In my last blog, I discussed managing dependencies with git submodules. However, when working with large projects that have many dependencies, traditional methods like git submodules can become cumbersome. Google’s repo tool emerges as a powerful solution specifically designed to handle this challenge.
What is repo tool?
repo is an in-house dependency management tool developed by Google. It excels at managing many dependencies, making it ideal for projects like the Android Open Source Project (AOSP) and custom Android ROMs.
Unlike git submodules, which are an integrated git feature, repo functions as a separate executable script. This necessitates installation before diving in.
Repo relies on a manifest file stored in a separate Git repository. This XML file is the central hub, outlining where to fetch project dependencies, their storage location, and specific revisions (commits).
The beauty of Repo lies in its ability to manage multiple manifests. Imagine a huge, complex project like the Android Operating system with 100 dependencies. You could create a dedicated “lib.xml” manifest to fetch those specific libraries, eliminating the need to include hundreds of unrelated dependencies from a broader manifest. Similarly, the testing and compliance team can have “qa.xml” and “compliance.xml” to manage extra QA and compliance-related dependencies separately, which might not be needed in production but required during development. Both could also have the same libraries but different versions. Hence repo using manifest.xml makes handling dependencies extremely flexible.
For this demo, we’ll keep things simple with a single “default.xml” file.
Examine the default.xml file: This file specifies the main Project (ex, EazyExit) with two dependencies, FastLED and PubSubClient, along with their corresponding URLs, paths, and revision IDs.
In software development, we rarely build projects entirely from scratch. We leverage open-source libraries and frameworks to accelerate development and avoid reinventing the wheel. But managing these dependencies can quickly become a tangled mess, especially as projects grow and dependencies multiply.
This blog post explores a simple yet powerful Git feature called git-submodule, which streamlines dependency management and keeps your codebase clean and organised.
The Downside of the Manual Approach
Many developers resort to simply manually cloning and directly pushing dependency code into their main project’s codebase. While this may seem convenient at first, it creates several challenges:
Version Control Issues: Updating dependencies becomes a manual process, increasing the risk of compatibility issues and security vulnerabilities.
Upstream Changes: New features or bug fixes in the original library require manual integration, which is time-consuming and error-prone.
Introducing Git Submodules
git submodules allow you to integrate external Git repositories (containing your dependencies) directly into your project. This creates a modular approach with several benefits:
Independent Updates: You can update submodules individually without affecting your main project code.
Version Tracking: Submodules track the specific commit hash of the dependency you’re using, ensuring consistency and reproducibility.
Modular Codebase: Your project remains clean and organised, with dependencies clearly separated from your core code.
Putting Git Submodules into Action
Let’s walk through a practical example. Imagine a project named “submodule-demo” that relies on two libraries:
FastLED: A library for controlling LEDs
PubSubClient: A library for implementing an MQTT client
Here’s how to leverage git-submodules to manage these dependencies:
Project Structure: You can create a dedicated directory (e.g., lib) within your project to store dependencies.
Adding Submodules: Use the git submodule add command to specify the URL of the external repository and the desired submodule path:
cd your_project/lib
git submodule add https://github.com/iayanpahwa/FastLED.git
git submodule add https://github.com/iayanpahwa/pubsubclient.git
This fetches the code from the specified repositories and stores them within the lib directory.
3. Initialising and Updating: Anyone cloning your project can easily initialise and update the submodules using the following commands:
Alternatively, you can use the --recursive flag during cloning to automate these steps:
git clone --recursive <your_project_URL>
4. Version Control: Git submodules record the specific commit hash used from each dependency. This ensures everyone working on the project uses the same library version, promoting consistency and preventing compatibility issues.
Beyond the Basics:
While submodules default to fetching the latest commit from the dependency’s main branch, you can specify a different branch or commit hash. Refer to the official Git documentation (https://git-scm.com/book/en/v2/Git-Tools-Submodules) for details on advanced usage.
Key Takeaways
By embracing git submodules, you can effectively manage dependencies, improve code organization, and streamline project collaboration. This approach promotes a more modular and maintainable codebase, saving you time and headaches in the long run.
Feel free to explore our other blog posts on Git internals for further insights!
Organizations use Terraform for devops infrastructure management and in interfacing with configuration files. They also use it in planning changes before they are applied to the infrastructure. Additionally, Terraform is employed in viewing the state of infrastructure and in importing infrastructure under Terraform control.
Terraform’s command line interface (CLI) is the tool that enables Infrastructure-as-Code management with the HashiCorp Configuration Language (HCL) through commands.
Using the Terraform CLI is somewhat of an art. Different users have different approaches. In many cases, teams fail to get the most out of it. Here’s a rundown of some of the best ways to maximize the use of Terraform’s command line interface to make IaC provisioning and management more efficient.
Mastering the Commands
Becoming an expert with the available commands is a foundational skill in using Terraform CLI. Users must become well-versed with essential Terraform CLI commands such as Terraform initialization (init), validation (validate), planning (plan), and application (apply) to proceed with provisioning, configuration, and management tasks intuitively. There are also important commands used to streamline workflows such as format (fmt) and refresh (refresh).
The use of these commands is not as straightforward as it may seem. Running the init command, for example, requires a working directory that contains the configuration files and a properly installed and configured Terraform Core. It is also possible for prompts to appear during the init command execution. These prompts can be for credentials and backend configuration details or for a confirmation to install a required plugin.
Also, still in connection with the init command, there are cases when modifications are needed through flags such as -lock and -upgrade. It is important to get acquainted with these options, as they are necessary for module upgrading and copying, state locking, and other purposes. The -upgrade flag is particularly important because it is used to update to the most recent compatible versions of providers and modules.
Mastery of available Terraform CLI commands ensures efficiency and consistency in managing infrastructure. It is especially crucial for collaborative provisioning and management actions, wherein everyone has to work seamlessly with version control systems like Git. Tools are only as good as their users are, so it is only logical to master Terraform CLI to use it optimally.
Working Separately and Collaboratively with Workspaces
Terraform CLI users should take advantage of the workspaces feature. This is important when organizing or managing different environments, as it enables the management of separate deployments of the same infrastructure codebase.
Workspaces make it possible to manage development, staging, and production environments in isolation. This separate management is necessary to test modifications in development in one environment without causing a cascading of changes to other environments.
Additionally, workspaces enable configuration variants. For example, it allows the creation of a separate workspace for a base configuration and another one for a specific region, where the configurations used in these workspaces are slightly deviating.
Ironically, the benefit of being able to manage environments separately with Terraform’s workspaces is an advantage for collaboration. Different teams can work in different environments at the same time to expedite the job, without the risk of inconsistencies or errors, because each workspace has its own state. There are no risks of accidental modifications or deletions.
Leveraging Modules
Another important tip when using the Terraform CLI is to make use of modules. These are collections of Terraform configuration files in one directory. Basically, they are self-contained and reusable sets of configurations that represent a specific infrastructure component, functionality, or element.
Working with the CLI can become confusing as the code becomes more and more complex. Modules help tone down this complexity and simplify infrastructure deployments by reducing the need to write the same configuration repeatedly for infrastructure elements present in multiple locations.
This eliminates code duplication, because infrastructure elements can be defined once in a module, and then the same module can be reused wherever it is needed.
Terraform modules enhance code maintainability because they make code easier to comprehend. They also provide the benefits of quick modifications and efficient debugging. Likewise, they ensure that changes made to an infrastructure element are reflected automatically across all places where the element exists.
Mindful State Management
When using the CLI, it is also critical to watch out for Terraform state files. These files house the mapping of configurations to actual infrastructure resources, making them a critical part of the Terraform CLI’s effective functioning. They serve as a central source of truth, which is important in maintaining consistency and the proper identification of changes in the code.
Since state files map configurations to resources, they are vital in Terraform’s ability to understand the current state of your infrastructure units. They create the basis for how to achieve the desired configuration. Also, they are useful in optimizing performance for large infrastructures, because they also store cached resource attribute values, which lessen the need to perform cloud provider querying whenever Terraform runs.
States files are saved locally in a file name labeled as terraform.tfstate by default. Many devops teams find it beneficial to utilize remote state backends like Terraform Cloud. Doing so enables centralized management, which is a boon for infrastructure visibility and collaboration. It also facilitates better version control and security, especially helpful in cases of agile disaster recovery.
Updating the CLI and Exploring Advanced Features
Constantly updating Terraform CLI to the latest version is a must to ensure that the CLI being used has all the security patches applied as well as the latest features. Also, it is advisable to explore new and advanced features.
Terraform’s CLI is a tool intended for developers, not ordinary app users who are easily impressed by the newest functions. Expect most of the new and advanced features to be purposeful and worth having.
For example, it is possible to access the attributes of other resources within variables. This function is great for dynamic and flexible configurations because it allows the referencing of attributes of existing resources within variables.
Here, configurations can adapt according to the infrastructure state, like setting a unique security group ID for a new resource in accordance with the ID of an existing security group.
Maximizing Terraform CLI
The best performance of any tool depends on its user. In other words, Terraform CLI can provide the best efficiency, consistency, and collaboration benefits if users gain expertise in using it. The four pointers briefly discussed above can serve as a good starting point in taking full advantage of Terraform’s Command Line Interface to work with Infrastructure-as-Code with maximum efficiency and the best infrastructure management outcomes.
Computing power is no longer a luxury, it’s a need. Whether you’re a creative professional pushing the boundaries of animation or a scientist address complex copy, having the right tools at your disposal can make all the difference. This is where NVIDIA GPU dedicated servers come in, offering a hard join of processing power and creativity that can transform your workflows.
But what exactly are NVIDIA GPU dedicated servers, and why should you consider them? Let’s explore into the world of GPU boost and explore five powerful reasons why incorporating an NVIDIA GPU dedicated server into your arms can empower your projects and move you towards success.
1. Release the Power of Similar Processing:
At the heart of an NVIDIA GPU dedicated server lies the Graphics Processing Unit (GPU). Unlike traditional CPUs designed for sequential tasks, GPUs excel at similar processing. Imagine a highway with multiple lanes – a CPU funnels tasks through one lane at a time, while a GPU utilizes numerous lanes simultaneously, significantly accelerating computations.
This similar processing skill makes NVIDIA GPU dedicated servers ideal for applications that involve massive datasets and complex calculations. Tasks like:
3D Rendering and Animation: Render hard scenes with breathtaking detail in a spot of the time compared to CPU-based systems.
Video Editing and Encoding: Edit high-resolution footage seamlessly and encode videos for various platforms at blazing speeds.
Scientific Simulations: Run complex simulations involving solution dynamics, weather patterns, or protein folding with unparalleled efficiency.
Deep Learning and AI: Train deep learning models faster and develop cutting-edge AI applications that leverage vast amounts of data.
2. Unmatched Performance for Demanding Workloads:
NVIDIA GPUs boast thousands of cores specifically designed for processing massive datasets and performing complex calculations. This translates to real-world benefits for users. With an NVIDIA GPU dedicated server, you can:
Reduce project turnaround times: Get results quicker, repeat faster, and meet deadlines with greater ease.
Handle larger and more complex projects: Take on hard attempt that would strain traditional CPU-based systems.
Increase productivity and efficiency: Focus on your core tasks while the server tackles computationally intensive workloads.
Unlock new creative possibilities: Experiment with innovative techniques and push the boundaries of your field without hardware limitations.
3. Scalability to Match Your Growing Needs:
As your projects become more demanding or your business scales, your computing needs will evolve. The beauty of NVIDIA GPU dedicated servers lies in their inherent scalability. Many providers offer a range of server configurations with varying numbers and types of NVIDIA GPUs. This allows you to choose a server that perfectly aligns with your current requirements, with the flexibility to upgrade seamlessly as your workload grows.
Considering Colocation vs. Cloud-Based Solutions:
While cloud-based NVIDIA GPU dedicated servers offer a convenient and scalable option, colocation server hosting presents a powerful alternative for users with specific requirements. Here’s a breakdown of the key considerations:
Control and Security: Colocation offers greater control over your hardware and network environment, ideal for businesses with strict security needs.
Customization: Colocation allows for customized server configurations tailored to your specific workload demands.
Latency Sensitivity: For applications where latency is critical, such as real-time simulations or high-frequency trading, colocation can provide a lower latency connection compared to cloud-based solutions.
4. Cost-Effective Solution for High-Performance Computing:
Investing in high-performance computing hardware can be a significant upfront cost. NVIDIA GPU dedicated servers provide a cost-effective alternative. Here’s why:
Shared Infrastructure: Cloud-based providers offer dedicated servers with powerful NVIDIA GPUs, eliminating the need to purchase and maintain expensive hardware yourself.
Pay-as-you-Go Model: Many providers offer flexible billing options, allowing you to pay only for the resources you utilize. This is ideal for projects with fluctuating workloads or those in the initial stages of development.
Reduced Downtime: Cloud providers manage server infrastructure, ensuring minimal downtime and maintenance headaches.
5. A Future-Proof Investment for Emerging Technologies:
The world of figure is constantly develop, and NVIDIA GPUs are at the lead of this revolution. As AI, deep learning, and other data-intensive applications continue to gain rank, NVIDIA GPU dedicated servers will become even more crucial.
By investing in an NVIDIA GPU dedicated server today, you’re not just get processing power; you’re provide yourself with a platform that can adapt and grow beside these emerging technologies. This future-proofs your investment and ensures you have the tools necessary to stay ahead of the turn.
Conclusion
NVIDIA GPU dedicated servers offer a strong idea for anyone try to push their workflows and unlock new creative or scientific possibilities. From the unparalleled processing power to the cost-effective scalability and future-proof design, these servers empower users to achieve remarkable results.
There are quite a few AI-based tools available today, and each one offers something unique. However, perhaps the most-used AI programs today are generative AI tools, including those that generate stories. A Forbes research says generative AI will be worth $280 billion by 2032.
That’s why, you’d want to build an AI story generator, that could potentially help users write the stories they want. But a tool like that is a sum of many great features. But what exactly is an AI story generator compared to other generative AI tools?
Moreover, what kind of features do you need, and which development path should you take? Let’s find out.
What is an AI Story Generator? Compared to Other Generative AI
An AI Story Generator is an AI/Machine Learning-based program, which uses advanced AI algorithms to generate stories and narratives. Like other chatbots or generative AI tools, these programs also use pre-trained algorithms.
Except, there is one major difference between a common chatbot and an AI story generator. The difference in question is that the latter is designed to create engaging narratives and write in a story-esque manner while providing means to the writers.
Let’s take ChatGPT for example, and how it would do something with a prompt like this:
“A story about Tom experiencing morning life in New York streets.”
Now, let’s put it into ChatGPT first:
Some might say it’s quite extraordinary, while others might smell AI all over it. But, if we do the same with an AI story generator like this one from Summarizer.org, our results look quite different:
And once the story is generated, here’s our result:
The story has a lot more details and offers a lot more depth compared to the ChatGPT version. That’s because ChatGPT is designed to be a chatbot only. Summarizer.org’s AI Story Generator is designed to write stories with minimal prompts.
Now, there are other options for AI story writers like these, which we’ll discuss later. But it’s important to understand how the two tools discussed above leverage AI, and the clear winner in this comparison is the story generator.
4 Key Features You Should Add in Your AI Story Generator
Now let’s talk about the development features that you should be adding to your AI story generator. It should feature quite distinctive elements compared to normal chatbots or generative AI tools. Here are five key things you need to provide:
1: Style Selection
Style selection is one of the key things you should provide in your story generator. For instance, if the user wants a narrated story, you should provide the ability to narrate a story. While some would want a story told in a more POV manner.
The idea is to provide features that help each writer/user create a story closest to their vision. So, providing a style selection like this would help your target users get just the type of story they want.
2: Tone & Type
Another thing you should focus on is the tone and type of the story your users want to write. Some would want to write a classic, while others would want a horror or thriller. The possibilities are endless and so they should be able to explore them.
Here’s an example of the AI story generator that we used earlier:
In the Classic mode, the story uses the traditional method of delivering the idea. But, for example, let’s say if we wanted the story to be more hilarious, then we could try the Humor story type:
As you can see, the humorous setting takes it on a way different path than the earlier classical version. So, the point is, to provide something that doesn’t only distinguish stories, but also eases the job for the writer/users.
3: Creativity Level
Creativity level is yet another thing you should provide, and it should help the user select their level of creativity. Now, this depends on the type of deep learning model you use, such as GPT 3.5 or 4.0. However, it should look something like this:
When the user selects each level, like in the AI story generator that we demonstrated earlier, it should be written in that tone. Here are two examples:
Imaginative:
Inspired:
So, make sure your users are able to select the creativity level, and you provide enough means for them to leverage AI.
4: Story Length
Story length is one of the key aspects of any written story, so you should ensure your tool has the right options. The Summarizer.org’s AI Story Generator we used has three main options, and each one is made to write content in three main lengths:
The short one stays around 500-600 words:
While the longer version is around 700 words:
So, these are must-haves in an AI story generator.
3 Keys In Developing the AI Story Generator
Now let’s talk about the development part of the AI story generator. This part depends on your preferences, the technology you use, and design elements. So, here’s what you should do:
1: Technology Stacks & Which One To Use
Make sure you’re using a proper programming language with proper frameworks. The technology stacks make all the difference, and choosing the right ones can help you create a high-quality AI story writer in no time. Here are our suggestions for each category:
Programming Language: Python
Machine Learning/Pre-Trained Models: GPT
DatabaseManagement: PostgreSQL
Backend: Django or Flask
Frontend: CSS, JavaScript, or Angular
AdditionalServices: Git, Docker
This should help you get started properly and help you create a solid AI story writer.
2: UI Design and Writing Method
The design of your AI story generator and the writing method in it should be simple and straightforward. The UI of the tool we used earlier should serve as an example. So, you should make sure it has:
A simple and readable interface.
Colors that are easy on the eye.
Offers dark mode.
Provides options clearly, i.e., story type, creativity level, etc.
And ensure the design isn’t cluttered.
This way, you will be able to keep it simple and ensure the users find it handy.
3: Testing & Finalizing
Testing and finalizing are two necessary steps to take, and you should ensure you create a checklist before deploying the tool. So, you should check for any usability problems, like errors that might pop up when users try different methods.
Or you should ask writers or other story experts to check the tool before deploying it. Besides, it’s always important to provide updates and make changes even after uploading the tool.
Conclusion
These are some of the key features and development paths for building an AI story generator. Remember, it’s about creating something that the users not only find helpful but can also leverage to break out of writer’s block, or simply generate creative ideas to work with. So, providing them with the options we explored can help you do just that easily.
So, you’re an app developer looking to build an application that is compatible with a wide range of existing applications and systems. In such a vast, highly competitive field, you know that UI design is everything, and having an app that is easy to use, runs smoothly, and has a wide variety of use cases is your best bet to make a product that sticks around.
You know where you are, and you know where you want to go; but how do you get there? App developers like yourself have a wide range of tools to choose from, and knowing which ones will suit your needs and which won’t gives you a huge leg up.
Whether you’re a developer with a vast knowledge base and a deep understanding of how these tools work, or an entrepreneur who wants to get a head-start on executing your plans for the future, this article will give you the lowdown on the best tools for cross development on the market.
A Brief Overview: Technological Advances in the Planning Phase
Before we dive into the tools themselves, let’s briefly explore how modern technological advances can make your app development process easier. These tools are meant to refine and streamline the planning phase of development, making the process of transitioning from a wireframe to a visual design significantly simpler; especially for collaborative efforts.
We have:
Lucidspark: Lucidspark is a free tool that you and your coworkers can use to streamline the collaborative design process. The mind-mapping technology acts as a whiteboard for all of your team’s ideas, allowing you to chart out the infrastructure of your app, break down complex ideas, and align stakeholders on your app’s overall structure.
Sketch: Sketch is a user-friendly vector-design tool that allows you and your team to build wireframe mockups, transition those to high-fidelity mockups, and create final designs. Useful throughout the app development process, Sketch isn’t free, but some would argue it’s worth every penny.
Core Animator: In-app animations can be a challenge unless you have a tool specifically made for designing and implementing them. Core Animator is one such tool, going the extra mile by not only letting you build animations in-house, but directly translating those animations to code. It’s great for efficient coding and can save you and your team a lot of time otherwise better spent.
The advancements in project management and app design software that are out there are begging to be taken advantage of – so if you feel that using one of these tools will allow your team to proceed more efficiently, don’t hesitate to give them a look!
Choosing the Right Framework
Now that we’ve touched on the planning phase, let’s briefly look at the tools you can use for cross-platform app development. Cross-platform app development can be challenging if done manually, as it would require you to re-code your app repeatedly for each platform while also accounting for subtle nuances between mediums. Fortunately, these tools provide automated support that cuts the redundancy out of this process and shortens your time-to-market.
If you are just starting out, we also recommend getting a firm understanding of basic computer science skills before diving into cross-platform development, as having a base knowledge of programming languages and software development will help you unlock the most value from each of the below tools.
We have:
Titanium: An open-source, JavaScript-based tool that allows developers to reuse designed content across applications. With drag-and-drop functionality and a user-friendly UI, this tool is a massive time-saver for developers that anticipate reusing code across applications.
Ionic: A completely free app development framework that allows you to create applications for various platforms simultaneously. With a vast library of pre-built JavaScript and HTML5 components, this is a great option for developers that are just starting out.
Unity 3D: Developing a game? Unity 3D is a cross-platform app development tool with amazing graphics for its medium. As well as being compatible with most types of mobile operating systems, it also offers options to publish games, track analytics, and access a massive support system.
Kotlin multiplatform: Consistency across platforms is key, so why not go with the best? Kotlin is widely recognized as a powerful industry-agnostic custom cross-platform development tool, allowing developers to target multiple platforms with just one line of code; all without sacrificing the benefits of native technology!
5app: Developing apps for your employees? 5app is a unique tool designed to create cross-platform applications for businesses and their employees. Employers will favor it for its emphasis on data security, its compatibility with most operating systems, and its ease of use!
Node.JS: For organizations that prize flexibility, efficiency, and responsiveness, Node has no equal. Node’s framework allows for the management of multiple platforms at once, and its coding language allows developers to quickly build and deploy flexible server-side applications.
If none of the above meet your specific needs, fear not; there’s such a wide variety of high-quality tools on the market that you’ll find the perfect fit sooner rather than later. Whether you’re working on a game for the public market, a corporate application for shareholder use, or a utility application that meets public demand, there’s a tool to streamline your development process and help you get your product to market quickly.
Imagine a massive interconnected web of physical devices, each with its own IP address, connected to a network through the cloud, offering businesses incredible insights and data with which to drive decision making. In essence, this is what the Internet of Things (IoT) is all about.
While this is a simplified explanation, it does offer a glimpse into the complex landscape of IoT. IoT is considered an ecosystem. That’s because all of its parts rely on one another for full functionality and maximum benefits.
The question that now arises is what is the role of developers in this ecosystem? What are some potential challenges and opportunities they are likely to face in this rapidly accelerating space? That’s what this article covers. So, keep reading to learn more.
Understanding the IoT Ecosystem
The great big IoT ecosystem is named as such for a reason. There are millions of smart devices that are connected to each other and to networks and gateways that enable us to carry out a myriad of tasks and simplify our lives.
There are certain key features that are involved in IoT, such as applications and user interfaces, analytics and data management, the IoT cloud, and of course, the network, gateways, and security. But in short, this ecosystem is primarily characterized by devices and sensors, connectivity, and data processing and storage.
1. Devices and sensors
Let’s begin with devices, sensors, and actuators. This is where the real magic begins. Each of these hardware devices has an IP address and, depending on the functionality in question, can monitor certain metrics and when a threshold is reached, inform a sensor which then triggers the actuator to take an action. Each of these hardware devices has an IP address and, depending on the functionality in question, can monitor certain metrics and when a threshold is reached, inform a sensor which then triggers the actuator to take an action. Adding a logo design can help in distinguishing these devices for easier identification and maintenance in complex systems.
For example, a car that has a built-in sensor to indicate when tire pressure is low. Alternatively, it can be when energy usage reaches a certain level in your home and your light switches are preprogrammed to turn off in order to save power. Whether it’s in our daily lives or in broader industries such as healthcare, agriculture, or even smart cities, the importance of connected devices is undeniable.
2. Connectivity
Connectivity with IoT devices and systems can be wired or wireless — e.g. Bluetooth, 2G, 3G, 4G, and 5G. Whether it’s a tablet, computer, smartphone, smartwatch, a smart vacuum cleaner, or something more complex, it’s essential to consider the connectivity options available. Connectivity is important because it takes up energy and power, and can sometimes use up quite a lot, resulting in short- to medium-term availability of battery power.
As such, this power consumption can affect the length of time for which an IoT device is connected and for how long it is operational before an action needs to be taken. With connectivity also comes the importance of considering balancing data rates and ranges.
3. Data processing and storage
One of the ultimate things that an IoT device does collectively is to provide valuable data to drive decision making forward in an informed manner. However, before this data is made available, it needs to be effectively processed. This is where machine learning comes into play and sometimes artificial intelligence (AI) steps in to extract key insights, information, and trends through fast data processing, akin to how a business name generatorrapidly produces diverse naming options.
But that’s not the end. Once data has been processed, it also needs to be stored properly, ensuring strong adherence to security measures. As such, data management is a big factor in providing a safer and more secure IoT usage experience and environment.
Challenges and Considerations in the IoT Landscape
Some of the challenges and considerations that developers face in the IoT landscape are the following:
Security and privacy: Cyber security is a major concern. It’s possible for hackers to infiltrate systems and introduce malicious software through bugs, ransomware, or Denial of Service (DDoS) attacks. Securing IoT systems and ensuring data protection against these cyber threats is critical.
Interoperability: A second challenge developers face is the issue of interoperability or compatibility issues. Often, this is caused by non-adherence to interoperability standards. Also worth mentioning is the importance of legacy app modernization.
Data overload: Data management comes to the fore once again and critical strategies must be implemented to ensure that organizations are capable of handling vast data volumes.
Power consumption: Servers that support the cloud infrastructure, if not managed accurately, can be large consumers of energy. That’s why it’s also essential to balance functionality with energy efficiency, especially in cases of battery-operated devices.
Ethical and regulatory concerns: A further challenge surrounds the question of data ownership. This is both an ethical and regulatory concern that must be considered. Developers and organizations must acquire consent for the use of user data and provide guarantees that it will not be misused.
Future Direction and Innovations in the IoT Landscape
On the flip side of the coin, there are incredible advancements and innovations in the IoT landscape that are shaping the direction of our digital future. Here are a few worth considering:
5G connectivity: 5G connectivity offers much faster data speeds with a lower latency for improved connectivity.
AI and machine learning integration: Machine learning and AI are capable of processing large volumes of data, strengthening predictive analytics processes and being able to detect anomalies at a fraction of the time.
Sustainability and green IoT: Further opportunities for improvement include the ability of the IoT sector to contribute to minimizing energy consumption for a lower environmental impact.
Blockchain and IoT: The integration of blockchain in IoT can lead to enhanced security and trustworthiness through secure, decentralized, and tamper-proof data management.
Conclusion
The IoT landscape is undoubtedly dynamic and complex. It presents developers with both challenges and great opportunities for growth. Whether creating applications or developing custom software that end-users will interact with, they need to think critically about various aspects.
These include the end-user experience, safety, security, and privacy, sustainability and energy usage, and a whole combination of factors. This should be achieved in a holistic and forward-thinking way as they work toward shaping a connected future for our world.
When it comes to developers, technical skills aren’t the only thing that matters. In order to survive in the workforce, they must equip themselves with soft skills to avoid miscommunication and gain credibility.
According to a research report, 85% of career success stems from proficient soft skills and people skills. In contrast, hard skills, such as technical expertise and knowledge, contribute only 15% to overall career success.
So, whether you’re a fresh-grad developer or a seasoned one, having well-developed soft skills is necessary. We’ve listed eight essential soft skills for developers to help you improve your professional career.
#1. Analytical Problem Solving
Analytical problem-solving skills are fundamental soft skills for developers, as you will encounter complex technical challenges regularly. This skill helps you break down intricate problems into smaller, more manageable tasks.
Managing your problems helps you quickly identify patterns, root causes, and potential solutions. This skill enables you to navigate through coding errors, optimize algorithms, and design efficient software architectures.
To grow analytics problem-solving skills, experiences play crucial roles. You can engage in activities like participating in coding competitions, solving algorithm puzzles, practicing systematic techniques, or discussing cases with experts.
Collaborating with peers on challenging projects and seeking mentorship from experienced developers give valuable knowledge and perspectives. So, the key is to gain insights and enrich your experience.
#2. Attention to Detail
Minor errors or oversights in code can lead to significant issues, such as software bugs or security vulnerabilities. That’s why attention to detail is necessary to ensure accuracy. Besides, this skill enhances the reliability and maintainability of your code.
When you review code and documentation meticulously, you can catch and rectify errors before they impact the functionality of your software. You can avoid unnecessary mistakes and build credibility as a developer.
To cultivate attention to detail, you can adopt practices such as code reviews and writing comprehensive unit tests. You’re also allowed to utilize code analysis tools to identify potential issues. Using tech helps you be more efficient while keeping your work perfect.
#3. Effective Time Management
As developers, you work with deadlines. What’s more challenging is that you work in a fast-paced working environment. You’ll easily get stressed and behind deadlines without proper time management skills.
Consider practicing prioritizing your tasks to meet project deadlines. Also, effective time management during work hours helps you balance multiple tasks and maintain productivity. Most importantly, you can avoid procrastination and deliver high-quality work timely.
You can improve time management skills using productivity techniques such as performing deep work, creating prioritized to-do lists and setting realistic goals and deadlines. Use project management tools like Kanban boards or task trackers to effectively organize their work and track progress.
#4. Clear Communication
As a developer, you will discuss projects, technical concepts, and problems with your teammates. You may also need to present your ideas and concepts to clients and stakeholders. If you can’t communicate effectively, it may lead to miscommunication and misinterpretation.
Understandably, developing communication skills is challenging. However, you can improve this skill by practicing active listening and using plain language to explain complex concepts.
Break down your ideas or concepts so that others easily understand your messages. You can provide concise and coherent explanations in meetings, emails, and documentation.
In addition, consider seeking feedback from your colleagues. If possible, try participating in communication workshops or training programs to refine your communication skills and build rapport with your teammates.
#5. Collaborative Teamwork
You’ll often find group projects that require you to communicate with teammates. For example, in collaborative coding, you will work with work partners, app designers, product managers, testers, and other stakeholders.
When a collaboration project occurs, make sure you respect others’ opinions even though they may be against your ideas. Show mutual support and consider putting away your personal feelings to achieve greater job satisfaction and project success.
To improve your collaborative teamwork skills, try to actively participate in team meetings, contribute ideas and insights, and respect the opinions of your teammates. With good relationships with your colleagues, you can feel a sense of belonging in the office.
#6. Critical Thinking
Developing critical thinking can take time and vary differently among people. This skill is crucial for developers to evaluate and analyze complex problems. Along with that, critical thinking is also helpful for you to assess different solutions and make informed decisions.
Acts like questioning assumptions, examining evidence, and considering alternative perspectives are parts of critical thinking. These acts will guide you to make well-reasoned conclusions and mitigate issues.
You can engage in code review sessions, brainstorming discussions, and problem-solving workshops with your peers. You can also cultivate a habit of asking probing questions and seeking diverse viewpoints to enhance your analytical reasoning abilities.
#7. Data Security Awareness
Data breaches and cyber threats are prevalent today, so building security awareness is essential for developers. This skill allows you to understand and mitigate risks related to protecting sensitive information within software systems.
Online security is important in safeguarding user data and maintaining the integrity and confidentiality of systems. You can implement appropriate security measures When you know common security vulnerabilities, such as injection attacks, cross-site scripting, and insecure authentication mechanisms.
Additionally, staying informed about industry best practices, emerging security threats, and regulatory requirements helps you address security concerns in software projects. Training programs, security workshops, and certifications in cybersecurity can also equip you with security-related knowledge and skills.
#8. Ethical Conduct
Ethical conduct refers to upholding integrity, honesty, and responsibility in your professional practices and interactions. Meanwhile, developers often face ethical dilemmas related to issues such as user privacy, data ownership, and algorithmic bias.
Adhering to ethical principles and values helps you ensure that your decisions and actions prioritize the well-being and rights of users, stakeholders, and society. But what can be included in ethical conduct?
Typically, it involves considering the potential impacts of technology on individuals and communities. Moreover, it means respecting diversity and inclusivity, as well as promoting transparency and accountability in software development processes.
Engaging in ethical discussions and debates is one of the best ways to grow this skill. You can seek guidance from professionals, ethical frameworks, and codes of conduct while reflecting on the ethical implications of your work.
Conclusion
Writing code isn’t the only job of developers. Even though you’ll spend a lot of time in front of computers, you’ll still need to communicate with others and yourself. Understanding how to behave really does matter for your career success.
In conclusion, soft skills for developers are essential to thrive in the ever-changing and collaborative field of software development. From problem-solving to ethical behavior, each skill plays a vital role in working effectively, communicating clearly, and ensuring project success.
Andre Oentoro is the founder of Breadnbeyond, an award-winning explainer video company. He helps businesses increase conversion rates, close more sales, and get positive ROI from explainer videos (in that order).
Learning software engineering opens the door to many job opportunities, but how do you know which one to pursue?
This article explores 7 software engineering disciplines, the skills involved, and the expected salary. We also look at an example of what your career path as a software engineer might look like—but remember, the journey will be different for everyone!
Types of software engineering jobs
Within software engineering are a whole array of disciplines to choose from. Finding programming jobs (and similar) is less daunting when you know what your options are and which discipline might suit you best.
1. Front-End engineer
Front-end engineers are responsible for how the front end of a site or application looks and how users can interact with it. They are responsible for planning, building, and implementing the user interface.
Front-end engineers must learn HTML, CSS, and JavaScript at a minimum. If you have an eye for design and an aptitude for improving user experience, you may be drawn to a career as a front-end engineer. According to Indeed, the average salary for a front-end engineer in the UK is around £53,884.
2. Back-End engineer
If the “front end” is the side that users see and interact with, then a back-end engineer is working behind the scenes on the particulars that make the application work. The “back end” includes server and server-side technologies like database design, data integration, and APIs.
Back-end engineers use a mix of programming languages, such as Java, Golang, Elixir, Python, and C++. If you’re interested in a career as a back-end engineer, it is also worth strengthening soft skills like problem-solving and collaboration.
According to Indeed, the average salary for a back-end engineer in the UK is around £60,801.
Combine the skills and responsibilities of front-end and back-end software engineers, and what do you get? A full stack engineer.
A full-stack engineer is a high-level software engineer who is expected to work across the entire system. They are responsible for designing, testing, and implementing various software applications, taking responsibility for APIs and databases as well as UX features and user interfaces.
You’ll notice that job titles like front-end, back-end, and full-stack engineer are quite general: you could be working on anything. For example, do you know the role of artificial intelligence in transportation? As technology continually develops, the possibilities for making a difference via coding skills are endless.
According to Indeed, the average salary for a full-stack engineer in the UK is around £55,780, although the high end is around £67,026.
4. Mobile app developer
Mobile developers build applications for tablets, smartphones, and other mobile devices. These applications will typically be on either iOS or Android operating systems, and engineers sometimes sub-specialise in one of the two.
Mobile app developers are similar to full-stack developers, since both need to cover the front and back ends of an app. They therefore need to be competent with user interfaces and back-end operations and should be proficient in languages like Java and Swift. Creativity and vision are a must to develop unique apps.
According to Indeed, the average salary for a mobile developer in the UK is around £40,627.
5. Graphic engineer
Graphic engineers usually focus either on video games or computer graphics. They tend to work with 2D/3D graphics, physics, and game mechanics.
Game development is perhaps one of the most exciting disciplines within graphics, and within software engineering overall. It is an opportunity to design characters and levels, write a story, and test a game that people can access and buy from games consoles, computers, smart phones, and more.
Specific requirements will differ depending on the project, but most game developers learn C++. This is a role for an individual with a flair for creativity, a passion for storytelling, and a desire to push boundaries in what video games can be.
It is more difficult to predict salary in more creative roles, but Glassdoor places the salary range between 20k and 40k in the UK.
6. DevOps engineer
DevOps engineers tend to be responsible for feature-facing work rather than client-facing work. Their job concerns infrastructure, automation, release cycles, and sometimes application health.
DevOps is short for developmental operations: the combination of practices, tools, and cultural philosophies that help an organization deliver applications and services at high velocity. In practice, that may look like managing the programs that allow an organization to deploy their software to big stacks of clusters.
To succeed as a DevOps engineer, you need to understand the fundamentals of the software development lifecycle (SDLC), including versioning strategies, source control management systems, and CI/CD pipelines.
Additionally, DevOPs engineers may be involved in managing programs like call center scheduling software, playing a key role in automating resource allocation and workflow for the organization.
According to Indeed, the average salary for a DevOps engineer in the UK is around £62,756.
7. Security engineer
Security engineers keep a company’s data and systems safe, taking responsibility for preventing hackers and cyber attacks while protecting against or removing viruses like ReceiverHelper Mac malware.
Tasks include:
Planning network and hardware updates
Implementing and monitoring an application’s security
Testing for exploits
Collaborating with other departments to safeguard sensitive data (e.g. in an IVR contact center, communications teams and security engineers would work to keep customer data secure).
Responding to security incidents when they occur
To do this role well, security engineers should be skilled in a variety of coding languages plus penetration and vulnerability testing.
According to Indeed, the average salary for a security engineer in the UK is around £37,574.
What does a typical software engineer career path look like?
Whether you learn on the job, get a certification, or earn a Bachelor’s degree at a renowned institute like Torrens University Australia, there are numerous directions your career can take.
Let’s dive into an example software engineer career path:
Junior engineer
Most junior engineers are fresh out of university or college, and have little to no experience in professional software development.
In this role, they’ll gain experience working with a development team, learning new skills, how to contribute to projects, and how to work to project deadlines. You can expect a steep learning curve at this point in your career.
While you’re still getting a grasp of the fundamentals, it’s best to be open and receptive to feedback from senior developers.
Senior engineer
A senior engineer—typically someone with 5+ years experience—is generally regarded as the expert on the team. They have seen a plethora of different projects and technologies, and have mastered the software lifecycle.
Responsibilities include:
Training new engineers
Delivering code
Working with data structures and algorithms
Helping with larger initiatives
Evaluating and executing long-term project goals
Finding ways to improve output
Ensuring product quality in the long term
At this stage, your career path starts to branch. You may choose a career in management, or you might decide to delve deeper into the technical realm.
Tech lead
This role varies between organizations, but is generally given to a candidate with 5+ years experience.
A tech lead works more closely with scoping project roadmaps for their teams and helping manage expectations with stakeholders. They’re responsible for making sure the team they are leading can work fluidly, removing any obstacles to productivity and success.
They may also take responsibility for domain management and testing—for example, if the company operates in multiple territories and has a Qa domain.
In some organizations this is purely technical/project work alongside leading a team, while in others being a tech lead is considered management experience.
Management
In a management role (again, 5+ years experience needed) much less time is spent on technical work. Instead, you’d be focusing on developing your team members in their careers, building a team to help meet the goals of the company, and managing stakeholders on projects.
Let’s look at some specific managerial positions:
Engineering manager (6+ years)
An engineering manager’s job is to manage a team of engineers day-today, building roadmaps and strategies for projects. They focus on building, coaching, and managing a team of high-performing engineers, and ensuring they deliver on expectations.
VP of engineering (10+ years)
This is a senior-level management position. The VP of engineering must lead and grow several teams, oversee project preparation and approval, organize budgets, oversee hiring, creatively problem-solve, and communicate strategies to other leadership. An upper manager may invest in a human resource information system (HRIS) to streamline HR tasks and manage employee data.
CTO (15+ years)
Chief Technology Officers (CTOs) are in charge of every technical aspect of a company, including engineering and other departments. They must be business-minded, with excellent communication and leadership skills.
Effective leadership development is crucial for CTOs to navigate the complexities of their role, inspire innovation, foster collaboration across teams, and drive strategic initiatives that align with the company’s goals and objectives.
Responsibilities include collaborating with the executive team to identify technical initiatives, developing and leading strategy for these initiatives, researching new technology systems, and reporting on KPIs and budgets.
Tips to get started on a software engineer career path
Practise your coding skills regularly
This should be a given if you’re serious about a career in software engineering. Coding skills are foundational to pretty much any discipline. Practicing on your own hones problem-solving and analytical skills, as well as building proficiency in essential coding languages.
Pursue software engineering courses or a bachelor’s degree in computer science
Before looking for entry-level positions, most software developers undertake a relevant university course, graduate training scheme, college course, or apprenticeship. This will usually be in computer science, information technology, or software development—although maths also has transferable skills.
Network
As in any career, it is important to network and make connections in the industry. If you’re not networking, then you’re likely missing out on roles and opportunities that you won’t find online. Additionally, networking provides a sense of community and keeps you up to date in the scene.
If you look online for communities and networking events, you’ll find plenty of options. Especially for women in tech, finding like-minded individuals can be everything.
Final thoughts
Whatever your skills and interests, there’s a software development role out there for you. Starting in an entry-level position as a junior software developer, you’ll find many opportunities throughout your career to specialisespecialize and grow. The key is to stay curious, keep learning, and make all the connections you can as you move along your chosen career path.
Jessica True is the Senior Director for Marketing Strategy and Operations at Dialpad, a modern business communications platform that takes every kind of conversation to the next level—turning conversations into opportunities. Jessica is an expert in collaborating with multifunctional teams to execute and optimize marketing efforts, for both company and client campaigns. She has written for other domains such as Agility PR Solutions and Developer Nation. Here is her LinkedIn.
Enhancing Online Security: Best Practices for Developers
Developing a new software platform, mobile application, or online tool can be a great opportunity to offer innovative tools to the public. It can also present some serious risks. There will be those who seek to steal your intellectual property during the dev process. Alternatively, your completed product may be targeted by those who want to exploit valuable user data.
This makes it vital that your development team enhances its online security measures.
Be Proactive
As a developer — or a leader of a dev team — it’s important not to treat security as a set of superficial defensive measures. This reactive attitude can put you and your applications on the back foot, struggling against the onslaught of threats. You and your team need to be proactive in making security as central and important to development as your coding.
One good approach to this is to make the product secure by design. As the name suggests, this process is about incorporating strong online security into the design phase of the development lifecycle. You’ll basically avoid waiting to consider security until the testing phase of the project or even fixing bugs in the beta phase, as is common. Instead, alongside brainstorming the key features of your product, your team should be looking at what the specific security challenges of the product are likely to be and how to minimize them. This allows you to build a strong security foundation from the outset.
Another way to be proactive in implementing security measures is to ensure your team follows Secure Software Development Lifecycle (SSDLC) protocols. This is effectively a set of actions that are baked into every task developers on your team perform so that they can identify and handle potential issues before they become problematic. It includes creating a culture of security in which threats are discussed and considered regularly. It should involve frequent cybersecurity training so that your dev team is fully aware of the latest threats and protection techniques. Importantly, the development environment itself should be secure, both digitally and physically.
Utilize Advanced Encryption Techniques
Encryption is one of the most powerful tools for ensuring online security. This is particularly effective for minimizing unauthorized access to data that is likely to be shared online both during the development lifecycle and by consumers when using the final product.
Identify and use strong encryption algorithms
Algorithms are the basis upon which encryption operates. Therefore, it’s important to utilize the most appropriate algorithms both for the product itself and protecting your networks. For instance, Advanced Encryption Standard (AES) is a common tool for development teams. This symmetric algorithm performs multiple encryption rounds before breaking the data down into smaller blocks. Some software and apps that require end-user authentication to access sensitive data — like financial information — may be better served by asymmetric encryption, such as the Rivest-Shamir-Adleman (RSA) protocol.
Adopting solid key management
Any encryption algorithm you adopt requires keys to be generated and shared to decrypt the information. It’s vital that you implement management measures to mitigate unauthorized access to and use of these keys. It’s important to formalize which members of the team can obtain and use these keys. It’s also vital to regularly change keys, much as you might update a password to keep it strong.
Conduct Vulnerability Assessments and Improvements
The cybersecurity landscape is in flux. Even within the timeline of your development process, new threats can emerge and come into favor. One of the best practices developers need to adopt is conducting regular vulnerability assessments and making relevant improvements.
Perhaps the most convenient approach during development is using automated scanning software. You can invest in tools that scan both the specific code of your project alongside your overall IT infrastructure. There’s even an increasing number of artificial intelligence (AI) driven scanners that use machine learning algorithms to learn about and adapt to the security landscape in relation to your development. In addition, utilizing a DevOps monitoring tool can allow you to see real-time performance issues that could suggest weaknesses in security, such as slow response times.
It’s also wise to remember that your development team’s workflow can be a source of vulnerability. For instance, too many unnecessary repetitive security processes might cause dev staff to become complacent and overlook key protective actions. A commitment to regular process improvement can help you not only minimize weak points but also boost efficiency. Not to mention it helps you to notice changes in the security landscape and adapt to them. You can do this by taking time to map out both formal and informal processes visually in flow diagrams at milestones during the development lifecycle. This helps you to analyze where inefficiencies occur and what processes you can consolidate and strengthen.
Conclusion
With some solid security best practices, you can ensure your development project is protected from threats throughout the project’s life cycle. This should include taking secure-by-design protocols and adopting string encryption, among other measures. Wherever possible make certain that you have a cybersecurity expert embedded into your dev team or available to consult regularly. This can help you both implement effective processes and stay abreast of any potential threats you need to prepare for.
