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Mitigating Threats and Vulnerabilities in CI/CD Environments through Secure Coding

Mitigating Threats and Vulnerabilities in CI/CD Environments through Secure Coding

As organizations increasingly embrace Continuous Integration/Continuous Deployment (CI/CD) methodologies to accelerate software delivery, security in these environments becomes a paramount concern. 

The fast-paced nature of CI/CD pipelines can inadvertently introduce significant vulnerabilities, exposing software systems to potential cyber threats.

To mitigate these risks and safeguard critical assets, adopting secure coding practices is crucial. In this article, we delve into the best practices for fortifying CI/CD pipelines against threats and vulnerabilities, empowering development teams to build and deploy software with security at its core.

Understanding the Risks in CI/CD Environments

Common Threats and Vulnerabilities in CI/CD Pipelines

1. Code Injection Attacks

Code injection attacks, including SQL injection and Remote Code Execution (RCE), are among the prominent risks in CI/CD environments. If not appropriately addressed, malicious actors can exploit vulnerable code to tamper with data, execute unauthorized commands, or gain illicit access to critical systems.

OWASP Top 10 reports that code injection remains a concerning issue, accounting for 19% of reported vulnerabilities in web applications.

2. Insecure Dependencies and Libraries

CI/CD pipelines often rely on third-party libraries and dependencies to streamline development. However, libraries that are not up-to-date or from unverified sources might contain potential vulnerabilities that could be exploited by malicious individuals.

3. Insider Threats and Privilege Escalation

Insiders with access to the CI/CD pipeline can inadvertently or maliciously introduce vulnerabilities. Privilege escalation is a concern when users are granted excessive permissions, enabling unauthorized actions within the pipeline. According to a recent Insider Threat Report, 68% of organizations experienced insider attacks in some form, emphasizing the importance of robust access controls.

4. Configuration Issues and Secrets Exposure

Misconfigured CI/CD tools and environments may inadvertently expose sensitive information, such as passwords and API keys, to unauthorized parties. 

5. Lack of Security Testing and Monitoring

Failing to incorporate security testing and monitoring in CI/CD pipelines can result in undetected vulnerabilities and prolonged exposure to threats. A recent survey revealed that only 40% of organizations conduct security testing throughout the development lifecycle.

Secure Coding Best Practices for CI/CD Pipelines

Code Review and Static Analysis

1. Importance of Peer Code Review

Peer code review is a fundamental practice in CI/CD environments to identify and rectify potential vulnerabilities early in the development process emphasizing the importance of CI/CD security from the outset. Studies show that peer review can detect up to 60% of defects and significantly reduce the number of security issues in software.

2. Utilizing Static Code Analysis Tools

Security sit in early-stage software development can be significantly enhanced by leveraging static code analysis tools. Static code analysis tools automatically scan the source code to identify security vulnerabilities and coding errors. The use of such tools can reduce the number of security defects by up to 85%.

Implementing Proper Authentication and Authorization

1. Secure Access Control Mechanisms

Robust authentication mechanisms, such as multi-factor authentication (MFA) and strong password policies, bolster the security of CI/CD pipelines against unauthorized access attempts.

2. Role-based Access Control (RBAC) 

RBAC ensures that users have the appropriate permissions based on their roles, limiting their access to only necessary resources within the CI/CD pipeline.

3. Least Privilege Principle 

Adhering to the least privilege principle grants users the minimum level of access required to perform their tasks, reducing the potential impact of a compromised account.

For example, a CI/CD pipeline administrator is given only the necessary permissions to manage the pipeline infrastructure. This limits the scope of an attacker who gains access to the administrator’s credentials, minimizing the potential damage.

Managing Dependencies and Third-Party Libraries

1. Regularly Updating Dependencies: 

Regularly updating third-party libraries and dependencies helps to patch security vulnerabilities and ensure the use of the latest features.

2. Validating and Verifying the Integrity of External Libraries

Ensuring the authenticity and integrity of third-party libraries before integrating them into the pipeline safeguards against supply chain attacks.

3. Using Trusted Sources and Repositories

Relying only on reputable and trusted sources for third-party libraries reduces the likelihood of introducing malicious code.

Instead of downloading libraries from random websites, developers should use official repositories and package managers like npm, Maven, or PyPI, which are more secure and continuously monitored for vulnerabilities.

Secrets Management and Configuration

1. Storing Secrets Securely 

Storing sensitive information, such as API keys and passwords, in secure, encrypted storage systems prevents unauthorized access.

2. Encryption and Decryption of Sensitive Data 

Encrypting sensitive data in transit and at rest ensures that even if intercepted, the information remains unreadable to unauthorized entities.

3. Techniques to Avoid Hardcoding Credentials

Avoiding the practice of hardcoding credentials directly into the code helps prevent accidental exposure.

For example: A developer utilizes environment variables or configuration files to pass sensitive data to the application during runtime, reducing the risk of accidental leakage through version control systems.

Security Testing and Quality Assurance

1. Incorporating Security Testing in the CI/CD Pipeline

Integrating security testing tools into the pipeline enables continuous security checks throughout the development lifecycle.

For example: A CI/CD pipeline includes automated security testing, such as SAST (Static Application Security Testing) and DAST (Dynamic Application Security Testing), to detect and address vulnerabilities early in the development process.

2. Automated Vulnerability Scanning 

Automated vulnerability scanning tools help identify security weaknesses in software components, improving overall security posture.

Before each deployment, the CI/CD pipeline automatically runs a vulnerability scanner to identify any known vulnerabilities in the application’s dependencies and libraries.

3. Fuzz testing and Penetration Testing

Fuzz testing and penetration testing help identify potential weaknesses and security flaws by simulating real-world attack scenarios.

Conclusion 

Securing CI/CD pipelines through robust coding practices is not just a choice; it is imperative for modern software development. As evidenced by the prevalence of code injection attacks, insider threats, and insecure dependencies, the risks faced by organizations today are both persistent and dynamic. 

To stay ahead in the cybersecurity landscape, organizations must integrate secure coding practices at every stage of the CI/CD pipeline. By conducting peer code reviews, utilizing static code analysis, enforcing proper authentication and access controls, and managing dependencies with care, teams can significantly reduce the attack surface. 

By recognizing the vital role secure coding plays in ensuring the integrity and confidentiality of software, organizations can foster a culture of security awareness among developers. 

AI Content Detection Report

Plagiarism Report 

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Tips

Headless Raspberry Pi Setup – WiFi and SSH

raspberry pi

Setting up a new Raspberry Pi Board can be daunting without a monitor and keyboard, Once you flash a new image of the Operating System – Raspberry Pi OS or similar, the next obvious step is to boot the Pi, log in to it and access the terminal over SSH. But for a headless setup, i.e. without a Monitor and Keyboard, it’s not that straightforward. The same goes if you’re using a lite image of the OS (without a Desktop Environment). For SSH to work, you first need to get your board on your home network, even if you manage to create an ad-hoc network between your Pi and workstation, the SSH is disabled for security reasons. 

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There are two simple ways to sort this out, and we’ll look into it one-by-one 

#1 The Simple Way: Using the official Raspberry Pi Imager, 

Raspberry Pi’s official flashing utility can be downloaded from here . This tool allows you to pick the OS image you want to flash. It also has a setting page where you can enable SSH and add credentials of your home router WiFi SSID and password. All this information is baked into the OS image during the SD card flashing process.

#2 The Ninja Way: Underneath the hood 

While the Raspberry Pi Imager way works pretty straightforward, for the ninja user, it’s important to understand how this all works underneath the hood. So the job of the flasher programmer is to partition your SD card into two segments – BOOT and the Root File System (rootfs) of the raspberry pi. This is how typical how Linux distributions are stored. 

The boot partition holds all the essential files used during the booting process, including the bootloader, and the rootfs partition holds the primary filesystem of the Linux operating system. Now let’s add settings for our WiFi connection and enable SSH on the raspberry pi board the ninja way. 

Once you flashed a new operating system, the SD card shall be auto-ejected, so re-insert the SD card, and you shall see a partition named BOOT mounted on your system. Create a new file in the root folder of the boot partition with the exact name – wpa_supplicant.conf. In this file add following using your favourite text editor or terminal: 

“` code-block

This information shall be used by “wpa_supplicant”, a utility used by Linux distributions like Debian to connect to wifi networks. After the boot is complete, it’ll scan for WiFi networks nearby and connect to your SSID and password you supplied. 

Don’t worry about supplying your password in plain text, after the boot, this file will be removed automatically.

Now to enable SSH, which is disabled by default for security, just create a new empty file with the name ssh in the root directory of the boot partition. Use the terminal command to create this file 

And that’s it, your raspberry pi will be connected to your WiFi network and ready to accept incoming SSH connection requests, and all this is done without ever connecting your board to a monitor and keyboard – Headless. 

Test your SSH connection from your workstation open the terminal, and type:

and you shall be logged in.

Found this tutorial interesting? Read more about the latest trends in Embedded System development in our previous blog here and take your embedded projects to IoT using MQTT via this blog here .

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News and Resources

Happy Code, Swift Code: The 10% Developer Advantage

developer happiness

Does happiness lead to productivity? It might sound intuitive already, but we are obsessed with data. So, we looked into it. And by “we” I mean SlashData and Sentry joined forces to analyse the feedback taken from survey respondents who are professional developers who write software on a regular basis.

To make our filtering even more accurate, it mainly involved experienced developers with at least 10 years of software development experience, as they were required to have a live application. This intentional filtering ensures that the average developer surveyed possesses extensive knowledge and can provide valuable insights into the software development process.

Are happier developers more productive?

Firstly we wanted to identify what makes developers happy and we found:

1. Company size and colleague count don’t significantly impact happiness levels.

2. Whether you’re an experienced coder or new to the field, everyone’s happiness is similar.

3. Delving into infrastructure tasks brings more joy! Devs spending 10 extra hours a week on these issues experience a 3% happiness boost.

4. Managers or those with ‘chief’ titles tend to be 6% happier than their peers.

These insights shed light on what contributes to developer satisfaction in the workplace. Understanding these factors can help foster a more positive and productive environment for all developers.

We conducted an in-depth analysis to uncover valuable developer efficiency insights:

We developed a unique productivity metric by combining three crucial measurements, focusing on how quickly developers complete programming tasks and deploy code to production.

Here’s what our productivity metric considers:

  1. Time from code committed to code in production.
  2. Time taken to recover from an unexpected outage.
  3. Frequency of code deployment to production.

Interestingly, we observed that developers in larger companies tend to take slightly more time to complete tasks compared to their counterparts in smaller organizations. This information provides valuable insights into the dynamics of developer productivity across various company sizes.

What hinders and boosts productivity?

When it comes to barriers, larger companies might experience a slight dip in productivity, with every 500 additional employees contributing to a 1% drop. 

Internal processes and bureaucracy can be culprits, but fear not – we’ll share tips to optimize workflow! Communication is another key player; if it’s smooth sailing, devs thrive, but if not, productivity could plummet by a whopping 48%. However, only 10% of developers face this issue. 

By combining frequency and time metrics, we unveil a cool productivity score measured in hours, allowing us to understand the overall productivity landscape. 

The best part? Happy developers are productive developers! Being 10% happier means completing tasks 10% faster, and each year of experience in software development boosts productivity by 6%. 

Let’s take a closer look at developers’ workloads and what they wish for versus reality! 

The biggest difference lies in dealing with internal messaging, processes, and infrastructure issues. Developers express the desire to allocate 19% and 17% less of their time to these time-consuming tasks. It’s clear that efficient communication and workflow tools are essential for smooth business operations. 

We analyzed their productivity and found that developers spend the most time on software development, followed by project management. 

They spend about 31% and 16% of their week on these tasks.

 Interestingly, developers want to keep doing these tasks as they’re crucial components of their ideal week too. Oh, and here’s a nugget;

the more time they spend coding, the happier they are!

Software development

Let’s dive into how developers spend their time on software development!

Writing code is the most time-consuming activity for 29% of developers, with a whopping 69% spending a lot of their overall time on it. 

The conceptual design phase also takes up significant time, but it’s an enjoyable activity for 60% of developers. However, debugging or fixing code is another time-consuming task, with 67% of devs dedicating a lot of time to it. But here’s the catch – only 51% actually enjoy it. Debugging can be a real workflow challenge and hurt productivity.

What do they feel about their tasks?

Fixing bugs and improving software performance bring joy to 65% of developers. 

They take particular pride in improving software/app performance (21%) and debugging code (12%). 

Writing good code is a big source of pride for 27% of developers, and a total of 69% find pride in this task.

What about the challenges?

The top two challenges are cleaning up legacy code (33% of developers) and running into untested code (32%).

Interestingly, cleaning up legacy code was more common in larger teams, where devs work with a 12% bigger team. But don’t worry, larger teams have more resources for testing, so running into untested code isn’t as big of a challenge for them.

Now, onto the root causes of issues. A whopping 37% of devs say a rushed timeline is the biggest problem they face. Among programmers and software developers, 45% identify rushed timelines as a key challenge, 14 percentage points more than CEOs and managers (31%).

Let’s explore the challenges faced by developers in different roles.

We’ll break it down by the prominent positions, such as management/chiefs, programmers/software developers, architects, and IT workers.

Surprisingly, shifting and unclear priorities are among the top three obstacles across all roles, but they’re especially prominent for programmers/software developers and managers/chiefs. Another common challenge for everyone, but particularly for architects, is too many meetings.

Interestingly, many of the top challenges reported in all roles are process-related. This emphasizes the importance for companies to implement good policies and procedures to optimize workflow and boost developer productivity.

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Tips

Building Scalable and Resilient Web Applications: Strategies for Developers

resilient web applictions

 Currently, there are 6.9 billion people with access to smartphones and at least some form of internet worldwide. This means that, when developing an app, you have a potential audience of well over 80% of humankind.

Now, while it’s unrealistic to expect any app to pull these numbers (even Instagram is used by “just” 2.35 billion), the tipping point past which your app can no longer function as before is far closer than you assume.

To make matters worse, it takes just a couple of (very) dissatisfied users to ruin your rating and leave enough bad reviews to ruin your app’s reputation. This is why you must ensure that your app is scalable and resilient. Here are the top six strategies to help you with that.

  1. Horizontal scaling

When structuring your servers, vertical scaling makes the most sense. After all, upgrading the server, you’re already using or starting with an impressive server (the one that gives you room for growth) is intuitive. The problem is that this system is not the most reliable. Instead, horizontal scaling, where you add more servers instead of improving a single one, might provide you with more value.

Horizontal scaling is impressive because it will allow you to withstand much higher traffic. For an app developer, having more users is the optimal end goal, so not having a plan for success simply makes no sense.

Horizontal scaling improves performance, and it’s much more cost-efficient. Adding a server sounds expensive, but it offers you flexibility and simplicity. After all, you can add more servers as you go. This means you don’t have to start too ambitious (like with vertical scaling). 

Most importantly, you have the privilege of isolating services from one another. This way, you gain a lot of resilience because a flaw, a failure, or an attack on a single service won’t compromise the rest. This also makes troubleshooting a lot easier.

The biggest challenge of horizontal scaling is achieving data consistency; however, there are more than a few ways to overcome this. 

  1. Work on load balancing

Previously, we’ve talked about the imperative of working on multiple servers. Without load balancing, this would be like having five rooms in a home and spending 90% of the time in a single one. With the help of load balancing, you can evenly distribute this and get the most out of the servers you’re using.

There are numerous load-balancing techniques:

  • Hardware load balancers: This is the simplest form of load balancing since it relies on having a device that distributes traffic when it reaches a certain load.
  • Software load balancers: This is a part of the application stack. These are virtual machines that act in a similar way to hardware load balancers.
  • Content delivery networks: A content delivery network is located in different locations. This caching service is scattered across the globe to provide you with an even higher service resilience. 

The best thing about load balancing is that it’s incredibly scalable. This is why the sooner you start doing this, the better results you will face. When your audience outgrows your current capacity, you can provide consistent performance across peak hours. 

More importantly, load balancing boosts the availability of your application. This means that, in the scenario where one of the servers falls, your app will not be completely unavailable. You’ll try to avoid this worst-case scenario at any cost.

  1. Use mobile IP proxy in research and testing

As a web developer, you have to do a lot of research. Now, some of this research will be unavailable due to geographical restrictions. This is why you must use a mobile IP proxy while researching.

While doing research, you’re assuming a role of a customer, which means that various competitor platforms you’re researching target you based on your history. Because your research patterns may take you to the most unexpected places, the experience you get when you try to emulate the customer experience will be all but authentic.

It’s also worth mentioning that mobile IP proxy helps you avoid being blocked or flagged. Some platforms will do this if you make too many requests, which is sensible from their standpoint but may seriously slow down your research. 

Then, there’s the issue of load testing and scalability. You need to see how the platform will behave when accessed through a different IP, especially one using a different locale. This way, you test whether the experience provided by your app gives a consistent experience.

Finally, you can avoid captchas and bot detection measures by rotating IP addresses. Sure, this is not a huge problem, but it’s a slight annoyance that you can easily bypass with the right approach. 

  1. Embrace asynchronous processing

Imagine a scenario where you plan a five-course meal at a restaurant but refuse to order all the meals simultaneously. Imagine waiting until you finish the first course only to request the second, the third, and so on. It would be inefficient, waste everyone’s time and cause a massive hold-up in the operations. 

This is what synchronous processing is like. It’s a system where you make one request at a time and must wait for the current task to be completed to move to the next one. It will slow down the application process and make your audience perceive your application as slow and inefficient.

The solution is asynchronous processing, which makes all the necessary requests without waiting for previous tasks to finish. Since modern apps and servers running them can run multiple processes in the background, there’s no good reason not to use all this computing power.

The benefits of this process are numerous:

  • Improved responsiveness
  • Reduced latency
  • Scalability
  • Parallelism

In other words, you improve your app in all fields, directly contributing to a superior UX.

Most of these tasks are achieved through asynchronous APIs, background tasks, and non-blocking I/O libraries. The latter performs network communication without blocking the main application thread. 

  1. Look into auto-scaling

Real-time demand will consistently change. Even in video game apps, you have peak times on servers. In the past, some games tried to handle this by adding a user queue. This is hardly a technique that would work in web applications. Instead, you must create a system with enough elasticity to handle increased traffic.

More importantly, you need a system capable of efficiently managing these resources and automatically adjusting to the increased demand.

The way this functions is quite simple – you have a system that monitors the application’s performance across all users. Instead of allowing the service to slow down during peak, the system would utilize a cloud-based environment to improve CPU utilization quickly. This can be set to happen as soon as the number of incoming requests passes a certain threshold. Even here, you need the right strategy. 

If we compared this to naval combat, it would be like firing your cannons seconds before the enemy vessel enters your range just because you know the shell will take a while to reach the target. In other words, you need to develop an in-depth understanding of your traffic patterns and create a system that will instantly respond (far quicker than a human-issued command ever could).

This way, you will get the optimal cost-efficiency, availability, and, most importantly, optimal performance.

The key, however, lies in finding the right auto-scaling triggers. The most effective ones are usually: 

  • Incoming traffic
  • CPU utilization
  • Response time

The last one is a bit imperfect because, from a user’s perspective, it’s reactive rather than proactive. 

  1. Double down on performance testing

Previously, we’ve discussed using an IP proxy to test how your platform behaves when accessed from different locations. However, this is not the only metric that you should test. You must also test the following:

  • Load
  • Stress
  • Endurance
  • Spike
  • Scalability
  • Volume

Besides determining the subject of your tests, you must also figure out the KPIs you’re looking into.

  • Response time: The most important aspect of user experience is response time. People hate using laggy apps. Chances are that they’ll switch to an alternative, provided that there is one.
  • Concurrency: Users only assess your app’s performance from their personal experience, which may vary based on the time of day when they access it. With scalable development, you’ll be able to achieve a pretty similar consistency around the clock. 
  • Error rate: Does the app break often? What are the odds of requests failing? Sure, people are more tolerant of this, but if your response time is slow, restarting the app or trying again will be even worse.

In the end, you can see how these KPIs stack. A poor response time can make a critical error exponentially worse. This is why you can’t afford to ignore a single problem. 

With the right strategy, your web applications will be more scalable and resilient

By Srdjan Gombar

Ultimately, you want to prepare for traffic growth and use as many resources as you need. Finding this balance is difficult but not impossible. This will determine your app’s functionality and the cost-effectiveness of your entire project. 

Veteran content writer, published author, and amateur boxer. Srdjan is a Bachelor of Arts in English Language & Literature and is passionate about technology, pop culture, and self-improvement. His free time he spends reading, watching movies, and playing Super Mario Bros. with his son.

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Community Tips

How to Build a Free Educational Web3 Community in Your Country

web3dev

Developers can earn financial incentives from the community by teaching other DEVs how to get into Web3.

Web3 has become increasingly popular among developers. Various job opportunities arise for companies wishing to develop decentralized software and applications in various sectors to bring innovation to their businesses. 

However, not all developers have enough knowledge about Web3 and its technologies to create solutions in this area. That is why a DAO (Decentralized Autonomous Organization) of DEVs in your country can be an excellent way to exchange knowledge about Web3 and still receive financial incentives for it. 

The Decentralized Autonomous Organization (DAO) is an autonomous entity based on blockchain technology, where the DAO is capable of automating administrative processes such as voting, resource allocation, and contract execution without the need for intermediaries. 

These organizations have a structure that enables democratic and transparent governance. Through blockchain technology, the DAO operates with a public and distributed ledger, ensuring transparency and immutability of operations conducted by the DAO. 

This means that all transactions, including votes, execution of smart contracts, among others, are recorded permanently and verifiably by any participant in the network. This strengthens trust and security in the DAO, as there is no central authority controlling or manipulating the records. 

Known as the “decentralized web”, Web3 is a new internet phase that is rapidly expanding and aims to create a more secure and fair internet. Web3 is based on blockchain technology and smart contracts. 

Even though it is still in its initial stages, Web3 is already the focus of projects that aim to revolutionize the way we interact within the internet. For developers who want to join this new web, one way to learn or teach about Web3 is by creating a Web3 community in their country. 

How to Create a Web3 Community in Your Country 

The meeting point of a Web3 community is usually a website or a free Discord application, which allows democratic access. The tool allows several types of interactions among

members, regardless of language or country, expanding the potential of each member, whether in personal or professional realms, with technical or behavioral skills. 

The WEB3DEV community is ready for educational expansion in new countries. In Discord, there is already support from proficient developers in English, Spanish, and Portuguese who can help create WEB3DEV in your country, providing support to DEVs in other languages. 

How to Receive Incentives to Expand WEB3DEV 

At WEB3DEV, for example, DEVs are encouraged to learn, following the concept of “learn to earn”, with a commitment to be rewarded for teaching what they learn through educational materials, whether in text, video, or audio, generating this multiplier effect. 

Developers can copy and redistribute the material in any medium or format and can adapt and transform it for any purpose. All the work at WEB3DEV is organized into “Pods”, working groups focused on specific needs. 

Each “pod” has a specific purpose, and the groups share responsibilities and autonomy among participating developers. You can create a community in your country and start a pod, collaborating and bringing other DEVs freely and earning proportional remuneration based on what is produced. Or you can create a community in your country with fixed members, where developers have a connection with the “pod” and commit to the routine and demands that arise. 

Based on our economic model, you can have a clearer understanding of how local community founders are remunerated: 

What is WEB3DEV? 

WEB3DEV is a DAO that focuses its initiatives on three pillars: education, community, and building. It brings the future of the internet in an accessible way to developers all around the world.

Created in 2022 by Daniel Cukier, Yan Luiz, and Melk, the community is dedicated to creating content that encourages all software developers to share high-quality knowledge about Web3. 

Through WEB3DEV, didactic content about blockchain is taught. Additionally, it promotes the connection of companies and developers to foster new talent and build and support DEV teams in Web3 projects. 

Any developer can start a WEB3DEV community in their country, using or creating content and adapting it to the local language. Participating in this community can be a unique opportunity to improve your skills, meet other developers, and contribute to the development of Web3 technology worldwide. If you want to create a community in your country, please get in touch with the DAO directly through our website. 

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Salaries Tips

How well-paid do developers feel?

well paid developers feel thumbnail

Studying wages and compensation can offer insights into the supply and demand of various skill sets in an employment market. Despite recent layoffs across many technology companies, our data indicate that the number of professional developers across the globe continues to rise. A driving factor in the persistent growth of developers worldwide is that modern enterprises recognise the fact that, as technology becomes increasingly intertwined with society, all companies are or will ultimately become technology companies. 

This means that grocery store chains, online commerce platforms, and car manufacturers alike must all compete against one another to attract developers. Compensation is one of the principal means used to vie for said talent. Understanding the compensation landscape for developers can help companies make informed decisions about salary, bonuses, equity, and other benefits they offer to attract and retain skilled developers. Likewise, studying compensation can aid developers in making decisions about their own careers, including negotiating salaries and benefits. 

In this chapter, we present findings from SlashData’s latest Developer Nation survey – the 24th edition – exploring developers’ compensation patterns. We look at differences across regions and note how developers and companies alike, when negotiating compensation, need to take into account differences in costs of living and expenses. Further, we will examine developers’ self-perceptions regarding their salaries and what factors are associated with believing that they are under or overpaid. 

The compensation landscape for professional developers varies greatly across the globe. In our latest survey, we collected information from developers living in more than 160 countries across the globe. As expected, the distribution of reported annual compensation reflects the diversity of respondents and the myriad of personal situations. 

According to our data, 9% of professional developers earn less than $1,000 per year in total compensation – including base salary, bonuses, stock options, and other perks. This group encapsulates many of the developers working part-time, starting off their careers in internships, or working on commission. As expected, reported annual compensation is significantly correlated with overall experience in software development. Hence, as developers gain experience, they are able to command higher compensation. When we control for the differences across the globe, we find that, on average, for every year of experience a developer gains in software development, they earn nearly $4,000 more each year. 

On the upper end of the spectrum, we find that roughly 6% of professional developers earn more than $200,000 per year. According to the World Inequality Database, in almost every country in the world, workers earning above $200K a year belong to the top 1% of earners in that country. This is one indicator that developers’ average compensation is higher than in other sectors of the economy. Below, we break down the average compensation by region to offer a bit more context to the earnings of developers.

Regional differences

North American professional developers report the highest average annual compensation – more than $100,000. The median compensation in the region, however, is closer to $75,000. Meanwhile, on the opposite end of the spectrum, developers working in South Asia report the lowest average compensation of just under $27,000 and the median compensation is around $5,500 per year. As is frequently the case with compensation, those with higher earnings greatly inflate the average, as is evident when we compare the median vs the average annual compensation. 

Anyone who has travelled outside their hometown recognises that the costs of goods and services can vary depending on where you are in the world. Compensation very often reflects these differences in the cost of living. Should developers and companies wish to compare compensation between two locales, considering these differences is crucial. 

As an example, we examine two countries with large developer populations: the United States of America and the People’s Republic of China. The median compensation of developers in the USA is around $75,000 per year. This is five times greater than the median developer compensation in China of $15,000 per year. However, when we account for differences in costs of living using the purchasing power parity index, we see that the average developer in China earning $15,000 per year can afford similar goods and services as a developer in the USA earning $25,000 a year. In practical terms, this means that developers in the USA still generally enjoy a higher wage compared to Chinese developers, but by a lesser margin (3 times more vs 5 times more) than is apparent when we directly compare compensation. 

Perceptions surrounding compensation

On top of asking developers about their current annual compensation, we also asked them about the compensation they think would be fair for their role. Just over half (51%) believe that the compensation they currently receive is fair for their role. Meanwhile, 39% believe they are underpaid, whereas 11% of developers report that their current compensation was more than what they believe is fair for their role. 

To better understand what factors are associated with developers believing they are over or underpaid, we modelled developers’ sentiments about the compensation in their current role. We find that men are significantly more likely to report feeling underpaid in their current role. More specifically, 16% of men report feeling underpaid compared to 11% of women and 14% of developers who identified as non-binary. Conversely, 7% of women feel overpaid compared to 4% of men and 1% of non-binary individuals.

We additionally see that developers with more experience and those working for larger companies are more likely to report feeling underpaid. For each additional year that a developer gains in experience, we estimate that there is approximately a 7% increase in the odds that the developer will report feeling underpaid compared to fairly compensated. This suggests that companies do not financially value experience to the same degree as developers do amongst themselves. 

However, more experience and working for a larger company are both correlated with being compensated higher. This could indicate that more experienced developers working at larger companies have responsibilities that they feel are not commensurate with their compensation. On the other hand, sentiments of being underpaid could also stem from a perception based on a lack of information, being influenced by larger companies’ generally greater profit margins, or unrealistic thinking from the developer. 

Finally, if a developer has an undergraduate degree in software engineering, they are more likely to report feeling underpaid. The odds of a developer with an undergraduate degree in software engineering feeling underpaid vs paid fairly, are 9% greater when compared to all other developers. This effect disappears, however, once developers have a postgraduate degree; as having a postgraduate degree increases the odds of feeling overpaid by 50% compared to not having a postgraduate degree.

This could indicate that companies place a lesser value on undergraduate education than developers perceive they will; possibly leading to the sentiment of feeling underpaid by those who do not yet hold advanced degrees. Other external factors, such as geographical location, also affect how a developer perceives their compensation, likely due to cost of living differences, as discussed in the previous section. 

Compensation is often considered a difficult topic to discuss and research due to the taboo nature of discussing money in many companies and cultures. Our aim with this chapter is to open up the conversation surrounding developer compensation with our analysis.

Do you like data such as the above?

If you’re a professional or hobbyist developer into Web, Mobile, Desktop, Cloud, Industrial IoT, Consumer Electronics, Embedded Software, AR & VR, Apps/extensions for 3rd-party ecosystems, Games, Machine Learning & AI, and Data science, we would like to hear your voice.

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Tips Tools

Artificial Intelligence Developer Toolkit: Essential Tools and Frameworks for AI Development

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Artificial Intelligence has been around for a long time. People have studied it and have made progress but it’s only in recent years that people have started to recognize how AI is being used. Research on AI shows how much it can affect different industries in the years to come.

AI can be used correctly to enhance the human experience as a whole. AI is used for automation so that processes that are tedious and repetitive can be done easily. Automation is needed by different industries. Whether it is businesses that are focused on healthcare or those who are running their Ecommerce website, automation is going to play a huge role in how consumers will use apps and purchase other needed items.

Importance of Essential Tools and Frameworks for AI Development

An AI engineer can work better with the right tools and frameworks to develop the right apps that people will love. People from various industries who would like to start an AI project should understand that there are always different requirements that are needed. Some tools and frameworks can work well together depending on the project being created.

A wide variety of tools and frameworks are thoroughly discussed by other professionals on the internet. They are available in forums, on some websites, and even through videos. An artificial intelligence developer will have no issues in trying to find the right information for a project.

Data Preparation and Preprocessing

If there is one thing that is crucial in data preparation and processing, it is data quality. Machines are created by people and they will not work unless people have set them up very well. It has always been said that people are only as good as their mentors. If they want to become better, they need experience, they need more than one mentor, and they need different inputs and outputs. 

This is the same with the machines for AI. The data quality can highly impact the reliability of the machines. The accuracy and performance of the machine will only be as good as the people who are making the machines work. Artificial intelligence programmers are aware of this fact. This is why they always make an effort to provide a diverse and quality dataset to the machines.

Tools and Techniques for Data Cleaning, Transformation, and Feature Engineering

Good data and bad data can help businesses. Recognizing the bad data can eliminate the extra work that will be done to create the right dataset for any industry. Data cleaning is not people’s favorite activity but it is required to create the right type of data for the project.

It is through data cleaning that bad data can be weeded out from the dataset. Once this is figured out, the issues will be properly corrected. Some data can be considered unfixable which means that they need to be removed.

The usual reasons for unclean or bad data are the following:

  • Human error
  • Getting scrap data
  • Combining data from different sources

The use of bad data can make businesses spend more money than they should which is why it should be eradicated.

To do effective data cleaning, transformation, and engineering, these are the techniques to do:

  • Get rid of duplicates – You can get duplicated entries when you get information from different sources. Get rid of duplicates so that you will not skew the results.
  • Get rid of irrelevant data – Data that is not important to the project will only slow down the results. Remove things that will add nothing to the data that you have.
  • Make sure that text is consistent – One way that you can do this is by standardizing capitalization. Those who can also do NLP labeling can help with this.
  • Clear formatting – Most machines are unable to read data accurately if the data is heavily formatted. You may be dealing with different formats especially if you have gotten your data from various sources. Clear formatting and the data will be read smoothly.
  • Carefully remove errors from the data – This should be done to get a reliable dataset. Key findings might become hard to see if you do not clean the errors immediately.

Machine Learning and Deep Learning Frameworks

Machine learning is continuously growing and it can provide the smart solutions that businesses from different industries need. The frameworks can be understood better because of the libraries, interfaces, and tools that are available for people to view and study.

TensorFlow

This is created by Google’s Brain Team and it can be used for Python. It uses dataflow graphs to create and process data. This is preferred by those who do AI development because the learning models are easy to build. It can also be used for powerful research and experimentation.

PyTorch

This is a framework created by Facebook’s AI Research Lab also known as FAIR. This can be used for different libraries such as Python and C++. The framework is designed to be scaled and improved so that it can become more flexible depending on the project that you are making. This is best for people who are already familiar with C and C++ as there are some similarities.

Scikit-Learn

This is an open-source data analysis library which is usually one of the first choices when people want to do machine learning for Python. This can be helpful for data that needs to be segmented depending on the algorithm. It will also have the ability to recognize data based on the patterns that it shows. 

Natural Language Processing Tools

NLP tools and techniques are very helpful for AI as they can make AI more accurate. The process can also be done in a faster time as compared to not using the right NLP tools. NLP allows applications to do more every day. People can also gain more every day because of this. The more that technology improves, the more sophisticated the algorithms that become available.

Essential NLP Libraries and Tools

People who are searching for IT jobs in Germany usually try to increase the number of skills that they have. Still, they cannot just rely on their skills. They need to make an effort to learn more about the libraries and tools that they can use.

  • Natural Language Toolkit (NLTK) – This is a library that supports various tasks from text segmentation to semantic reasoning in Python. This is the main tool that professionals use for NLP and machine learning.
  • TextBlob – This is the tool that most beginners use when they want to make better experiences while still exploring Python and NLTK. This can help design people’s prototypes.
  • Core NLP – This is one of the tools that can be used when you are using Java. It is required that you have Java installed on your device before you can use this for different processes like sentiment analysis and part-of-speech tagger.

Model Evaluation and Deployment

How sure are you that your machine is providing the type of data that you are looking for? You need AI development services from a trusted company or professionals. They should know the different techniques to check the accuracy of the AI model that has been created.

Accuracy

This is the most widely used metric for model evaluation. This will show you the ratio between the corrected values and the data that you have placed on the machine. This will also show you if the classes that you are trying to analyze are imbalanced.

Precision

This will provide the percentage of the predicted positive instances. This will let you know if the model is giving you information about how right the machine is when it says that it can accurately read the data.

Specificity

The percentage of the negative instances are being measured against the actual total of the negative instances. This can be the most effective if you want to measure the actual number of people who have indicated negatives in the data set vs what the machine says is the percentage of negative instances.

Machine learning is not something new. An artificial intelligence development company can offer professionals who can use the right tools to deploy AI and machine learning easily. People have already learned a lot of details about it and it is expected to become more accurate in the years to come. 

Different machine learning tools might become steeper for beginners especially if they do not know anything about the processes. The sheer determination of people can weed out those who can become good at it.

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News and Resources

On the role of female coders in software development

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Since the beginning of computing, women have consistently played a pivotal role in software development that has frequently been overlooked; from Ada Lovelace developing the first algorithms for modern computers to Margaret Hamilton’s crucial role in the development of on-board guidance software for NASA’s Apollo program.

However, despite women’s exceptional contributions to the field, they have often received less credit than their male counterparts, and their place in the field is questioned.

Today, efforts are being made across the software development ecosystem to address these historical biases. While efforts have been made to promote women to get involved in the historically male-dominated field, there is still considerable work to be done. 

Data and technology are not free from bias. Past applications and software development projects have demonstrated the need for input from diverse groups2.

In this chapter, we specifically explore the involvement of women in software development. According to our latest global developer survey (Q1 2023), nearly a quarter of all developers (22%) self-identify as females, the highest proportion since we began asking respondents about their gender.

This is a small increase from two years ago, since Q1 2021, when female coders accounted for 19% of all developers. 

This slight increase in the proportion of developers self-identifying as females can be partially attributed to the rise in the representation of women among early-to-mid-career developers. Women currently make up a quarter (25%) of developers between the ages of 25 and 34, the highest proportion of all age groups, up from less than 20% in Q1 2021.

This is followed closely by 23% of developers between the ages of 18 and 24. The highest proportion of women falling within the 25-34 age bracket indicates the possible beginning of a positive trend for the future of women in the tech industry. This is the age when people begin to settle into their careers and is a point where people are likely to develop additional skills that allow them to cross-train and enter industries of their choosing.

Further to this, we are also seeing an increasing presence of women in certain regions that are leading to an increase in the proportion of women in technology overall.

Specific highlights include the Middle East and Africa, where the proportion of women in technology in this region has gone from 10% in Q1 2021 to over 20% currently. Similarly, women made up 15% of developers in East Asia in Q1 2021 and now makeup almost 30% of developers. 

Overall, a higher representation of women in the software development ecosystem is a great development. Not only do they bring critical perspectives and approaches to the work being undertaken, but diversity in the workforce offers fresh experiences that can help businesses address underserved needs.

It also enhances efforts to make spaces that are less hostile to women in both overt and subtle ways, allowing even more women to follow their interests in the technology space.

The proportion of women among developers varies substantially depending on the types of projects they are involved in. Virtual reality (VR) and augmented reality (AR) projects have the highest proportion of women, at 33% and 28% respectively, followed by games (28%). 

On the contrary, backend services and web application projects have the lowest concentration of female coders, at just 13% and 16%, respectively.

With these sectors selecting those with formal degrees at higher rates than other areas, and a 10 percentage point difference between men and women having such a degree, this may be one factor in the lower presence of women.

Undergraduate degrees in computer science or equivalent are held by 45% of backend developers and 43% of web developers, compared to 37% of all developers.

Further, the lower proportion of women working in backend services and web application development may, in part, be attributed to the historically male-dominated culture within these sectors. Addressing cultural differences3 and fostering a more inclusive atmosphere can contribute to balancing representation and mentorship opportunities within these sectors.

Further, there may be potential unconscious biases in hiring practices derived from existing workplace culture, which may prevent certain development areas from harnessing the full spectrum of talent, and benefit from the input of individuals with diverse backgrounds.

Examining the sizes of organisations that female developers work for throughout various stages of their life and career could indicate that company characteristics have an influence on women’s decisions in the technology sector.

Like young men, young women are more likely to work as freelancers relative to other age groups and only return to similar proportions among developers aged 55 and above. Additionally, younger female developers (18-24) tend to work for smaller companies, whereas older female developers (45+) are more inclined to work for larger organisations with over 10,000 employees.

Examining a particular age group, women between the age of 35 and 44, may offer an insight into issues women have with progressing through their careers. Previous research into women’s careers in the software development sector has highlighted that women are promoted at a lower rate than men4.

However, when looking at the roles women self-identify with, we find that at mid-market companies (251-1,000 employees) and enterprises (1,001-10,000 employees) the percentage of women in management positions (20% and 29%) is significantly higher than at other organisation sizes (13% on average).

These organisations could offer better opportunities for career growth, decision-making, and leadership. In larger companies, management roles might be more hierarchical and bureaucratic, leading to less autonomy and slower career progression.

In smaller companies, limited opportunities due to their size might result in fewer leadership positions being available overall, and with women being a minority in software development, there are fewer women in leadership positions.

Further, there is an underrepresentation of women in certain leadership roles. 11% of men list their role as CIO, CTO, or IT manager, and 14% identify as technical team leads, compared to just 9% and 8% of women. This could create a cycle whereby there may be fewer mentorship opportunities for other women.

When there are fewer female leaders, it has been found in a range of fields5 that it can be harder for women to progress in their careers, and it can be more challenging for aspiring women to find mentors who can guide them, provide valuable insights, and help them navigate their career paths. 

However, while still a minority of those in such roles, 25% of those in CEO or management positions are women, compared to their position as 22% of the developer population.

While only a small percentage difference, given their underrepresentation in other leadership roles, this represents an area where women are getting leadership positions. Among the previously discussed issues women may face, women are also less likely to apply for leadership positions where they do not fulfil all of the requirements than men6.

This may be leading women to also self-select towards management positions that are not solely dependent on technical skills. 

The observation that women hold a higher proportion of CEO/management roles compared to men (7% against 5%, respectively), particularly in companies with more than 250 employees (8% of women to 4% of men), could indicate a positive shift in gender representation and diversity in leadership positions.

This trend might be driven by a changing corporate culture that is increasingly recognising the importance of gender diversity in leadership, leading companies to seek out and promote women into these roles6 proactively.

Embracing diverse perspectives at the decision-making level can result in better organisational performance and decision-making.

Another factor that may contribute to this observation is the growing appreciation for women’s leadership styles, which tend to be more collaborative, participative, and relationship-oriented. These qualities are often valued in today’s business environment and might make women particularly well-suited for CEO/management roles.

Moreover, women, through their skills and abilities, are likely actively contributing to this positive trend, demonstrating that they are well-equipped for leadership roles. Despite women remaining a minority in leadership this growing representation in CEO/management roles is a step in the right direction, highlighting the benefits of diverse and inclusive leadership.

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Community

Introducing Developer Nation forums

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It’s been a while (read 3 months) since we launched the Official Developer Nation forum along with our revamped website. But we have yet to make a formal announcement about it. This blog will serve as an official bulletin illustrating our rationale behind launching a self-hosted forum for Developer Nation.

Being a global community, we are aware that developers worldwide depend on us and each other for support, sharing ideas, collaboration, and diverse perspectives to make informed decisions in their programming journey. However, we didn’t want to hastily create yet another Discord server or Slack workspace without careful consideration, which could result in unanswered queries and inactivity.

How we support our global developer community 

We have been providing extensive assistance to our community members via email for a considerable period. Our support ranges from answering their questions, and connecting them with relevant individuals in the community, to sharing developer market research reports upon request from our vast data repository. We also extend it to help them with job hunting, among other things. However, we noticed all this happening behind closed doors, isolated from the rest of the community, for no reason but a lack of an open platform. Even if another developer had a similar query or request, they could not benefit from previous conversation flows with other members. Therefore, we decided to take this to the next level by providing the community with a platform to collaborate openly and benefit from the conversations other members are having.

Announcing Developer Nation Forums

Developer Nation forums are our discourse server which can be accessed at: https://forum.developernation.net/, now without actually telling you what you can do here, I would highly encourage you to check it out yourself and consider this our community playground where nothing is wrong, and everything posted is regarded as a healthy flow of conversations within the community. We’ve created the categories we see fit (for now), but this is ever-evolving as we receive community feedback. 

One of the key goals of creating our own forums is to help our community self-serve themselves; that means once the forums have significant conversations, the chances of you finding an answer to your query increase by many folds. Thus, new members can better navigate our community and surveys and get support without needing to reach out to us personally.

Apart from creating your own threads and participating in conversations started by other community members, you can customise the look and feel from dark to light mode. Feel free to explore more and share your feedback with me on how we can make it better and more inclusive for everyone. I believe our community members will generously help each other on the forums and make it a sustainable healthy hangout place for all the members.

P.S: Since every member of the Developer Nation community team, including me, spends time on forums every day, the chances of your query being addressed are relatively high there.

I’ve created this short video as a quick crash course on using the forums for the first time; check it out, and I look forward to welcoming you there. Cheers!

Join forums here

– Ayan

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News and Resources

AI-Powered Predictive Analytics: A New Era in Project Estimation and Planning for Software Development

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Software development projects are like puzzles with countless pieces that must come together seamlessly. But one of the biggest challenges in this process is estimating and planning the project accurately. It’s a bit like trying to predict the future-a daunting task. However, with the introduction of AI-powered predictive analytics and the emergence of AI-based project management tools, a new era of software development project estimation and planning has begun.

Understand the terms

Project estimation and planning

Project estimation and planning in software development involves predicting the project’s duration, effort, and resource requirements. Project managers and teams break down the project into smaller tasks, estimate the time and effort for each task, and create a timeline. They consider factors like team size, skills, and available resources. The goal is to set realistic expectations and use resources wisely. Good estimation and planning prevent surprises, delays, and extra costs. It’s about understanding what needs to be done, how long it will take, and what resources are necessary for success.

Most of the time, the estimation process would cost the company significant money and time at the start of developing a brand-new website, app, or software.

AI-powered predictive analytics

AI algorithms can predict future events or behaviours by analyzing large amounts of data and identifying patterns. AI-powered predictive analytics in software development can estimate project timelines, identify risks, and optimize resource allocation. It enables us to make data-driven decisions and adjust plans as necessary. It’s all about using AI to predict and plan for the future based on insights from past data.

Project Estimation and Planning Before AI

Before the introduction of AI-powered predictive analytics, project estimation and planning in software development relied heavily on human expertise and historical data. Project managers and teams would analyze previous projects with similar characteristics and use their experience to estimate the effort, time, and resources required for the new project. The following are some notable challenges of traditional project estimation and planning.

Limited data insights

The amount of historical data available for analysis limited traditional methods. Estimates were frequently based on a few previous projects, which may not accurately represent the complexities of new projects.

Biases and assumptions

Estimates may be influenced by human biases and assumptions, resulting in overestimation or underestimation of effort and timelines. These biases may result from previous experiences or personal perspectives, affecting the accuracy of estimations.

Identifying risks

Another challenge was anticipating potential risks and challenges early in the planning process. Due to the lack of comprehensive data analysis capabilities, project managers relied on their intuition and experience, which may have covered only some potential risks.

Adaptability and optimization

Traditional methods lacked the flexibility to adjust estimates and plans as the project progressed. Real-time data integration was limited, preventing optimal decision-making and resource allocation based on changing project needs.

Enter: AI-Powered Predictive Analytics

The implementation of AI-powered predictive analytics has changed the process radically. By leveraging machine learning and data analysis, AI can analyze vast amounts of historical project data to identify patterns, trends, and correlations that humans might miss. Here are some of the ways AI transforms project estimation and planning:

Uncovering hidden insights

AI algorithms examine massive amounts of historical project data, detecting patterns, trends, and correlations humans may overlook. AI uncovers hidden insights that enable more accurate predictions by analyzing project variables such as scope, complexity, team size, and resource allocation.

Data-driven decision-making

Project managers and stakeholders can make data-driven decisions from the start with AI-powered predictive analytics. They gain insight into potential bottlenecks, allowing them to allocate resources better. AI provides realistic timelines, enabling stakeholders to set appropriate expectations and avoid overpromising or underdelivering.

Effective risk management

AI identifies potential risks early on by analyzing historical project data. It identifies factors that have historically resulted in delays or cost overruns. With this information, project managers can proactively mitigate risks and develop contingency plans, resulting in more efficient project execution.

Continuous improvement

AI algorithms learn from real-time project data, adapting and refining their predictions. AI provides valuable insights as projects progress, allowing teams to course-correct, make data-driven decisions, and optimize resource allocation. Over time, this iterative learning process improves estimation accuracy.

Human-AI collaboration

It is critical to understand that AI-powered predictive analytics does not replace human expertise but supplements it. Project managers and stakeholders contribute valuable experience and domain knowledge. AI provides them with new insights, enhancing their decision-making abilities.

Final thoughts

AI-powered predictive analytics has transformed software development project estimation and planning. It enables project managers and teams to make more accurate predictions, optimize resource allocation, and manage risks more proactively. We can uncover hidden insights, make data-driven decisions, and adapt plans in real time by leveraging AI’s data analysis capabilities. 

This new era of project estimation and planning combines the best of human expertise with the power of artificial intelligence, resulting in more successful and efficient software development projects. We can expect even greater accuracy and efficiency in the future as AI technology advances, paving the way for continued innovation and growth in the software development industry.