in tech, the role of the full stack developer has undergone massive transformation over the past two decades.

So, how did we get from the simple websites of the early 2000s to today’s complex, cloud-integrated, API-driven web apps? Let’s walk through the evolution of the full stack web developer: then vs. now.

Back Then: Simpler Times, Simpler Stacks

In the early days of the internet, being a full stack developer meant you were a jack-of-all-trades—but the stack was far less complicated. Websites were relatively static, and the tools were limited but manageable.

What defined a full stack developer then?

HTML, CSS, and a bit of JavaScript: These were the core technologies for building any web interface.

Backend scripting with PHP or ASP.NET: Most developers used server-side languages like PHP for form processing and basic database interactions.

Databases like MySQL: Relational databases were the go-to for storing content.

Little to no version control: Most code was shared via ZIP files or FTP uploads.

Solo development: Often, a single developer managed the entire website—from writing HTML to setting up servers.

This era was defined by simplicity, but also by limitations. Sites were slower, less interactive, and rarely mobile-friendly. Yet, in those early days, one developer could manage it all.

Now: Complexity, Collaboration, and Constant Learning

Fast forward to today, and the web is a different beast. Users expect speed, responsiveness, personalized experiences, and seamless integration with other apps. To meet these expectations, the full stack developer has had to evolve dramatically.

What does a full stack developer look like now?

Front-End Frameworks: React, Angular, or Vue are commonly used for building dynamic user interfaces.

Back-End Powerhouses: Node.js, Django, Ruby on Rails, or even serverless functions on AWS or Azure.

Cloud & DevOps: Modern full stack developers often deploy on cloud platforms and manage CI/CD pipelines.

APIs and Microservices: Today’s applications are modular, and developers must work with RESTful APIs and sometimes GraphQL.

Database Variety: From SQL to NoSQL (MongoDB, Firebase), data storage is more versatile.

Version Control and Collaboration Tools: Git, GitHub, GitLab, and platforms like Jira and Slack are essential.

Security & Performance: Awareness of cross-site scripting, data encryption, and performance optimization is critical.

Modern full stack developers don’t just write code—they’re architects, problem-solvers, and collaborators.

The Human Side of the Evolution

Let’s not forget the human element. Twenty years ago, being a full stack developer often meant learning by doing. There were fewer formal resources, and “Googling it” wasn’t even a thing. Now, developers have access to endless online courses, forums, and bootcamps—but they also face constant pressure to keep up.

Challenges modern full stack developers face:

Burnout from constant learning

Juggling too many technologies

Unclear job definitions in some companies

Need to balance depth vs. breadth of skills

However, despite the complexity, today’s developers are part of a global community. They share code, contribute to open source, and support one another. That’s something that has only grown stronger over time.

The Stack Is Evolving—And So Is the Developer

The definition of a full stack developer continues to shift. Some developers specialize more in either front-end or back-end, while still understanding both. Others become tech leads, DevOps engineers, or product-focused developers. But at its core, the role is about versatility and adaptability.

Key skills of a modern full stack developer:

Proficiency in multiple languages and frameworks

Problem-solving mindset

Understanding of UI/UX principles

Ability to work with databases, APIs, and cloud infrastructure

Strong communication and teamwork skills

Conclusion: From Hackers to Architects

The journey from the humble beginnings of web development to today’s sophisticated tech stacks is a fascinating one. The full stack developer of the past may have worked alone, but the modern developer thrives in collaboration, supported by tools, teams, and an ever-growing tech ecosystem.

The evolution of the full stack web developer: then vs. now reminds us that while tools and technologies will continue to change, the heart of development—curiosity, creativity, and code—remains the same.

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cloudastra795 · 3 months ago

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Technical Aspects of MVP Development

In today's digital landscape, bringing an idea to market quickly and efficiently is hard yet important for success. This is where Minimum Viable Product (MVP) development plays an important role. MVP development allows businesses to test their ideas with minimal resources, collect user feedback, and iterate before investing heavily in full-scale development. Companies like CloudAstra MVP Development services specialize in building robust and scalable MVPs that set the foundation for successful products. In this blog, we’ll explore the technical aspects of MVP development and how CloudAstra’s expertise can help businesses achieve their goals efficiently.

Understanding the Technical Foundation of MVP Development

MVP development isn’t just about creating a simple version of your product; it involves careful planning and execution to ensure scalability and efficiency. Here are some key technical aspects that are essential for a successful MVP:

1. Choosing the Right Technology Stack

Selecting the right technology stack is a hard decision in MVP development. The technology stack should be scalable, cost-effective, and aligned with the product's needs.MVP Development services emphasize using modern technologies such as:

Frontend: React, Angular, or Vue.js for a seamless user experience.

Backend: Node.js, Python (Django/Flask), or Ruby on Rails for a fast and efficient server-side application.

Database: PostgreSQL, MongoDB, or Firebase depending on the data storage needs.

Cloud Services: AWS, Google Cloud, or Azure for robust hosting and deployment solutions.

2. Agile Development Methodology

Agile methodology plays a vital role in MVP development. It allows for fast iterations based on user feedback, ensuring continuous improvement. CloudAstra MVP Development services follow agile principles to ensure flexibility, quicker time-to-market, and improved adaptability to changes.

3. Building a Scalable Architecture

Even though an MVP is a basic version of the final product, it should be built with scalability in mind. Some key architectural considerations include:

Microservices vs. Monolithic Architecture: CloudAstra often recommends microservices for MVPs that need scalability and flexibility.

API-first Approach: Using RESTful APIs or GraphQL ensures seamless integration with third-party tools and future expansions.

Containerization: Technologies like Docker and Kubernetes help in smooth deployments and scaling of applications.

4. Rapid Prototyping and UI/UX Design

User experience plays a crucial role in MVP success. CloudAstra MVP Development services prioritize rapid prototyping using tools like Figma or Adobe XD to create user-friendly interfaces. A well-designed MVP should be intuitive, responsive, and engaging to attract early adopters.

5. Testing and Quality Assurance

A functional MVP must be tested thoroughly before launch. Some important testing processes include:

Automated Testing: Ensuring code quality through unit and integration testing.

Usability Testing: Gathering feedback from early users to improve the product.

Load Testing: Making sure the application performs well under high traffic. CloudAstra uses advanced testing tools to ensure that the MVP meets high-performance and reliability standards.

6. Cloud Deployment and Security Measures

Cloud-based deployment ensures cost-efficiency and scalability. CloudAstra MVP Development services leverage:

CI/CD Pipelines: Continuous integration and deployment for smooth updates.

Data Security: Implementing SSL encryption, secure authentication (OAuth, JWT), and data protection measures.

Cloud Hosting: Using AWS, GCP, or Azure for high availability and performance.

Why Choose CloudAstra MVP Development Services?

CloudAstra stands out as a reliable partner for MVP development due to its technical expertise and industry experience. Here’s why businesses prefer CloudAstra:

Experienced Developers: A team skilled in cutting-edge technologies.

End-to-End Development: From ideation to deployment and maintenance.

Agile and Scalable Solutions: Ensuring products evolve based on market demands.

Cost-Effective Approach: Delivering high-quality MVPs within budget constraints.

Final Thoughts

MVP development is a crucial step in transforming an idea into a successful product. Focusing on the right technical aspects—such as technology selection, scalable architecture, agile development, and security—can make all the difference. CloudAstra MVP Development services provide expert solutions that help businesses launch their MVPs quickly, efficiently, and with the best possible user experience. Whether you're a startup or an established company, partnering with CloudAstra ensures a solid foundation for your product’s success.

If you're looking to develop an MVP , CloudAstra MVP Development services are your go-to experts. Get started today and bring your vision to life with confidence! Visit Here : https://cloudastra.co/mvp

#mvp #mvp development company #mvp development agency #mvp development services

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thealgorithmblog · 4 months ago

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Building a Scalable Web Application for Long-Term Success

Introduction

In today's fast-paced digital world, web applications must be designed for scalability to ensure long-term success.

A scalable application can efficiently handle increasing user traffic, maintain high performance, and adapt to evolving business needs.

Whether you're developing an e-commerce site, a SaaS platform, or a social media network, adopting the right architecture and best practices is crucial.

This guide outlines the key principles, architectural patterns, and technologies needed to build a web application that scales efficiently over time.

1. Understanding Scalability

What is Scalability?

Scalability refers to a system's ability to handle increased workloads efficiently by leveraging additional resources such as computing power, storage, and network bandwidth. A well-designed scalable web application can support more users and process greater data loads without performance degradation.

Types of Scalability

Vertical Scaling (Scaling Up): Expanding a single server's resources (CPU, RAM, storage) to improve performance.

Horizontal Scaling (Scaling Out): Adding more servers to distribute workloads and enhance reliability.

Horizontal scaling is generally preferred for long-term success due to its resilience and ability to handle traffic spikes effectively.

2. Choosing the Right Architecture

A well-structured architecture is fundamental to scalability. Popular architectural patterns include:

Monolithic vs. Microservices

Monolithic Architecture: A single codebase integrating all components. While easier to develop initially, scaling becomes complex as the application grows.

Microservices Architecture: A modular approach where independent services communicate via APIs, allowing flexible scaling of individual components.

Serverless Architecture

Serverless computing enables developers to focus on code while cloud providers manage infrastructure dynamically, making it highly scalable and cost-effective.

3. Database Design for Scalability

Choosing the Right Database

Selecting a database that aligns with your application’s needs is crucial:

Relational Databases (SQL): MySQL, PostgreSQL – Ideal for structured data and transactional consistency.

NoSQL Databases: MongoDB, Cassandra – Suitable for unstructured data and large-scale applications.

Database Optimization Strategies

Sharding: Distributes data across multiple database instances.

Replication: Creates copies of data for redundancy and load balancing.

Indexing: Enhances query speed.

Caching: Uses tools like Redis or Memcached to store frequently accessed data in memory.

4. Efficient Backend and API Design

REST vs. GraphQL

REST APIs: Stateless architecture, widely used but may lead to over-fetching of data.

GraphQL: Allows clients to request only necessary data, optimizing bandwidth usage.

Asynchronous Processing

Using message queues (RabbitMQ, Kafka) enables background task processing, improving application responsiveness.

5. Frontend Scalability Considerations

Selecting the Right Framework

Popular frontend frameworks such as React, Angular, and Vue.js support scalable development with their component-based structures.

Frontend Performance Optimization

Lazy Loading: Loads only necessary components to enhance performance.

Code Splitting: Reduces initial load time by dividing JavaScript bundles.

CDN (Content Delivery Network): Improves load times by serving assets from distributed locations.

6. Load Balancing and Caching Strategies

Load Balancing

Distributing traffic across multiple servers prevents bottlenecks. Common solutions include Nginx, HAProxy, and AWS Elastic Load Balancer.

Caching Strategies

Client-Side Caching: Stores static files in the user's browser.

Server-Side Caching: Uses Redis or Memcached for frequently requested data.

Edge Caching: CDNs (Cloudflare, AWS CloudFront) serve cached content closer to users.

7. Security and Compliance

Implementing Security Best Practices

HTTPS Everywhere: Encrypts communication with TLS/SSL.

Authentication & Authorization: Uses OAuth, JWT, or OpenID Connect for secure user access.

Data Encryption: Protects sensitive information.

Rate Limiting & DDoS Protection: Prevents abuse using security services like Cloudflare.

Compliance Standards

Ensuring compliance with regulations such as GDPR, HIPAA, and PCI DSS protects user data and meets legal requirements.

8. Automated Testing and Continuous Deployment

Testing Strategies

Unit Testing: Validates individual components (Jest, Mocha, JUnit).

Integration Testing: Ensures smooth service interactions.

Load Testing: Simulates high traffic using JMeter and Locust.

CI/CD Pipelines

Automating deployment with GitHub Actions, Jenkins, and GitLab CI/CD ensures faster and more reliable releases.

9. Monitoring and Logging

Observability Tools

Tracking application health and performance is essential for scalability:

Logging: ELK Stack (Elasticsearch, Logstash, Kibana), Fluentd.

Monitoring: Prometheus, Grafana, New Relic.

Error Tracking: Sentry, Rollbar.

Automated Alerts

Using tools like PagerDuty ensures proactive issue resolution before they impact users.

10. Cloud Infrastructure and Hosting Choices

Cloud Providers

Choosing a scalable cloud platform ensures flexibility. Popular options include:

AWS (Amazon Web Services)

Google Cloud Platform (GCP)

Microsoft Azure

Containerization and Orchestration

Docker: Ensures consistency across development environments.

Kubernetes: Manages containerized applications at scale, providing resilience and efficiency.

Conclusion

Building a scalable web application requires thoughtful planning, robust architecture, and best practices in database management, API design, frontend optimization, and security.

Leveraging cloud infrastructure, automation, and monitoring tools ensures your application remains resilient and adaptable over time.

By following these principles, you can develop a high-performance, future-proof web application capable of handling increasing user demand and evolving business requirements.

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meeranjaz · 6 months ago

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Tips for Scaling Your Mobile Application Effectively

As your mobile application gains more users, the need to scale it becomes inevitable. Scaling ensures your app remains responsive, reliable, and efficient as the number of users and data grow. However, scaling a mobile app is not just about handling more users—it's about optimizing performance, improving infrastructure, and maintaining a seamless user experience. In this blog, we’ll discuss essential tips for scaling your mobile application effectively.

1. Optimize Your Backend Infrastructure The backend of your mobile app plays a crucial role in handling requests, storing data, and managing user interactions. As your app scales, your backend infrastructure must be able to support the increased load without compromising performance.

Cloud Services: Using cloud platforms like AWS, Google Cloud, or Microsoft Azure can provide the scalability needed. These platforms allow you to scale your app up or down depending on traffic and usage.

Load Balancing: Implement load balancers to evenly distribute traffic across servers, preventing any single server from becoming a bottleneck.

Microservices Architecture: Instead of a monolithic approach, consider breaking your backend into smaller, manageable microservices. This makes it easier to scale specific components of your app without affecting the entire system.

2. Improve Database Scalability As your app grows, so does the volume of data it needs to process. A poorly optimized database can cause slow performance, leading to a bad user experience. To scale your database:

Database Sharding: Distribute your database across multiple servers to reduce the load on a single server and ensure faster access times.

Caching: Implement caching strategies to reduce the need for constant database queries. Use tools like Redis or Memcached to store frequently accessed data temporarily.

Optimize Queries: Regularly review and optimize your database queries to minimize the strain on your database. Indexing, query optimization, and database normalization can make a significant difference in performance.

3. Focus on Mobile App Performance Optimization As your app scales, ensuring it remains responsive is essential. Slow load times or laggy performance can drive users away. Focus on these areas to enhance app performance:

Image Optimization: Large images can slow down app loading times. Use image compression techniques and modern formats like WebP to reduce image size without compromising quality.

App Caching: Cache static data and assets to speed up loading times and reduce the need for frequent data requests.

Code Splitting: Break your code into smaller chunks and load only the necessary parts of the app. This reduces the app’s initial load time and allows for faster updates.

App Profiling and Testing: Regularly use profiling tools (e.g., Android Profiler or Xcode Instruments) to test and monitor the app’s performance. Address memory leaks, unnecessary background processes, and other performance bottlenecks.

4. Implement Scalable APIs As the user base of your app grows, the demand on your app’s API also increases. To ensure your API can handle the scaling process:

API Rate Limiting: Implement rate limiting to prevent API abuse and ensure the server isn’t overwhelmed by too many requests at once.

Versioning: Maintain version control for your APIs to prevent compatibility issues as new features or updates are introduced.

REST vs GraphQL: Consider using REST APIs for simple use cases, but for more complex data-fetching needs, GraphQL might be a better option, offering more flexibility and efficiency in data retrieval.

5. Manage User Data Effectively With a growing user base, managing large amounts of data efficiently becomes critical. Implement the following best practices:

Data Compression: Use compression techniques to reduce the size of stored data, particularly for large files and images.

Data Encryption: Ensure sensitive user data is encrypted both at rest and in transit to maintain security and compliance with data protection regulations like GDPR.

Data Backup: Regularly back up user data to avoid loss due to unforeseen server failures or other issues.

6. Improve App Security as You Scale Security becomes increasingly important as your app gains more users and handles more data. Protecting user information and app data from potential breaches is critical:

Authentication: Use secure and scalable authentication methods, like OAuth or multi-factor authentication (MFA), to protect user accounts.

Secure APIs: Ensure your APIs are secure by using protocols like HTTPS, and implement regular security testing and vulnerability scans.

App Permissions: Be transparent with users about the permissions the app requests, ensuring you’re only collecting necessary data and maintaining user trust.

7. Implement User Analytics and Monitoring As your app scales, tracking user behavior, performance, and system health becomes crucial. Use analytics and monitoring tools to stay on top of your app’s performance and user engagement:

User Behavior Analytics: Tools like Firebase Analytics, Mixpanel, and Amplitude can help you understand user behavior, identify trends, and make data-driven decisions for future updates.

Crash and Performance Monitoring: Tools like Sentry or Firebase Crashlytics can provide insights into crashes, bugs, and performance bottlenecks, allowing you to address issues before they impact a large number of users.

8. Plan for Continuous Updates and Maintenance Scaling an app doesn’t stop once you’ve hit a certain number of users. Continuous updates, bug fixes, and feature enhancements are essential for keeping users engaged and maintaining a positive experience.

Agile Development: Use agile methodologies to ensure your app evolves with user needs. Break your development into iterative sprints to deliver regular updates.

Automated Testing: Implement automated testing frameworks to catch bugs early and ensure that new updates don’t break existing functionality.

User Feedback: Regularly collect feedback from your users and use this data to guide your app’s updates and features.

Conclusion Scaling a mobile application effectively requires a comprehensive approach to performance, infrastructure, database management, and security. By focusing on these key areas and implementing best practices, you can ensure that your app remains responsive, secure, and capable of handling an expanding user base. With the right strategies in place, your app can grow seamlessly while continuing to deliver a high-quality experience for users.

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korshubudemycoursesblog · 9 months ago

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Rest API Testing (Automation): Rest Assured + PostMan

In today's digital world, Rest API Testing plays a crucial role in ensuring that web services function efficiently. As more companies shift towards microservices and web-based solutions, automation testing of APIs becomes even more essential. The two most popular tools for Rest API Testing (Automation) are Rest Assured and PostMan.

These tools offer a seamless testing experience, making it easier for developers and testers to validate API functionality, performance, and security. In this article, we'll explore the fundamentals of Rest API Testing (Automation) and why Rest Assured and PostMan are the go-to tools for this purpose.

What is Rest API Testing?

Rest API Testing involves sending various HTTP requests (like GET, POST, PUT, DELETE) to an API endpoint and validating the responses. It's essential for verifying the functionality of APIs that allow communication between software systems. This process helps in detecting issues in the communication flow and ensuring the API meets the expected performance and security standards.

Why Choose Automation in Rest API Testing?

Manual testing of APIs can be time-consuming and prone to human error. This is where automation comes into play. Automating Rest API Testing not only saves time but also ensures consistency in test execution. Automation allows tests to be run repeatedly with minimal effort, which is particularly beneficial during continuous integration and deployment (CI/CD).

Key benefits of automated API testing include:

Faster execution of tests

Improved accuracy

Efficient handling of large datasets

Integration with CI/CD pipelines

Reduced manual effort

Rest Assured: A Powerful Tool for API Automation

Rest Assured is a powerful Java-based library designed specifically for RESTful API automation testing. It simplifies the process of testing APIs by eliminating the need to write complex code for HTTP requests.

Key Features of Rest Assured:

Supports BDD (Behavior Driven Development) style tests

Seamless integration with JUnit and TestNG frameworks

Supports JSON, XML, and XPath responses

Simplified syntax for making HTTP requests

Comprehensive reporting features

With Rest Assured, developers and testers can easily write scripts to automate API tests, ensuring that the APIs are functioning as intended. The BDD approach also helps in creating more readable and maintainable tests.

PostMan: A User-Friendly Tool for API Testing

PostMan is another widely used tool for API testing. It provides a user-friendly interface, allowing users to manually test APIs by sending requests and receiving responses. However, PostMan also supports automated testing through its built-in Collection Runner and Newman CLI tool.

Key Features of PostMan:

Intuitive UI for creating and managing API requests

Support for scripting tests using JavaScript

Ability to save requests as collections and run them as tests

Integration with CI/CD pipelines using Newman

Detailed reporting and logging features

Supports testing of SOAP and GraphQL APIs along with REST APIs

PostMan is ideal for both manual and automated testing, and its scripting capabilities allow users to automate API tests with ease.

Rest Assured vs. PostMan: Which is Better for API Testing?

When it comes to Rest API Testing (Automation), both Rest Assured and PostMan offer unique advantages.

Rest Assured is more suitable for testers who prefer writing scripts in Java and integrating API tests into their test automation framework. It’s great for developers and testers who need a more programmatic approach.

PostMan, on the other hand, is perfect for users who prefer a graphical interface and need quick and simple API tests. Its Newman CLI allows for automation, making it a great choice for both manual and automated testing.

Both tools can be integrated with CI/CD pipelines, but your choice will depend on your team’s preference for either script-based or UI-based testing.

Best Practices for Rest API Testing (Automation) with Rest Assured and PostMan

Define Clear Test Cases: Before beginning automation, ensure you have a set of clear and well-defined test cases.

Use Data-Driven Testing: Test your APIs with different sets of data inputs to validate their behavior under various conditions.

Validate Response Codes: Always verify the response status codes (e.g., 200 OK, 400 Bad Request, 500 Internal Server Error) to ensure correct API functionality.

Test Both Positive and Negative Scenarios: Ensure that your tests cover both expected (positive) and unexpected (negative) outcomes.

Integrate with CI/CD: Use tools like Jenkins, Newman, or Maven to integrate your API tests with continuous integration pipelines, ensuring that the tests run automatically during deployment.

FAQs

Q1: What is Rest API Testing?A1: Rest API Testing involves sending HTTP requests to a REST API and verifying the response to ensure that the API is functioning as expected.

Q2: Why should I automate API testing?A2: Automation ensures faster, more consistent test execution, reduces manual errors, and integrates well with CI/CD processes for continuous testing.

Q3: Which is better for API automation testing, Rest Assured or PostMan?A3: Both tools are excellent for automation. Rest Assured is better for script-based testing, while PostMan offers a user-friendly interface and is great for both manual and automated testing.

Q4: Can I use PostMan for continuous integration?A4: Yes, PostMan integrates with CI/CD tools through Newman, allowing API tests to be automated during deployment.

Q5: What languages are supported by Rest Assured?A5: Rest Assured is a Java library and is primarily used in Java-based automation frameworks.

Q6: Is PostMan suitable for testing large API suites?A6: Yes, PostMan’s collection feature allows you to group API requests and run them together, making it ideal for testing large API suites.

Conclusion: Choose the Right Tool for Rest API Testing (Automation)

In conclusion, whether you choose Rest Assured or PostMan for Rest API Testing (Automation) depends on your team’s preferences and project requirements. Both tools offer robust features for automating API tests, ensuring that your APIs function correctly under various conditions. By integrating these tools into your development workflow, you can significantly improve the quality of your web services.

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bythebayio · 4 years ago

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SBTB 2021 Program is Up!

Scale By the Bay (SBTB) is in its 9th year.

See the 2021 Scale By the Bay Program

When we started, Big Data was Hadoop, with Spark and Kafka quite new and uncertain. Deep Learning was in the lab, and distributed systems were managed by a menagerie sysadmin tools such as Ansible, Salt, Puppet and Chef. Docker and Kubernetes were in the future, but Mesos had proven itself at Twitter, and a young startup called Mesosphere was bringing it to the masses. Another thing proven at Twitter, as well as in Kafka and Spark, was Scala, but the golden era of functional programming in industry was still ahead of us.

AI was still quite unglamorous Machine Learning, Data Mining, Analytics, and Business Intelligence.

But the key themes of SBTB were already there:

Thoughtful Software Engineering

Software Architectures and Data Pipelines

Data-driven Applications at Scale

The overarching idea of SBTB is that all great scalable systems are a combination of all three. The notions pioneered by Mesos became Kubernetes and its CNCF ecosystem. Scala took hold in industry alongside Haskell, OCaml, Cloujure, and F#. New languages like Rust and Dhall emerged with similar ideas and ideals. Data pipelines were formed around APIs, REST and GraphQL, and tools like Apache Kafka. ML became AI, and every scaled business application became an AI application.

SBTB tracks the evolution of the state of the art in all three of its tracks, nicknamed Functional, Cloud, and Data. The core idea is still making distributed systems solve complex business problems at the web scale, doable by small teams of inspired and happy software engineers. Happiness comes from learning, technology choices automating away the mundane, and a scientific approach to the field. We see the arc of learning elevating through the years, as functional programming concepts drive deep into category theory, type systems are imposed on the deep learning frameworks and tensors, middleware abstracted via GraphQL formalisms, compute made serverless, AI hitting the road as model deployment, and so on. Let's visit some of the highlights of this evolution in the 2021 program.

FP for ML/AI

As more and more decisions are entrusted to AI, the need to understand what happens in the deep learning systems becomes ever more urgent. While Python remains the Data Science API of choice, the underlying libraries are written in C++. The Hasktorch team shares their approach to expose PyTorch capabilities in Haskell, building up to the transformers with the Gradual Typing. The clarity of composable representations of the deep learning systems will warm many a heart tested by the industry experience where types ensure safety and clarity.

We learn how Machine Learning is used to predict financial time series. We consider the bias in AI and hardware vs software directions of its acceleration. We show how an AI platform can be built from scratch using OSS tools. Practical AI deployments is covered by DVC experiments. We look at the ways Transformers are transforming Autodesk. We see how Machine Learning is becoming reproducible with MLOps at Microsoft. We even break AI dogma with Apache NLPCraft.

Cloud

Our cloud themes include containers with serverless functions, a serverless query engine, event-driven patterns for microservices, and a series of practical stacks. We review the top CNCF projects to watch. Ever-green formidable challenges like data center migration to the cloud at Workday scale are presented by the lead engineers who made it happen. Fine points of scalability are explored beyond auto-scaling. We look at stateful reactive streams with Akka and Kafka, and the ways to retrofit your Java applications with reactive pipelines for more efficiency. See how Kubernetes can spark joy for your developers.

Core OSS Frameworks

As always, we present the best practices deploying OSS projects that our communities adopted before the rest -- Spark, Kafka, Druid, integrating them in the data pipelines and tuning for the best performance and ML integration at scale. We cover multiple aspects of tuning Spark performance, using PySpark with location and graph data. We rethink the whole ML ecosystem with Spark. We elucidate patterns of Kafka deployments for building microservice architectures.

Software Engineering

Programming language highlights include Scala 3 transition is illuminated by Dean Wampler and Bill Venners, Meaning for the Masses from Twitter, purity spanning frontend to backend, using type safety for tensor calculus in Haskell and Scala, using Rust for WebAssembly, a categorical view of ADTs, distributed systems and tracing in Swift, complex codebase troubleshooting, dependent and linear types, declarative backends, efficient arrays in Scala 3, and using GraalVM to optimize ML serving. We are also diving into Swift for distributed systems with its core team.

Other Topics

We look at multidimensional clustering, the renessance of the relational databases, cloud SQL and data lakes, location and graph data, meshes, and other themes.

There are fundamental challenges that face the industry for years to come, such as AI bias we rigirously explore, hardware and software codevelopment for AI acceleration, and moving large enterprise codebases from on-prem to the cloud, as we see with Workday.

The companies presenting include Apple, Workday, Nielsen, Uber, Google Brain, Nvidia, Domino Data Labs, Autodesk, Twitter, Microsoft, IBM, Databricks, and many others.# Scale By the Bay 2021 Program is Up!

Reserve your pass today

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mbaljeetsingh · 5 years ago

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100 Jamstack Tools, APIs & Services to Power Your Sites

We’ve explained the Jamstack, a popular new way to build secure, scalable, high-performance sites. Now we’ll introduce you to the tools, services, and APIs that power Jamstack sites.

The A in Jamstack stands for API. APIs can do anything for you, from sending a form to authenticating a user, or from storing and retrieving data in real time to shopping for products.

In this article, we’ll do an extensive review of existing APIs and how they compare to one another. This review couldn’t possibly encompass the whole spectrum of third-party APIs that you can integrate into your website, but hopefully you’ll still find the coverage enlightening enough.

We’ll use the words “headless”, “detached”, and “serverless” a lot in this article. If you haven’t already, check out our introduction to the Jamstack, which covers all the basics.

Hosting (Mostly for Free)

Provided: Netlify

Hosting a Jamstack site usually involves automated deployment pipelines. For example, you might have a repository in GitHub which, on every push, automatically triggers an online deployment (via webhooks), running the necessary build tools (such as Jekyll) and regression tests (via Travis CI).

Sound difficult? It can be a surprisingly simple process!

Most of the services here include these goodies out of the box:

SSD drives

CDN deployments

free SSL (including for custom domains)

command line deployments and rollbacks

Note: look out for another article in this series, coming soon, covering how to use these services.

Services

Google Firebase and AWS Amplify

Firebase Hosting is Google’s take on a hosting service that’s easy to understand and implement, and it’s free to use (limits apply). Firebase’s backbone actually lies on top of the Google Cloud Platform (GCP), and you can in fact access and tweak some Firebase deployments through the GCP console. But by implementing something of an “gateway” (Firebase) that transparently handles GCP resources for us, Google gave developers a brand new and highly improved user experience (UX) … and the Firebase’s YouTube channel is just brilliant! 👏

AWS Amplify is also an effort to reduce the complexities of Amazon Web Services (AWS) for web and mobile deployment that doesn’t quite offer free hosting but 12 months of free use for new accounts for its Storage with Amplify as part of the AWS Free Tier.

Google really made a brilliant move with the Firebase family of products by “detaching” them from the GCP, but Amazon went half-way with AWS Amplify. It sure is a dramatic improvement from the regular AWS workflow, especially for novice users, and its documentation hub is superb and way more down-to-earth than the way Amazon usually documents services. But Amplify is still accessed from the same old (horrifically bloated) console. You still need a credit card to just open an account, deployments are still region-specific (no built-in CDN, seriously?), and the workflow isn’t as straightforward when compared to that of Firebase or Netlify.

GitHub Pages and GitLab Pages

Both hosting services for Git repositories also have a built-in service to host static pages right out of your codebases, 100% free: GitHub Pages and GitLab Pages.

In a future article we’ll cover how to use these services, but in the meantime make sure to check out these easy-to-follow guides:

Getting Started with GitHub Pages

Hosting on GitLab.com with GitLab Pages

Netlify and Heroku

In a very short period of time, Netlify not only coined the Jamstack term but also positioned itself as the place to go for all things static. While you could certainly accomplish more with an elaborated AWS pipeline, the simplicity and unparalleled ease of use that Netlify offers is unbeatable. Want to host a static site? Just drop it here and it’s online. Want automatic updates? Link a repo and just push a commit. And batteries are included — instant builds, worldwide CDN, free SSL, CLI tool, on-click rollbacks, and more.

Heroku is the only service in this list that allows you to host dynamic pages: Node.js, Ruby, Python, Java, PHP, Go, Scala and Clojure (check their Language Support page). So if you aren’t yet quite ready to go static, this might be a good way to test your dynamic sites online for free.

Others Services

With 194 data centers as of 2020, Cloudflare is — by many metrics — the company that offers the lowest latency for their DNS and CDN services around the world. They serve big companies but also have a number of services oriented to developers, like Workers Sites. The service isn’t free ($5/mo minimum charge) but it’s as top performant as you can get, and fairly easy to use.

Other tools targeted at static pages include Aerobatic, which offers a free trial with no credit card required and support for internationalization (i18n) and full-text search built-in plugins; Surge.sh with npm run scripts and CI services; and Vercel (formerly ZEIT Now) with an Edge Network serving big names such as Twilio and The Washington Post.

Comparison

Service Free plan Easy-of-use Tooling Aerobatic 1 month easy good Firebase Hosting yes easy very good GitHub Pages completely free easy poor GitLab Pages completely free easy good Heroku yes somewhat easy very good Netlify yes extremely easy very good Storage with Amplify 1-year (new accounts) somewhat easy very good Surge.sh yes easy good Vercel yes easy good Workers Sites no somewhat easy good

Storing and Retrieving Data: Real-time NoSQL Databases

NoSQL solutions like MongoDB have been coexisting with relational databases like MySQL for some time (see the differences and how to choose), but real-time processing takes NoSQL to the next level by enabling cloud storage for state management, such as a user entering their name or clicking a radio button.

If you’re familiar with Redux and Vuex — React and Vue.js libraries for state management, respectively — think of integrating that concept with a cloud storage provider.

Services

Amazon DynamoDB is a “fully managed, multiregion, multimaster, durable database with built-in security, backup and restore, and in-memory caching for internet-scale applications”. But as with many things AWS, it’s difficult to implement and very hard to debug (see Why Amazon DynamoDB isn’t for everyone, by Forrest Brazeal). In all fairness to Amazon, they also built DataStore into AWS Amplify (with GraphQL and REST API support) with a more straightforward approach, in line with the simplicity of the rest of Amplify’s products.

Google Firestore made real-time NoSQL databases — a fairly complex topic in and of itself — as simple as they can be, with pretty much all the capabilities DynamoDB has. It’s very well documented (with introductory clips that are fun to watch). And React and Vue.js have wrappers around Firestore with react-redux-firebase and Vuexfire, respectively.

Cloudflare sure knows how to take performance to the very extreme, and Workers KV, a serverless key-value storage for applications, is a fine example of what a well engineered product looks like. The premise of Workers KV is that you can access a key as if it were a local file within your app, and the content will be the value stored for that key. That’s it — no API to implement, no extra coding. And because of the unbeatable performance of the Cloudflare CDN, this approach can actually be faster than querying a NoSQL database. And as simple as it is, it scales seamlessly to millions of requests. 👏

And finally, there’s FaunaDB, a startup that crafted a solution with native GraphQL and a simple pricing (including a free plan) that can be implemented in minutes.

Managing Content: Headless CMS

In the “monolithic” way of doing things, whenever we used a given content management system — such as WordPress, Django, or Joomla! — it meant that we also needed to use the front-end engine that came attached to it, as back and front end were “coupled” components of a single piece of software (see our introduction to the Jamstack for more info about tightly vs loosely coupled sites).

Enter the headless CMS — a back end only without a front end. Since a headless CMS would normally expose an API or generate static content in the way of Markdown or HTML files, the front end can be anywhere really. In fact, multiple and simultaneous interfaces can be created for web sites, mobile apps, and Internet of Things (IoT) apps.

Products and Services

There are a number of headless CMSs, both as software you can download and configure where you do the deployments yourself, or offered in the software-as-a-service (SaaS) model where everything is taken care of for you.

Some features you can expect to find:

localization (l10n) and internationalization (i18n)

microservices architecture with a RESTful API

editor interface

customization

versioning*

* Since some headless CMS will integrate smoothly with your git repo, the versioning capability can actually be a remarkable improvement over a regular CMS.

Self-hosted Headless CMS

Ghost, “the #1 open source headless Node.js CMS”, is certainly the one with the most stars on GitHub. Not only can Ghost handle content, but it also offers a number of integrations to manage payments (Stripe), email lists (MailChimp), shopping (Shopify), and many more. And then there’s Ghost(Pro), which is the official managed hosting for Ghost with commercial support.

Fairly close to Ghost in popularity comes Strapi, with REST and GraphQL APIs, and 1-click deployments on Heroku, AWS, and DigitalOcean. It has “starters” (template projects) to work seamlessly with Gatsby, Vue.js with Nuxt.js, React with Next.js, and Angular. It also runs on Node.js and has support for a number of database engines.

Netlify CMS is also a popular option built as a single–page React app. There’s Directus, which wraps custom SQL databases with an API and provides an intuitive admin app to manage its content, and the commercial companion Directus Cloud. There’s also TinaCMS, which is also React-based, and Ponzu, Copckpit, and many more, which you can explore oin the comprehensive list provided by headlesscms.org.

SaaS Headless CMS

CloudCannon is the cloud CMS for Jekyll (we’ll review Jekyll later in the “static site generators” section), with smooth integration with GitHub, Bitbucket and Dropbox. They have a free plan as well but with no global CDN hosting.

Contentful is something different: a content hub where business owners, marketers, developers and project managers can all go to set and manage all of the data sources of an organization. And their headless CMS is just a part of that strategy. The Contentful platform is fully featured, very well documented, with plenty of open-source tools. And while the pricing is a bit confusing, there’s actually a free plan that only requires attribution.

There are other SaaS headless CMSs with free plans, such as DatoCMS and Sanity with a proposition similar to that of Contentful; Forestry, with support for a number of static generators; GraphCMS, with GraphQL support; and Prismic. These are just a few of the many options.

Sending Information: Forms without Code

Sending data through forms has forever been one of the main uses for server-side processing. There are essentially two approaches to addressing this problem on a static site, each with pros and cons.

From Builders, Embedded and Hosted Forms

Many times integrating a “powered by” external form is more than enough to collect email addresses or to receive feedback.

Google Forms have offered this possibility since 2008 entirely for free, with a simple interface that stores submissions on Google Sheets, and that can send alerts via email every time there’s a submission.

Formstack takes forms to another level by providing an integrated workflow supporting digital signatures, document generation, Salesforce integration, and more. They offer a free tryout but no free plans.

Then you have the extremely easy-to-use form builders JotForm and Wufoo, which integrate handling payments, among other things, or Typeform, which makes forms and surveys … pretty? All of them offer free plans.

External API: Form Processing as a Service (FPaaS)

Sometimes a builder won’t cut it, as you need more flexibility to present information and fields, or to fully integrate the look and feel of the form with the rest of your website. For this you will need to integrate an API.

The way these services work is surprisingly easy: you specify a URL for submission that will do the processing for you. At most you’ll have to set a few things up but most probably won’t need to do any extra coding.

There are a number of providers offering free plans, such as Form.IO, Formcarry, Formspark, and Netlify Forms. They all work in a similar way and are very easy to implement.

FormDen and FormKeep are also form builders that can otherwise be used just as back ends, though none of them offer free plans.

Programming Server-Side Logic: Function as a Service (FaaS)

Couldn’t find an API that does quite what you want? Create it! You don’t need to resort back to a hosted back-end system to process server-side logic, with all the hassle that comes with it (maintenance, bills, credentials, security patches). Instead, you can implement a micro-service in your language of choice (oftentimes JavaScript, Python, or Go), encapsulate that logic into functions, and offer them through a RESTful API.

As with pretty much everything else in this list, you won’t be paying anything for a function that’s not being actively used, so no worries for just leaving it sitting there (but beware that spikes in traffic might also trigger extra billing).

Providers

While the implementation details for AWS Lambda, Azure Functions and Google Cloud Functions may differ, they all work in pretty much the same fashion and you’ll need a degree of familiarity with AWS, Azure or GCP. AWS Lambda has the richest language support of them all (and also Amazon API Gateway to help you wrap your functions into a maintainable API with monitoring tools), while Azure — not surprisingly — has the best support for .NET Framework and .NET Core (with different versions supporting different runtimes and even TypeScript transpiled to JavaScript). But be aware that Azure systematically ranks as the slowest service by a margin.

Cloud Functions for Firebase and Netlify Functions are wrappers around Google Cloud Functions and AWS Lambda, respectively. They greatly simplify the management of functions on the cloud, as you effectively can get away without even having an account on such services. Code deployment and versioning become trivial with Netlify — which also has very good community support — as it will smoothly integrate with your repo offering stage, previewing, and rolling back at a click (or a commit). Simplicity naturally comes at the expense of losing some flexibility (see Firebase Cloud Functions: the great, the meh, and the ugly by Pier Bover).

IBM Cloud Functions (based on Apache OpenWhisk) and Cloudflare Workers are other services you might want to look at. IBM has an impressive list of supported languages, including the option to deploy Docker containers with your own runtime. However, it ranked somewhat poorly performance wise. And just as Netlify systematically manages to make things the simplest, Cloudflare again makes things the fastest (and by a difference).

Comparison

service languages overhead* coldstart* difficulty support AWS Lambda C#, Go, Java, JavaScript, PowerShell, Python, Ruby 86 ms 🟢 589 ms high 👍 very good Azure Functions C#, F#, Java, JavaScript and TypeScript, PowerShell, Python 760 ms 🔴 5,907 ms 🔴 high 👎 very poor Cloud Functions for Firebase JavaScript and TypeScript 642 ms 🔴 168 ms low 👍 very good Cloudflare Workers JavaScript, COBOL 70 ms 🟢 76 ms 🟢 intermediate intermediate Google Cloud Functions Go, Java, Node.js, Python 642 ms 🔴 168 ms high 👍 very good IBM Cloud Functions .C#, Go, Java, JavaScript, PHP, Python, Ruby, Swift, and Docker containers 136 ms 2,103 ms 🔴 high no info Netlify Functions Go, Node.js 86 ms 🟢 589 ms very low 👍 very good

* As measured by λ Serverless Benchmark, the overhead is the time from request to response without the time the function took (for a concurrency of 50), and the coldstart is how long the servers takes to respond when queried are spanned every 3 hours; the lower the values, the better.

Authenticating Users: Identity as a Service

Identity as a Service (IDaaS), also called sometimes Authentication as a Service (AaaS), involves managing a full user registration, confirmation, and authentication with just APIs. The Geist of “stateless authentication” is that a user will authenticate against a third-party and come back to you with a valid “token” that you can verify, or revoke if need be.

In some cases, a provider might even offer a “drop-in” user interface (UI) that will work seamlessly across desktop and mobile, all of which could potentially save you very long hours of work.

Services

Auth0 has been in business the longest and has quickstart guides for a number of scenarios. It’s an excellent provider if you want to implement a complex solution and already have some experience implementing authentication. But as they point out, “identity is complex, deal with it”. The large scope Auth0 services (universal login, single sign on (SSO), multifactor authentication, branch password detection, and so on) can be overwhelming if you’re just starting on the topic.

Firebase Authentication (with its ready-to-use UI) and Authentication with Amplify are also very comprehensive and flexible, and somewhat presented in a more straightforward manner than Auth0. Firebase also offers anonymous authentication! Curious? Check out this clip:

youtube

Once again, Netlify seems to come up with the easiest solution to implement with Netlify Identity and its open-source zero config netlify-identity-widget to create a secure login in 10 minutes! But of course, there are some limitations (check out Four Dealbreakers in Netlify Identity, by Jean Cochrane).

You can also check Okta, FusionAuth and LoginRadius, all of which have free plans. There are no freebies for Ping Identity, OneLogin, and Ubisecure, which are more oriented to the enterprise sector. Finally, consider Cloudflare Access, as everything Cloudflare does is rock solid.

Going F·A·S·T: Static Site Generators (SSG)

I can hear some of you saying “all of this might be okay for future projects, but my sites are already dynamic, so what to do?” Here’s when static site generators enter the picture.

You can have the best of both worlds — the convenience of a familiar CMS and static pages with code and data splitting, preloading, caching, image optimization, and all sorts of performance enhancements. An SSR will bridge that gap by querying your database and generating static output out of it (for example, Markdown pages), and with some settings to set your template, you’ll be all set.

The listing here is tiny compared to the ever increasing list of SSRs. Have a look at StaticGen for more info.

Main Products

GatsbyJS is powered by React.js and webpack, meaning that it can generate progressive web apps (aka PWAs, websites that look and feel like an apps). It also supports GraphQL (see Write Apps with Better Building Blocks) and it has +1,000 plugins to get data from anywhere (WordPress, Drupal, Contentful, GraphCMS, DatoCMS, and many more). See how GatsbyJS says it compares to its main competitors, Hugo and Jekyll.

All of this flexibility comes at a cost, as setting and customizing GatsbyJS can be a time-consuming process, and if you don’t have a decent understanding of React — and therefore JavaScript — you won’t be able to make much of it. That’s where Gatsby Cloud comes in, offering support to build and maintain Gatsby sites for free or for a fee, where you could automate your fast builds, access to previews, generate daily edits, and fire deployments with ease to Netlify, Cloudflare, AWS CloudFront or Akamai.

Hugo claims to be “the world’s fastest framework for building websites”, and it sure can generate massive sites in milliseconds. With built-in templates (literally hundreds of them available) and native support for internationalization (i18n), it’s also one of the most popular SSGs. Hugo is a Go app, and while Go isn’t hard to set and learn, you’ll definitely need to be checking the documentation often if you aren’t familiar with it.

Unlike GatsbyJS, configuring and deploying Jekyll is a rather straightforward process. Furthermore, Jekyll is the only SSR supported by GitHub Pages (Tom Preston-Werner, creator of Jekyll, is also a co-founder of GitHub), and can smoothly deploy static sites for free right out of your GitHub repos! Jekyll uses Shopify’s Liquid template language, which is also easy to learn. The downsides? As a Ruby app, Jekyll can be hard to set on a Windows environment, and optimizations such as minimizing JavaScript code and image preloading aren’t included by default. In fact, Jekyll doesn’t even aim at generating a PWA but just purely static sites — which might still be fine depending on what you need.

Comparison

Product Language Templating Setting GitHub stars GatsbyJS JavaScript React.js difficult

Hugo Go Go (library) intermediate

Jekyll Ruby Liquid easy

Others

WP2Static is an SSR designed specifically for WordPress (WP). It has a small but very interesting set of plugins, like Algolia search, and Cloudflare Workers and Netlify deployments. HardyPress is actually a SaaS solution to generate static WP sites, and for a fee you’ll have an admin panel from where you can enter some credentials to access your online WP installations to manage everything: shut down live WP installs that were already imported, transparent deployment to global a CDN, HTTPS, forms, search. Other WP-related SSGs with commercial support are Shifter, Strattic, and Sitesauce.

Since I am admittedly biased towards Vue.js, I had to include VuePress, which is intended to generate single page applications (SPAs) and has a minimal setup with markdown-centered files, and it’s also powered by webpack. Gridsome and Nuxt.js are more featured Vue.js powered frameworks with SSR capabilities.

Selling and Processing Payments: Headless Shopping Carts

The architecture and benefits of headless ecommerce is not that different from that of a headless CMS: massive cost reduction (hosting, licenses, maintenance), less time to market, seamless integration, and — a big one for commerce — “omnichannel” capabilities.

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codeonedigest · 2 years ago

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Difference between Rest API & Graphql Explained with Example for Beginners

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REST (Representational State Transfer) is an architectural style that conforms to a set of constraints when developing web services. A REST request is made up of the endpoint, HTTP method, Header, and Body. GraphQL is an open-source data query and manipulation language for APIs, and a runtime for fulfilling queries with existing data The biggest difference between GraphQL and REST is the…

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megatechcrunch · 7 years ago

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