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Building a Security-First Culture in Cloud Development

In an increasingly data-rich environment, businesses and individuals are increasingly looking for alternatives to storing and sharing information from their own networks. Not to mention that there are users who want software services that aren’t dependent on their internal systems. These are elements that are helping make the cloud developer landscape so rich with opportunities. Yet, when creating products to bring to the market, it’s important to recognize that alongside opportunity comes risk.  

Development teams in the cloud sector are subject to both internal and external threats. Adopting protective tools is certainly important here. Yet, it is the behavior of staff, the collaborations between teams, and the approach to management that really makes a difference. By building a security-first culture in your cloud development organization, you’re making your company more robust against threats.

Fostering Cross-Departmental Collaborations

Any good cloud development startup has talented development professionals and skilled security experts. Nevertheless, simply having these professionals working independently on their tasks alone is not the way to a security-first culture. Meaningful collaborations make for a more holistically secure product and business.

So, how can you boost collaborations between security and development?

  • Improve cross-departmental communication: Communication is key in any collaboration. Members of both dev and security teams must find it easy to connect regularly. This may include having specific channels for joint security and development discussions, such as direct messaging groups.
  • Integrate security professionals in dev teams: One of the most effective ways of improving cross-departmental collaborations is project integration. This means that for every cloud development project, there should be at least one security professional embedded as a core member of the project team. This ensures security considerations are a meaningful part of the development process.

In addition, bear in mind that each team and its members will have nuanced preferences for collaboration. Take the time to regularly reach out to your security and dev teams to ask what they feel is particularly good or especially challenging about their collaborations. Importantly, leadership should collaborate with them on identifying the resources or protocols that can help and commit to implementing these.

Creating a Secure Environment

It’s difficult to establish a security-first culture in cloud development if the environment in which your teams operate isn’t protected. Therefore, part of your approach should be to fill any potential security gaps that could pose or exacerbate risks to the cloud development team, the work they’re doing, and the overall business.

Some elements to focus on here include the following.

Physical security

Physical access controls in the development space help to ensure that nobody who isn’t a core part of each cloud development team can interact with data or assets related to projects. While you can doubtlessly trust all your staff members, it is not unusual to face insider threats, including when your development process involves continuous integration/continuous deployment (CI/CD) practices. 

Limiting unnecessary access to sources of information is key to keeping cloud development projects secure. You might consider installing biometric security tools at certain checkpoints or providing radio-frequency identification (RFID) fobs for specific areas of the business.

Digital security

With any cloud development project, there also has to be strict control over interactions with the digital landscape of the business. One approach to this is to create network silos. By dividing the network where needed and allocating portions to teams or projects, you gain greater control over the security access to each project’s portion.

Another useful approach is to arrange for dedicated internet access (DIA) for your development teams. This involves arranging with your internet service provider (ISP) to deliver a portion of the connection specifically provisioned for the use of your business or project. This doesn’t just enable you to guarantee a certain level of reliable bandwidth. It also tends to be more secure than sharing connections with others on the network that aren’t connected to a project or even to your organization.

Establishing Cloud Security Best Practice Protocols

Another vital component of a security-first culture in cloud development is to create practical and robust company-wide policies. Some of the cloud security strategies to protect data and maintain compliance that you should outline in your protocols include:

  • The shared security responsibility: The responsibility for protection isn’t just with your security or information technology (IT) professionals. Everybody who interacts with your cloud systems, project tools, and any other data has a role in protecting these items. Clarifying this in your security protocols and staff handbook sends a message that everyone can and should take steps to make a positive difference in their day-to-day activities.
  • Utilizing data encryption: Encryption is one of the most powerful tools to keep cloud project data protected even if bad actors breach other forms of defense. Therefore, it’s important that your security culture protocols clearly outline the circumstances in which development staff should apply encryption and what tools they should use for encrypting and key sharing.

These protocols should be well documented and readily available to all staff, perhaps stored on cloud platforms to ensure workers can access them wherever they’re operating from. That said, to be a good influence on security culture, they can’t just exist in document form and sit on your servers. Alongside giving general security awareness training, you also need to thoroughly educate staff on how to access this information and what they should and should not have stored on the cloud. 

In the onboarding phases, there should be a detailed walkthrough of each best practice, with room for questions to address uncertainty. Throughout employees’ time with the company, you should also provide regular update training on key elements of cloud security practice, particularly when tools, systems, and job roles change.

Conclusion

Building a security-first culture in your cloud development company is an effective way to make your projects more robust against threats. This involves a range of actions, from strengthening the development environment to training your staff on solid protocols. It’s also important to gain staff feedback on security practices. They interact with your systems and projects most directly and will have insights into both issues and potential solutions. It also keeps your workers a meaningful part of the security culture.

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SOA vs. Microservices: Which is the Right Choice For Your Firm?

With various styles to create and structure apps available, SOA and Microservices architecture have become two go-to methods for savvy software teams to design, launch, and smoothly maintain the latest applications for cloud environments. Additionally, 94% of companies worldwide used some form of cloud services in 2023; a 14% increase from 2020.

Witnessing notable growth between 2018-2023, the Service-Oriented Architecture (SOA) Governance Software Market is expected to grow considerably by 2030. Over 90% of organizations have also adopted or plan to adopt microservices.

In this article, we’ll explain these two popular approaches to application software development, their benefits, and which is the best choice for your enterprise.

SOA vs. Microservices

What is SOA?

Developers use a range of architectural styles to effectively organize modern software systems within the cloud. Used to structure applications to align with specific standards and best practices, whilst providing cross-platform app consistency, Service-Oriented Architecture (SOA) is a method that allows software developers to create independent business applications that can communicate across a diverse range of platforms and languages.

Organizing software systems as a collection of services, SOA services:

  • Offer a modular method of splitting up monolithic (single codebase) applications into smaller parts.
  • Function independently of development technologies and platforms.
  • Use loose coupling to minimize the impact of changes and failures within large enterprises.
  • Communicate with each other over standard protocols.

So, why are increasing numbers of enterprises looking to improve their business outcome driven enterprise architecture by adopting an SOA approach?

What are the main benefits of SOA?

SOA delivers several benefits for developers. Most notably:

  • Sustainability
  • Better collaboration
  • Ease of integration
  • Centralized Governance
  • Technology Diversity

For example, Customer Relationship Management Systems (CRMs) use SOA structures to manage various aspects of customer interactions and data. Improving a wide range of industries, call centers use customer relationship management to enhance their services even further. One of the most common call center problems and solutions is agent burnout, with savvy enterprises using workflow automation software and other automation tools to reduce agent stress.

Another tool to unify your understanding of technology and enable integrated business planning is business capability modeling. Helping enterprises realize their unique possibilities, while reducing IT redundancies and costs too, business capability examples include inventory management, online booking capabilities, and more.

What businesses use service-oriented architecture?

Suited to enterprises with complex IT environments, SOA’s streamlined integration features are often used by large enterprises. These include:

  • Financial services, e.g., banks, insurance companies, and other financial institutions.
  • Healthcare providers.
  • Telecommunications.
  • Retail and E-commerce.
  • Manufacturing.
  • Government Agencies.
  • Transportation and Logistics.
  • Hospitality and travel.

As you can see, SOA benefits enterprises with diverse application portfolios and where agility, interoperability, and scalability matter most. 

Examples of SOA architectures

Used to address issues such as data sharing amongst stakeholders and interoperability between disparate systems, here are a few examples of how a healthcare provider might implement SOA.

  • Integration of Electronic Health Records (EHR): SOA allows health providers to implement different functionalities for managing electronic health records (EHR) in real-time, e.g. patient registration, medical history, laboratory results, etc.
  • Clinical Decision Support Systems (CDSS): Healthcare providers deploy clinical decision support systems (CDSS) to help clinicians make evidence-based decisions. SOA is used here to develop modular and reusable services for implementing a range of clinical decision support functionalities, such as allergy alerts.
  • Health Information Exchange (HIE): The health information exchange network is used to share patient information with other healthcare enterprises securely. SOA aids the development of interoperable services for sharing patient data, e.g. demographic information, test results.
  • Telemedicine and Remote Patient Monitoring: SOA supports the development of services for telemedicine, e.g. virtual consultations, secure messaging, remote sensor data extraction.
  • Scalability and Flexibility: SOA gives health providers the opportunity to scale resources based on demand and ensure high performance healthcare IT systems.

What are microservices?

While each SOA service offers full business capabilities, microservices architecture has evolved from traditional SOA architecture to specialize in single tasks. So, rather than building an expansive monolithic application, microservices are small, self-contained building blocks that strengthen the structure from within.

Found in a range of applications and stretching across multiple industries, companies that use microservices architecture to enhance the buyer experience include Netflix, Spotify, and Twitter. Each one of these examples uses microservices to manage essential functions closely, such as user authentication and recommendations.

SOA vs. Microservices

What are the benefits of microservices?

Yes, SOA and microservices architecture both support independent development, scalability, and technology diversity. But what are the main differences when it comes to the benefits?

When implementing microservices, Java is a popular choice for many developers. Designed to work together yet perform specific tasks, here are five advantages of microservices architecture that developers need to be aware of.

  • Adaptability
  • Decentralized data management
  • Decentralized governance
  • System resilience
  • Greater testability

To make sure each microservice has a clear role and purpose, it’s also worth considering Domain-Driven Design (DDD). Enabling the smooth development and maintenance of complex software systems, microservices perfectly align with the DDD model; allowing each microservice to focus on a specific subdomain. So, whether it’s a co.il domain or a .uk domain name, by aligning services with the business domain, it’s that much easier to understand and manage.

Compared to monolithic architectures, as microservices are designed for independence and isolation, they’re often easier to test. Testing smaller segments of functionality can boost the reliability of the testing process.

By leveraging data analytics, using visualization tools, and comparing an enterprise’s architecture with industry benchmarks, enterprise architects deliver insights and recommendations for optimizing and developing your company’s technology. Modern Enterprise Architecture from Ardoq, for example, offers an effective way to evaluate existing capabilities and take them to the next level.

Who uses microservices architecture?

Beneficial for enterprises that prioritize scalability and rapid innovation, microservices architecture often benefits:

  • Startups and digital-native companies e.g., tech companies.
  • Social media platforms.
  • Streaming services.
  • Fintech companies.
  • Online marketplaces.
  • Gaming companies.
  • Travel and hospitality platforms.
  • Healthcare technology providers.

Microservices are ideal for enterprises that put agility and quick software updates first.

SOA vs. Microservices

Examples of microservices?

Used to create feature-rich platforms for streaming media content to millions of users, here’s an example of how a streaming platform might implement microservices:

  • User Authentication and Authorization: Dedicated to managing user authentication and authorization, microservices separate authentication into a dedicated service. This ensures security and scalability at every touch point across multiple devices.
  • Content Management: Streaming services maintain a microservice responsible for content management, including metadata for movies, TV shows, music albums, or podcasts. Its decoupling feature enables streaming platforms to handle large volumes of content updates and provide personalized recommendations based on user viewing or listening history.
  • Playback and Streaming: Without microservices, there would be no playback or different streaming options for different devices and platforms. Breaking playback functions into smaller, specialized microservices ensures a smooth streaming experience for users, no matter the network conditions or device capabilities
  • Personalization and Recommendation: Streaming service microservices analyze user behavior, viewing history, preferences, and social interactions to provide personalized recommendations.
  • Billing and Subscription Management: Integrating with payment gateways and CRM platforms, microservices handle billing and subscription options like plan upgrades/downgrades and payment processing.
  • Analytics and Monitoring: Microservices also collect, process, and analyze data from user interactions, system events, and infrastructure metrics. Microservices provide real-time insights into platform performance, user engagement, content popularity, service availability, and more.

When would developers prefer microservices?

  1. Large enterprise-scale projects.
  2. Agile development practices and decentralized teams.
  3. Projects that require technological diversity.
  4. Projects that require frequent updates and independent deployments of services.
  5. For building new, independent services.

When should SOA be used?

  1. Smaller software development projects with less complexity.
  2. Organizations with a more centralized structure.
  3. Suited to standardized technology stacks.
  4. Projects that need minimal updates.
  5. For integrating legacy systems.

Regardless of when your team implements SOA or microservices, it’s important that they understand how to use both types of architecture. Adopting a skill management platform to identify any skill gaps means you can provide software developers with the necessary tools and support to ensure your business benefits.

So, to summarize:

Service oriented architecture (SOA)Microservices
Maximizes app reusabilityFocused on decoupling
Systematic changes require modifying the monolithSystematic changes create new services
Continuous Delivery and DevOps used but not widespreadStrong emphasis on DevOps and Continuous Delivery
Focused on enterprise functionalist reuseMore focus on “bounded context”
Enterprise Service Bus (ESB) is used to communicateMuch simpler messaging systems used to communicate
Supports multiple message protocolsUses lightweight protocols, e.g. HTTP or REST
Common platform used to deploy servicesCloud platforms typically used
SOA services share data storageEach microservice can have independent data storage
Established governance and standardsEasygoing governance, with more emphasis on team collaboration and freedom of choice
SOA vs. Microservices

Final Thoughts

It’s clear to see that enterprises with legacy applications gain the most from SOA architecture, whilst microservices are preferred when multiple microservices need to be deployed with ease and finesse.

Largely dependent on the size of the project, as well as your team’s expertise and company culture, taking a hybrid approach to both architectures is a feasible option to consider too.

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Vue.js vs. React: Which is the Ideal JavaScript Framework for 2024?

The use of JavaScript frameworks has become very important in today’s modern web development, as it is important to identify the best one that will help to develop efficient and manageable applications. When it comes to 2024, two frameworks, Vue. and React, will still be in demand. They are well-supported, have a lot of active users and contributors, and offer features that are useful for various development tasks. 

The following is a detailed comparison between Vue.js and React that will help in determining which of the two is ideal to choose.

Basic Understanding of Vue.js and React.js

What is Vue.js?

Vue.js is an open-source framework created by Evan in February 2014. It aims at aiding coders in developing interactive and effective user interfaces.

Vue is simple, easy to incorporate with other libraries, and it can be applied to the most basic projects as well as complicated applications. It is a minimal feature set that is best defined as simply the view layer and can be easily integrated into some other frameworks or used in an existing project.

What is React.js?

React.js is a JavaScript library, developed by Facebook developers and was established in the year 2013. It is primarily used for creating User Interfaces, especially in scenarios where data ought to be refreshed over time. 

Remarkably, React was the first to propose the concept of the virtual DOM to enhance the speed of rendering. It enables developers to create elements which have their own state and then use these elements to create interfaces.

Vue.js vs React.js: A Detailed Comparison

1. Popularity and Community Support

Vue.js

  • Popularity: Vue.js has recently become popular, specifically in Asia and Europe. It is highly preferred by many users since it has a user-friendly interface and does not require much of the user’s effort when in use.
  • Community Support: Vue has an active community. It is an open-source tool,  has more than 207204 stars in GitHub and comes with numerous plugins, tutorials, and much more.

React.js

  • Popularity: React is very popular and has a large market share in the US. Its successful applicability  with large-scale corporations such as Facebook, Netflix, and Airbnb testifies to its popularity.
  • Community Support: React has a huge community. It is an open-source tool, backed up by Facebook Corporation. As of now, it has 223644 stars on GitHub and consist of a rich set of tools and resources available.

2. Learning Curve and Documentation

Vue.js

  • Learning Curve: Vue is considered to be easily learned since it has few lines of code. The features are well-designed, and its unique layout can easily be comprehended by the user who has little or no technical experties.
  • Documentation: Vue has documentation that is both easy to find and clearly written, accompanied with guidelines and tutorials.

React.js

  • Learning Curve: React is comparatively tougher and takes more time to learn. This is because the developers must learn about JSX as one of the extensions of JavaScript and must use other frameworks like Redux for state management.
  • Documentation: The documentation of React is better than Vue. However, React lacks in many learning resources as compared to Vue.

3. Performance

Vue.js

  • Performance: Vue also uses a virtual DOM as React, making it more efficient by  avoiding frequent DOM modifications. It also excels at handling dependencies and changes within its reactivity system.

React.js

  • Performance: React is optimized because it has a virtual DOM and a fiber that splits the production task into parts. It also makes the updates and rendering to be faster.

4. Flexibility and Scalability

Vue.js

  • Flexibility: Vue is highly flexible and can be adopted in an incremental manner. Vue.js and its ecosystem, like Vuex for state management and Vue Router for routing, work well together.
  • Scalability: It is useful to develop simple and intermediate applications; however, complex applications can also be developed with Vue if structured correctly.

React.js

  • Flexibility: React is quite flexible. But when compared with other frameworks, it needs other libraries for making it a complete solution. 
  • Scalability: It is extensible and can be used in the development of large and complex applications because of the component based approach.

5. Ecosystem and Tooling

Vue.js

  • Ecosystem: The Vue ecosystem is quite consistent and logically thought-out. It has various tools that support the building of web applications and libraries, including Vue CLI, Vue Router, and Vuex, making it a complete package.
  • Tooling: Vue DevTools is an extension that provides powerful tools for debugging, and the Vue CLI is a convenient tool for project creation.

React.js

  • Ecosystem: Since React has a very large ecosystem, there are many libraries and tools available, but this can make things confusing. Building  projects to optimize their features can be done quite quickly through tools such as Create React App.
  • Tooling: React DevTools are very useful for debugging.  It consists of many other tools that can be used for increasing the efficiency of the development.

6. Integration and Compatibility

Vue.js

  • Integration: Vue.js is very flexible and can be gradually integrated into projects in a hasselfree manner. It incorporates with most other libraries and existing projects to give an enhanced result. It allows flexibility in development of complex and time consuming projects.
  • Compatibility: Vue supports various backend frameworks and platforms, enabling its impactful implementation in various contexts.

React.js

  • Integration: React is a versatile and flexible framework that seeks integration with other libraries to end up with a full-fledged solution. Its modularity makes it possible to easily combine with different tools and frameworks whenever needed.
  • Compatibility: Integrates with most environments and platforms, such as server-side with Next. js and mobile development with React Native.

Best Use Cases of Vue and React

Vue.js

  • Prototyping and Small Projects: Vue is relatively easier to use as compared to other libraries and has a good support for integration. This makes it useful in the creation of a prototype and for projects of small as well as medium level.
  • Incremental Adoption: Vue can be adopted into existing projects without the need to rewrite everything from scratch.
  • Enterprise-Level Applications: Some of the companies that have adopted Vue include Alibaba and Xiaomi, proving its effectiveness for large-scale development.

React.js

  • Single-Page Applications (SPAs): Due to its efficient rendering and state management, React is one of the best frameworks for building SPAs.
  • Data-Driven Dashboards: It is a brilliant framework for developing real-time dashboards through the use of reactive components, thatallow for easy and efficient update of the data presented to the user. 
  • Enterprise-Level Applications: React is useful in big enterprises since it has a sound architecture and good state management. It is backed by Facebook so it is sustainable and frequently updated.

Which Framework to Choose: Vue.js or React in 2024?

When it comes to comparing Vue.js and React in 2024, it is crucial to consider the specifics of your project and your team’s experience. 

Vue.js is a perfect match for these people who don’t want to struggle with a steep learning curve and complex integration; while, React is more suitable for large-scale applications due to its powerful ecosystem and fat corporate support.

When to Choose the Vue.js Framework?

  • Ease of Learning: The availability of developers with an inclination towards front-end frameworks can be a point of consideration whene choosing Vue.js since it is easier to learn and the documentation is vast.
  • Incremental Integration: Vue is perfect for projects when it is gradually implemented, it can be easily adopted as a part of the project without interrupting the team.
  • Community and Support: In terms of active communities and well-integrated ecosystems, Vue offers a solid and easy-to-navigate development foundation.

When to Choose the React. js Framework?

  • Large-Scale Applications: React is scalable and ideal for large projects that will need more focus on state management and UI.
  • Corporate Backing: If corporate support and long-term stability are important, React’s backing by Facebook offers essential assurance about continuous progression.
  • Cross-Platform Development: In cases where a project needs both a web and a mobile application, the ability to use React and React Native is another benefit.

Conclusion

Both Vue. js and React are great frameworks with their own benefits and are best suited for specific conditions. 

Overall, Vue is the best tool for developing small-to-medium projects and teams that don’t want to struggle with complex learning curves. On the other hand, React possesses a vast and stable environment, the support of large corporations, and the ability to work on large-scale projects. 

Stepping into 2024, the choice between Vue. js and React should be based on the requirements of your project or application, the experience of your team, and the further development of the application. Considering the above factors, this will enable you to come up with the right framework for your project development strategy and goals.

About the author

Harikrishna Kundariya is the Co-founder, Director, & Marketer
of eSparkBiz Technologies – an excellent Software
Development Company. Also, a notable IoT, ChatBot &
Blockchain-savvy Developer. His 12+ years of profound
experience enables him to create Digital Innovations for
Startups & large Enterprises alike based on futuristic
technologies like IoT, Artificial Intelligence, DevOps, and
ChatBot. Adopting a modern yet extremely flexible leadership
approach, he believes in building businesses & lasting bonds
with his clients in the process.

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Advanced git: Demystifying git Remotes and git cherry-pick: Powerful Tools for Collaboration

Collaboration is key in the world of Git version control. But keeping track of changes from multiple developers can get tricky. This blog post dives into two essential Git features—remotes and cherry-pick—that empower you to streamline your workflow and effectively manage contributions.

Understanding Git Remotes: A Bird’s Eye View

By default, your GitHub repository typically has a single remote—the origin, representing the main repository you cloned from. However, in larger projects with multiple developers, things get more interesting. Often, developers create personal forks before they push their code.This allows them to work on a separate copy of the code base, and once they are satisfied with the changes, they can merge back into the main codebase.

Here’s where remotes come into play. They are references to additional copies of your Git repository, potentially containing valuable contributions from other developers.

Let’s use an Open-Source project: Lottie

Imagine we’re working with the fantastic Lottie by Airbnb, a library that renders After Effects animations on mobile platforms. We’ve cloned a fork (iayanpahwa/lottie-android) and want to explore changes made by other contributors to lottie (gpeal and felipecsl).

Adding Remotes: Reaching Out to Other Forks

To access these developers’ workspaces, we can add them as remotes using the git remote add command:

git remote add <remote_name> <repository_URL>

For example:

git remote add gpeal https://github.com/gpeal/lottie-android.git
git remote add felipecsl https://github.com/felipecsl/lottie-android.git

Now, using git remote -v, you can see all configured remotes, including their URLs.

Fetching the Goods: Downloading Changes

With remotes in place, we can retrieve changes from other contributors using git fetch.

  • Fetching from a specific remote:
  • Fetching from all configured remotes:
	git fetch --all

This downloads the commits made by these developers without integrating them into your local working directory yet.

git cherry-pick: Borrowing the Best Bits

Git cherry-pick allows you to meticulously select and apply specific commits from other branches (including those fetched from remotes) onto your current branch. This is particularly useful for integrating contributions from multiple developers, testing them individually, or incorporating specific fixes.

A Real-World Cherry-picking Scenario

Imagine you manage an open-source project that receives a wave of pull requests. You might want to test these contributions together before merging them. Here’s how cherry-picking can help:

Create a New Branch:

git checkout -b my-test-branch
  1. Fetch Necessary Code (if not already done): Use git fetch as explained earlier.
  2. Cherry-picking Commits: Once you have access to the desired commits, cherry-pick them one by one using their commit hashes:
git cherry-pick <commit_hash>

For instance, to test a specific commit (648c61f5275998c461347b5045dc900405306b31) by contributor gpeal:

git cherry-pick 648c61f5275998c461375647845dc900405306b31 [ commit made by gpeal ]

This brings gpeal’s changes to your my-best-branch for isolated testing.

Remember: Cherry-picking can rewrite history, so use it cautiously. Always create a dedicated branch for testing before integrating changes into your main codebase.

Wrapping Up:

By mastering remotes and cherry-pick you can effectively collaborate on Git projects, leverage valuable contributions from others, and ensure a smooth and efficient development workflow.

Feel free to reach out with any questions! Happy coding! Do check our blogs on git internals for more learning: 

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Managing Complex Dependencies with Google’s repo tool

In my last blog, I discussed managing dependencies with git submodules. However, when working with large projects that have many dependencies, traditional methods like git submodules can become cumbersome. Google’s repo tool emerges as a powerful solution specifically designed to handle this challenge.

What is repo tool?

repo is an in-house dependency management tool developed by Google. It excels at managing many dependencies, making it ideal for projects like the Android Open Source Project (AOSP) and custom Android ROMs.

Unlike git submodules, which are an integrated git feature, repo functions as a separate executable script. This necessitates installation before diving in.

Installation (Choose your adventure!)

Linux: 

Create a directory for Repo:

mkdir ~/bin

Update your PATH environment variable:

export PATH=~/bin:$PATH

Download and make Repo executable:

curl https://storage.googleapis.com/git-repo-downloads/repo > ~/bin/repo
chmod a+x ~/bin/repo
Google repo tool

OSX:

Use Homebrew to install Repo:

brew install repo
Google repo tool

For other platforms, refer to official docs: https://gerrit.googlesource.com/git-repo

Manifest Magic: Defining Dependencies

Repo relies on a manifest file stored in a separate Git repository. This XML file is the central hub, outlining where to fetch project dependencies, their storage location, and specific revisions (commits).

The beauty of Repo lies in its ability to manage multiple manifests. Imagine a huge, complex project like the Android Operating system with 100 dependencies. You could create a dedicated “lib.xml” manifest to fetch those specific libraries, eliminating the need to include hundreds of unrelated dependencies from a broader manifest. Similarly, the testing and compliance team can have “qa.xml” and “compliance.xml” to manage extra QA and compliance-related dependencies separately, which might not be needed in production but required during development. Both could also have the same libraries but different versions. Hence repo using manifest.xml makes handling dependencies extremely flexible. 

For this demo, we’ll keep things simple with a single “default.xml” file.

Creating a Manifest

Clone the Example Repository having our manifest:

git clone git@github.com:iayanpahwa/manifest-demo.git

Examine the default.xml file:
This file specifies the main Project (ex, EazyExit) with two dependencies, FastLED and PubSubClient, along with their corresponding URLs, paths, and revision IDs.

<?xml version="1.0" encoding="UTF-8"?>
<manifest>

<remote fetch="https://github.com/iayanpahwa/" name="EazyExit" />
    
    <project name="FastLED.git" path="lib/FastLED" remote="EazyExit" revision="c1ab8fa86f6d6ecbf40ab7f28b36116a3c931916" />
    <project name="pubsubclient.git" path="lib/PubSubClient" remote="EazyExit" revision="dddfffbe0c497073d960f3b9f83c8400dc8cad6d" />

</manifest>

Note: The manifest allows for various configurations, including project branches and alternative remotes (like Bitbucket or GitLab). Refer to the official documentation for a comprehensive list: https://gerrit.googlesource.com/git-repo/+/master/docs/manifest-format.md

Putting it All Together: Fetching Dependencies

  1. Push the default.xml file to your GitHub repository (if using the provided example).
  2. Create a project directory (e.g., EazyExit).

Navigate to your project directory and initialise Repo

Google repo tool

3. This command establishes the current directory as your project workspace.

Fetch dependencies using the repo sync command:

4. This command retrieves all dependencies specified in the manifest and stores them according to the defined paths.

By leveraging repo, you can effectively manage many dependencies within a single, streamlined workflow.

Repo empowers you to manage complex dependencies with ease, promoting a more flexible and adaptable development process. Checkout our other blogs on: 

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How Git Submodules Can Save You Time (and Headaches): Taming the Dependency Beast

In software development, we rarely build projects entirely from scratch. We leverage open-source libraries and frameworks to accelerate development and avoid reinventing the wheel. But managing these dependencies can quickly become a tangled mess, especially as projects grow and dependencies multiply.

This blog post explores a simple yet powerful Git feature called git-submodule, which streamlines dependency management and keeps your codebase clean and organised.

Git Submodules

The Downside of the Manual Approach

Many developers resort to simply manually cloning and directly pushing dependency code into their main project’s codebase. While this may seem convenient at first, it creates several challenges:

  • Version Control Issues: Updating dependencies becomes a manual process, increasing the risk of compatibility issues and security vulnerabilities.
  • Upstream Changes: New features or bug fixes in the original library require manual integration, which is time-consuming and error-prone.

Introducing Git Submodules

git submodules allow you to integrate external Git repositories (containing your dependencies) directly into your project. This creates a modular approach with several benefits:

  • Independent Updates: You can update submodules individually without affecting your main project code.
  • Version Tracking: Submodules track the specific commit hash of the dependency you’re using, ensuring consistency and reproducibility.
  • Modular Codebase: Your project remains clean and organised, with dependencies clearly separated from your core code.

Putting Git Submodules into Action

Let’s walk through a practical example. Imagine a project named “submodule-demo” that relies on two libraries:

  • FastLED: A library for controlling LEDs
  • PubSubClient: A library for implementing an MQTT client
Git Submodules

Here’s how to leverage git-submodules to manage these dependencies:

  1. Project Structure: You can create a dedicated directory (e.g., lib) within your project to store dependencies.
  2. Adding Submodules: Use the git submodule add command to specify the URL of the external repository and the desired submodule path:
cd your_project/lib
git submodule add https://github.com/iayanpahwa/FastLED.git
git submodule add https://github.com/iayanpahwa/pubsubclient.git
Git Submodules

This fetches the code from the specified repositories and stores them within the lib directory.

3. Initialising and Updating: Anyone cloning your project can easily initialise and update the submodules using the following commands:

git clone <your_project_URL>
cd <your_project_URL>
git submodule init
git submodule update
Git Submodules

Alternatively, you can use the --recursive flag during cloning to automate these steps:

git clone --recursive <your_project_URL>
Git Submodules

4. Version Control: Git submodules record the specific commit hash used from each dependency. This ensures everyone working on the project uses the same library version, promoting consistency and preventing compatibility issues.

Beyond the Basics:

While submodules default to fetching the latest commit from the dependency’s main branch, you can specify a different branch or commit hash. Refer to the official Git documentation (https://git-scm.com/book/en/v2/Git-Tools-Submodules) for details on advanced usage.

Key Takeaways

By embracing git submodules, you can effectively manage dependencies, improve code organization, and streamline project collaboration. This approach promotes a more modular and maintainable codebase, saving you time and headaches in the long run.

Feel free to explore our other blog posts on Git internals for further insights!

Git Internals Part 1- List of basic Concepts That Power your .git Directory

Git Internals Part 2: How does Git store your data?

Git Internals Part 3: Understanding the staging area in Git

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Squeezing Performance Value from Terraform’s Command Line Interface

Terraform’s Command Line Interface

Organizations use Terraform for devops infrastructure management and in interfacing with configuration files. They also use it in planning changes before they are applied to the infrastructure. Additionally, Terraform is employed in viewing the state of infrastructure and in importing infrastructure under Terraform control.

Terraform’s command line interface (CLI) is the tool that enables Infrastructure-as-Code management with the HashiCorp Configuration Language (HCL) through commands.

Using the Terraform CLI is somewhat of an art. Different users have different approaches. In many cases, teams fail to get the most out of it. Here’s a rundown of some of the best ways to maximize the use of Terraform’s command line interface to make IaC provisioning and management more efficient.

Mastering the Commands

Becoming an expert with the available commands is a foundational skill in using Terraform CLI. Users must become well-versed with essential Terraform CLI commands such as Terraform initialization (init), validation (validate), planning (plan), and application (apply) to proceed with provisioning, configuration, and management tasks intuitively. There are also important commands used to streamline workflows such as format (fmt) and refresh (refresh).

The use of these commands is not as straightforward as it may seem. Running the init command, for example, requires a working directory that contains the configuration files and a properly installed and configured Terraform Core. It is also possible for prompts to appear during the init command execution. These prompts can be for credentials and backend configuration details or for a confirmation to install a required plugin.

Also, still in connection with the init command, there are cases when modifications are needed through flags such as -lock and -upgrade. It is important to get acquainted with these options, as they are necessary for module upgrading and copying, state locking, and other purposes. The -upgrade flag is particularly important because it is used to update to the most recent compatible versions of providers and modules.

Mastery of available Terraform CLI commands ensures efficiency and consistency in managing infrastructure. It is especially crucial for collaborative provisioning and management actions, wherein everyone has to work seamlessly with version control systems like Git. Tools are only as good as their users are, so it is only logical to master Terraform CLI to use it optimally.

Working Separately and Collaboratively with Workspaces

Terraform CLI users should take advantage of the workspaces feature. This is important when organizing or managing different environments, as it enables the management of separate deployments of the same infrastructure codebase. 

Workspaces make it possible to manage development, staging, and production environments in isolation. This separate management is necessary to test modifications in development in one environment without causing a cascading of changes to other environments. 

Additionally, workspaces enable configuration variants. For example, it allows the creation of a separate workspace for a base configuration and another one for a specific region, where the configurations used in these workspaces are slightly deviating.

Ironically, the benefit of being able to manage environments separately with Terraform’s workspaces is an advantage for collaboration. Different teams can work in different environments at the same time to expedite the job, without the risk of inconsistencies or errors, because each workspace has its own state. There are no risks of accidental modifications or deletions.

Leveraging Modules

Another important tip when using the Terraform CLI is to make use of modules. These are collections of Terraform configuration files in one directory. Basically, they are self-contained and reusable sets of configurations that represent a specific infrastructure component, functionality, or element. 

Working with the CLI can become confusing as the code becomes more and more complex. Modules help tone down this complexity and simplify infrastructure deployments by reducing the need to write the same configuration repeatedly for infrastructure elements present in multiple locations. 

This eliminates code duplication, because infrastructure elements can be defined once in a module, and then the same module can be reused wherever it is needed.

Terraform modules enhance code maintainability because they make code easier to comprehend. They also provide the benefits of quick modifications and efficient debugging. Likewise, they ensure that changes made to an infrastructure element are reflected automatically across all places where the element exists.

Mindful State Management

When using the CLI, it is also critical to watch out for Terraform state files. These files house the mapping of configurations to actual infrastructure resources, making them a critical part of the Terraform CLI’s effective functioning. They serve as a central source of truth, which is important in maintaining consistency and the proper identification of changes in the code.

Since state files map configurations to resources, they are vital in Terraform’s ability to understand the current state of your infrastructure units. They create the basis for how to achieve the desired configuration. Also, they are useful in optimizing performance for large infrastructures, because they also store cached resource attribute values, which lessen the need to perform cloud provider querying whenever Terraform runs.

States files are saved locally in a file name labeled as terraform.tfstate by default. Many devops teams find it beneficial to utilize remote state backends like Terraform Cloud. Doing so enables centralized management, which is a boon for infrastructure visibility and collaboration. It also facilitates better version control and security, especially helpful in cases of agile disaster recovery.

Updating the CLI and Exploring Advanced Features

Constantly updating Terraform CLI to the latest version is a must to ensure that the CLI being used has all the security patches applied as well as the latest features. Also, it is advisable to explore new and advanced features. 

Terraform’s CLI is a tool intended for developers, not ordinary app users who are easily impressed by the newest functions. Expect most of the new and advanced features to be purposeful and worth having.

For example, it is possible to access the attributes of other resources within variables. This function is great for dynamic and flexible configurations because it allows the referencing of attributes of existing resources within variables. 

Here, configurations can adapt according to the infrastructure state, like setting a unique security group ID for a new resource in accordance with the ID of an existing security group.

Maximizing Terraform CLI

The best performance of any tool depends on its user. In other words, Terraform CLI can provide the best efficiency, consistency, and collaboration benefits if users gain expertise in using it. The four pointers briefly discussed above can serve as a good starting point in taking full advantage of Terraform’s Command Line Interface to work with Infrastructure-as-Code with maximum efficiency and the best infrastructure management outcomes.

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From Rendering to AI: 5 Reasons Why You Can Consider an NVIDIA GPU Dedicated Server?

Consider an NVIDIA GPU Dedicated Server

Computing power is no longer a luxury, it’s a need. Whether you’re a creative professional pushing the boundaries of animation or a scientist address complex copy, having the right tools at your disposal can make all the difference. This is where NVIDIA GPU dedicated servers come in, offering a hard join of processing power and creativity that can transform your workflows.

But what exactly are NVIDIA GPU dedicated servers, and why should you consider them? Let’s explore into the world of GPU boost and explore five powerful reasons why incorporating an NVIDIA GPU dedicated server into your arms can empower your projects and move you towards success.

1.  Release the Power of Similar Processing:

At the heart of an NVIDIA GPU dedicated server lies the Graphics Processing Unit (GPU). Unlike traditional CPUs designed for sequential tasks, GPUs excel at similar processing. Imagine a highway with multiple lanes – a CPU funnels tasks through one lane at a time, while a GPU utilizes numerous lanes simultaneously, significantly accelerating computations.

This similar processing skill makes NVIDIA GPU dedicated servers ideal for applications that involve massive datasets and complex calculations. Tasks like:

  • 3D Rendering and Animation: Render hard scenes with breathtaking detail in a spot of the time compared to CPU-based systems.
  • Video Editing and Encoding: Edit high-resolution footage seamlessly and encode videos for various platforms at blazing speeds.
  • Scientific Simulations: Run complex simulations involving solution dynamics, weather patterns, or protein folding with unparalleled efficiency.
  • Deep Learning and AI: Train deep learning models faster and develop cutting-edge AI applications that leverage vast amounts of data.

2. Unmatched Performance for Demanding Workloads:

NVIDIA GPUs boast thousands of cores specifically designed for processing massive datasets and performing complex calculations. This translates to real-world benefits for users. With an NVIDIA GPU dedicated server, you can:

  • Reduce project turnaround times: Get results quicker, repeat faster, and meet deadlines with greater ease.
  • Handle larger and more complex projects: Take on hard attempt that would strain traditional CPU-based systems.
  • Increase productivity and efficiency: Focus on your core tasks while the server tackles computationally intensive workloads.
  • Unlock new creative possibilities: Experiment with innovative techniques and push the boundaries of your field without hardware limitations.

3. Scalability to Match Your Growing Needs:

As your projects become more demanding or your business scales, your computing needs will evolve. The beauty of NVIDIA GPU dedicated servers lies in their inherent scalability. Many providers offer a range of server configurations with varying numbers and types of NVIDIA GPUs. This allows you to choose a server that perfectly aligns with your current requirements, with the flexibility to upgrade seamlessly as your workload grows.

Considering Colocation vs. Cloud-Based Solutions:

While cloud-based NVIDIA GPU dedicated servers offer a convenient and scalable option, colocation server hosting presents a powerful alternative for users with specific requirements. Here’s a breakdown of the key considerations:

  • Control and Security: Colocation offers greater control over your hardware and network environment, ideal for businesses with strict security needs.
  • Customization: Colocation allows for customized server configurations tailored to your specific workload demands.
  • Latency Sensitivity: For applications where latency is critical, such as real-time simulations or high-frequency trading, colocation can provide a lower latency connection compared to cloud-based solutions.

4. Cost-Effective Solution for High-Performance Computing:

Investing in high-performance computing hardware can be a significant upfront cost. NVIDIA GPU dedicated servers provide a cost-effective alternative. Here’s why:

  • Shared Infrastructure: Cloud-based providers offer dedicated servers with powerful NVIDIA GPUs, eliminating the need to purchase and maintain expensive hardware yourself.
  • Pay-as-you-Go Model: Many providers offer flexible billing options, allowing you to pay only for the resources you utilize. This is ideal for projects with fluctuating workloads or those in the initial stages of development.
  • Reduced Downtime: Cloud providers manage server infrastructure, ensuring minimal downtime and maintenance headaches.

5. A Future-Proof Investment for Emerging Technologies:

The world of figure is constantly develop, and NVIDIA GPUs are at the lead of this revolution. As AI, deep learning, and other data-intensive applications continue to gain rank, NVIDIA GPU dedicated servers will become even more crucial.

By investing in an NVIDIA GPU dedicated server today, you’re not just get processing power; you’re provide yourself with a platform that can adapt and grow beside these emerging technologies. This future-proofs your investment and ensures you have the tools necessary to stay ahead of the turn.

Conclusion

NVIDIA GPU dedicated servers offer a strong idea for anyone try to push their workflows and unlock new creative or scientific possibilities. From the unparalleled processing power to the cost-effective scalability and future-proof design, these servers empower users to achieve remarkable results.

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A Developer’s Guide About Building an AI Story Generator

There are quite a few AI-based tools available today, and each one offers something unique. However, perhaps the most-used AI programs today are generative AI tools, including those that generate stories. A Forbes research says generative AI will be worth $280 billion by 2032.

That’s why, you’d want to build an AI story generator, that could potentially help users write the stories they want. But a tool like that is a sum of many great features. But what exactly is an AI story generator compared to other generative AI tools?

Moreover, what kind of features do you need, and which development path should you take? Let’s find out. 

What is an AI Story Generator? Compared to Other Generative AI

An AI Story Generator is an AI/Machine Learning-based program, which uses advanced AI algorithms to generate stories and narratives. Like other chatbots or generative AI tools, these programs also use pre-trained algorithms.

Except, there is one major difference between a common chatbot and an AI story generator. The difference in question is that the latter is designed to create engaging narratives and write in a story-esque manner while providing means to the writers. 

Let’s take ChatGPT for example, and how it would do something with a prompt like this:

“A story about Tom experiencing morning life in New York streets.”

Now, let’s put it into ChatGPT first:

Some might say it’s quite extraordinary, while others might smell AI all over it. But, if we do the same with an AI story generator like this one from Summarizer.org, our results look quite different:

And once the story is generated, here’s our result:

The story has a lot more details and offers a lot more depth compared to the ChatGPT version. That’s because ChatGPT is designed to be a chatbot only. Summarizer.org’s AI Story Generator is designed to write stories with minimal prompts.

Now, there are other options for AI story writers like these, which we’ll discuss later. But it’s important to understand how the two tools discussed above leverage AI, and the clear winner in this comparison is the story generator. 

4 Key Features You Should Add in Your AI Story Generator

Now let’s talk about the development features that you should be adding to your AI story generator. It should feature quite distinctive elements compared to normal chatbots or generative AI tools. Here are five key things you need to provide:

1: Style Selection

Style selection is one of the key things you should provide in your story generator. For instance, if the user wants a narrated story, you should provide the ability to narrate a story. While some would want a story told in a more POV manner.

The idea is to provide features that help each writer/user create a story closest to their vision. So, providing a style selection like this would help your target users get just the type of story they want.

2: Tone & Type

Another thing you should focus on is the tone and type of the story your users want to write. Some would want to write a classic, while others would want a horror or thriller. The possibilities are endless and so they should be able to explore them.

Here’s an example of the AI story generator that we used earlier:

In the Classic mode, the story uses the traditional method of delivering the idea. But, for example, let’s say if we wanted the story to be more hilarious, then we could try the Humor story type:

As you can see, the humorous setting takes it on a way different path than the earlier classical version. So, the point is, to provide something that doesn’t only distinguish stories, but also eases the job for the writer/users.

3: Creativity Level

Creativity level is yet another thing you should provide, and it should help the user select their level of creativity. Now, this depends on the type of deep learning model you use, such as GPT 3.5 or 4.0. However, it should look something like this:

When the user selects each level, like in the AI story generator that we demonstrated earlier, it should be written in that tone. Here are two examples:

Imaginative:

Inspired:

So, make sure your users are able to select the creativity level, and you provide enough means for them to leverage AI.

4: Story Length

Story length is one of the key aspects of any written story, so you should ensure your tool has the right options. The Summarizer.org’s AI Story Generator we used has three main options, and each one is made to write content in three main lengths:

The short one stays around 500-600 words:

While the longer version is around 700 words:

So, these are must-haves in an AI story generator.

3 Keys In Developing the AI Story Generator

Now let’s talk about the development part of the AI story generator. This part depends on your preferences, the technology you use, and design elements. So, here’s what you should do:

1: Technology Stacks & Which One To Use

Make sure you’re using a proper programming language with proper frameworks. The technology stacks make all the difference, and choosing the right ones can help you create a high-quality AI story writer in no time. Here are our suggestions for each category:

  • Programming Language: Python 
  • Machine Learning/Pre-Trained Models: GPT
  • Database Management: PostgreSQL 
  • Backend: Django or Flask
  • Frontend: CSS, JavaScript, or Angular
  • AdditionalServices: Git, Docker

This should help you get started properly and help you create a solid AI story writer. 

2: UI Design and Writing Method

The design of your AI story generator and the writing method in it should be simple and straightforward. The UI of the tool we used earlier should serve as an example. So, you should make sure it has:

  • A simple and readable interface.
  • Colors that are easy on the eye.
  • Offers dark mode.
  • Provides options clearly, i.e., story type, creativity level, etc.
  • And ensure the design isn’t cluttered.

This way, you will be able to keep it simple and ensure the users find it handy.

3: Testing & Finalizing

Testing and finalizing are two necessary steps to take, and you should ensure you create a checklist before deploying the tool. So, you should check for any usability problems, like errors that might pop up when users try different methods.

Or you should ask writers or other story experts to check the tool before deploying it. Besides, it’s always important to provide updates and make changes even after uploading the tool.

Conclusion

These are some of the key features and development paths for building an AI story generator. Remember, it’s about creating something that the users not only find helpful but can also leverage to break out of writer’s block, or simply generate creative ideas to work with. So, providing them with the options we explored can help you do just that easily.

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Continuous Learning Strategies for Beginner Developers for Career Success

Let’s face it, the tech industry is evolving rapidly. Developers are expected to understand the latest developments with new languages, frameworks, and methods. For beginners, this journey can be challenging but necessary for their career growth. 

Employing continuous learning strategies is essential for developers. This allows them to improve their knowledge and skills while remaining competitive in the job market. Many opportunities are available online and offline, and we will discuss this in no time!

If you are a beginner developer, we have listed five ways to stay updated in the tech industry. But before we dive into the details, let’s understand more in-depth why continuous learning is important for beginner developers.

Benefits of Continuous Learning for Beginner Developers

Continuous learning has become a necessity as the tech industry rapidly developed. Ongoing education and development can help you improve technical skills and foster personal growth as a beginner developer. Here are more benefits you can get.

  • Improve programming skills and problem-solving abilities
  • Foster adaptability and familiarity with various new technology
  • Connect with other professionals and experienced developers
  • Enhance career prospects in the job market

As continuous learning is essential for beginner developers, we’ve listed some strategies to keep you updated on the recent developments in the industry.

Staying On Track With Industry Trends

There are many ways to stay updated on the newest trends. One of the easiest ways is following industry blogs and publications. Consider following and subscribing to reputable tech blogs, such as TechCrunch, Wired, or Medium’s programming section.

These platforms often provide insights into emerging technologies, best practices, and industry news. Other ways to stay abreast of industry trends are watching YouTube book review videos, attending conferences, and engaging in online communities. 

Participating in tech conferences allows you to network with industry professionals. Meanwhile, online communities like Stack Overflow and Reddit give you opportunities to learn from others, ask questions, and discuss industry trends.

Participating in Online Courses

Online courses are a great and quick way to learn new skills and technologies. You can find online courses with flexible hours and affordable prices that offer skill improvement programs and other courses with experienced developers.

Here are some tips to consider. First, choose reputable platforms. Coursera, Udemy, and Pluralsight usually offer a wide range of courses taught by industry experts. You can also take online classes provided by experts.

As a beginner, you can start with courses that cover fundamental programming concepts, languages (e.g., Python, JavaScript), and development frameworks (e.g., React, Django). Developing a strong foundation is essential for long-term success.

Once you have a solid understanding of the basics, explore specialized topics based on your interests or career goals. This could include machine learning, web development, mobile app development, or cloud computing.

Engaging in Coding Challenges

Coding challenges are excellent for beginner developers to practice problem-solving skills and improve coding abilities. You can go to websites such as LeetCode, HackerRank, and CodeSignal to try a variety of coding challenges categorized by difficulty level and topic. 

While joining challenges offers a fun experience, you also need dedicated practice time. Schedule regular practice sessions dedicated to solving coding challenges. Consistency is key to improving your knowledge, skills, and portfolio over time.

After attempting a coding challenge, review the explanations for the solutions provided by others on the platform. Pay attention to different approaches and techniques used. Also, get feedback from peers or mentors to identify areas for improvement.

Contributing to Open-Source Projects

Contributing to open-source projects gives you many opportunities. You can learn real cases, collaborate with other developers, and even practice programming for free. These can enrich your portfolio and attract recruiters. 

However, many beginner developers don’t know where to join this project. You can begin by exploring popular open-source repositories on platforms like GitHub. Look for projects that align with your interests and skill level. 

Many projects label issues as “beginner-friendly” or “good first issue” to help newcomers get started. You can always start with small contributions like fixing typos or adding tests. But never feel intimidated by the complexity of larger projects.

Projects help you familiarize yourself with the project’s codebase and contribution process. Keep the consistency to improve your skills, build your portfolio, and establish your presence within the open-source community.

Networking and Mentorship

Networking and mentorship will help you with professional development. Building meaningful connections with peers and industry professionals opens doors to new opportunities in the future. 

The easiest way to do this is to leverage online platforms, especially LinkedIn. Connect with fellow developers or join developer groups to engage in discussions. You can always share your expertise and experiences to attract recruiters. 

If you don’t mind spending some budget, try seeking online mentorship. Find experts who can provide guidance, support, and career advice. Mentorship also helps accelerate your learning, expand your professional network, and navigate the challenges and new trends in tech.

Takeaway

Continuous learning is key for beginner developers who aim to make their mark in the tech world. The more effort you make as a developer will guide you to better career opportunities. 

Those continuous learning strategies outlined above lay the groundwork for success. You don’t have to try them all. Focus on strategies that can benefit you the most as a beginner developer. 

Also, maintain consistency when building your portfolio. Projects, challenges, and online courses are excellent aspects that help your portfolio stand out among competitors.