Secure Your Network

The foundation of a secure smart home starts with a strong and well-protected network. Set up a unique and complex password for your Wi-Fi network, enable encryption (WPA2 or WPA3), and change the default username and password of your router. Regularly update your router’s firmware to ensure the latest security patches are installed.

Use Strong and Unique Passwords

Create unique, strong passwords for all your smart home devices, including cameras, smart locks, and hubs. Avoid using easily guessable information and consider using a password manager to securely store and manage your credentials.

Keep Software and Firmware Updated

Regularly update the software and firmware of your smart home devices to ensure you have the latest security patches and bug fixes. Enable automatic updates whenever possible to stay protected against emerging threats.

Implement Two-Factor Authentication (2FA)

Enable two-factor authentication whenever available. This adds an extra layer of security by requiring a second form of verification, such as a code sent to your smartphone, in addition to your password. Two-factor authentication significantly reduces the risk of unauthorized access to your smart home devices.

Secure Your Smart Home Hub

Your smart home hub acts as the central control point for your devices. Protect it by securing the physical location, regularly updating its firmware, and using a strong password. Enable any built-in security features and only download apps or integrations from trusted sources.

Secure Wireless Communication

Ensure that your smart home devices use secure communication protocols such as Wi-Fi Protected Access (WPA2 or WPA3) and Transport Layer Security (TLS). Avoid using devices that rely solely on insecure protocols like WEP (Wired Equivalent Privacy).

Create Guest Networks

If your router supports it, set up a separate guest network for visitors. This keeps your smart home devices isolated from guest devices, minimizing the risk of unauthorized access to your network.

Secure Your Smart Cameras

Protect your privacy by changing default camera passwords, disabling remote access when not needed, and regularly reviewing camera settings. Ensure that cameras are positioned to respect your privacy and avoid capturing sensitive areas of your home.

Regularly Monitor and Review Device Activity

Stay vigilant by regularly monitoring your smart home devices’ activity logs and reviewing any suspicious or unauthorized access attempts. Immediately investigate and take necessary action if you notice any unusual activity.

Educate Yourself and Family Members

Educate yourself and your family members about smart home security best practices. Teach them about the importance of strong passwords, avoiding suspicious links or downloads, and being cautious when granting permissions to third-party apps or services.

According to Futurehome, a leading provider of smart home solutions, “Building a secure smart home requires a proactive approach to protect your privacy and prevent unauthorized access. By following best practices and implementing robust security measures, homeowners can create a safe and trusted smart home ecosystem.”

Conclusion

Creating a secure smart home environment is essential to protect your privacy, data, and the integrity of your connected devices. By following these tips and best practices, homeowners can enjoy the convenience and benefits of a smart home while minimizing the risk of unauthorized access or privacy breaches. Remember, a secure smart home is a smart home that offers peace of mind and a sense of safety.

The post Creating a Secure Smart Home: Tips and Best Practices appeared first on Tech Today Info.

Knowing how to work with Excel is very important and gives you useful tools at work . That is why it is recommended that you learn the basics, including some beginner formulas that can be very helpful. And one of the most interesting operations that you should know has to do with the calculation of percentages.

Therefore, in the next few lines we will tell you how you can perform this operation in a simple way , which will not take more than a couple of seconds.

• How to calculate the percentage of an amount in Excel
• Another formula to know the percentage in Excel
  • How to convert a decimal number to a percentage

How to calculate the percentage of an amount in Excel

To begin, we will start from the situation in which you are interested in knowing the percentage of a specific quantity. This can, for example, help you find out how much the actual discount is in some shopping deals and many other scenarios. And you just have to follow the steps that we will show you below.

So you can calculate the percentage that is applied to an amount in a simple way and using Excel

• The first thing you should do is access Microsoft Excel from your computer and open a new workbook or spreadsheet.
• In one cell you must write the total amount you have and in the other you must enter the percentage that will be applied.
• Once you have the cells with their respective information, it will be time to enter the formula.
• In a third cell, you must enter the formula: =(total amount * percentage to apply) and press Enter .
• In this way, the mathematical operation will be carried out.

In our example, we have written the total amount in cell “C4”, while in cell “D4” we have entered the percentage to be applied . Following the formula that we have told you about, it would look something like this: in cell “F4” write =(C4*D4) and press Enter .

After this, the mathematical operation will be carried out, giving as a result that 25% of 470 is 117.5. This can be very useful to know how much money you could save if, for example, you see that a product that originally costs 470 euros has a 25% discount.

Another formula to know the percentage in Excel

On the other hand, it can also happen that what you need is to discover the percentage of a quantity to have a more complete perspective . In this case, the formula that is used is slightly different from the previous one, but, in the same way, it is very simple.

If, on the contrary, you want to know how much is the percentage of something, then you must resort to this formula

In the event that, for example, you have a certain number of products and you have sold some and you want to know how much the percentage of total sales is , then you can use this formula in your Excel sheet.

• The first thing you should do is access your spreadsheet in Excel.
• Then, you must position yourself in a cell and write the total amount that you originally had.
• While, in the other cell, you must write the number of products you have sold, according to our example.
• After this, in the next cell you will have to write the formula: =(number of products sold / total number of products) .
• If you press Enter , the mathematical operation will be carried out, which will give you a result.

Following the example we have mentioned, if you originally had 50 products, which you have entered in cell “C4”, and of this total you have sold 15, which you have registered in cell “D4” , you probably want to know what percentage these correspond to. sales. So, you just have to plug the amounts into the formula and you will have a result.

Thus, the formula would be =(D4/C4) , which returns 0.3 . This is a decimal number, but one that is necessary to know the percentage.

How to convert a decimal number to a percentage

Lastly, you need to change the cell format to Percentage to change the decimal number

Now that the division operation has resulted in a decimal number, you’re closer to knowing the percentage of total sales , as it only takes one last step.

You must click on the cell that contains the result of 0.3 and then click on the “%” icon found in the Home tab of Excel and in the Number section . After this, the amount will automatically become 30%.

Calculating the percentage of an amount is very simple, because you only have to know the values ​​and the formula that you will have to apply.

The post How to calculate a percentage in Excel appeared first on Tech Today Info.

Introduction

In the world of software development, DevOps has emerged as a set of practices that combine software development (Dev) and IT operations (Ops) to enhance collaboration, automation, and efficiency. It emphasizes continuous integration, continuous delivery, and constant feedback loops to enable faster and more reliable software development processes.

Data science has become an integral part of modern businesses, driving insights and decision-making across various industries. With the increasing availability of data and advancements in machine learning and artificial intelligence, organizations are leveraging data science to gain a competitive edge, improve customer experiences, optimize operations, and make data-driven decisions.

As data science gains prominence, there is a need to apply DevOps principles to data science workflows. DevOps for data science aims to bridge the gap between data scientists, software engineers, and operations teams to enable faster and more reliable model development, deployment, and iteration.

Understanding Data Science in DevOps

Data science plays a crucial role in software development and operations. Data scientists work on developing and refining models that can extract valuable insights from data. These models are integrated into software applications or systems to automate processes, provide recommendations, or make predictions.

Traditional software development workflows often do not cater to the unique requirements of data science projects. Data scientists face challenges in version control, collaboration, reproducibility, and deployment, leading to slower development cycles, potential bottlenecks, and difficulties in scaling models to production environments.

By adopting DevOps principles, data science projects can benefit from improved collaboration, increased automation, enhanced reproducibility, and faster deployment cycles. DevOps brings together the expertise of data scientists, software engineers, and operations teams, enabling them to work in harmony and deliver high-quality models and applications.

Implementing DevOps in Data Science Projects

Data science teams can leverage existing DevOps tools and practices and tailor them to their specific needs. Version control systems, such as Git, can be used to manage code, data, and model versions. Continuous integration and delivery pipelines can be designed to automate the testing, training, and deployment of models.

Successful implementation of DevOps for data science requires fostering a culture of collaboration and shared responsibility. Data scientists, software engineers, and operations teams need to work together, communicate effectively, and share knowledge and best practices throughout the project lifecycle.

Implementing version control for data and models ensures traceability and reproducibility. Data and model artifacts can be stored in versioned repositories, enabling teams to track changes, revert to previous versions, and collaborate seamlessly.

Data pipelines should be designed to handle the collection, preprocessing, and transformation of data. Automation can be applied to streamline these processes, reducing manual effort and minimizing the risk of errors. Similarly, model training processes can be automated, allowing for quicker experimentation and iteration.

Testing, validation, and quality assurance are essential components of DevOps for data science. Testing frameworks and practices should be integrated into the workflow to ensure the reliability and accuracy of models. Data validation techniques, such as cross-validation, can be employed to assess the performance and generalizability of models.

DevOps practices enable smooth and reliable deployment of models into production environments. Continuous monitoring and performance optimization ensure that models deliver accurate results and meet business requirements. Monitoring systems can provide insights into model performance, identify anomalies, and trigger alerts for necessary actions.

Benefits and Challenges of DevOps for Data Science

DevOps for data science encourages collaboration and communication between data scientists, software engineers, and operations teams. This leads to better alignment of goals, improved knowledge sharing, and more effective problem-solving.

Applying DevOps principles accelerates the development and deployment cycles of data science projects. Automation and streamlined workflows reduce manual effort, enabling data scientists to focus on experimentation, iteration, and delivering value faster.

DevOps practices ensure reproducibility and traceability, enabling teams to understand and reproduce results. Version control and artifact management systems provide a clear history of changes, facilitating collaboration and ensuring the integrity of data and models.

DevOps for data science promotes continuous monitoring and performance optimization in production environments. Teams can proactively monitor model performance, identify and address issues promptly, and optimize models to maintain their effectiveness over time.

Implementing DevOps in data science projects requires overcoming challenges such as the complexity of data workflows, managing large datasets, ensuring data privacy and security, and integrating different tools and technologies. Organizations should carefully plan and tailor their DevOps practices to address these specific challenges.

Conclusion

DevOps principles offer significant benefits to data science projects, including improved collaboration, faster development cycles, enhanced reproducibility, and better performance optimization. By integrating DevOps practices into their workflows, data science teams can achieve greater efficiency, reliability, and success in delivering valuable insights and models.

As the field of data science continues to evolve and gain prominence, the application of DevOps principles will become increasingly important. The future of DevOps in data science lies in the seamless integration of data science workflows with software development and operations, enabling organizations to leverage data-driven insights to drive innovation and achieve business goals.

The post DevOps for Data Science appeared first on Tech Today Info.

The Telegram messaging application was banned from Brazil this Friday, the 18th, after the Federal Court of Espírito Santo determined that telephone operators and app stores immediately suspend access to the app .

The platform did not deliver complete data on measures to combat neo-Nazi groups to the Federal Police .

How to communicate with relatives, friends and co-workers when the chat app is down? EXAME separated a list of the best messaging apps for cell phones and computers . Look:

Whatsapp

The best known on the list, WhatsApp is the application most used by Brazilians, being present in 99% of cell phones in the country.

It is available on the Apple Store and Google Play .

signal

The choice of Elon Musk , Jack Dorsey and Edward Snowden, Signal is a non-profit organization that does not collect any user data. With end-to-end encryption on all services offered on the platform, there is no way for the app to access your contacts, groups, messages, images or searches, unlike other apps.

It is available on the App Store and Google Play .

Jumbo

Ideal for anyone who wants to clean up their privacy options , Jumbo is the app that makes it easy to understand which of your data is being collected by giants like Facebook , Twitter , Instagram and Google — just click and it does the work for you. user.

Although many tools are offered in the paid version (the minimum is R$ 19 per month), the free version already helps the user to protect himself. First, he answers a brief questionnaire; then he indicates which apps he uses and Jumbo scans them.

In the free version, for example, you can see what Facebook collects from the user. “Your relationship status is being used for targeted advertising”, “Facebook shows you ads based on data about you that it has obtained from “partners” and other third parties” are some of the things that can appear and, with just one click, the user allows Jumbo to disable options .

messenger

From Facebook, the messaging application does not protect your data like Telegram and Signal, but it gives you the possibility to chat with Facebook friends, Instagram followers and, soon, even those you have added on Facebook’s virtual reality platform, the Oculus.

Its tools for watching movies with friends, facial recognition for unlocking the app, and custom themes for each chat are also a highlight for some users.

Install the app from the App Store or Google Play .

Hangouts

Google Hangouts is a communication platform for exchanging messages, voice calls and video calls. In it, the user can create chats with groups of up to 100 people and video calls for up to ten.

The user can access Hangouts through the website or by downloading the application through the App Store or Google Play .

skype

More traditional, Skype is an easy tool for video calls, chats or calls. It has a “Meet Now” option on its website for those who are in a hurry and need to make a free video call, without installing an app or creating an account.

For those who want to have an account, it is possible to access the tool through the website , downloading the application for the computer or in the App Store and Google Play .

DuckDuckGo

Competitor of Google, DuckDuckGo receives around 102 million daily searches on its platform. All searches made are private and responses are organic and not personalized (unlike Google, which uses user data to provide links that it thinks are most likely to be clicked).

The platform has an extension available to be added to any browser, which allows you to perform searches and see how reliable a site is with one click.

Go to the website to install the extension or do a search.

FirefoxFocus

A different option from the original Firefox, the FirefoxFocus browser has user privacy at heart. Without collecting cookies, history or location data, the browser does not store any data, much less sell it to third parties. All ads and trackers from visited websites are also automatically blocked .

Install FirefoxFocus here. It is also available as an app on the App Store and Google Play .

The post Telegram banned from Brazil: get to know Signal and 7 other messaging apps appeared first on Tech Today Info.

In this article, we’ll discuss five branding techniques that will help you boost your tech resume and find the job you so much deserve.

Why Is Branding Important for Your Tech Resume?

Personal branding is essential for your tech resume because it sets you apart from other applicants. It helps you create a unique identity that showcases your skills, knowledge, and experience.

A strong personal brand attracts recruiters and makes them interested in learning more about you.

Additionally, branding helps you establish a reputation in the industry and build a network of professional contacts. It becomes easier to network and connect with others, which can lead to new job opportunities, collaborations, and mentorship.

Building a personal brand takes time and effort, but the benefits are invaluable to position yourself as a top candidate.

1. Showcase Your Unique Value Proposition (Uvp)

Your Unique Value Proposition (UVP) is what makes you stand out from other applicants. It’s your combination of skills, knowledge, and professional background that makes you different from other professionals in your field.

Place your UVP in the summary section of your resume. This section should point out your key strengths and accomplishments, demonstrating your value to potential employers.

Research the company and the job description to understand what they’re looking for in a candidate. Then, you can customize your UVP to match their requirements and explain how you can meet their needs.

Remember to keep your UVP concise and focused, highlighting the most important skills and experiences that make you the ideal applicant for the job.

2. Leverage Your Social Media Presence

Your social media presence is a vital component of your personal brand. It’s an opportunity to demonstrate your expertise, share your insights, and engage with the tech community.

When creating your tech resume, it’s essential to add links to your professional social media profiles. This can include LinkedIn, Twitter, GitHub, and other relevant platforms.

However, it’s also important to ensure that your social media profiles are professional and aligned with your personal brand. This means avoiding controversial or inappropriate content and focusing on sharing valuable insights and information related to your industry.

You can also use social media to build your network and connect with other professionals in your field. By engaging with others in the industry, you can expand your knowledge and learn about new job opportunities.

3. Highlight Your Relevant Skills and Achievements

Your skills and achievements are critical components of your personal brand. This can include technical abilities, soft skills, certifications, academic papers, and awards.

To effectively stress your abilities and accomplishments, use specific examples and metrics wherever possible. This can help you demonstrate the impact of your work and provide evidence of your abilities.

For instance, instead of simply listing your programming languages, you can describe how you used them to develop a project or solve a problem. You can also use numbers and statistics to show the results of your work, such as increasing website traffic or improving user engagement.

4. Include Testimonials and Recommendations

Testimonials and recommendations are powerful tools to enhance your personal brand. They show proof of your credibility and expertise and provide validation of your skills and achievements.

When creating your tech resume, add testimonials and recommendations from previous employers, clients, or colleagues. By doing so, you build trust with recruiters. The feedback from others not only proves your credibility but also highlights your strengths and accomplishments.

To obtain strong testimonials, reach out to previous supervisors, colleagues, or clients and ask if they would be willing to write a brief endorsement of your work. Be sure to choose testimonials that are relevant to the tech industry and showcase the skills that you want to emphasize.

5. Customize Your Resume for Each Job Application

Customizing your resume for each job application is a critical branding strategy. It demonstrates your attention to detail and your ability to tailor your skills and career history to the job requirements.

To customize your tech resume for each job application, carefully review the job description and identify the key skills and qualifications that the employer is looking for. You can then customize your resume by emphasizing the experience and achievements that align with those requirements.

This can include adjusting your summary section, highlighting specific abilities or accomplishments, or reordering your bullet points to point out related positions.

Final Word

To stand out in the competitive tech job market, it is crucial to adopt effective branding techniques for your resume. These include emphasizing your distinctive value, utilizing your social media profile, listing pertinent skills and achievements, featuring testimonials and recommendations, and tailoring your resume for each job application.

By implementing these strategies, you can establish a strong personal brand that appeals to employers and places you as a top contender for the job.

The post 5 Branding Strategies to Boost Your Tech Resume appeared first on Tech Today Info.

Over the recent years, many celebrities have endorsed and openly promoted different cryptos and exchanges, even creating their own NFTs. However, there are also some who have always been and continue to be vocal about their skepticism toward crypto. One of them is “The O.C.” and “Gotham” actor Ben McKenzie, who also wrote a book on it entitled “Easy Money: Cryptocurrency, Casino Capitalism, and the Golden Age of Fraud.”

McKenzie also testified at the Senate Banking Committee hearing about the alleged FTX fraud, and has personally interviewed big names in the crypto industry, such as FTX Founder and CEO Sam Bankman-Fried. It is not surprising that the self-proclaimed “former teen idol” has become a known crypto critic and is invited to speak at a number of crypto and blockchain conferences.

And again, the actor and author attended Day 2 of the London Blockchain Conference 2023 held at the Queen Elizabeth II Centre last May 31 to June 2, where he was a panelist sharing his views about how regulation can “enable the growth of blockchain and digital currency.”

McKenzie was joined by Bryan Daugherty, chairman of blockchain distribution channel SmartLedger and global public policy director of Switzerland-based Bitcoin Association, and Yves Mersch, former executive board member of the European Central Bank (ECB) and former governor of the Central Bank of Luxembourg.

For McKenzie, one big thing that policymakers and regulators in his home country, the United States, need to think about when drafting crypto regulation is its classification. While the Securities and Exchange Commission (SEC) considers cryptos a security, the Commodity Futures Trading Commission (CFTC), classifies it as a commodity. The two agencies need to agree first on how to classify crypto in order to enforce more appropriate and effective regulation.

“I know about lying because I’m an actor and I do it for a living. And folks were lying. They were presenting these things as currencies even though they didn’t serve the three functions of money. They weren’t an effective medium of exchange, unit of account, or store of value,” Mckenzie said.

“Well, how do they work? You put real money into them. You expected to make money off of that investment through no work of your own. That sounded like an investment contract to me… So, by and large, I think they’re securities,” McKenzie added.

On top of being part of a panel about crypto regulation, he was also interviewed by Bitcoin historian Kurt Wuckert Jr., where he further shared his views about crypto regulation and blockchain, among other things. According to the actor, regulations are there to protect the people; and self-regulation is not something that can be relied on, especially when it comes to activities involving money.

“Self-regulation to me—I’m a father of a nine-year-old, seven-year-old and a two-year-old—that’s not a thing. The times we’ve tried self-regulation in my house, it ends up with writing on the wall and stains on my couch. There’s no such thing as self-regulation,” McKenzie shared.

“At the end of the day, I’m an American. I want the American consumer to be protected. And I think it’s crucially important that America gets this right because we are the global leader when it comes to capitalism legal frameworks,” he added.

Although McKenzie is a known crypto critic, he remains agnostic when talking about blockchain. He admits, he does not really know much about blockchain and he is waiting for the time when blockchain can prove its worth as a useful technology that can provide both privacy and transparency.

“I think blockchain being used as a ledger in which you could have both privacy but also a public database that people could reference is an alluring idea. Money is trust, we made it up, it’s this social construct. And it’s difficult to create trust if you’re not able to really have full transparency,” McKenzie pointed out.

The actor also feels that there is a fine line between using privacy to protect personal information and privacy that can be used for illicit activities. What McKenzie is alluding to here may be the anonymity that crypto crime cartels promote.

For instance, Bitcoin Cash (BCH) Founder and self-described “anarcho-capitalist” Roger Ver changed the original Bitcoin protocol to prioritize the anonymity of its transactions. This is akin to protecting criminals and providing a new avenue for their activities to be untraceable by authorities.

However, what the London Blockchain Conference is promoting is an enterprise utility blockchain that can scale unbounded to meet global data demands. What this means is that data blocks and throughput as measured in transactions per second (TPS) can be increased according to demand. At the same time as the blockchain scales, transaction fees are also reduced to the bare minimum.

So far, the BSV Blockchain is the largest public blockchain in the global market and also the only one that can scale unbounded. While BCH has a block size cap of 32MB and a throughput of about 100 TPS, BSV is already processing 4GB blocks at 50,000 to 100,000 TPS.

In fact, London Blockchain Conference host Lucy Hedges, who is also a BBC Travel Show presenter and technology journalist, announced during the first day of the event that BSV processed over 85 million transactions in 24 hours on May 26. This breaks the world record for the most number of transactions processed by a blockchain in a day. The number also accounted for 95.2% of all transactions processed on that day.

This enables the BSV Blockchain conference to be powerful enough to accommodate the transaction and data needs of both small and big enterprises. This, in turn, allows for businesses and governments to better innovate digital systems and platforms that will not only maximize profit and revolutionize processes, but also gain the trust and loyalty of consumers and citizens.

“I want to see how this develops. I am very curious to see what’s next. Because, as you say, there is an underlying technology here—blockchain conference that predates the invention of cryptocurrencies by more than a decade,” McKenzie shared.

In other words, for the actor, only time will tell if a scalable blockchain can really provide the utility it promised. If BSV Blockchain proponents and developers are to be believed, then McKenzie will not have to wait too long.

The post Gotham Actor Ben McKenzie Discusses Crypto Regulation at London Blockchain Conference appeared first on Tech Today Info.

So let’s examine how APIs may make file sharing and upload easier.

Understanding APIs for file uploads

Application Programming Interfaces operate as a link between various software programs, enabling communication and interaction between them. Developers may easily include the upload file feature into their apps using APIs. RESTful APIs, which are known for their simplicity and scalability, are important for effectively managing file uploads. 

Here are key API concepts,

• Endpoint – Represents URLs of specific resources or actions within an API.
• Request method – To perform various actions, HTTP provides multiple methods of requests. The most famous methods are POST and PUSH.
  • POST – used when uploading data to the server.
  • PUSH – used when updating or replacing existing resources.
• Headers – Include request and response details, authentication credentials, content type, cache control, file size, format, and tokens.

Common API endpoints and methods for file uploads

Endpoints for uploading files

APIs offer efficient file upload methods, including POST/files for file uploading, and PUT/files for updating existing files. These endpoints facilitate file sharing and maintenance.

Common request methods used for file uploads

Different HTTP methods are used for managing and uploading files using APIs. POST is a method for efficiently managing and storing files when uploading them to a server or FTP site. PUT replaces or alters files, resulting in updates. The DELETE method deletes files, making it important for purging unused files. These HTTP techniques let programmers build dependable and effective file-handling systems.

Common HTTP headers used for file upload

HTTP headers are essential for API calls and file uploads. The Content-Type header identifies the file type, allowing the server to handle it correctly. By specifying the file’s size in bytes, the content length enables the server to allocate resources effectively. The authorization header provides tokens or API keys for authentication and authorization, ensuring that only authorized users or programs can upload or access files. These headers provide an additional layer of protection and control, shielding private information from unwanted access.

Common issues during file uploads

Here are some common issues encountered with file uploading.

• File Size – Sometimes file uploads fail because the file size is large than the allowed limit. APIs help resolve file upload limitations by providing size information, separating files, and resolving errors.
• File Type – We need to ensure only valid file types are allowed to upload. APIs verify file types, reducing malicious uploads and compatibility concerns.
• Authentication – APIs enable authorized file uploads using authentication measures like OAuth or keys.
• Network Speed – APIs improve file upload experiences with resumable or chunked uploads.
• Error Handling – APIs offer robust error-handling mechanisms for file uploads. They provide detailed error messages and notifications, guiding users in resolving upload issues. 

Role of APIs in facilitating file uploads for sharing

Let’s look at a few key variables that must be considered while processing file upload requests and sharing.

• Handling file upload requests – In order to ensure legitimate and secure sharing, APIs evaluate user file uploads, checking files for size restrictions, file formats, and security checks. Additionally, APIs organize and maintain file metadata by extracting and storing data for file processing.

• Storage and retrieval of uploaded files- Developers must choose the optimal storage option for file upload APIs, considering scalability, usability, and data protection. Local storage offers rapid access, control, and ease of sharing, ensuring safe transfer and storage.

• Access control and security- APIs prioritize access control and security, providing authentication, authorization mechanisms, and granular control over file access, including read-only and role-based access models.

• Facilitating file sharing- When you want to share files, APIs enable secure file sharing by creating unique links, ensuring authorized access, and logging access activities for auditing, compliance, and usage insights.

• Error handling- APIs for file uploads detect and handle errors, and provide informative messages, HTTP status codes, and notifications for a smooth user experience.

Enhancing file upload APIs

Several essential strategies are involved in improving file upload APIs. To provide a smooth file upload experience that complements the application’s overall design, developers might alter the UI/UX. Implementing an eye-catching button style, clear progress indicators, and practical drag-and-drop capabilities are some examples of how to do this.

APIs should include encryption technologies that provide safe transfers and end-to-end protection to guarantee the security of file uploads. An extra layer of protection is added for sensitive data by supporting secure file transfers using protocols like HTTPS or SFTP.

File uploads can be improved by integrating third-party services by taking advantage of tools like picture recognition and text extraction. This integration gives the API more intelligence, enabling useful functions like content analysis and automated tagging, which can provide value for users.

APIs’ automated file processing functions are useful for improving submitted files. By automatically reducing file sizes while retaining visual quality, these capabilities guarantee compatibility with a wide range of systems and devices. Users can save time and effort and get the best performance by automating this procedure.

A strong file upload API requires efficient file management and categorization tools. Features like folder creation, file renaming, metadata editing, and search functionality ought to be provided using APIs. Users may conveniently organize, find, and manage their uploaded files with the help of these tools, which improve usability and productivity.

5 Must-have features of APIs for file uploads

Here are some essential features of APIs for successful file uploads.

• User-friendly file uploads – APIs should offer user-friendly file upload experiences with intuitive interfaces, clear instructions, and helpful feedback.

• Security and privacy – APIs must support secure protocols like HTTPS and SFTP for encrypted file transmission, while client-side encryption, server validation, and vulnerability protection ensure integrity and confidentiality.

• Flexible storage options – APIs should provide flexibility in storage options, including local and cloud services, to cater to diverse user requirements.

• Chunked and resumable uploads – Chunked and resumable uploads improve file transfer reliability, especially in unreliable network connections or large files. APIs should support file chunking and resuming interrupted uploads.

• Access control and file-sharing capabilities-APIs should implement access control mechanisms for effective file-sharing, including user authentication, authorization, and permission management, enabling shareable links and options.

Best practices and considerations

We have to use best practices to maintain the security and effectiveness of file uploads using APIs. Here are some best practices and performance considerations for successful file uploads.

• Implementing rate limiting and throttling – By regulating the quantity and pace of file upload requests, we can guarantee fair utilization of API resources and guard against abuse.
• Validating file formats and preventing malicious uploads – By ensuring that only secure and expected file types are accepted and preventing malicious uploads, file format validation improves the security and integrity of submitted files.
• Implementing content type validation for security – Confirms that the uploaded files are handled securely and that the file’s actual content corresponds to the specified content type.
• Optimizing Upload Speed – Methods including file compression, parallel processing, and network protocol optimization increase upload speed, which enhances user experience.
• Handling Large Files Efficiently- Using techniques like chunked transfers, streaming uploads, and scalable storage options guarantees effective handling and archiving of large files without affecting system performance.
• Minimizing Network Latency – Utilizing content delivery networks (CDNs), putting in place caching systems, and optimizing network configurations help to lower network latency, which makes file uploads quicker and more responsive.

Conclusion

For secure file uploads, storage, retrieval, access control, and file sharing, APIs are necessary. User-friendly interfaces, security precautions, adaptable storage choices, and access control should be given priority by developers. API High performance can be achieved by following best practices into effect, such as rate limitation, throttling, verifying file formats, and content type validation. By keeping informed on API technologies and best practices, which enhance functionality and performance, file sharing in apps may reach its maximum efficiency.

FAQs

Can we use APIs for uploading files in any size?

Yes, APIs can process files of any size that are being uploaded. However, we must take into account network constraints and streamline the upload procedure for extremely large files.

Are security precautions available for protecting uploaded files?

APIs provide security measures like encryption, secure protocols like HTTPS, and content screening to ensure the confidentiality and integrity of input files.

Can I modify the file upload interface to match the style of my application?

Definitely! Thanks to the adaptability of APIs, you can match the user interface and user experience of the file upload procedure with the layout and branding of your application.

Can I combine file uploads with other features like picture recognition or file processing?

Using APIs, external services may be interfaced with to enhance file uploads. You may take advantage of services like image recognition, text extraction, or automated file processing to add complex functionality to your file upload API.

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Cross-platform or platform-agnostic development allows developers to create software applications for multiple operating systems with minimal changes. This saves time and resources.

At one point in time, building a backend that works across multiple platforms was once a big challenge, but cross-platform development has come to the rescue. Some of the finest tech stacks, including React Native and Flutter, have sprung up thanks to this approach.

A cross-platform app allows developers to share some or even all of the source code across multiple platforms, including Android and iOS. This means that mobile assets only need to be coded once and will work seamlessly on all platforms without recoding for each platform.

Frameworks like Flutter and React Native enable software applications to run on multiple platforms, saving developers time and resources. Among them, Flutter is now a crowd favorite.

Why is Flutter Gaining Ground

Unlike any programming language, Flutter is an SDK similar to an Android SDK (for only Android development). Consider Flutter, a reactive programming framework that uses a single codebase to generate spectacular iOS and Android applications.

The following image explains the advantages of employing Flutter.

Disadvantages of Flutter

Flutter’s biggest limitation is its limited access to native APIs and platform-specific features. While Flutter provides a rich set of widgets and packages, accessing certain device functionalities may require writing platform-specific code, which can be time-consuming and complicate the development process of the application.

Another limitation is the larger app size of Flutter compared to native apps. Flutter apps include a runtime and framework, which adds to the overall app size. This can be a concern, especially for apps with limited storage or regions with slower internet connections.

Flutter’s performance may be affected when dealing with complex UI animations or heavy computations. While Flutter is known for its high-performance UI rendering, certain scenarios may require additional optimizations to maintain smooth animations and responsiveness, especially on lower-end devices.

Why Look for Alternatives

Flutter employs a novel programming language called Dart, which differs from most native programming languages for building applications.

Native frameworks like iOS’s Swift and Android’s Java/Kotlin are supposedly better in terms of performance, despite Flutter’s growing popularity.

Flutter has limitations regarding specific platform features or integrations compared to the native frameworks. Developers should explore alternative frameworks that provide better integration with that specific platform.

React Native

• Introduction: React Native is a popular framework that allows developers to build native mobile apps using JavaScript and the React library.
• Achievements: React Native has gained significant adoption and has been used to develop high-profile apps like Facebook, Instagram, and Airbnb.
• USP: The main selling point of React Native is its ability to write code once and deploy it on both iOS and Android platforms, resulting in time and cost savings.
• Advantages over Flutter: React Native has a larger and more mature ecosystem with a vast selection of community-contributed libraries and resources. It also enjoys a larger developer community, leading to more support and learning opportunities.

Xamarin

• Introduction: Xamarin is a cross-platform framework that allows developers to build native apps using C# and .NET, providing a shared codebase across multiple platforms.
• Achievements: Xamarin has been widely adopted and used to develop apps by companies such as Slack, GitHub, and UPS.
• USP: Xamarin’s main strength lies in its ability to leverage existing .NET libraries, making it ideal for developers with a background in C# development.
• Advantages over Flutter: Xamarin offers seamless integration with platform-specific APIs and allows access to native features, giving developers more flexibility and control over the app’s behavior and performance.

Kotlin Multiplatform

• Introduction: Kotlin Multiplatform is a cross-platform framework that enables code sharing between different platforms using Kotlin as the programming language.
• Achievements: Kotlin Multiplatform has gained traction, particularly in the Android development community, and is actively supported by JetBrains.
• USP: The key feature of Kotlin Multiplatform is the ability to share business logic and core code across platforms while still allowing platform-specific implementations for UI and other platform-specific features.
• Advantages over Flutter: Kotlin Multiplatform leverages Kotlin’s interoperability with existing Java libraries and frameworks, making it easier to integrate with existing codebases and utilize platform-specific features and APIs.

NativeScript:

• Introduction: NativeScript is an open-source framework that allows developers to build native mobile apps using JavaScript, TypeScript, or Angular.
• Achievements: NativeScript has been developed by companies such as Philips, Progress, and the NBA to develop apps.
• USP: NativeScript provides a native UI experience by rendering components using native APIs, resulting in high-performance apps with access to all platform features.
• Advantages over Flutter: NativeScript offers direct access to native APIs and UI components, allowing developers to create highly customizable and platform-specific user interfaces. It also supports popular JavaScript frameworks like Angular, making it an attractive option for developers familiar with those ecosystems.

Other Notable Cross-Platform Frameworks

1. Ionic: An open-source framework built on top of Angular and Apache Cordova, allowing developers to create cross-platform mobile apps using web technologies like HTML, CSS, and JavaScript. Ionic offers a wide range of pre-built UI components and integrates well with Angular.
2. PhoneGap/Cordova: PhoneGap (formerly known as Apache Cordova) is an open-source framework that enables building mobile apps using HTML, CSS, and JavaScript. It provides access to device features through JavaScript APIs and allows for easy deployment across multiple platforms.

Finding the Right Alternative for Your Project

When it comes to cross-platform application development, choosing the right alternative for your project is crucial for a successful outcome. The options may seem overwhelming, but one company truly stands out as the go-to choice: GeekyAnts.

GeekyAnts has extensive expertise and a deep understanding of Flutter’s capabilities, enabling the building of high-performance, visually stunning, and feature-rich mobile apps. With a skilled team of developers, including core contributors, GeekyAnts leverages Flutter’s power to create seamless user experiences across iOS and Android platforms. Visit GeekyAnts

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In fact, as long as you follow this guide and the courses we’ll refer you to, you’ll have no issues starting your new career. So keep on reading to find how to become a QA engineer and make a change in your future.

Table of Contents:

• What do I need to become a QA Engineer?
• How to search for work?
• Starting with the right course
• FAQs

What do I need to become a QA Engineer?

Do you have a computer? What about an internet connection? If you answered yes to both of these: Congratulations, you can become a QA engineer.

Something that it’s all too easy to forget is that nobody was born with expertise on any topic. And while QA testing can sound overwhelming it’s more straightforward than it seems. In fact: You can pick up the skills in just 9 weeks right here.

QA testing is easy to pick up but challenging and rewarding in the long run. So even for someone with no coding experience, learning the basics is perfectly doable. It all comes down to making the choice and sticking to the right courses.

How to search for work?

Let’s assume that you already have the skills and completed your training: Where should you begin to look for work?

There are various ways to look at this situation, but let’s go over the biggest question first: Will you need a degree? The answer thankfully is a solid no.

Degrees can of course go a long way, and nobody is ever too prepared. But QA testing is an area where practical experience matters a lot, and that means that companies will hire people as long as their portfolio backs them up.

To build a portfolio without a degree your best bet is courses and bootcamps with a practical focus. A bootcamp has one clear focus: Making sure its participants get a job. This means that they have practical lessons both for interviews and building a portfolio, and this will make a difference when applying for a job.

Starting with the right course

If you want to know how to become a QA engineer the best option is to get started on Test Pro’s QA Bootcamp.

This 9-week online bootcamp is geared towards training QA manual testers for real work regardless of their preexisting skills. There are no previous requirements needed to enroll, and thanks to its practical focus it is designed to land its enrollees a job as soon as possible.

Whether you take the course online or in person, you’ll get the required skills and certifications to begin working at QA in just 9 weeks. And with companies like Career Karma backing the bootcamp as one of the top 6 tech courses online you know it’s a good investment

So in short: Becoming a QA engineer is as simple as starting the right course today. And whether you are a complete beginner or an experienced programmer, the practical focus of the Test Pro QA bootcamp will help you build a portfolio to get hired soon.

FAQs

Can I really start without previous coding knowledge?

Yes. Test Pro’s course is fully meant for people without any tech background, so there’s nothing to worry about.

How much does a QA engineer make?

On average you can expect to find work in the $30-$50/hour range.

What’s the demand for QA engineers?

Very high. QA testing is needed in any business that uses software for its service or products, which basically means the entire industry.

The post How to Become a QA Engineer? appeared first on Tech Today Info.

Metrics determine business development. It is important for software testing companies to focus on effective indicators in order to track changes and success (or vice versa) of their actions. However, often metrics that employees consider valuable do not correspond to the business and its global goals. As the founder of VPE Forum Melanie Ziegler noted, it is impossible to get income by increasing activity: business develops thanks to results. Software testing is no exception. It affects how a business views the quality assurance function and how it evaluates the results of its work.

What are testing metrics?

Testing metrics are numerical indicators that are used when it is necessary to evaluate the progress, quality, performance and operability of the testing process.

Focusing on this data, specialists can adjust the workflow, increase the efficiency and effectiveness of testing, and make the best decisions to optimize work. For example, “gram” is a metric for measuring weight. The software also has its own “meters”: e.g. “How many errors are there per 1000 lines of code?”

Businesses need measurable results in order to see an improvement in quality and understand how this is related to an increase in the return on investment. As you know, “we can’t control what we can’t measure”. Let’s give an example with HelloFresh, where initially the key metric was the number of subscribers to a box of recipes. The QA team then tracked the impact of poor quality on the number of subscribers. The areas that were affected by this metric became a key area of testing. Thanks to the rethinking of the indicators, the company managed to change its strategy and reduce the number of critical errors in the release.

There are a lot of metrics. For example, they can describe the success of SDLC, product quality, or measure the effectiveness of the entire software testing outsourcing team. The calculation of indicators takes place according to special formulas. By the way, the percentage of completed test cases is calculated as follows: the number of completed test cases is divided by the total number of test cases written, and their quotient is multiplied by 100. It’s like comparing the weekly mileage of a car with the ideal mileage recommended by the manufacturer.

Difficulties with metrics

If there are special formulas, what could be the difficulties? A good testing strategy implies that the team uses the right performance indicators. Testing by its nature seeks to provide more information about the product in order to bring clarity and manage risks.

The problem with metrics is that they determine all further work, and choosing them incorrectly can lead to adverse consequences. For example, if a QA specialist aims to find as many errors as possible, in pursuit of numbers, he/she may neglect critical areas. That is, functions that are not very valuable for business will be tested, and indicators will improve due to this. It will turn out to be a kind of imaginary picture of software quality, because the number of errors was the only criterion by which one could judge someone’s efforts. But the numbers themselves don’t tell the whole story.

Due to the fact that measurement can affect the way of checks, it is important for specialists who provide software testing services to think carefully about metrics. The priority should be indicators that are valuable for business and the improvement of which will bring real benefits to the company. So that in the pursuit of beautiful numbers, the team members do not forget about the most important thing – quality. After all, as economist Charles Goodhart said, “When a measure becomes a target, it ceases to be a good measure”.

It is worth being guided by sound logic, why it is important to measure something. For example, if the execution of an automated test suite takes more than two hours, it is advisable to divide it into two pipelines. First of all, run the script with the most important test cases. And then all that is left (for example, regression tests).

Testing metrics that are important to pay attention to

User satisfaction

The more the customer buys, the more success is guaranteed to the business. Accordingly, the first thing the QA team during the quality assurance audit should start from is the user’s reaction to the product and error messages. If testers measure this quality indicator and strive to improve it, the business will be successful. After all, 92% of customers leave the app if they are not satisfied with its quality.

Satisfied customers are regular customers. They usually return if they liked the service or product they purchased. If quality issues arise, almost 13% of dissatisfied customers share negative experiences with more than 20 people. Which significantly affects the company’s image.

Process metrics

These indicators can have a big impact on the software product quality. For example, you can measure the time from the moment a requirement is created to the moment the code implementing this requirement is deployed in a production environment. Or the time spent on the development of the function from the moment of obtaining permission to start working on it.

Finally, you can measure the time it takes to solve problems. Another option to increase the efficiency of processes is to pay attention to where the work stops. This is a bottleneck for which it is worth finding ways to optimize.

Coverage indicators

Test coverage is a test quality indicator that tells you which part of the code or how many requirements have been tested. Here, experienced QA recommends a top-down approach: start by covering the module and functionality, then analyze the data coverage for each functionality.

According to a review of academic studies that examined the relationship between application quality and code coverage, levels from 70% to 90% assume reliable software. In addition, the test coverage metric helps eliminate ambiguity that occurs in large teams and leads to consistent testing methods.

Code quality metrics

Automatic checks using tools such as SonarQube help to assess the code quality. According to them, it is easy to track how much technical debt is in the system. The accumulated problems and vulnerabilities should be sorted by degree of importance and decide what to pay more attention to. 

To measure the code quality, you need to focus on its key features:

• Reliability (high-quality code works without failures);
• Maintainability (software should be easy to maintain);
• Testability (there are no barriers to software testing);
• Portability (with high-quality code, the program can work in various environments).

Taking into account these features, specialists engaged in software testing services determine five main indicators of code quality: maintainability index, complexity metrics, depth of inheritance, connection of classes and code lines.

Error or incident indicators

Tracking crashes and downtime due to software errors can give an idea of the application quality. This indicator determines the end user’s impression of the product.

When reporting problems, it is worth noting which of them are serious and which are suggestions for improvement. It is important for business to know which aspects of quality are more important than others. For certain business models, productivity may be paramount, for example, for online stores with peak traffic on pre-holidays or sales days.

It is worth paying attention not only to the number of errors, but also to analyze the numbers, taking into account useful categories to improve the testing process. 

Research testing metrics

Research testing involves exploring the capabilities of the program. In simple words, what can and cannot be done with the application. During research checks, the software is tested without any plans. So how to measure it?

There are two types of metrics that were proposed by Michael Bolton and James Bach to evaluate exploratory testing. According to the first one, it is necessary to record in each session the time spent on configuration and execution, and the number of defects found. According to the second metric, it is important to take notes of the time it took to get acquainted with the charter of research testing, comparing it with the time it took to observe the interesting behavior of the product.

The following indicators are also used in quality assurance services:

• research or scheduled testing hours;
• average research session time;
• separation of the research session (installation, testing, possibility, troubleshooting);
• sessions;
• number of defects per session.

Test automation metrics

Metrics help to improve the automated testing process and track its status in the company. Over time, the software product becomes more complex, because the number of lines of code increases, new functions are added, errors are corrected, and so on. As a result, the test coverage may decrease, and the cost of the product and the delivery time of the software, on the contrary, increase.

Indicators can give an overall picture of the automatic testing state. If the work is being done in the right way, the introduction of automation should correct the negative dynamics by increasing the test coverage and speeding up the delivery time.

Performance indicators

It is extremely important for enterprises to know the state of peak traffic, as well as to evaluate the performance of software both in normal mode and at times of heavy load. Knowing the maximum operating capacity of the application, it is easier to prevent its downtime and failures after release.

Load tests consider a wide range of performance-related indicators. When evaluating the efficiency of work, response time, error rate, throughput, and the presence of bottlenecks are often measured.

Indicators of “Happiness”

This metric concerns the effectiveness of the software testing outsourcing team and helps answer the questions: “Will the tasks of a specialist who goes on vacation be completed?”, “Do employees have emotional burnout?” and so on. These metrics are assigned to each team member and help to understand the employee’s workload. Based on this data, it can be reduced or vice versa, you can include additional tasks.

This is very important, because the overall mood of the team directly affects the effectiveness of its work and the product quality. These indicators are not easy to measure, but they are worth it, because the cohesion and well-being of the team help the business to work better.

Conclusion

Rapidly growing competition in the service market has led to a demand for shorter production cycles. As a result, QA specialists are forced to accelerate together with the development team in order to deliver high-quality software on time. In order to perform the work correctly and quickly, it is important to use testing metrics that can provide valuable information about the state of the product. 

However, using the right metrics is not an easy task. For example, a person cannot say that a new car is wonderful until he/she drives it. Judging only by the picture, then such an assessment can hardly be called objective. Only with a reasonable and conscious approach to evaluating important indicators, software testing outsourcing can guarantee the product quality and the business success.

It is important to understand that metrics need to be updated regularly depending on changes in the project. Over time, technologies will change, as will the specialists involved in working on the product. Regardless of what is being tested and verified, the goal remains the same – to provide high-quality software that will bring value to users.

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