Artificial Intelligence (AI) has emerged as a game-changer in software development, revolutionizing how applications are built and enhancing their capabilities. From personalized recommendations to predictive analytics, AI has the power to transform traditional applications into intelligent systems that learn from data and adapt to user needs. This blog will explore the diverse facets of constructing Smart applications by integrating AI within development endeavours. We’ll delve into the various AI types, their advantages for software applications, and the efficient steps to infuse AI seamlessly into your development process.
What does AI in software development include?
AI in software development encompasses a variety of techniques and technologies that enable applications to mimic human intelligence. Machine Learning forms the foundational element of AI, allowing the applications to glean insights from data and make forecasts devoid of explicit programming instructions. Natural Language Processing (NLP) empowers applications to understand and interpret human language, giving rise to chatbots and virtual assistants.
On the other hand, Computer Vision allows applications to process and analyze visual data, enabling tasks like facial recognition and image classification. Deep Learning, a subset of ML, uses artificial neural networks to process vast amounts of complex data, contributing to advancements in speech recognition and autonomous vehicles.
What are the benefits of incorporating AI into development projects?
Integrating AI into development projects brings many benefits that enhance applications’ overall performance and user experience. Personalized Recommendations, enabled by AI algorithms that analyze user behaviour, lead to tailored content and product suggestions, significantly improving customer satisfaction and engagement. Automation is another key advantage, as AI-driven processes automate repetitive tasks, increasing efficiency and reducing human error. Leveraging AI models, Predictive Analytics empowers applications to anticipate forthcoming trends and results grounded in historical data, contributing to informed decision-making and strategic foresight.
How to prepare your development team for AI integration?
Before embarking on AI integration, preparing your development team for this transformative journey is essential. Assessing the AI skills and knowledge gap within the team helps identify areas for training and upskilling. Collaboration with data scientists and AI experts fosters cross-functional Learning and ensures a cohesive approach to AI integration. Understanding data requirements for AI models is crucial, as high-quality data forms the foundation of practical AI applications.
How to select the right AI frameworks and tools?
Choosing the appropriate AI frameworks and tools is paramount to successful AI integration. TensorFlow and PyTorch are popular AI frameworks for ML and deep learning tasks. Scikit-learn offers a rich set of tools for ML, while Keras provides a user-friendly interface for building neural networks. Selecting the proper framework depends on project requirements and team expertise. Additionally, developers should familiarize themselves with AI development tools like Jupyter Notebooks for prototyping and AI model deployment platforms for seamless integration.
What are AI models?
AI models are computational systems trained on data to perform tasks without explicit programming. They encompass a range of techniques, including supervised learning models for predictions, unsupervised learning for data analysis, reinforcement learning for decision-making, and specialized models like NLP and computer vision models. These models underpin many AI applications, from chatbots and recommendation systems to image recognition and autonomous vehicles, by leveraging patterns and knowledge learned from data.
What is the data collection and preprocessing for AI models?
Data collection and preprocessing are vital components of AI model development. High-quality data, representative of real-world scenarios, is essential for training AI models effectively. Proper data preprocessing techniques, including data cleaning and feature engineering, ensure the data is ready for AI training.
Addressing data privacy and security concerns is equally crucial, especially when dealing with sensitive user data.
What do developing AI models for your applications include?
Building AI models is a fundamental step in AI integration. Depending on the application’s specific requirements, developers can choose from various algorithms and techniques. Training AI models involves feeding them with the prepared data and fine-tuning them for optimal performance. Evaluating model performance using relevant metrics helps ensure that the AI models meet the desired accuracy and effectiveness, which helps boost the performance of your application.
Why is integrating AI models into your applications important?
Integrating AI models into applications requires careful consideration of the integration methods. Embedding AI models within the application code allows seamless interaction between the model and other components. Developers address real-time inference and deployment challenges to ensure that the AI models function efficiently in the production environment.
Why is testing and validation of AI integration crucial?
Rigorous testing and validation are critical for the success of AI-integrated applications. Unit testing ensures that individual AI components function correctly, while integration testing ensures that AI models work seamlessly with the rest of the application. Extensive testing helps identify and address issues or bugs before deploying the application to end users.
The journey of building intelligent applications continues after deployment. Continuous improvement is vital to AI integration, as AI models must adapt to changing data patterns and user behaviours.
Developers should emphasize constant Learning and updates to ensure that AI models remain relevant and accurate. Model monitoring is equally important to identify model drift and performance degradation. Developers can proactively address issues and retrain models by continuously monitoring AI model performance in the production environment.
Addressing ethical considerations in AI development
As AI integration becomes more prevalent, addressing ethical considerations is paramount. AI bias and fairness are critical areas of concern, as biased AI models can lead to discriminatory outcomes. Ensuring transparency and explainability of AI decisions is essential for building trust with users and stakeholders. It is critical to manage privacy and security issues about user data properly to protect user privacy and comply with applicable legislation.
Conclusion
In conclusion, building intelligent applications by incorporating AI into development projects opens up possibilities for creating innovative, efficient, and user-centric software solutions. By understanding the different types of AI, selecting the right frameworks and tools, and identifying suitable use cases, developers can harness the power of AI to deliver personalized experiences and predictive insights. Preparing the development team, integrating AI models seamlessly, and continuously improving and monitoring the models are crucial steps in creating successful AI-driven applications. Moreover, addressing ethical considerations ensures that AI applications are intelligent but also responsible and trustworthy. As AI technology advances, integrating AI into software development projects will undoubtedly shape the future of applications and pave the way for a more intelligent and connected world.
Organizations require to establish comprehensive enterprise IT strategies to fulfil the overarching business requirements and stay competitive. Information Technology constantly evolves to provide new ways to do business, and the last decade saw the emergence of cloud computing solutions as a powerful technology to drive long-term benefits for an enterprise.
IT infrastructure is a broad field comprising different components such as network and security structure, storage and servers, business applications, operating systems, and databases. Organizations are grappling with key challenges when it comes to scaling up their IT infrastructure.
⦁ Difficulty in keeping the IT team abreast with the latest IT infrastructure advancements and complexity, which subsequently also impacts productivity.
⦁ High expense ratios such as almost about 70% of the IT budget are spent on maintaining current IT infrastructures, and only around 30% of the IT budget is spent on new capabilities.
⦁ Infrastructure security which is a primary concern for all businesses is predicted to face security breaches of 30% of their critical infrastructure by 2025.
In this blog, we’ll explore some critical top-of-the-mind questions for cloud professionals, such as-
⦁ How do I keep pace with the rate of innovation in the evolving and ever-dynamic environment?
⦁ How could IT help me gain a competitive advantage against new competitors?
⦁ What is the best strategy to optimize IT costs? How do I find the perfect balance between fixed and variable IT costs?
⦁ Which cloud consumption models are best suited for my organization’s business model?
⦁ What is the right strategy for cloud adoption? Observe and implement or predict and innovate?
⦁ How to get started with cloud pilots?
Exploring the Potential of Cloud Computing
Cloud computing solutions have been a key enabler for big innovations in enterprises and could provide the answers to the myriad of questions that challenge CIOs today. Cloud computing services enable enterprises to become more agile. Cloud offers better data security, data storage, extra flexibility, enhanced organizational visibility, smoother work processes, more data intelligence, and increased employee collaboration. It optimizes workflows and aids better decision-making while minimizing costs.
Cloud has now moved from merely being an on-demand and grid computing platform and is now tapping into advancements in virtualization, networking, provisioning, and multi-tenant architectures. Cloud services are critical to building leaner and more nimble IT organizations. It gives companies access to innovative capabilities with robust data centers and IT departments.
The first step to designing a cloud strategy is to outline the business goals and the challenges the cloud will be able to resolve. A holistic approach to creating a cloud strategy will help create an adaptable governance framework empowering businesses with the flexibility to handle different implementation demands and risk profiles.
How Does Cloud Create Tangible Business Value for Enterprises?
Cloud computing and digital transformation are integral to modernizing the IT environment. Listed here are the top six cloud value drivers that are transforming the enterprise business strategy:
⦁ Catalyzing business innovation through new applications developed in cost-effective cloud environments.
⦁ Maximizing business responsiveness.
⦁ Reducing total ownership cost and boosting asset utilization.
⦁ Offering an open, flexible, and elastic IT environment.
⦁ Optimizing IT investments.
⦁ Facilitating real-time data streams and information exchange.
⦁ Providing universally accessible resources.
Let’s dive deeper into how cloud computing creates tangible value for enterprises.
Reducing operating costs and capital investments
Cloud computing services encompass applications, systems, infrastructures, and other IT requirements. By adopting the cloud, companies can save an average of 15 % on all IT costs. Cost optimization is the main reason why 47% of enterprises have opted for cloud migration.
Cloud services provide natural economies of scale allowing businesses to pay only for what they need. Businesses can achieve cost savings with the cloud as it optimizes both software licenses and hardware or storage purchases both on-premise or within the data center. A cloud strategy allows businesses to reduce upfront costs and shift to an OpEx model.
Pay-for-use models enable businesses to access services on-a-need basis. Cloud lowers IT costs and frees up time to focus on optimization, innovation, and more critical projects. Enterprises could prune their IT operations and allow CSPs to manage all operating responsibilities using cloud solutions that sit higher in the stack.
Access to finer-grained IT services
Cloud eliminates multiple barriers that stand in the way of small enterprises. Small enterprises often don’t have the resources to access sophisticated IT infrastructure and solutions. Cloud allows small enterprises to access IT solutions in small increments depending on their budget and business goals without compromising efficiency and productivity. The biggest advantage of cloud models is that they open up access to flexible solutions that are otherwise economically not feasible. Cloud computing solutions, before, level the playing field for small businesses and allow them to compete with larger enterprises.
Eliminating IT complexity for end users
Cloud can simplify IT systems making it easy for businesses to operate. With the cloud, users don’t have to bother about upgrades, backups, and patches. Cloud providers can handle all these functions so users are ensured of seamless access. Cloud’s open approach architecture paves way for new IT outsourcing models. So far, cloud models primarily catered to large enterprises with large IT requirements and at times had lesser scope to accommodate the IT requirements of smaller enterprises. However, the advent of the cloud has enabled small companies to access quality IT services at affordable rates. Mobility and data security are the two key areas where businesses will benefit from the cloud.
Leveraging the pay-per-use cost structure for cloud IT services
Cloud has transformed IT costs from fixed costs to variable costs. That means enterprises with varying IT requirements can safely rely on the cloud. Enterprises may have varying storage needs and the pay-per-use cost structure is highly beneficial for such enterprises. Large enterprises can expand or contract capacity for select applications if they already have existing IT infrastructure.
As updates are included in the cost, enterprises don’t have to deal with obsolescence. An organization’s overall IT requirements determine to what extent the IT costs will transform into a variable cost structure. The cloud allows businesses to trade fixed expenses like data centers and physical servers for variable expenses and only pay for IT services as they are used. The variable expenses are much lower compared to the capital investment model.
Standardizing applications, infrastructure, and processes
Digital transformation and cloud adoption are foundational to standardizing applications, infrastructure, and processes. A ‘lift and shift’ approach where legacy applications are simply moved to the cloud will not yield benefits. The dynamic features of the cloud help replace current processes with industry best practices to eliminate process bottlenecks and high costs. Standardization helps tame the complexity of modern infrastructures and their potential pitfalls. Cloud-driven solutions can also replace non-core applications that greatly improve business processes and provide the level of transparency and standardization that modern companies are looking for. Cloud-based data standardization is driving digital transformation across business functions in multiple industries. Cloud makes applications more scalable and interoperable and opens access to a scalable set of secured solutions.
Cloud computing for organizations in emerging markets
Organizations in emerging markets have been quick to realize the benefits of cloud computing. Cloud computing represents a paradigm shift; it has transitioned from ‘computing as a product’ to ‘computing as a service.’ Organizations in emerging markets get an opportunity to leapfrog their counterparts in developed countries with cloud adoption. Rather than buying hardware and software and investing in maintenance and configuration, cloud computing services enable companies to use applications and computing infrastructures in the cloud-as-a-service (CaaS).
Cloud piloting
Capturing the benefits of cloud adoption requires a holistic approach. Even companies that once preferred to have their own IT infrastructure and systems are shifting to the cloud to leverage its scalability and higher-order functionality. Pilots help determine the impact of cloud adoption on core IT operations as well as the business model. An initial assessment of the impact of the cloud is integral to creating a sound cloud strategy.
Businesses that adopt a cloud-first approach will witness a significant impact on their products/services and delivery and sales models. Pilots should be initiated depending on whether cloud adoption will impact the application layer or infrastructure layer in your enterprise. A decrease in time to market for new applications is a crucial benefit of cloud adoption.
How to Get Started with Cloud Computing?
While some enterprises have adopted a hybrid approach, others have moved to a private or public cloud solution. Companies have embraced the cloud in one way or another as a part of their digital transformation journey. Moving to the cloud will enable businesses to focus on more strategic problems like accurately forecasting through good data management and automating repetitive business processes.
Though the cloud is no longer in its infancy, many enterprises are still faced with challenges when it comes to starting their cloud computing journey. Conducting a pilot is the perfect way to start the cloud computing journey. You can choose from a variety of products and services to conduct a cloud pilot.
Conducting a Successful Pilot? Following are the Key Steps to Follow:
Step 1: Assess your business need
Define the business imperatives and determine key areas where the business needs to integrate with the cloud. Assess the triggers for cloud transformation. If you want to reduce costs or accelerate digital innovation, you will need to conduct pilots accordingly. Cost reduction and performance improvement of business applications will require you to conduct a SaaS pilot.
Step 2: Evaluate options
Take the SaaS pilot as an example. You would have multiple providers to choose from, all with capabilities and experiences that match your requirements. You must evaluate the level of cloud adoption in your industry and assess how various Saas providers match up to that. The evaluation should support the logic used to determine the right type of pilot for your business.
Step 3: Launch the pilot
The final step is to launch the pilot and collect data that will give insights into the road ahead in your cloud computing journey. The data collected at this stage will form the basis for your future cloud strategies and serve as the cornerstone for creating a robust, data-driven, and actionable cloud adoption blueprint for your organization. Once you’ve done a pilot, you can move to the next phase of your cloud journey.
How can NeoSOFT Help?
NeoSOFT can help businesses in their digital transformation and cloud adoption journey with its sustained digital capabilities. We leverage the most in-demand technologies, methodologies, and framework components to craft effective cloud strategies that bring substantial value to businesses. NeoSOFT drives stronger business results by taking a holistic approach to cloud integration.
Here is a quick overview of the NeoSOFT strategy to assist clients with cloud adoption:
1. Readiness analysis
A ‘one cloud-fits-all’ approach won’t work for businesses of different sizes and goals. The first step is to pinpoint the areas in dire need of cloud services. This can be achieved by conducting a deep analysis of the business models, goals, opportunities, and weaknesses. The organization’s skills, resources, and capabilities are taken into consideration at this stage. Its ability to adapt to change and ways to minimize potential project failure are key concerns addressed.
2. Formulating strategy
We create an effective IT strategy that maps to business goals and focuses on deriving outcomes that are sustainable, scalable, and secure. Our strategy is based on principles of agility with faster and safer adoption techniques.
3. Creating a roadmap
This step includes prioritizing workloads to target in the pilot. We help develop initial cloud configurations with associated cost analysis. We create a strategic roadmap designed according to best practices and your organization’s policies and standards. This phase is focused on developing cloud strategies that will keep your cloud infrastructure right-sized and cost-efficient over the long term.
Wrapping Up
Cloud has undoubtedly had a massive impact on the enterprise-technology ecosystem. In 2020, 81% of technology decision-makers said their company already made use of at least one cloud application or relied on some cloud infrastructure. The two key aspects of cloud computing, as with any other technology, are cost reduction and risk mitigation. A well-architected cloud environment is integral to reaping the full benefits of cloud technology. Legacy applications pose risks such as security issues to organizations. A sound cloud strategy takes into consideration cost recovery and risk mitigation. Businesses must prioritize investments in cloud transformation after performing a thorough assessment of their existing business models.
The cloud transformation journey for each organization is unique. The cloud strategy depends on multiple factors such as risk appetite, scope, existing technology stack, and budget. Even organizations planning to start small should consider cloud adoption as a vital part of their IT enterprise strategy to accelerate digital transformation and stay ahead of the competitive curve.
The cloud computing explosion has led to the development of software programs and applications at an exponential rate. The ability to deliver features faster is now a competitive edge.
To achieve this your DevOps teams, structure & ecosystem should be well-oiled. Therefore it is critical to understand how to build an ideal CI/CD pipeline that will help to deliver features at a rapid pace.
Through this blog, we shall be exploring important cloud concepts, execution playbooks, and best practices of setting up CI/CD pipelines on public cloud environments like AWS, Azure, GCP, or even hybrid & multi-cloud environments.
HERE’S A BIRD’S EYE VIEW OF WHAT AN IDEAL CI/CD PIPELINE LOOKS LIKE
Let’s take a closer look at what each stage of the CI/CD involves:
Source Code:
This is the starting point of any CI/CD pipeline. This is where all the packages and dependencies relevant to the application being developed are categorized and stored. At this stage, it is vital to have a mechanism that offers access to some reviewers in the project. This prevents developers from randomly merging bits of code into the source code. It is the reviewer’s job to approve any pull requests in order to progress the code into the next stage. Although this involves leveraging several different technologies, it certainly pays off in the long run.
Build:
Once a change has been committed to the source and approved by the reviewers, it automatically progresses to the Build stage.
1) Compile Source and Dependencies The first step in this stage is pretty straightforward, developers must simply compile the source code along with all its different dependencies.
2) Unit Tests This involves conducting a high coverage of unit tests. Currently, many tools show whether or not a line of code is being tested. To build an ideal CI/CD pipeline, the goal is to essentially commit source code into the build stage with the confidence that it will be caught in one of the later steps of the process. However, if high coverage unit tests are not conducted on the source code then it will progress directly into the next stage, leading to errors and requiring the developer to roll back to a previous version which is often a painful process. This makes it crucial to run a high coverage level of unit tests to be certain that the application is running and functioning correctly.
3) Check and Enforce Code Coverage (90%+) This ties into the testing frameworks above, however, it deals with the output code coverage percent related to a specific commit. Ideally, developers want to achieve a minimum of 90% and any subsequent commit should not fall below this threshold. The goal should be to achieve an increasing percentage for any future commits – the higher the better.
Test Environment:
This is the first environment the code enters. This is where the changes made to the code are tested and confirmed that they’re ready for the next stage, which is something closer to the production stage.
1) Integration Tests The primary thing to do as a prerequisite is to run integration tests. Although there are different interpretations of what exactly constitutes an integration test and how they compare to functional tests. To avoid this confusion, it is important to outline exactly what is meant when using the term.
In this case, let’s assume there is an integration test that executes a ‘create order’ API with an expected input. This should be immediately followed with a ‘get order’ API and checked to see if the order contains all the elements expected of it. If it does not, then there is something wrong. If it does then the pipeline is working as intended – congratulations.
Integration tests also analyze the behavior of the application in terms of business logic. For instance, if the developer inputs a ‘create order’ API and there’s a business rule within the application that prevents the creation of an order where the dollar value is above 10,000 dollars; an integration test must be performed to check that the application adheres to that benchmark as an expected business rule. In this stage, it is not uncommon to conduct around 50-100 integration tests depending on the size of the project, but the focus of this stage should mainly revolve around testing the core functionality of the APIs and checking to see if they are working as expected.
2) On/Off Switches At this point, let’s backtrack a little to include an important mechanism that must be used between the source code and build stage, as well as between the build and test stage. This mechanism is a simple on/off switch allowing the developer to enable or disable the flow of code at any point. This is a great technique for preventing source code that isn’t necessary to build right away from entering the build or test stage or maybe preventing code from interfering with something that is already being tested in the pipeline. This ‘switch’ enables developers to control exactly what gets promoted to the next stage of the pipeline.
If there are dependencies on any of the APIs, it is vital to conduct testing on those as well. For instance, if the ‘create order’ API is dependent on a customer profile service; it should be tested and checked to ensure that the customer profile service is receiving the expected information. This tests the end-to-end workflows of the entire system and offers added confidence to all the core APIs and core logic used in the pipeline, ensuring they are working as expected. It is important to note that developers will spend most of their time in this stage of the pipeline.
ON/OFF SWITCHES TO CONTROL CODE FLOW
Production:
The next stage after testing is usually the production stage. However, moving directly from testing to a production environment is usually only viable for small to medium organizations where only a couple of environments are used at the highest. But the larger an organization gets, the more environments they might need. This leads to difficulties in maintaining consistency and quality of code throughout the environment. To manage this, it is better for code to move from the testing stage to a pre-production stage and then move to a production stage. This becomes useful when there are many different developers testing things at different times like QA or a new specific feature is being tested. The pre-production environment allows developers to create a separate branch or additional environments for conducting a specific test.
This pre-production environment will be known as ‘Prod 1 Box’ for the rest of this article.
Pre-Production: (Prod 1Box)
A key aspect to remember when moving code from the testing environment is to ensure it does not cause a bad change to the main production environment where all the hosts are situated and where all the traffic is going to occur for the customer. The Prod 1 Box represents a fraction of the production traffic – ideally around less than 10% of total production traffic. This allows developers to detect when anything goes wrong while pushing code such as if the latency is really high. This will trigger the alarms, alerting the developers that a bad deployment is occurring and allowing them to roll back that particular change instantly.
The purpose of the Prod 1 Box is simple. If the code moves directly from the testing stage to the production stage and results in bad deployment, it would result in rolling back all the other hosts using the environment as well which is very tedious and time-consuming. But instead, if a bad deployment occurs in the Prod 1 Box, only one host is needed to be rolled back. This is a pretty straightforward process and extremely quick as well. The developer is only required to disable that particular host and the previous version of the code will be reverted to in the production environment without any harm and changes. Although simple in concept, the Prod 1 Box is a very powerful tool for developers as it offers an extra layer of safety when they introduce any changes to the pipeline before it hits the production stage.
1) Rollback Alarms When promoting code from the test stage to the production stage, several things can go wrong in the deployment. It can result in:
An elevated number of errors
Latency spikes
Faltering key business metrics
Various abnormal and expected patterns
This makes it crucial to incorporate the concept of alarms into the production environment – specifically rollback alarms. Rollback alarms are a type of alarm that monitors a particular environment and is integrated during the deployment process. It allows developers to monitor specific metrics of a particular deployment and that particular version of the software for issues like latency errors or if key business metrics are falling below a certain threshold. The rollback alarm is an indicator that alerts the developer to roll back the change to a previous version. In an ideal CI/CD pipeline these configured metrics should be monitored directly and the rollback initiated automatically. The automatic rollback must be baked into the system and triggered whenever it determines any of these metrics exceed or fall below the expected threshold.
2) Bake Period The Bake Period is more of a confidence-building step that allows developers to check for anomalies. The ideal duration of a Bake Period should be around 24 hours, but it isn’t uncommon for developers to keep the Bake Period to around 12 hours or even 6 hours during a high volume time frame.
Quite often when a change is introduced to an environment, errors might not pop up right away. Errors and latency spikes might be delayed, unexpected behavior of APIs or a certain code flow of APIs doesn’t occur until a certain system calls it, etc. This is why the Bake Period is important. It allows developers to be confident with the changes they’ve introduced. Once the code has sat for the set period and nothing abnormal has occurred, it is safe to move the code onto the next stage.
3) Anomaly Detection or Error Counts and Latency Breaches During the Bake period, developers can use anomaly detection tools to detect issues however that is an expensive endeavor for most organizations and often is an overkill solution. Another effective option, similar to the one used earlier, is to simply monitor the error counts and latency breaches over a set period. If the sum of the issues detected exceeds a certain threshold then the developer should roll back to a version of the code flow that was working.
4) Canary A canary tests the production workflow consistently with expected input and expected outcome. Let’s consider the ‘create order’ API we used earlier. In the integration test environment, the developer should set up a canary on that API along with a ‘cron job’ that triggers every minute.
The cron job should be given the function of monitoring the create order API with expected input and hardcoded with an expected output. The cron job must continually call or check on that API every minute. This would allow the developer to immediately know when this API begins failing or if the API output results in an error, notifying that something wrong has occurred within the system.
The concept of the canary must be integrated within the Bake Period, the key alarms as well the key metrics. All of which ultimately links back to the rollback alarm which reverts the pipeline to a previous software version that was assumed to be working perfectly.
Main Production:
When everything is functioning as expected within the Prod 1 Box, the code can be moved on to the next stage which is the main production environment. For instance, if the Prod 1 Box was hosting 10% of the traffic, then the main production environment would be hosting the remaining 90% of that traffic. All the elements and metrics used within the Prod 1 Box such as rollback alarms, Bake Period, anomaly detection or error count and latency breaches, and canaries, must be included in the stage exactly as they were in the Prod 1 Box with the same checks, except on a much larger scale.
The main issue most developers face is – ‘how is 10% of traffic supposed to be directed to one host while 90% goes to another host?’. While there are several ways of accomplishing this task, the easiest is to transfer it at the DNS level. Using DNS weights, developers can shift a certain percentage of traffic to a particular URL and the rest to another URL. The process might vary depending on the technology being used but DNS is the most common one that developers usually prefer to use.
DETAILED IDEAL CI/CD PIPELINE
Summary
The ultimate goal of an ideal CI/CD pipeline is to enable teams to generate quick, reliable, accurate, and comprehensive feedback from their SDLC. Regardless of the tools and configuration of the CI/CD pipeline, the focus should be to optimize and automate the software development process.
Let’s go Over the key Points Covered One More Time. These are the key Concepts And Elements that Make up an Ideal CI/CD Pipeline:
The Source Code is where all the packages and dependencies are categorized and stored. It involves the addition of reviewers for the curation of code before it gets shifted to the next stage.
Build steps involve compiling code, unit tests, as well as checking and enforcing code coverage.
The Test Environment deals with integration testing and the creation of on/off switches.
The Prod 1 Box serves as the soft testing environment for production for a portion of the traffic.
The Main Production environment serves the remainder of the traffic
NeoSOFT’s DevOps services are geared towards delivering our signature exceptional quality and boosting efficiency wherever you are in your DevOps journey. Whether you want to build a CI/CD pipeline from scratch, or your CI/CD pipeline is ineffective and not delivering the required results, or if your CI/CD pipeline is in development but needs to be accelerated; our robust and signature engineering solutions will enable your organization to
Scale rapidly across locations and geographies,
Quicker delivery turnaround,
Accelerate DevOps implementation across tools.
NEOSOFT’S DEVOPS SERVICES IMPACT ON ORGANIZATIONS
Solving Problems in the Real World
Over the past few years, we’ve applied the best practices mentioned in this article.
Organizations often find themselves requiring assistance at different stages in the DevOps journey; some wish to develop an entirely new DevOps approach, while others start by exploring how their existing systems and processes can be enhanced. As their products evolve and take on new characteristics, organizations need to re-imagine their DevOps processes and ensure that these changes aren’t affecting their efficiencies or hampering the quality of their product.
DevOps helps eCommerce Players to Release Features Faster
When it comes to eCommerce, DevOps is instrumental for increasing overall productivity, managing scale & deploying new and innovative features much faster.
For a global e-commerce platform with millions of daily visitors, NeoSOFT built their CI/CD pipeline. Huge computational resources were made to work efficiently, giving a pleasing online customer experience. The infrastructure was able to carry out a number of mission-critical functions with substantial savings resulting in both: time and money.
With savings up to 40% on computing & storage resources matched with an enhanced developer throughput, an ideal CI/CD pipeline is critical to the eCommerce industry.
Robust CI/CD Pipelines are Driving Phenomenal CX in the BFSI Sector
DevOps’ ability to meet the continually growing user needs with the need to rapidly deploy new features has facilitated its broader adoption across the BFSI industry with varying maturity levels.
When executing a digital transformation project for a leading bank, NeoSOFT upgraded the entire infrastructure with an objective to achieve continuous delivery. The introduction of emerging technologies like Kubernetes into the journey enabled the institution to move at startup speed, driving the GTM 10x faster rate.
As technology leaders in the BFSI segment look to compete through digital capabilities, DevOps & CI/CD pipelines start to form their cornerstone of innovation.
A well-oiled DevOps team, structure, and ecosystem can be the difference-maker in driving business benefits and leveraging technology as your competitive edge.
What do developers want? Money, flexible schedules, pizza? Sure. Effortless remote collaboration? Hell, yes! Programming is a team sport and without proper communication, you can’t really expect spectacular results. A remote set-up can make developer-to-developer communication challenging, but if equipped with the right tools, you have nothing to fear. Let’s take a look at the best VS Code extensions that can seriously improve a remote working routine.
1. Live Share
If you’ve been working remotely for a while now, chances are you’re already familiar with this one. This popular extension lets you and your teammates edit code together.
It can also be enhanced by other extensions such as Live Share Audio which allows you to make audio calls, or Live Share Whiteboard to draw on a whiteboard and see each other’s changes in real-time.
Benefits for remote teams: Boost your team’s productivity by pair-programming in real-time, straight from your VS Code editor!
2. GitLive
This powerful tool combines the functionality of Live Share with other super useful features for remote teams. You can see if your teammates are online, what issue and branch they are working on and even take a peek at their uncommitted changes, all updated in real-time.
But probably the most useful feature is merge conflict detection. Indicators show in the gutter where your teammates have made changes to the file you have open. These update in real-time as you and your teammates are editing and provide early warning of potential merge conflicts.
Finally, GitLive enhances code sharing via LiveShare with video calls and screen share and even allows you to codeshare with teammates using other IDEs such as IntelliJ, WebStorm or PyCharm.
Benefits for remote teams: Improve developer communication with real-time cross-IDE collaboration, merge conflict detection and video calls!
3. GistPad
Gists are a great way not only to create code snippets, notes, or tasks lists for your private use but also to easily share them with your colleagues. With GistPad you can seamlessly do it straight from your VS Code editor.
You can create new gists from scratch, from local files or snippets. You can also search through and comment on your teammate’s gists (all comments will be displayed at the bottom of an opened file or as a thread in multi-file gists).
The extension has broad documentation and a lot of cool features. What I really like is the sorting feature, which when enabled, will group your gists by type (for example note — gists composed of .txt, .md/.markdown or .adoc files, or diagram — gists that include a .drawio file) which makes it super-easy to quickly find what you’re looking for.
Benefits for remote teams: Gists are usually associated with less formal, casual collaboration. The extension makes it easier to brainstorm over the code snippet, work on and save a piece of code that will be often reused, or share a task list.
4. Todo Tree
If you create a lot of TODOs while coding and need help in keeping track of them, this extension is a lifesaver. It will quickly search your workspace for comment tags like TODO and FIXME and display them in a tree view in the explorer pane.
Clicking on a TODO within the tree will bring you to the exact line of code that needs fixing and additionally highlight each to-do within a file.
Benefits for remote teams: The extension gives you an overview of all your TODOs and a way to easily access them from the editor. Use it together with your teammates and make sure that no task is ever forgotten.
5. Codetour
If you’re looking for a way to smoothly on-board a new team member to your team, Codetour might be exactly what you need. This handy extension allows you to record and playback guided walkthroughs of the codebase, directly within the editor.
A “code tour” is a sequence of interactive steps associated with a specific directory, file or line, that includes a description of the respective code and is saved in a chosen workspace. The extension comes with built-in guides that help you get started on a specific task (eg. record, export, start or navigate a tour). At any time, you can edit the tour by rearranging or deleting certain steps or even change the git ref associated with the tour.
Benefits for remote teams: A great way to explain the codebase and create project guidelines available within VS Code at any time for each member of the team!
6. Git Link
Simple and effective, this extension does one job: allows you to send a link with selected code from your editor to your teammates, who can view it in GitHub. Besides the advantage of sharing code with your team (note that only committed changes will be reflected in the link), it is also useful if you want to check history, contributors, or branch versions.
Benefits for remote teams: Easily send links of code snippets to co-workers.
Conclusion
Good communication within a distributed team is key to productive remote working. Hopefully, some of the tools rounded up in this short article will make your team collaboration faster, more efficient and productive. Happy hacking!
Whether you are already an experienced developer or just starting out, if you want to become really good in this industry, you need to constantly sharpen your skills to stay relevant. Here are some of the most valuable developer skills to tackle this year.
Of course, you won’t need all of them and this list isn’t complete. But it should give you a good idea of what to learn next or what to improve on.
1. Practice Coding Every Day
Even if it’s for only 30 minutes. This will help you learn the best development practices and grow your skills. It will also help you stay in top form and master new technologies.
2. Learn To Be A Good Communicator (Both While Writing And Speaking)
You don’t need to speak English like a native speaker, but you do need good enough communication skills to help clients understand what you are saying. Whether it’s in meetings, emails, or even on the phone, you don’t want to lose a client because they couldn’t understand your words. Also, good speaking and writing skills help make you stand out from other developers.
3. Practice Object-Oriented Design Principles
Even if you just started programming, learning OOP will give you many benefits over time. It will also make it much easier for you to read other people’s code, which is essential when working with other developers and your team members.
4. Learn How To Use Version Control Systems (e.g. Git) Effectively
Version control systems are essential for any developer who works on multiple projects simultaneously or collaborates with other developers on projects.
5. Improve Your Problem-Solving Skills
Software development is a complex field. You’ll be exposed to many different problems and tasks during your career. Make sure you can solve them effectively by learning how to think like a developer.
6. Learn How To Use Design Tools Such As Photoshop, Sketch, And Illustrator
Good-looking websites and apps are essential if you want to create high-quality products that users love. While it’s possible to learn how to design using tutorials and YouTube videos, most of the time, you will need some formal training in this area when you start working on real projects.
7. Keep Learning New Technologies And Languages
Don’t get stuck on one stack! Learning new languages and frameworks will help you stay employable in this industry. If you have had the same stack for a long time, then there is a good chance that your skills will become obsolete over time. Always try to stay up to date with the newest technologies used by top developers around the world.
8. Learn At Least One Scripting Language (e.g. Python)
Scripting languages are useful for automating repetitive tasks. Even if you don’t want to become a full-time developer, scripting can make your life easier as a software engineer.
9. Learn How To Write Clean And Maintainable Code
You will have to spend lots of time reading other people’s code. If the code is not clean, then it will be very hard for you to understand what’s going on. So you must write clean and readable code yourself.
One way to improve your coding skills is by writing unit tests (e.g. by using JUnit). This will help you catch bugs early in the development process. Also, try to keep your methods short so it will be easier to read them later when you need to come back and fix something in the project that you wrote months ago.
10. Learn To Think Ahead And Plan Out How A Feature Should Work Before You Start Developing It
It takes time to go from writing an initial idea for a feature/product/bug fix to having that feature ready on the market. You need to be able to think ahead and make sure that everything fits together properly during this whole process (and also after). This includes planning with your team members, asking users what they want, talking with stakeholders about their requirements, etc. Don’t just start coding things without thinking first!
11. Learn How To Implement Security Measures Properly
There is a lot of information out there about security, and it’s easy to get confused and overwhelmed. Make sure that you go beyond the obvious like ‘make sure your password is strong enough’ and learn more about security threats and how to fix them.
12. Don’t Be Afraid To Ask Questions
Asking questions is a great way to learn. One of the biggest mistakes you can make is to assume that you know everything. Many developers tend to think that asking for help is a sign of weakness, but it’s actually a sign of strength. If you don’t understand something, ask someone who does and then try to figure it out yourself as well. This will help you gain a deeper understanding of the topic in question.
13. Learn How To Work With Different Environments (Mac, Linux, Windows)
You don’t have to become an expert in all platforms, but you should know how they work and what their pros and cons are. Also, knowing how different development environments work will allow you to save time when switching between them. For example, developing an Android app on Windows or Mac will force you to change your workflow since the process is quite different from using Linux or Ubuntu.
14. Practice Pair Programming Regularly With Your Team Members (or Others)
Pair programming means two people working together on one computer at the same time — one person sitting behind the keyboard writing code while the other person observes and gives feedback/suggestions/code reviews, etc.
Pair programming has many benefits, including a better understanding of the problem domain, sharing knowledge and ideas between team members, faster debugging, etc. It also allows developers to get comfortable with each other through regular communication and helps team members build trust towards each other, which greatly improves teamwork.
15. Understand Design Patterns (SOLID Principles And Object-Oriented Design Patterns)
You don’t have to know every single pattern by heart, but understanding what they are will help you a lot as a software developer. Object-oriented design patterns are used repeatedly in different frameworks and technologies, so understanding them will be extremely useful for your job as a software developer.
The SOLID principles guide us when writing code:
Single-responsibility principle
Open/closed principle
Liskov substitution principle
Interface segregation principle
Dependency inversion principle
16. Learn How To Deal With Change As A Software Developer
When working on new projects or even when working with existing code base, things change from time to time (and not always because we want them to). You need to constantly adapt to these changes if you’re going to continue being productive in this business. If you cannot handle change well, you will eventually get stuck with outdated skills that won’t help you much anymore.
17. Learn How To Put Yourself In Other People’s Shoes
This is a beneficial skill in the software development industry. You need to learn how to see things through your client’s eyes and try to understand what they want or need. You need to communicate with them and make sure you deliver what they want.
18. Learn About Business Processes And Soft Skills
It doesn’t matter if you work for yourself or for another company. You must understand business processes and soft skills like communication, time management, problem-solving, and more. These are all crucial skills that will make you stand out from other developers who don’t know anything about this stuff.
19. Learn How To Deal With Deadlines
Everybody knows that projects sometimes run late and deadlines are not met. As a developer, you need to learn how to meet deadlines by setting smaller checkpoints in your projects that you can check off as you go. This will help you be more efficient and get the job done on time.
20. Learn How To Learn New Technologies Fast
As mentioned before, developers need to stay relevant and learn new technologies quickly. This means learning new languages and learning about new frameworks or libraries that can help you solve problems more efficiently. It’s not only important that you know about the technology but also why it’s better than the others.
If you don’t understand something or there is something that isn’t clear to you, ask questions! Don’t be afraid of looking stupid because if someone doesn’t understand something, they will never fully master it!
If you ever had a chance to compare the resumes of 2 developers who come from nearly identical backgrounds and skills – languages, frameworks, platforms, methodologies, industries; you may find them practically to be the same person – on paper. However, not both could be equal while comparing their success metrics.
The roadmap to success for a developer is not limited to bearing technical skills and credible experience. It is a long journey of immense hard work and dedication as well as crucial behavioral characteristics and optimal mindset that sets one apart from the crowd. To make a mark in the software development industry, there are a few traits and habits that are widely considered by professionals as value-boosting add-ons that give them an edge over the rest. 1. Write Clean, Readable, And Reusable Code
In the context of software development, everyone can write code, but not everyone can write good code. A successful developer is the one who makes sure their code is clean, robust, flexible, and reusable – not just for themselves in the future but also for anyone else working on it in the future, irrespective of the coding standard or methodology used. While it is easy to write line after line and not pay attention to your function size, you need to pause and remember that you’re going to be spending more time reading and testing it than writing it. It is important to understand that when you go back to read it, you should be able to understand it quickly and know what you’re meant to do. 2. Constantly Expand Your Knowledge Base
Underestimating oneself is dangerous – but so is overestimating. A successful software developer is never complacent; they know there is always something new that they do not know about and are always levelling up their know-how.
Be on the lookout for new improvement opportunities. To keep pace with the advancements, you can join skill enhancement programs, online training, read tutorials, watch videos, etc. Upskilling yourself will be a valuable habit to develop in your career. 3. Be Disciplined And Persistent
A successful software developer is constantly looking to expand their knowledge and sticking their nose into new languages. However, that route is not free of obstacles. To successfully learn something new and gain expertise, one needs to be stubbornly disciplined and not too attached to their comfort zones.
Being disciplined helps finish what you started – and on time – without compromising on quality for speed. Persistence, on the other hand, is what will help you to go beyond the pain-points, beat all the odds and obstacles, and ace your deadlines – both personal and professional. 4. Get Help From Strangers On The Internet
Don’t confuse persistence with pride. Successful developers don’t allow their egos to turn a programming problem into an unnecessary productivity drain—especially not when a solution may be readily available online. Sometimes, asking for help—yes, Google counts—is the most efficient first step toward a solution. Research what the code does and why it solves the problems. Do not just cut/copy and paste. Lack of background knowledge could create problems in your code. 5. Know Your Forte
Not everyone is made for doing everything. You may be good at developing UI and UX but may not be an expert at developing the back-end of an application. Successful software developers know their forte and work around that to succeed in whatever they do. 6. Be Open For New Things
Another habit of successful developers is being open to new things and going the distance in embracing them when it is required. To meet a client’s expectation, a developer may be required to go an extra mile in researching and discovering every aspect of technology. Successful developers are in a constant feat of exploring new technologies, methodologies, and frameworks that help them stay abreast with the latest trending topics. 7. Listen More Than You Speak—Or At Least Listen Before You Speak
If you’re in an office with other developers, listen first, then speak. It’s the quickest way to learn.
This requires humility, especially if you think you’re the smartest person in the room. Great developers have the ability and willingness to admit when they do not know something. Refrain from being that programmer who spews out a bunch of technical jargon instead of acknowledging they might not yet know the answer to a particular question. 8. Pay Attention To The Details
Any successful developer can tell you that to write a perfect code or to complete a project, one needs to pay detailed attention to the client’s requirements and work accordingly. You would not want to work on a piece of code again and again because of a small semicolon that you forgot to add while terminating a line of code. Similarly, be responsible for the objective and the goal that the code you are working on is intended to achieve. Successful developers are always aware of how each line of their code helps to drive the business as a whole. 9. Deeply Focus On The Right Thing
The ability to focus on the shared goal of a particular project without getting side-tracked by nice-to-haves or pie-in-the-sky thinking that isn’t moving you closer to your target is vital. It is understandable to go down rabbit holes or get wrapped up in the edge cases of a particular technical implementation. When you step back a little bit, you might realize that you’re putting a lot of effort into something that is not that crucial to the broader goal that everyone is trying to achieve. Make sure you’re on the same wavelength as the rest of the team. Successful developers understand that innovation is a team sport. 10. Have The End Product In Mind All The Time
You cannot hit a target that you cannot see. You must set clear goals for where you are headed and what you really want to achieve at the end of your project. If you start developing a project keeping this mantra in your mind, there is always a better chance to stand out from the rest.
Source: https://content.techgig.com/7-habits-of-successful-developers/articleshow/72996679.cms
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