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Exploring the Benefits of Cloud Development

  • By Gcore
  • October 31, 2023
  • 9 min read
Exploring the Benefits of Cloud Development

Cloud development allows you to write, debug, and run code directly in the cloud infrastructure, rather than working in the local environment and subsequently uploading to the cloud. This streamlines the development process, allowing you to deploy and update applications faster. This article explains what cloud development is, what tools can help you with it, and how you can use cloud development to develop and update your application to meet your customers’ needs.

What Is Cloud Development?

Cloud development is the practice of creating and managing applications that run on remote servers, allowing users to access them over the internet.

Every application is made up of different types of services, such as backend services, frontend services, and monitoring services. Normally, without cloud development, creating a new service or updating an existing service means writing and running your code in the local environment first. After ensuring your service works as expected, you then push your code to the cloud environment, and run it there. Finally, you publish your service and integrate it with the app. This process is time-consuming, and requires sufficiently powerful computing resources to run the service on the local machine.

This is when cloud development proves its value. With cloud development, you write your code directly in the cloud infrastructure. After you have finished writing your code, publishing your service takes just one click.

Diagram comparing the difference in steps between traditional development vs. cloud development

Useful Cloud Development Tools

To apply cloud development to your projects, several tools are required to build and manage the code efficiently:

  • Code editor to help you write code more efficiently
  • Version control tool to manage the code changes
  • Compiler/interpreter to run your code
  • Publisher to allow public use of your application

Let’s learn about each of the tools in more detail.

Code Editor

A code editor is a software tool that supports code highlighting, easy navigation within the codebase, test execution, and debugging capabilities. When you’re working on applications that are hosted in a cloud environment, it’s essential for your code editor to support remote access because the code you’re working on is stored on a remote cloud server.

Remote access support enables you to establish an SSH connection between your local code editor and the remote server. You can then use your code editor to create, view, and modify code files as if they were local.

Popular code editors—like Visual Studio Code and JetBrains IDE—have features that support remote development. For example, with Visual Studio Code, you can install Microsoft’s “Remote – SSH” extension to enable remote code access via SSH. Once the extension is installed, you can connect to the remote server by entering its IP address, username, and password, and work on your cloud-based projects just as easily as you would local ones.

Below is an example of using Visual Studio Code to access code via a remote machine.

Example of using Visual Studio Code to access code via a remote machine

Version Control

In software development, it’s common for many people to be working on the same code base. Having a version control tool allows you to review who made the changes, and when, to certain lines of code so that you can trace any problems back to their source. Having a version control tool also allows you to revert your code to the version you want in the instance that new code introduces bugs.

There are several version control tools out there, such as Git, SVN, and Mercurial; Git is currently the most popular. Git is an open-source version control system that allows you to manage the changes in the code. It is distributed software, meaning that you create a local copy of the Git repository on your local machine, and then create new branches, add files, commit, and merge locally. When your code is ready to ship, you then push your code to the Git repository on the server.

Compiler/Interpreter

After tools that help you to write and track changes in the code, the next most important tool required to run code in the cloud is a compiler or interpreter. You need either a compiler or an interpreter to translate your code into machine code, depending on the programming languages or the runtime you are working on. They allow the computer to understand and execute your instructions. Generally speaking, the compiler or interpreter helps to build your code into executable files. Let’s look at each in turn to understand their differences.

Compiler

Before a service actually runs, a compiler translates the high-level code that you have written into low-level code. For example, a Java compiler compiles source code to the bytecode first, then the Java Virtual Machine will interpret and convert the bytecode to a machine-code executable file. As a result, compilers require time to analyze the source code. However, they also show obvious syntax errors, so you don’t need to spend a lot of time debugging your service when it’s running.

The programming languages that use compilers to translate code are Java, C#, and Go.

Interpreter

Unlike a compiler, an interpreter only translates written code into machine code when the service runs. As a result, the interpreter does not take time to compile the code. Instead, the code is executed right away. However, an application using an interpreter is often slower than one using a compiler because the interpreter executes the code line by line.

The programming languages that use interpreters are Python, Javascript, and Ruby.

Publisher

To allow other users to access your service, you need a publisher tool. This manages the following key aspects of your service:

  • Configuring the network
  • Creating the domain name
  • Managing the scalability

Network Configuration

To allow users to access your service, the network configuration is crucial. The method for making your service available online varies based on your technology stack. For instance, if you use the Next.js framework to build your web application, you can choose Vercel to deploy your application code.

You can also customize the behavior of your application with network configuration. Here’s an example of how to use the vercel.json file to redirect requests from one path to another:

{  "redirects": [    { "source": "/book", "destination": "/api/book", "statusCode": 301 }  ]}

Domain Setting

Every service requires a URL for applications to interact with it. However, using direct IP addresses as URLs can be complex and unwieldy, so it’s advisable to assign a domain name to your service, like www.servicedomain.com. Various platforms, such as GoDaddy or SquareSpace, offer domain registration services for this purpose.

Scalability

To allow your service to handle more requests from your users, you need to define a scalability mechanism for your services. This way, your service will automatically scale according to the workload. Scalability also keeps costs in check; you pay for what you use, rather than wasting money by allocating resources based on peak usage.

Below is an example definition file for applying autoscaling to your service, using Kubernetes HorizontalPodAutoscaler.

apiVersion: autoscaling/v1        kind: HorizontalPodAutoscaler        metadata:        name: app        spec:        scaleTargetRef:            apiVersion: apps/v1            kind: Deployment            name: appdeploy        minReplicas: 1        maxReplicas: 10        targetCPUUtilizationPercentage: 70

How to Run Code In the Cloud

Now that you are familiar with the tools you need for cloud development, let’s learn about how to run code in the cloud. There are two ways to run code in the cloud: using virtual machines or using containers. We explain the difference in depth in our dedicated article, but let’s review their relevance to cloud development here.

Virtual Machines

A virtual machine (VM) is like a computer that runs within a computer. It mimics a standalone system, with its own virtual hardware and software. Since a VM is separate from its host computer, you can pick the VM operating system that suits your needs without affecting your host’s system. Plus, its isolation offers an extra layer of security: if one VM is compromised, the others remain unaffected.

Architecture of a VM, which includes a guest OS

While VMs offer versatility in terms of OS choices for cloud development, scaling applications on VMs tends to be more challenging and costly compared to using containers. This is because each VM runs a full operating system, leading to higher resource consumption and longer boot-up times. Containers, on the other hand, share the host OS and isolate only the application environment, making them more lightweight and quicker to scale up or down.

Containers

A container is a software unit that contains a set of software packages and other dependencies. Since it uses the host operating system’s kernel and hardware, it doesn’t possess its own dedicated resources as a virtual machine does. As a result, it’s more lightweight and takes less time to start up. For instance, an e-commerce application can have thousands of containers for its backend and frontend services. This allows the application to easily scale out when needed by increasing the number of containers for its services.

Architecture of a container, which is more lightweight than VM architecture due to the lack of guest OS

Using containers for cloud code enables efficient resource optimization and ease of scaling due to their lightweight nature. However, you have limited flexibility in choosing the operating system, as most containers are Linux-based.

Cloud Development Guide

We’ve addressed cloud development tools and ways to run code in the cloud. In this section, we offer a step-by-step guide to using cloud development for your project.

Check Computing Resources

Before anything else, you’ll need the correct computing resources to power your service. This includes deciding between virtual machines and containers. If your service tends to have a fixed number of user requests everyday, or it needs a specific operating system like Mac or Windows in order to run, go with virtual machines. If you expect your service to experience a wide range in the number of user requests and you want it to be scalable to optimize operational costs, go with containers.

After choosing between virtual machines and containers, you need to allocate computing resources for use. The important resources that you need to consider are CPUs, RAM, disk volumes, and GPUs. The specifications for these resources can vary significantly depending on the service you’re developing. For instance, if you’re building a monitoring service with a one-year data retention plan, you’ll need to allocate disk volumes of approximately 100GB to store all generated logs and metrics. If you’re building a service to apply deep learning models to large datasets, you’ll require not only a powerful CPU and ample RAM, but also a GPU.

Install Software Packages and Dependencies

After preparing the computing resources, you’ll next install the necessary software and dependencies. The installation process varies depending on whether you’re using virtual machines or containers.

As a best practice, you should set up the mechanism to install the required dependencies automatically upon initialization of the virtual machine or container. This ensures that your service has all the necessary dependencies to operate immediately upon deployment. Additionally, it facilitates easy redeployment to a different virtual machine or container, if necessary. For example, if you want to install software packages and dependencies for an Ubuntu virtual machine to host a Node.js service, you can configure cloud-init scripts for the deployed virtual machine as below:

#cloud-config...apt:  sources:    docker.list:      source: deb [signed-by=$KEY_FILE] https://deb.nodesource.com/node_18.x $RELEASE main      keyid: 9FD3B784BC1C6FC31A8A0A1C1655A0AB68576280package_update: truepackage_upgrade: truepackages:  - apt-transport-https  - ca-certificates  - gnupg-agent  - software-properties-common  - gnupg  - nodejspower_state:  mode: reboot  timeout: 30  condition: True

To set up a web service on containers using Node.js, you’ll need to install Node along with the required dependencies. Below is a Dockerfile example for doing so:

# Pull the Node.js image version 18 as a base imageFROM node:18# Set the service directoryWORKDIR /usr/src/appCOPY package*.json ./# Install service dependenciesRUN npm install

Write Code

When you’ve installed the necessary software packages and dependencies, you can begin the fun part: writing the code. You can use code editors that support remote access to write the code for your service directly in the cloud. Built-in debugging tools in these editors can help you to identify any issues during this period.

Below is an example of using IntelliJ to debug a Go service for managing the playlists.

Using IntelliJ to debug a Go service

Test Your Service

After you finish writing your code, it’s crucial to test your service. As a best practice, start with unit tests to ensure that individual components work, followed by integration tests to see how your service interacts with existing application services, and finally E2E (end-to-end) tests to assess the overall user experience and system behavior.

Below is a test pyramid that gives a structured overview of each test type’s coverage. This will help you allocate your testing efforts efficiently across unit and integration tests for your service.

Test pyramid demonstrates the proportion that should be allocated to each test

Configure Network Settings

To make your service available to users, you need to configure its network settings. This might involve configuring the rules for inbound and outbound data, creating a domain name for your service, or setting a static IP address for your service.

Here is an example of using cloud-init configuration to set a static IP for a virtual machine that hosts your service:

#cloud-config...write_files:  - content: |        network:            version: 2            renderer: networkd            ethernets:              enp3s0:                addresses:                - 192.170.1.25/24                - 2020:1::1/64                nameservers:                  addresses:                  - 8.8.8.8                  - 8.8.4.4    path: /etc/netplan/00-add-static-ip.yaml    permissions: 0644power_state:  mode: reboot  timeout: 30  condition: True

Add Autoscaling Mechanism

With everything in place, it’s time to add an autoscaling mechanism. This adjusts resources based on demand, which will save costs during quiet times and boost performance during busy periods.

Assuming that you use Kubernetes to manage the containers of your service, the following is an example of using Gcore Managed Kubernetes to set the autoscaling mechanism for your Kubernetes cluster:

Configuring a Gcore Managed Kubernetes cluster to enable cluster autoscaling

Set Up Security Enhancement

Finally, ensure your service is secure. Enhancements can range from setting up robust authentication measures to using tools like API gateways to safeguard your service. You can even set up a mechanism to protect your service from malicious activities such as DDoS attacks.

Below is an example of how to apply security protection to your service by creating a resource for your service URL using Gcore Web Security:

Create a web security resource for the service domain to protect it from attacks

Gcore Cloud Development

Accelerating feature delivery through cloud development can offer a competitive edge. However, the initial setup of tools and environments can be daunting—and mistakes in this phase can undermine the benefits.

Here at Gcore, we recognize these obstacles and offer Gcore Function as a Service (FaaS) as a solution. Gcore FaaS eliminates the complexities of setup, allowing you to dive straight into coding without worrying about configuring code editors, compilers, debuggers, or deployment tools. Ideally suited for straightforward services that require seamless integration with existing applications, Gcore FaaS excels in the following use cases:

  • Real-time stream processing
  • Third-party service integration
  • Monitoring and analytics services

Conclusion

Cloud development allows you to deliver your service to users immediately after you’ve finished the coding and testing phases. You can resolve production issues and implement features faster to better satisfy your customers. However, setting up cloud infrastructure can be time intensive and ideally needs a team of experienced system administrators for building and maintenance.

With Gcore FaaS, you don’t have to take on that challenge yourself. You can focus on writing code, and we’ll handle the rest—from configuring pods and networking to implementing autoscaling. Plus, you are billed only for time your customers actually use your app, ensuring cost effective operation.

Want to try out Gcore FaaS to see how it works? Get started for free.

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Unlike basic anti-scraping tools, AI learns new ways that scraping is done, keeping businesses one step ahead.Behavioral tagging and profilingAI-powered systems are quite good at analyzing user behavior. They study the tendencies of session parameters, IP addresses, and interaction rates. For instance, most regular users save session data, while bots do not prioritize this action. The AI system flags suspicious behavior and highlights the user in question for review.These systems also count the recurrence of certain actions, such as clicks or requests. The AI is supposed to build an in-depth profile for every IP or user and find something out of the ordinary to suggest a way to block or throttle the traffic.IP rescoring for smarter detectionOne of the unique capabilities of AI-driven bot protection is Dynamic IP Scoring. Based on external behavior data and threat intelligence, each incoming IP is accorded a risk score. For example, an IP displaying a number of failed login attempts could be suspicious. If it persists, that score worsens, and the system blocks the traffic.This dynamic scoring system does not focus on mere potential threats. It also allows IPs to “recover” if their behavior normalizes, reducing false positives and helping to ensure that real users are not inadvertently blocked.Practical insights: operationalizing AI-driven bot protectionImplementing AI/ML-driven bot protection requires an understanding of both the technology and the operational context in which it’s deployed. Businesses can take advantage of several unique features offered by platforms like Gcore WAAP:Tagging system synergy: Technology-generated tags, like the Gcore Tagging and Analysis Classification and Tagging (TACT) engine, are used throughout the platform to enforce fine-grained security policies and share conclusions and information between various solution components. Labeling threats allows users to easily track potential threats, provides input for ML analysis, and contributes data to an attacker profile that can be applied and acted on globally. This approach ensures an interlinked approach in which all components interact to mitigate threats effectively.Scalable defense mechanisms: With businesses expanding their online footprints, platforms like Gcore scale seamlessly to accommodate new users and applications. The cloud-based architecture makes continuous learning and adaptation possible, which is critical to long-term protection against automation threats.Cross-domain knowledge sharing: One of the salient features of Gcore WAAP is cross-domain functionality, which means the platform can draw from a large shared database of user behavior and threat intelligence. Even newly onboarded users immediately benefit from the insights gained by the platform from its historical data and are protected against previously encountered threats.Security insights: Gcore WAAP’s Security Insights feature provides visibility into security configurations and policy enforcement, helping users identify disabled policies that may expose them to threats. While the platform’s tagging system, powered by the TACT engine, classifies traffic and identifies potential risks, separate microservices handle policy recommendations and mitigation strategies. This functionality reduces the burden on security teams while enhancing overall protection.API discovery and protection: API security is among the most targeted entry points for automated attacks due to APIs’ ability to open up data exchange between applications. Protecting APIs requires advanced capabilities that can accurately identify suspicious activities without disrupting legitimate traffic. Gcore WAAP’s API discovery engine achieves this with a 97–99% accuracy rate, leveraging AI/ML to detect and prevent threats.Leveraging collective intelligence: Gcore WAAP’s cross-domain functionality creates a shared database of known threats and behaviors, allowing data from one client to protect the entire customer base. New users benefit immediately from the platform’s historical insights, bypassing lengthy learning curves. For example, a flagged suspicious IP can be automatically blocked across the network for faster, more efficient protection.Futureproof your security with Gcore’s AI-enabled WAAPBusinesses are constantly battling increasingly sophisticated botnet threats and have to be much more proactive regarding their security mechanisms. AI and machine learning have become integral to fighting bot-driven attacks, providing an unprecedented level of precision and flexibility that no traditional security systems can keep up with. With advanced behavior analysis, adaptive threat models, and cross-domain knowledge sharing, Gcore WAAP establishes new standards of bot protection.Curious to learn more about WAAP? Check out our ebook for cybersecurity best practices, the most common threats to look out for, and how WAAP can safeguard your businesses’ digital assets. Or, get in touch with our team to learn more about Gcore WAAP.Learn why WAAP is essential for modern businesses with a free ebook

How to choose the right technology tools to combat digital piracy

One of the biggest challenges facing the media and entertainment industry is digital piracy, where stolen content is redistributed without authorization. This issue causes significant revenue and reputational losses for media companies. Consumers who use these unregulated services also face potential threats from malware and other security risks.Governments, regulatory bodies, and private organizations are increasingly taking the ramifications of digital piracy seriously. In the US, new legislation has been proposed that would significantly crack down on this type of activity, while in Europe, cloud providers are being held liable by the courts for enabling piracy. Interpol and authorities in South Korea have also teamed up to stop piracy in its tracks.In the meantime, you can use technology to help stop digital piracy and safeguard your company’s assets. This article explains anti-piracy technology tools that can help content providers, streaming services, and website owners safeguard their proprietary media: geo-blocking, digital rights management (DRM), secure tokens, and referrer validation.Geo-blockingGeo-blocking (or country access policy) restricts access to content based on a user’s geographic location, preventing unauthorized access and limiting content distribution to specific regions. It involves setting rules to allow or deny access based on the user’s IP address and location in order to comply with regional laws or licensing agreements.Pros:Controls access by region so that content is only available in authorized marketsHelps comply with licensing agreementsCons:Can be bypassed with VPNs or proxiesRequires additional security measures to be fully effectiveTypical use cases: Geo-blocking is used by streaming platforms to restrict access to content, such as sports events or film premieres, based on location and licensing agreements. It’s also helpful for blocking services in high-risk areas but should be used alongside other anti-piracy tools for better and more comprehensive protection.Referrer validationReferrer validation is a technique that checks where a content request is coming from and prevents unauthorized websites from directly linking to and using content. It works by checking the “referrer” header sent by the browser to determine the source of the request. If the referrer is from an unauthorized domain, the request is blocked or redirected. This allows only trusted sources to access your content.Pros:Protects bandwidth by preventing unauthorized access and misuse of resourcesGuarantees content is only accessed by trusted sources, preventing piracy or abuseCons:Can accidentally block legitimate requests if referrer headers are not correctly sentMay not work as intended if users access content via privacy-focused methods that strip referrer data, leading to false positivesTypical use cases: Content providers commonly use referrer validation to prevent unauthorized streaming or hotlinking, which involves linking to media from another website or server without the owner’s permission. It’s especially useful for streamers who want to make sure their content is only accessed through their official platforms. However, it should be combined with other security measures for more substantial protection.Secure tokensSecure tokens and protected temporary links provide enhanced security by granting temporary access to specific resources so only authorized users can access sensitive content. Secure tokens are unique identifiers that, when linked to a user’s account, allow them to access protected resources for a limited time. Protected temporary links further restrict access by setting expiration dates, meaning the link becomes invalid after a set time.Pros:Provides a high level of security by allowing only authorized users to access contentTokens are time-sensitive, which prevents unauthorized access after they expireHarder to circumvent compared to traditional password protection methodsCons:Risk of token theft if they’re not managed or stored securelyRequires ongoing management and rotation of tokens, adding complexityCan be challenging to implement properly, especially in high-traffic environmentsTypical use cases: Streaming platforms use secure tokens and protected temporary links so only authenticated users can access premium content, like movies or live streams. They are also useful for secure file downloads or limiting access to exclusive resources, making them effective for protecting digital content and preventing unauthorized sharing or piracy.Digital rights managementDigital rights management (DRM) refers to a set of technologies designed to protect digital content from unauthorized use so that only authorized users can access, copy, or share it, according to licensing agreements. DRM uses encryption, licensing, and authentication mechanisms to control access to digital resources so that only authorized users can view or interact with the content. While DRM offers strong protection against piracy, it comes with higher complexity and setup costs than other security methods.Pros:Robust protection against unauthorized copying, sharing, and piracyHelps safeguard intellectual property and revenue streamsEnforces compliance with licensing agreementsCons:Can be complex and expensive to implementMay cause inconvenience for users, such as limiting playback on unauthorized devices or restricting sharingPotential system vulnerabilities or compatibility issuesTypical use cases: DRM is commonly used by streaming services to protect movies, TV shows, and music from piracy. It can also be used for e-books, software, and video games, ensuring that content is only used by licensed users according to the terms of the agreement. DRM solutions can vary, from software-based solutions for media files to hardware-based or cloud-based DRM for more secure distribution.Protect your content from digital piracy with GcoreDigital piracy remains a significant challenge for the media and entertainment industry as it poses risks in terms of both revenue and security. To combat this, partnering with a cloud provider that can actively monitor and protect your digital assets through advanced multi-layer security measures is essential.At Gcore, our CDN and streaming solutions give rights holders peace of mind that their assets are protected, offering the features mentioned in this article and many more besides. We also offer advanced cybersecurity tools, including WAAP (web application and API protection) and DDoS protection, which further integrate with and enhance these security measures. We provide trial limitations for streamers to curb piracy attempts and respond swiftly to takedown requests from rights holders and authorities, so you can rest assured that your assets are in safe hands.Get in touch to learn more about combatting digital piracy

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