LetStart

Mastering Java Packages: A Comprehensive Guide for Organizing Code

Real-Time tricks: Harnessing Kafka Streams for Seamless Data Tasks

How to Create a 2D Character Controller in Unity: Part 1

কিভাবে ঐক্যে একটি 2D ক্যারেক্টার কন্ট্রোলার তৈরি করবেন: পার্ট 1

So erstellen Sie einen 2D-Charakter-Controller in Unity: Teil 1

Cómo crear un controlador de personajes 2D en Unity: Parte 1

Comment créer un contrôleur de personnage 2D dans Unity : partie 1

यूनिटी में 2D कैरेक्टर कंट्रोलर कैसे बनाएं: भाग 1

Unity で 2D キャラクター コントローラーを作成する方法: パート 1

Unity에서 2D 캐릭터 컨트롤러를 만드는 방법: 1부

Como criar um controlador de personagem 2D no Unity: Parte 1

Как создать контроллер 2D-персонажа в Unity: часть 1

Unity'de 2D Karakter Kontrol Cihazı Nasıl Oluşturulur: Bölüm 1

Cách tạo bộ điều khiển nhân vật 2D trong Unity: Phần 1

如何在 Unity 中创建 2D 角色控制器：第 1 部分

Many of you probably know that one of the most crucial steps in running a successful startup company is to define the right minimum viable product, simply known as MVP. Developing an MVP even after conducting initial market tests can be challenging, as the version of your product is essentially an unvalidated hypothesis. It's common for developers to waste time and resources on MVPs that are not well-defined. This guide will help you identify the core features of your product, enabling you to avoid wasting time and money. To define your MVP, you must envision the first instance of your product and find a working method on how to showcase its best possible features in a simple and brief way. Let’s take a look at the 7-step guide on how you can turn your product idea into a successful startup and appeal to early adopters. How to Find Your MVP MVP is not a beta version of your product designed to determine bugs. It is also not an idea written down on a piece of paper or presented in a couple of slides. Your MVP is intended to test market demand assumptions, refine the product vision, and help you choose where to focus future development efforts. MVPs are therefore a very effective strategy for determining your product-market fit. So, what should be your first few moves when turning your idea into a viable product? 1. Your Idea: The Basics Let’s start with the basics. What is the ground idea of your perfect product, and what is your reality at the moment? At this stage, your priority is to analyze the problem that you are trying to solve. Describe the size of your problem, and provide all the necessary statistics and data – how does this problem impact your user? How does it impact your product idea? Are there any existing products that can successfully solve the same type of problem? Collect as much evidence as possible – it can help you massively in achieving success. Do not forget to keep it well-structured. For instance, let’s take a look at Uber. In the past, getting a taxi could be rather annoying when you would have to wait at a curb in an attempt to catch a car. Uber appealed to those who wanted the ability to rapidly call a cab by simply pulling out their smartphone, making a couple of clicks in a user-friendly app, and therefore, solving the initial problem and pain point completely. 2. Understand Your Users During this stage, you need to analyze the current state of the market, identify your target audience, and study your competitors. This will help you understand how your product can stand out among others and what features are important to your product users. Here, your product team must ensure they clearly know who their users are. Identify each class (or type) of the user, their needs, wants, pain points, expectations, experience, and other metrics you find useful in your case. The final step of your research should be to draft the so-called success criteria – the standard to judge whether an objective has been achieved – for each type of product user. Once you have identified your users, it’s time to learn if you can actually understand them. Collect information about their behavior, their profiles, and habits – of course, by complying with the data collection laws in your country. Get as much knowledge and publicly accessible insights into who your users are. You can also carry out a few interviews, and create surveys or focus groups to further deepen your research. 3. What Is Your Big Picture Product? What would your product look like if you had all the possible resources, time, and investment? What is the ideal state of your product? It is recommended that you list down all the valid ideas collected from your team that could help your startup reach its final stage of development. Moreover, you can also collect feedback from your users. To help you think big, you can answer the following questions: What major issue are you aiming to address? What ambitions do you have for your product? Which user requirements are you trying to meet? What challenges faced by users are you aiming to overcome? What tasks require improvement, efficiency, or innovation that your product will accomplish? 4. What Is Your Minimum Product? Now that you have got an idea regarding your ideal product, your next step is to define what would be enough for your product to work with the least amount of resources, time, and investment. Identify your best interactions with the users and gather a list of top-priority features that would be able to provide just enough value. The question you must answer before you move on to the next step is ‘What is the single thing that your product absolutely must do to fulfill its promises?’  For instance, if your goal is to create a trustworthy and efficient communication platform, you might say that your product must deliver seamless and secure communication between users without compromising privacy or data integrity. 5. What Is Your Viable Product? Gather your team’s and users’ feedback – it’s time to generate ideas! It might take a couple of brainstorming sessions, but your end goal is to ensure you have captured a few high-potential thoughts. Here are several questions you might want to answer at this stage: Do you have the necessary skills, expertise, time, resources, and funding? Do you have sufficient knowledge and resources to deliver value solely to early adopters? Have you conducted thorough user research and identified potential early adopters? Do you have mechanisms in place to gather user feedback and collect data on user interactions and contexts? Can you handle product scalability? Can your MVP cope with the potential surge in user activity? Once you have collected all the necessary data, it is time to review and combine your ideas in order to define your MVP draft, which should show the way your product solves the problems you indicated during the first few stages of research and with what features this result is reached. 6. Define Your MVP Put together the results of the above steps and define your minimum viable product. Keep in mind that defining your MVP means that you already have your product vision on a much larger scale. Do not make the mistake of many beginner product managers who do not have a sufficient definition of what their ‘full product’ should be. One way you can define your minimum viable product is by scanning the backlog of your ‘full product’ and highlighting the best features, which are expected to help make the product user happy, satisfied, and keep the user engaged. You can divide these features into sets and highlight the exact function this or that set plays in the product vision. Now that you have your feature sets defined, find the subset that can provide the minimum viability. Carefully analyze each case of user stories – a description of a software system written from the perspective of an end-user or system user – in terms of cost, value, importance, and so on. Rank your user stories from top to least priority. Your team must make their business judgment call and apply their product sense to see where the thin line between top and least priority cases is. Your top priority user story might be the exact MVP you’ve been searching for. There is another important point to make here: until you have at least a couple of paying customers, it is never a good idea to pour money into developing your own unique software. Remember that the market is already full of existing tools you can use to define your MVP, like using a third-party API. 7. Innovate Your MVP Obviously, your work does not stop here. It could take a few tries to define the right MVP, but it is worth the time and the effort. Your MVP must reflect what you build, why you build, for whom you build, and when you build. You have to continue your business journey with systematic feedback, new integrations, innovative features, and so on – while your MVP becomes the base, or the vessel, for your experiments. Conclusion Let’s summarize all the ideas pinpointed in the article so that you can start working on your MVP right away. Define the problem you want to solve. Decide whether it is worth solving and if there are existing products on the market that can already solve this exact problem successfully. Step 1. Analyze your users by applying different tactics like surveys, focus groups, interviews, etc. Step 2. Define what your full product should look like. Collect feedback from your team and first adopters. Step 3. Create a list of top-priority features that your product must have in order to carry out its basic functionalities. Step 4. Generate, combine, and sort ideas on the viability of your product – how it works, what its features are, and how you are planning to scale the product in the future. Create an MVP draft. Step 5. Define an MVP by finding your best user stories. Use existing tools to create an MVP before you start pouring investments into developing your own in-house software. Step 6. Continue to generate feedback, and innovate your MVP. Step 7.

Step-by-Step Guide on How to Define Your Startup MVP and Save Time and Money

আপনার স্টার্টআপ এমভিপি কীভাবে সংজ্ঞায়িত করবেন এবং সময় এবং অর্থ সাশ্রয় করবেন সে সম্পর্কে ধাপে ধাপে নির্দেশিকা

Schritt-für-Schritt-Anleitung zum Definieren Ihres Startup-MVP und zum Sparen von Zeit und Geld

Guía paso a paso sobre cómo definir el MVP de su startup y ahorrar tiempo y dinero

Guide étape par étape sur la façon de définir votre MVP de démarrage et d'économiser du temps et de l'argent

अपने स्टार्टअप एमवीपी को कैसे परिभाषित करें और समय और पैसा कैसे बचाएं, इस पर चरण-दर-चरण मार्गदर्शिका

スタートアップの MVP を定義して時間とコストを節約する方法のステップバイステップガイド

스타트업 MVP를 정의하고 시간과 비용을 절약하는 방법에 대한 단계별 가이드

Guia passo a passo sobre como definir seu MVP de inicialização e economizar tempo e dinheiro

Пошаговое руководство о том, как определить MVP вашего стартапа и сэкономить время и деньги

Startup MVP'nizi Nasıl Tanımlayacağınız ve Zaman ve Paradan Tasarruf Etme Konusunda Adım Adım Kılavuz

Hướng dẫn từng bước về cách xác định MVP khởi nghiệp của bạn và tiết kiệm thời gian và tiền bạc

如何定义你的创业公司 MVP 并节省时间和金钱的分步指南

Hi! My name’s Amir. I’m a Web3 Community Manager and a podcast host. To improve the reach of my podcast, 2 months ago, I tried the Rask.ai platform, and have edited over 10 hours of footage since. In this review, I’ll go into the challenges Rask.ai can solve for you, its features, and the pros/cons of the platform. What Is Rask.ai, and Why Did I Buy It? Essentially, Rask.ai is a platform that uses AI for video/audio localization and repurposing. By repurposing, I mean auto reframing to vertical format, and auto-editing long videos to capture the most interesting moments. Rask.ai poses itself as a platform that has all the AI features for content makers in one place, a one-stop-shop of some sort. In one subscription, you get all the AI tools you would need to make your video content better. The main purpose that I had in mind when checking out Rask.ai was to increase the reach of my podcast on TikTok and YouTube. The podcast originally is in Kazakh, but to expand the potential audience and potential advertisers, I was looking for ways to target the English-speaking market as well. Price, Interface, and Functionality The platform is very flexible when it comes to pricing: you have 3 options to choose from, which vary by the price, the amount of minutes, and other available features. Honestly, I think the only metric you should really look at is the amount of minutes, as it will influence your work the most. I’ve picked the second plan, Creator Pro. It includes 100 minutes of edited footage per month and costs me $120. They also offer a plan for $50 and 25 minutes, as well as a corporate plan - $600 and 500 minutes. The biggest plan the platform offers is enterprise, which starts at 2000 minutes with a custom price. Note that all prices are correct if you pay annually - plans with monthly payments will be ~15% more expensive. Last month, I had 2 podcasts instead of one, and I ran out of minutes on my regular plan. However, you can always buy additional minutes at a $3 rate. Setting up the account is very easy (as it should be in 2024): you can use your Google account to log in or create the account with your email. The interface is very clean and isn’t overloaded by different buttons and links. You have FAQ and customer support at the top right corner, accessible from any page, so if you get a bit confused, there’s always that. I can’t say that I’m a tech guru of any kind, but I got used to the website in a matter of minutes. I’ve never worked with a mobile version of the site as I always store all raw footage on my Mac, but if you’re editing a small TikTok/Reels, you can easily do it from your phone. What Does Rask.ai Do, and How Do I Use It? The platform has 2 main features: localization and shorts. Let’s start with the first one, which became a selling point for me. You download a video from your device or paste a link from YouTube or Google Drive, choose the number of speakers, original language, and the language you want to translate the video to, and click “translate.” After that, the magic begins. In a matter of minutes (depending on the length of the video), you get the same video but translated to a different language. The voice-over keeps the voice’s depth, tone, and emotion, and even creates a lip sync, so the video footage is similar to the audio. How do I use that feature? Before discovering Rask.ai, in order to reach the English-speaking market, I was adding EN subtitles to all my podcasts. However, that approach was far from ideal as I was always encountering many barriers: Time-consumption. The current speech-to-text AI solutions are very far from perfect. On 100 AI-generated subtitles, I was getting ~30 errors that I needed to edit manually. Scale that to hours of footage and thousands of text, and you get yourself many hours of manual work.


Accessibility. Subtitles can’t be a permanent solution to expand your foreign audience, especially when it comes to podcasts. When was the last time you paid attention to video footage on a podcast? People listen to them while exercising, cooking, cleaning, and working. My podcast gets 40% more listeners on Spotify and Google Podcasts (which don’t have video) vs YouTube (which has video), meaning that people aren’t looking at the screen and subtitles when listening.


Retention. Even if a person bothers to actively read the subtitles, they still are getting less than people watching the original. Many intonations, jokes, or facial expressions are just not working when perceptive through text. Listeners are too busy reading to actually relax and enjoy the podcast. The Rask.ai platform solved all these problems for me. The amount of manual work I had to do had decreased to practically 0, since in 2 months of using the platform, I haven’t encountered any errors in translations. The retention improved a lot as well: YouTube has statistics that show you how many people watch your videos until the end, and this number significantly improved, since your listeners can actually LISTEN instead of reading. Another feature that I didn’t even know about when getting the subscription to Rask.ai is Shorts. Basically, it takes your hour-long footage and splits the most interesting moments into many short vertical videos. As you probably know, one of the best ways to promote your podcast in 2024 is to share these videos on TikTok, Shorts, and Reels, because these platforms have much better recommendation systems than YouTube, and putting the link to the full podcast in your bio. That’s how I personally discovered many of my favorite podcasts and began to host them myself. Before discovering that feature, I had a friend on a part-time salary doing that for me, because apart from the podcast, I also have a full-time job in Web3 that is taking a significant part of my day. Creating 15 short videos from one podcast took us about 5-6 hours of manual work since you have to fully watch the podcast, then edit all shorts separately, and add some graphics and subtitles. When I discovered a shorts feature on Rask.ai, the same amount of work took me from 5 to 10 minutes (again, depending on the length of the footage). This let me cut my editorial costs down to the sole price of my Rask.ai plan, without having to pay the salary to a whole person doing that. And you say AI won’t take our jobs :) There are a couple of smaller features that I haven’t really tested a lot until today, but I’m planning on exploring them in the future as well. For example, subtitles generation, and API for translations. The company also plans on integrating some features that I’m really excited about: AI video generation (Like MidJourney, but videos), and Zapier integration. Pros, Cons, and Who Can Use It? In conclusion, Rask.ai won’t make your video content more interesting or helpful and won’t make you a superstar overnight. However, with the right distribution strategy and exciting content, Rask.ai will significantly cut your editorial costs, saving you hundreds of dollars on people who translate and edit your content for you, as well as save you A LOT of time, letting you focus on the stuff that really matters: scripts, topics, guests, and other things that make your content better. Rask.ai is a great solution for podcast hosts like myself, social media or community managers producing content for their companies, or TikTok and Instagram influencers that focus on short video content. Pros: Clean and simple interface
Precise translations
Multiple features in one subscription Cons: Relatively high prices
Not all features are ready yet Hi! My name’s Amir. I’m a Web3 Community Manager and a podcast host. To improve the reach of my podcast, 2 months ago, I tried the Rask.ai platform, and have edited over 10 hours of footage since. In this review, I’ll go into the challenges Rask.ai can solve for you, its features, and the pros/cons of the platform. What Is Rask.ai, and Why Did I Buy It? What Is Rask.ai, and Why Did I Buy It? Essentially, Rask.ai is a platform that uses AI for video/audio localization and repurposing. By repurposing, I mean auto reframing to vertical format, and auto-editing long videos to capture the most interesting moments. Rask.ai poses itself as a platform that has all the AI features for content makers in one place, a one-stop-shop of some sort. In one subscription, you get all the AI tools you would need to make your video content better. The main purpose that I had in mind when checking out Rask.ai was to increase the reach of my podcast on TikTok and YouTube. The podcast originally is in Kazakh, but to expand the potential audience and potential advertisers, I was looking for ways to target the English-speaking market as well. Price, Interface, and Functionality Price, Interface, and Functionality The platform is very flexible when it comes to pricing: you have 3 options to choose from, which vary by the price, the amount of minutes, and other available features. Honestly, I think the only metric you should really look at is the amount of minutes, as it will influence your work the most. I’ve picked the second plan, Creator Pro. It includes 100 minutes of edited footage per month and costs me $120. They also offer a plan for $50 and 25 minutes, as well as a corporate plan - $600 and 500 minutes. The biggest plan the platform offers is enterprise, which starts at 2000 minutes with a custom price. Note that all prices are correct if you pay annually - plans with monthly payments will be ~15% more expensive. Last month, I had 2 podcasts instead of one, and I ran out of minutes on my regular plan. However, you can always buy additional minutes at a $3 rate. Setting up the account is very easy (as it should be in 2024): you can use your Google account to log in or create the account with your email. The interface is very clean and isn’t overloaded by different buttons and links. You have FAQ and customer support at the top right corner, accessible from any page, so if you get a bit confused, there’s always that. I can’t say that I’m a tech guru of any kind, but I got used to the website in a matter of minutes. I’ve never worked with a mobile version of the site as I always store all raw footage on my Mac, but if you’re editing a small TikTok/Reels, you can easily do it from your phone. What Does Rask.ai Do, and How Do I Use It? What Does Rask.ai Do, and How Do I Use It? The platform has 2 main features: localization and shorts. Let’s start with the first one, which became a selling point for me. You download a video from your device or paste a link from YouTube or Google Drive, choose the number of speakers, original language, and the language you want to translate the video to, and click “translate.” After that, the magic begins. In a matter of minutes (depending on the length of the video), you get the same video but translated to a different language. The voice-over keeps the voice’s depth, tone, and emotion, and even creates a lip sync, so the video footage is similar to the audio. How do I use that feature? Before discovering Rask.ai, in order to reach the English-speaking market, I was adding EN subtitles to all my podcasts. However, that approach was far from ideal as I was always encountering many barriers: Time-consumption. The current speech-to-text AI solutions are very far from perfect. On 100 AI-generated subtitles, I was getting ~30 errors that I needed to edit manually. Scale that to hours of footage and thousands of text, and you get yourself many hours of manual work. Accessibility. Subtitles can’t be a permanent solution to expand your foreign audience, especially when it comes to podcasts. When was the last time you paid attention to video footage on a podcast? People listen to them while exercising, cooking, cleaning, and working. My podcast gets 40% more listeners on Spotify and Google Podcasts (which don’t have video) vs YouTube (which has video), meaning that people aren’t looking at the screen and subtitles when listening. Retention. Even if a person bothers to actively read the subtitles, they still are getting less than people watching the original. Many intonations, jokes, or facial expressions are just not working when perceptive through text. Listeners are too busy reading to actually relax and enjoy the podcast. Time-consumption. The current speech-to-text AI solutions are very far from perfect. On 100 AI-generated subtitles, I was getting ~30 errors that I needed to edit manually. Scale that to hours of footage and thousands of text, and you get yourself many hours of manual work. Time-consumption. The current speech-to-text AI solutions are very far from perfect. On 100 AI-generated subtitles, I was getting ~30 errors that I needed to edit manually. Scale that to hours of footage and thousands of text, and you get yourself many hours of manual work. Accessibility. Subtitles can’t be a permanent solution to expand your foreign audience, especially when it comes to podcasts. When was the last time you paid attention to video footage on a podcast? People listen to them while exercising, cooking, cleaning, and working. My podcast gets 40% more listeners on Spotify and Google Podcasts (which don’t have video) vs YouTube (which has video), meaning that people aren’t looking at the screen and subtitles when listening. Accessibility. Subtitles can’t be a permanent solution to expand your foreign audience, especially when it comes to podcasts. When was the last time you paid attention to video footage on a podcast? People listen to them while exercising, cooking, cleaning, and working. My podcast gets 40% more listeners on Spotify and Google Podcasts (which don’t have video) vs YouTube (which has video), meaning that people aren’t looking at the screen and subtitles when listening. Retention. Even if a person bothers to actively read the subtitles, they still are getting less than people watching the original. Many intonations, jokes, or facial expressions are just not working when perceptive through text. Listeners are too busy reading to actually relax and enjoy the podcast. Retention. Even if a person bothers to actively read the subtitles, they still are getting less than people watching the original. Many intonations, jokes, or facial expressions are just not working when perceptive through text. Listeners are too busy reading to actually relax and enjoy the podcast. The Rask.ai platform solved all these problems for me. The amount of manual work I had to do had decreased to practically 0, since in 2 months of using the platform, I haven’t encountered any errors in translations. The retention improved a lot as well: YouTube has statistics that show you how many people watch your videos until the end, and this number significantly improved, since your listeners can actually LISTEN instead of reading. Another feature that I didn’t even know about when getting the subscription to Rask.ai is Shorts. Basically, it takes your hour-long footage and splits the most interesting moments into many short vertical videos. As you probably know, one of the best ways to promote your podcast in 2024 is to share these videos on TikTok, Shorts, and Reels, because these platforms have much better recommendation systems than YouTube, and putting the link to the full podcast in your bio. That’s how I personally discovered many of my favorite podcasts and began to host them myself. Before discovering that feature, I had a friend on a part-time salary doing that for me, because apart from the podcast, I also have a full-time job in Web3 that is taking a significant part of my day. Creating 15 short videos from one podcast took us about 5-6 hours of manual work since you have to fully watch the podcast, then edit all shorts separately, and add some graphics and subtitles. When I discovered a shorts feature on Rask.ai, the same amount of work took me from 5 to 10 minutes (again, depending on the length of the footage). This let me cut my editorial costs down to the sole price of my Rask.ai plan, without having to pay the salary to a whole person doing that. And you say AI won’t take our jobs :) There are a couple of smaller features that I haven’t really tested a lot until today, but I’m planning on exploring them in the future as well. For example, subtitles generation, and API for translations. The company also plans on integrating some features that I’m really excited about: AI video generation (Like MidJourney, but videos), and Zapier integration. Pros, Cons, and Who Can Use It? Pros, Cons, and Who Can Use It? In conclusion, Rask.ai won’t make your video content more interesting or helpful and won’t make you a superstar overnight. However, with the right distribution strategy and exciting content, Rask.ai will significantly cut your editorial costs, saving you hundreds of dollars on people who translate and edit your content for you, as well as save you A LOT of time, letting you focus on the stuff that really matters: scripts, topics, guests, and other things that make your content better. Rask.ai is a great solution for podcast hosts like myself, social media or community managers producing content for their companies, or TikTok and Instagram influencers that focus on short video content. Pros: Pros: Clean and simple interface Precise translations Multiple features in one subscription Clean and simple interface Precise translations Multiple features in one subscription Cons: Cons: Relatively high prices Not all features are ready yet Relatively high prices Not all features are ready yet

How to Localize Your Shorts in 3 Clicks

Organizations are rapidly embracing cloud-native architectures in the rapidly evolving landscape of modern software development, where Kubernetes has solidified its position as the standard orchestration tool for containerized applications. As applications become increasingly distributed and complex, the demand for a robust, scalable, and efficient deployment strategy has never been more pressing. It must be capable of seamlessly scaling and managing these intricate systems. GitOps emerges as a game-changing methodology poised to revolutionize the continuous deployment of cloud-native applications. Let us delve into why GitOps is heralded as a revolutionary approach. Before the rise of GitOps, the deployments over Kubernetes clusters and Cloud were based on traditional CI/CD pipelines. The traditional deployments were executed by writing deployment scripts manually. There were some issues with the traditional CI/CD, such as the inconsistency in configuration. The manual process added the drift between the actual state and the desired state of the application. These manual configurations were prone to errors, causing security vulnerabilities. Changes made to the infrastructure of cloud-native applications were hard to track. The rollbacks were challenging. There was a need for a deployment strategy that would eradicate all these challenges. GitOps is a way to implement continuous deployment pipelines for cloud-native applications. It follows the Git approach for deployments of cloud-native applications where the Git repository is a single source of truth. GitOps follows four principles: Declarative: In GitOps, declarative means the desired state of your infrastructure. The focus is more on what, not how; we need to declare the desired state of our infrastructure in the Git repository.


Versioned: As GitOps follows the way of Git, like maintaining the Git repositories for infrastructure. It’s easy to version this Git repository, and it provides the power to rollback and disaster recovery.


Pulled Automation: By using GitOps, forget pushing changes and hope for the best. GitOps works on a pull-based mechanism where every change made to the Git repository is updated to your Kubernetes cluster.


Continuous Reconciliation: GitOps maintains the state of your Git repository and Kubernetes cluster/cloud-native environment in sync by pulling every change made in the Git repository. With the adoption of GitOps, we can maintain our infrastructure as code better and have fewer configuration errors. It will be maintained in the Git repository, which can be reviewed by seniors, too, before getting merged into the main branch. With GitOps, we can include security scanning tools that help in scanning for security vulnerabilities. In GitOps, the Git repository is considered to be the single source of truth. This solves the issue of inconsistent maintenance of the state of the application. GitOps employs an operator in your Kubernetes cluster or cloud-native environment, which will consistently keep scanning for changes in the repository. As soon as the change is noticed, the pipeline will be triggered. New changes will be applied to your Kubernetes cluster automatically. That’s the continuous reconciliation, so there is no need for kubectl apply for every change. All changes that are made in deployments of the Kubernetes cluster stay in Git Repository. These can be easily tracked and versioned, empowering us to roll back to the previous state of deployments with ease. Also provides us the power for disaster recovery. NOTE: GitOps is not restricted to Kubernetes, but most of the GitOps tools are developed for the Kubernetes environment. Let’s understand with examples: Suppose you are a busy e-commerce company gearing up for an annual sale. You know that there will be a surge in traffic. For that, you want your application resources to dynamically auto-scale to handle the traffic without compromising the performance of the application. For that, you write some configuration files and apply them to the production environment. If these configuration files have any kind of error or misconfiguration, it will cause absolute chaos. At the same place you are using GitOps, GitOps includes a robust testing and approval process. Which will make it hard to let any error or misconfiguration get merged into the main branch. Even if it gets merged, you can easily roll back to previous versions of configurations. Now, Imagine yourselves playing and experimenting around your cluster. Making some configuration changes, ending up deleting some important resources, or having any misconfiguration. As mistakes are inevitable. GitOps will come to save your day as the operator continuously scans and maintains the state. As it will see changes that are not mentioned in the Git repository, it will quickly reconcile and bring the cluster to the same state as mentioned in the Git repository. In a situation where the developer finds a bug. After noticing the bug, changes are made to the Kubernetes cluster as a fix for the bug, and things are forgotten to update in version control. There will be no trace; neither the bug nor the fix will cause a loss of knowledge and traceability. With GitOps, this can be avoided. GitOps uses the Git repository as a single source of truth. To fix the bug, the developer will make changes in the Git repository, which keeps track of every change and deployment done on the Kubernetes cluster. Beyond this, GitOps offers fast deployments, as you just need to develop and push your code to the Git repository. Further execution of the deployment will be fully automated and handled by GitOps. With each deployment, GitOps follows the self-documenting method so that you can easily track all the changes that are applied to your cluster by just looking at the Git repository. In the continuously changing cloud-native landscape, GitOps stands as a transforming concept. Revolutionizing the traditional concept of continuous deployment and accurately detecting and solving pain points in traditional deployments. The four principles of GitOps bridge the gap between infrastructure and code. With the use of GitOps, you unlock the benefits of reduced errors, simplified disaster recovery, dynamic scaling, improved security, and self-documenting. GitOps is a whole paradigm shift, so let’s start our journey in the world of GitOps. In upcoming blogs, we will explore the tools for setting up GitOps and discuss which suits us best. Thank you for reading😊 Leaving some resources for you https://youtu.be/eqiqQN1CCmM?list=PLdpzxOOAlwvKu7OZpgj1-MzJFqZ8RBp6f https://youtu.be/GlG6Xr2HH1g https://youtu.be/MeU5_k9ssrs Also published here. Organizations are rapidly embracing cloud-native architectures in the rapidly evolving landscape of modern software development, where Kubernetes has solidified its position as the standard orchestration tool for containerized applications. As applications become increasingly distributed and complex, the demand for a robust, scalable, and efficient deployment strategy has never been more pressing. It must be capable of seamlessly scaling and managing these intricate systems. GitOps emerges as a game-changing methodology poised to revolutionize the continuous deployment of cloud-native applications. Let us delve into why GitOps is heralded as a revolutionary approach. Before the rise of GitOps, the deployments over Kubernetes clusters and Cloud were based on traditional CI/CD pipelines. The traditional deployments were executed by writing deployment scripts manually. There were some issues with the traditional CI/CD, such as the inconsistency in configuration. The manual process added the drift between the actual state and the desired state of the application. These manual configurations were prone to errors, causing security vulnerabilities. Changes made to the infrastructure of cloud-native applications were hard to track. The rollbacks were challenging. There was a need for a deployment strategy that would eradicate all these challenges. GitOps is a way to implement continuous deployment pipelines for cloud-native applications. It follows the Git approach for deployments of cloud-native applications where the Git repository is a single source of truth. GitOps follows four principles: Declarative: In GitOps, declarative means the desired state of your infrastructure. The focus is more on what, not how; we need to declare the desired state of our infrastructure in the Git repository. Versioned: As GitOps follows the way of Git, like maintaining the Git repositories for infrastructure. It’s easy to version this Git repository, and it provides the power to rollback and disaster recovery. Pulled Automation: By using GitOps, forget pushing changes and hope for the best. GitOps works on a pull-based mechanism where every change made to the Git repository is updated to your Kubernetes cluster. Continuous Reconciliation: GitOps maintains the state of your Git repository and Kubernetes cluster/cloud-native environment in sync by pulling every change made in the Git repository. Declarative: In GitOps, declarative means the desired state of your infrastructure. The focus is more on what, not how; we need to declare the desired state of our infrastructure in the Git repository. Declarative : In GitOps, declarative means the desired state of your infrastructure. The focus is more on what, not how; we need to declare the desired state of our infrastructure in the Git repository. Declarative Versioned: As GitOps follows the way of Git, like maintaining the Git repositories for infrastructure. It’s easy to version this Git repository, and it provides the power to rollback and disaster recovery. Versioned : As GitOps follows the way of Git, like maintaining the Git repositories for infrastructure. It’s easy to version this Git repository, and it provides the power to rollback and disaster recovery. Versioned Pulled Automation: By using GitOps, forget pushing changes and hope for the best. GitOps works on a pull-based mechanism where every change made to the Git repository is updated to your Kubernetes cluster. Pulled Automation : By using GitOps, forget pushing changes and hope for the best. GitOps works on a pull-based mechanism where every change made to the Git repository is updated to your Kubernetes cluster. Pulled Automation Continuous Reconciliation: GitOps maintains the state of your Git repository and Kubernetes cluster/cloud-native environment in sync by pulling every change made in the Git repository. Continuous Reconciliation : GitOps maintains the state of your Git repository and Kubernetes cluster/cloud-native environment in sync by pulling every change made in the Git repository. Continuous Reconciliation With the adoption of GitOps, we can maintain our infrastructure as code better and have fewer configuration errors. It will be maintained in the Git repository, which can be reviewed by seniors, too, before getting merged into the main branch. With GitOps, we can include security scanning tools that help in scanning for security vulnerabilities. In GitOps, the Git repository is considered to be the single source of truth. This solves the issue of inconsistent maintenance of the state of the application. GitOps employs an operator in your Kubernetes cluster or cloud-native environment, which will consistently keep scanning for changes in the repository. As soon as the change is noticed, the pipeline will be triggered. New changes will be applied to your Kubernetes cluster automatically. That’s the continuous reconciliation, so there is no need for kubectl apply for every change. kubectl apply All changes that are made in deployments of the Kubernetes cluster stay in Git Repository. These can be easily tracked and versioned, empowering us to roll back to the previous state of deployments with ease. Also provides us the power for disaster recovery. NOTE : GitOps is not restricted to Kubernetes, but most of the GitOps tools are developed for the Kubernetes environment. NOTE NOTE Let’s understand with examples: Suppose you are a busy e-commerce company gearing up for an annual sale. You know that there will be a surge in traffic. For that, you want your application resources to dynamically auto-scale to handle the traffic without compromising the performance of the application. For that, you write some configuration files and apply them to the production environment. If these configuration files have any kind of error or misconfiguration, it will cause absolute chaos. At the same place you are using GitOps, GitOps includes a robust testing and approval process. Which will make it hard to let any error or misconfiguration get merged into the main branch. Even if it gets merged, you can easily roll back to previous versions of configurations. Now, Imagine yourselves playing and experimenting around your cluster. Making some configuration changes, ending up deleting some important resources, or having any misconfiguration. As mistakes are inevitable. GitOps will come to save your day as the operator continuously scans and maintains the state. As it will see changes that are not mentioned in the Git repository, it will quickly reconcile and bring the cluster to the same state as mentioned in the Git repository. In a situation where the developer finds a bug. After noticing the bug, changes are made to the Kubernetes cluster as a fix for the bug, and things are forgotten to update in version control. There will be no trace; neither the bug nor the fix will cause a loss of knowledge and traceability. With GitOps, this can be avoided. GitOps uses the Git repository as a single source of truth. To fix the bug, the developer will make changes in the Git repository, which keeps track of every change and deployment done on the Kubernetes cluster. Beyond this, GitOps offers fast deployments, as you just need to develop and push your code to the Git repository. Further execution of the deployment will be fully automated and handled by GitOps. With each deployment, GitOps follows the self-documenting method so that you can easily track all the changes that are applied to your cluster by just looking at the Git repository. In the continuously changing cloud-native landscape, GitOps stands as a transforming concept. Revolutionizing the traditional concept of continuous deployment and accurately detecting and solving pain points in traditional deployments. The four principles of GitOps bridge the gap between infrastructure and code. With the use of GitOps, you unlock the benefits of reduced errors, simplified disaster recovery, dynamic scaling, improved security, and self-documenting. GitOps is a whole paradigm shift, so let’s start our journey in the world of GitOps. In upcoming blogs, we will explore the tools for setting up GitOps and discuss which suits us best. Thank you for reading😊 Leaving some resources for you https://youtu.be/eqiqQN1CCmM?list=PLdpzxOOAlwvKu7OZpgj1-MzJFqZ8RBp6f https://youtu.be/eqiqQN1CCmM?list=PLdpzxOOAlwvKu7OZpgj1-MzJFqZ8RBp6f https://youtu.be/GlG6Xr2HH1g https://youtu.be/GlG6Xr2HH1g https://youtu.be/MeU5_k9ssrs https://youtu.be/MeU5_k9ssrs Also published here. Also published here . here

GitOps For Beginners: Getting Started With Cloud-Native Architectures

SLI, SLO, and SLA: Your Terminology Guide

Do you think AI is big? Well, quantum computing will be much bigger. Quantum computing is expected to have a significant impact on several key industries like Finance, Healthcare, Cybersecurity, Logistics, AI and ML, Chemistry, Defense, Aerospace, Energy, Telecommunications, the list goes on and on. Briefly: Quantum computing uses quantum mechanics to do complex calculations that regular computers can't handle. With quantum bits (qubits) that can be in multiple states at once, these computers could change fields like cryptography, healthcare, and finance. I looked into the current state of the industry, starting with trends and diving deeper. I did research to understand what the industry looks like today. I started by looking at the trend, then wanted to find something more interesting and went down the rabbit hole. I found lots of data that could be useful for investors, entrepreneurs, and engineers who are thinking about starting something new. Here, in this report, we have industry leaders, startups, recent investments, grants, and some business ideas. Let’s Start With Some Nerdy Stats Quantum computers need to be super cold, almost at absolute zero (-273°C or -460°F). Funding for quantum tech startups jumped from $700 million in 2020 to $1.4 billion in 2021. It's predicted to hit $64.98 billion by 2030, growing 56.0% annually from 2021 to 2030. China plans to invest roughly $15 billion in quantum tech, the most worldwide. IBM aims to have a 1,000-qubit quantum computer by 2023. Google achieved quantum supremacy in 2019 using a 53-qubit processor. Quantum computers could solve problems in seconds that classical computers would take billions of years to crack. Physicist Richard Feynman first suggested quantum computing in 1982, but practical quantum computers are still in their early stages almost 40 years later. Big Tech Is Crushing It (as Always). IBM: Developed Qiskit framework and offers cloud-based quantum systems.Google- Achieved quantum supremacy in 2019 and created Cirq library.Microsoft- Developing Azure Quantum platform and Q# language.Amazon- Offers Braket, a fully managed quantum computing service.D-Wave Systems- Develops quantum annealing processors and Ocean software suite. Popular Quantum Tools Qiskit: Open-source quantum computing framework for building quantum programs. Cirq: Python library for writing, manipulating, and optimizing quantum circuits. Q#: Microsoft's open-source programming language for quantum computing. Ocean: D-Wave's suite of tools for solving optimization problems on quantum computers. Strawberry Fields: Xanadu's cross-platform Python library for simulating and executing quantum algorithms. Startups and Recent Investments: I wanted to find small players too, but it’s rare that someone will start a quantum computing business without significant funding. Here are some startups that making the noise. Quantum Source, Founded in 2021, based in Israel. Developing quantum random number generators and entropy sources.


Quantum Art - Founded in 2022, based in Israel. Develops ion trap quantum computers based on research from the Weizmann Institute of Science.


Quantum Machines, Founded in 2018, based in Israel. Develops quantum control systems for superconducting quantum computers.


Classiq, Founded in 2020, based in Israel. Provides software to model, synthesize, and analyze quantum circuits.


Multiverse Computing, Spanish quantum software company founded in 2019 Nanofiber Quantum Technologies (NanoQT) Raised $8.5 million from Phoenix Venture Partners (US), JAFCO Group, SPARX Group, Keio Innovation Initiative, and Waseda University Ventures (Japan). QphoX Received €8.0M (~$8.7M) led by QDNL Participations, alongside the EIC Fund, Quantonation, Speedinvest, High-Tech Gründerfonds, and Delft Enterprises. Rebellions Raised $124.0M in Series B funding led by KT Corp with participation from several Korean investors. Quantum Business Ideas and How to Jump In It seems challenging for small players or startups to enter the quantum computing industry with limited investments due to several factors: High infrastructure costs: Building quantum computers requires specialized hardware like cryogenic cooling systems, precision control electronics, and high-end fabrication facilities.


Talent shortage: There is a significant lack of workforce with the interdisciplinary skills (quantum physics, mathematics, computer science, engineering) needed to develop quantum technologies.


Long-time horizons: Startups need to sustain long periods of R&D without near-term revenue, which requires substantial funding.


Current market demand for quantum computing and commercial applications is still limited and speculative. This makes it risky for startups relying on near-term revenue But Still, There’s a Chance Learn fast. Apply for courses and programs, read a lot, and visit events to network with professionals.


Start a news platform with curated news, analysis, and insights on the rapidly evolving quantum computing landscape.


Build an online community for collaboration, knowledge sharing, and networking among quantum researchers, developers, and enthusiasts.


Create quantum computing education and training programs for developers and researchers.


Offer marketing, content creation (blogs, videos, infographics), and social media management services tailored to quantum technology companies and startups.


Start a niche recruitment firm that specializes in sourcing and matching quantum talent (physicists, engineers, programmers). Try to Apply for Grants I made a list of active grants for doing research in quantum computing across the US, Europe, the Middle East, and Asia. Some of these grants are: NSF Quantum Leap Challenge Institutes
European Innovation Council (EIC) funding
Technology Innovation Institute (TII) in Abu Dhabi
Singapore Quantum Engineering Programme (QEP)
UNICEF Innovation Fund More research data, with more startups, funding, and grants can be found in the report (it’s free) I hope you enjoyed it and found something useful for you. If this entangled your curiosity a little bit, feel free to share it with your friends and colleagues. Do you think AI is big? Well, quantum computing will be much bigger. Quantum computing is expected to have a significant impact on several key industries like Finance, Healthcare, Cybersecurity, Logistics, AI and ML, Chemistry, Defense, Aerospace, Energy, Telecommunications, the list goes on and on. Briefly : Briefly Quantum computing uses quantum mechanics to do complex calculations that regular computers can't handle. With quantum bits (qubits) that can be in multiple states at once, these computers could change fields like cryptography, healthcare, and finance. I looked into the current state of the industry, starting with trends and diving deeper. I did research to understand what the industry looks like today. I started by looking at the trend, then wanted to find something more interesting and went down the rabbit hole. I found lots of data that could be useful for investors, entrepreneurs, and engineers who are thinking about starting something new. Here, in this report, we have industry leaders, startups, recent investments, grants, and some business ideas. research Let’s Start With Some Nerdy Stats Quantum computers need to be super cold, almost at absolute zero (-273°C or -460°F). Quantum computers need to be super cold, almost at absolute zero (-273°C or -460°F). zero Funding for quantum tech startups jumped from $700 million in 2020 to $1.4 billion in 2021. It's predicted to hit $64.98 billion by 2030, growing 56.0% annually from 2021 to 2030. Funding for quantum tech startups jumped from $700 million in 2020 to $1.4 billion in 2021. It's predicted to hit $64.98 billion by 2030, growing 56.0% annually from 2021 to 2030 . 2030 China plans to invest roughly $15 billion in quantum tech, the most worldwide. China plans to invest roughly $15 billion in quantum tech, the most worldwide . worldwide IBM aims to have a 1,000-qubit quantum computer by 2023. IBM aims to have a 1,000-qubit quantum computer by 2023 . 2023 Google achieved quantum supremacy in 2019 using a 53-qubit processor. Google achieved quantum supremacy in 2019 using a 53-qubit processor . processor Quantum computers could solve problems in seconds that classical computers would take billions of years to crack. Quantum computers could solve problems in seconds that classical computers would take billions of years to crack . crack Physicist Richard Feynman first suggested quantum computing in 1982, but practical quantum computers are still in their early stages almost 40 years later. Physicist Richard Feynman first suggested quantum computing in 1982, but practical quantum computers are still in their early stages almost 40 years later . later Big Tech Is Crushing It (as Always). IBM : Developed Qiskit framework and offers cloud-based quantum systems. Google - Achieved quantum supremacy in 2019 and created Cirq library. Microsoft - Developing Azure Quantum platform and Q# language. Amazon - Offers Braket, a fully managed quantum computing service. D-Wave Systems - Develops quantum annealing processors and Ocean software suite. IBM Google Microsoft Amazon D-Wave Systems Popular Quantum Tools Qiskit : Open-source quantum computing framework for building quantum programs. Qiskit Cirq : Python library for writing, manipulating, and optimizing quantum circuits. Cirq Q# : Microsoft's open-source programming language for quantum computing. Q# Ocean : D-Wave's suite of tools for solving optimization problems on quantum computers. Ocean Strawberry Fields : Xanadu's cross-platform Python library for simulating and executing quantum algorithms. Strawberry Fields Startups and Recent Investments: I wanted to find small players too, but it’s rare that someone will start a quantum computing business without significant funding. Here are some startups that making the noise. Quantum Source, Founded in 2021, based in Israel. Developing quantum random number generators and entropy sources. Quantum Art - Founded in 2022, based in Israel. Develops ion trap quantum computers based on research from the Weizmann Institute of Science. Quantum Machines, Founded in 2018, based in Israel. Develops quantum control systems for superconducting quantum computers. Classiq, Founded in 2020, based in Israel. Provides software to model, synthesize, and analyze quantum circuits. Multiverse Computing, Spanish quantum software company founded in 2019 Quantum Source, Founded in 2021, based in Israel. Developing quantum random number generators and entropy sources. Quantum Source , Founded in 2021, based in Israel. Developing quantum random number generators and entropy sources. Quantum Source Quantum Source Quantum Art - Founded in 2022, based in Israel. Develops ion trap quantum computers based on research from the Weizmann Institute of Science. Quantum Art - Founded in 2022, based in Israel. Develops ion trap quantum computers based on research from the Weizmann Institute of Science. Quantum Art Quantum Art Quantum Machines, Founded in 2018, based in Israel. Develops quantum control systems for superconducting quantum computers. Quantum Machines , Founded in 2018, based in Israel. Develops quantum control systems for superconducting quantum computers. Quantum Machines Quantum Machines Classiq, Founded in 2020, based in Israel. Provides software to model, synthesize, and analyze quantum circuits. Classiq , Founded in 2020, based in Israel. Provides software to model, synthesize, and analyze quantum circuits. Classiq Classiq Multiverse Computing, Spanish quantum software company founded in 2019 Multiverse Computing, Spanish quantum software company founded in 2019 Multiverse Computing, Multiverse Computing, Nanofiber Quantum Technologies (NanoQT) Raised $8.5 million from Phoenix Venture Partners (US), JAFCO Group, SPARX Group, Keio Innovation Initiative, and Waseda University Ventures (Japan). Nanofiber Quantum Technologies (NanoQT) Raised $8.5 million from Phoenix Venture Partners (US), JAFCO Group, SPARX Group, Keio Innovation Initiative, and Waseda University Ventures (Japan). Nanofiber Nanofiber QphoX Received €8.0M (~$8.7M) led by QDNL Participations, alongside the EIC Fund, Quantonation, Speedinvest, High-Tech Gründerfonds, and Delft Enterprises. QphoX Received €8.0M (~$8.7M) led by QDNL Participations, alongside the EIC Fund, Quantonation, Speedinvest, High-Tech Gründerfonds, and Delft Enterprises. QphoX QphoX Rebellions Raised $124.0M in Series B funding led by KT Corp with participation from several Korean investors. Rebellions Raised $124.0M in Series B funding led by KT Corp with participation from several Korean investors. Rebellions Rebellions Quantum Business Ideas and How to Jump In It seems challenging for small players or startups to enter the quantum computing industry with limited investments due to several factors: High infrastructure costs: Building quantum computers requires specialized hardware like cryogenic cooling systems, precision control electronics, and high-end fabrication facilities. Talent shortage: There is a significant lack of workforce with the interdisciplinary skills (quantum physics, mathematics, computer science, engineering) needed to develop quantum technologies. Long-time horizons: Startups need to sustain long periods of R&D without near-term revenue, which requires substantial funding. Current market demand for quantum computing and commercial applications is still limited and speculative. This makes it risky for startups relying on near-term revenue High infrastructure costs: Building quantum computers requires specialized hardware like cryogenic cooling systems, precision control electronics, and high-end fabrication facilities. High infrastructure costs: Building quantum computers requires specialized hardware like cryogenic cooling systems, precision control electronics, and high-end fabrication facilities. Talent shortage: There is a significant lack of workforce with the interdisciplinary skills (quantum physics, mathematics, computer science, engineering) needed to develop quantum technologies. Talent shortage: There is a significant lack of workforce with the interdisciplinary skills (quantum physics, mathematics, computer science, engineering) needed to develop quantum technologies. Long-time horizons: Startups need to sustain long periods of R&D without near-term revenue, which requires substantial funding. Long-time horizons: Startups need to sustain long periods of R&D without near-term revenue, which requires substantial funding. Current market demand for quantum computing and commercial applications is still limited and speculative. This makes it risky for startups relying on near-term revenue Current market demand for quantum computing and commercial applications is still limited and speculative. This makes it risky for startups relying on near-term revenue But Still, There’s a Chance Learn fast. Apply for courses and programs, read a lot, and visit events to network with professionals. Start a news platform with curated news, analysis, and insights on the rapidly evolving quantum computing landscape. Build an online community for collaboration, knowledge sharing, and networking among quantum researchers, developers, and enthusiasts. Create quantum computing education and training programs for developers and researchers. Offer marketing, content creation (blogs, videos, infographics), and social media management services tailored to quantum technology companies and startups. Start a niche recruitment firm that specializes in sourcing and matching quantum talent (physicists, engineers, programmers). Learn fast. Apply for courses and programs, read a lot, and visit events to network with professionals. Learn fast. Apply for courses and programs, read a lot, and visit events to network with professionals. Start a news platform with curated news, analysis, and insights on the rapidly evolving quantum computing landscape. Start a news platform with curated news, analysis, and insights on the rapidly evolving quantum computing landscape. Build an online community for collaboration, knowledge sharing, and networking among quantum researchers, developers, and enthusiasts. Build an online community for collaboration, knowledge sharing, and networking among quantum researchers, developers, and enthusiasts. Create quantum computing education and training programs for developers and researchers. Create quantum computing education and training programs for developers and researchers. Offer marketing, content creation (blogs, videos, infographics), and social media management services tailored to quantum technology companies and startups. Offer marketing, content creation (blogs, videos, infographics), and social media management services tailored to quantum technology companies and startups. Start a niche recruitment firm that specializes in sourcing and matching quantum talent (physicists, engineers, programmers). Start a niche recruitment firm that specializes in sourcing and matching quantum talent (physicists, engineers, programmers). Try to Apply for Grants Try to Apply for Grants I made a list of active grants for doing research in quantum computing across the US, Europe, the Middle East, and Asia. Some of these grants are: NSF Quantum Leap Challenge Institutes European Innovation Council (EIC) funding Technology Innovation Institute (TII) in Abu Dhabi Singapore Quantum Engineering Programme (QEP) UNICEF Innovation Fund NSF Quantum Leap Challenge Institutes NSF Quantum Leap Challenge Institutes NSF Quantum Leap Challenge Institutes European Innovation Council (EIC) funding European Innovation Council (EIC) funding European Innovation Council (EIC) funding Technology Innovation Institute (TII) in Abu Dhabi Technology Innovation Institute (TII) in Abu Dhabi Technology Innovation Institute (TII) in Abu Dhabi Singapore Quantum Engineering Programme (QEP) Singapore Quantum Engineering Programme (QEP) Singapore Quantum Engineering Programme (QEP) UNICEF Innovation Fund UNICEF Innovation Fund UNICEF Innovation Fund More research data, with more startups, funding, and grants can be found in the report (it’s free) the report report I hope you enjoyed it and found something useful for you. If this entangled your curiosity a little bit, feel free to share it with your friends and colleagues.

The Analysis of The Future of Quantum Computing

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