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Generative AI and Its Evolving Role in Software Development

Remember the days when software development was solely the domain of humans painstakingly writing lines of code? Those days are evolving rapidly. Generative AI, a branch of artificial intelligence capable of creating original content, is quickly becoming the co-pilot for software developers worldwide. This technology, leveraging advanced models like GPT-4, is not only automating mundane tasks but is also opening doors to unprecedented creativity and efficiency in the software development lifecycle.

 The Rise of AI Coding Companions

Generative AI models, like OpenAI’s ChatGPT or GitHub’s Copilot, have emerged as powerful allies for developers. These models can:

  • Generate Code: Need a function to sort a list? Just describe what you need, and the AI can generate the code for you.
  • Complete Code: Start typing a line of code, and the AI can suggest how to finish it, saving you keystrokes and brainpower.
  • Refactor Code: Want to clean up or optimize your code? The AI can suggest improvements.
  • Explain Code: Encountered a complex piece of code? Ask the AI to break it down for you in simple terms.
  • Detect Bugs: The AI can scan your code for potential bugs and suggest fixes, reducing the time spent on debugging.

Boosting Productivity and Creativity

The benefits of these AI coding companions are clear:

  • Increased Efficiency: Developers can accomplish tasks much faster, from writing boilerplate code to debugging complex issues.
  • Enhanced Creativity: The AI can offer alternative solutions or suggest innovative approaches, sparking new ideas.
  • Reduced Tedium: Developers can focus on higher-level problem-solving instead of getting bogged down in repetitive tasks.
  • Accelerated Learning: Newcomers can learn faster by getting instant feedback and explanations from the AI.

Real-World Applications

Generative AI isn’t just a theoretical concept; it’s already being used in the real world:

  • GitHub Copilot: This popular tool integrates with various code editors, providing code suggestions and completions in real time.
  • Tabnine: Another AI-powered code completion tool that supports multiple languages and frameworks.
  • Replit Ghostwriter: This tool offers AI-powered code generation, completion, and transformation features.
  • Deep TabNine: A deep learning-based code completion tool that can be integrated with various IDEs and text editors.

Challenges and Considerations

While the potential of generative AI is exciting, there are also challenges to address:

  • Accuracy: AI-generated code might not always be perfect and may require human review and correction. While these tools can significantly speed up the coding process, developers should still verify the AI’s suggestions to ensure they meet required standards and project specifications.
  • Bias: AI models can inherit biases from their training data, leading to potentially biased or unfair code suggestions. This requires developers to remain vigilant and critically assess any suggestions made, ensuring equitable and inclusive coding practices.
  • Security: The security of code generated by AI needs careful consideration to prevent vulnerabilities. Developers must be aware of potential security gaps and rigorously test AI-generated code to protect against cyber threats and maintain the integrity of their applications.
  • Ethics: As with any technology, the ethical implications of AI in coding should be carefully evaluated and addressed. This entails considering the broader impact of AI-generated solutions and ensuring that their use aligns with ethical standards and promotes positive societal outcomes.

The Future of AI-Assisted Development

The future of AI software development services is undoubtedly intertwined with generative AI. As these models continue to improve, we can expect even more sophisticated tools that will:

  • Understand Natural Language Better: Allowing developers to communicate with AI in a more intuitive way. As natural language processing capabilities advance, developers will be able to describe the functionality they need in plain English, and the AI will generate the corresponding code, reducing the need for detailed programming knowledge.
  • Generate More Complex Code: Tackling larger, more complex programming tasks. Future AI models will be capable of handling intricate logic, cross-functional dependencies, and larger codebases, thus enabling the automation of more sophisticated software projects.
  • Integrate with More Development Tools: Becoming a seamless part of the developer’s workflow. As generative AI tools continue to evolve, their integration with a wider range of development environments, version control systems, and project management tools will ensure a smoother and more cohesive development experience.

The Developer Nation Survey, a comprehensive look at developer trends, already highlights a growing interest in AI tools for coding. This indicates a shift in how developers perceive and use AI, moving from skepticism to embracing its potential.

Conclusion

Generative AI is a game-changer for software development, offering a glimpse into a future where humans and AI collaborate to create more efficient, innovative, and secure software. While challenges remain, the potential benefits are too significant to ignore. As we move forward, developers who embrace these AI-powered tools will be well-positioned to thrive in the ever-evolving landscape of software development.

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Cloud Application Performance Monitoring: Strategies to Boost User Experience

The performance of cloud applications plays a big role in user experience. At the end of the day, we’re all looking for a smooth-running service that’s free from bugs and crashes. A slow-running app is a one-way street to frustrated users, but you can avoid this eventuality with Cloud Application Performance Monitoring (CAPM). 

CAPM is the process by which you track and manage the performance of cloud applications. It involves monitoring the key metrics that determine performance and taking measures to optimise where necessary. Overall, the goal is to achieve the best possible experience for all of your users. 

What is CAPM?

Cloud application performance management is achieved by monitoring important performance metrics so that any issues looming on the horizon are caught early. It helps you to maintain the best user experience possible and should be a key part of your customer orientation strategy.

Core Components of CAPM

Let’s take a look at the essential elements of CAPM: 

  • Real-time monitoring: Application performance is continuously tracked to pick up issues instantly, meaning no problem goes undetected. For instance, a live chat app relies heavily on real-time monitoring to ensure smooth and uninterrupted user interactions, making it crucial to address any performance issues immediately.
  • Alerts and notifications: You can set up alerts to notify you when performance metrics drop out from the acceptable range, so you’re always kept in the loop.
  • Root cause analysis: Knowing there is a problem is only half the story. Root cause analysis will also tell you what the underlying problem is. 
  • Performance optimisation: This is where you swing into action to make the changes needed to get your cloud application performance back on track.

CAPM vs. Traditional APM

If you’re familiar with application performance monitoring, you might be wondering if CAPM is really so different. However, they are distinct in a few ways. 

Environment Focus

Traditional APM typically applies to on-premises applications and, as the name suggests, CAPM focuses on cloud-based applications. What’s important about this differentiation is that on-premises applications need to be monitored within a static, controlled environment, whereas cloud applications require a dynamic environment that can change based on usage and demand.

Scalability

Cloud environments are scalable by nature, and CAPM is able to handle this. As user demand rises or drops, CAPM can likewise scale resources up and down, achieving optimal performance with minimum manual intervention. Meanwhile, traditional APM usually deals with fixed resources that need manual adjustments.

Integration

The transition from mainframe to cloud applications is an important consideration. CAPM integrates with cloud services and platforms to allow for comprehensive monitoring across different components within the cloud ecosystem. This provides a complete view of the performance of the application, whereas traditional APM tools are unlikely to offer the same level of integration with cloud-specific services, and are therefore less effective. 

Moreover, as CAPM integrates deeply with cloud services and platforms, it also expands the attack surface — the set of points where unauthorized access can occur. Therefore, it is crucial to ensure that security measures are part of the performance monitoring process to protect against vulnerabilities that could be exploited through these additional points of exposure.

Resource Allocation

APM’s primary focus is on the application itself, and this rarely widens to the infrastructure around it. CAPM, on the other hand, not only monitors the application’s performance but keeps an eye on the underlying infrastructure and resources. Memory, CPU, and storage are all tracked to assess if they are being used efficiently.

Key Metrics in CAPM

The effectiveness of CAPM lies in closely monitoring the right metrics.

Response Time

How long is a user waiting for an application to respond to a request? Faster response times keep everything ticking over quickly and, most importantly, keep users happy. High response times point to performance bottlenecks, suggesting improvement might need to be made in database indexing strategies or in optimising server configurations to speed up retrieval times.

Error Rates

Keeping on top of the frequency of errors happening within the application will tell you where there are common problems that are damaging the user experience. If errors are happening a lot users are likely to get frustrated quickly, and you may lose their trust. As such, lowering error rates should be a top priority.

Request Rates

How is the application managing traffic? This metric will tell you the volume of user requests currently being handled, which makes sure the application scales as needed. As high request rates can put a strain on resources, causing slowdowns or even crashes, they need to be monitored to keep performance steady during peak times.

Application Availability

Measuring the accessibility of an application and the extent to which it’s operational shows you how consistent your service is. High availability is a must to make sure users know they can rely on the application to be there when they need it, whereas excessive downtime can damage that trust.

Strategies for Effective Cloud Application Performance Monitoring

Use these tactics for CAPM to work at maximum effectiveness.

Ensure Compatibility with Existing IT Infrastructure

Effective software development practices are crucial for integrating CAPM tools with existing IT infrastructure, ensuring that all systems operate cohesively and are aligned with business objectives.

Before you go live, conduct some tests to make sure everything is working well together and the data you’re capturing is accurate. If you have a team, provide them with adequate training. 

Managing Real-Time Monitoring and Alerts

When you are informed in real-time of high error rates or slow response times, you can fix issues before they snowball and cause big problems for users. Configure alerts for specific performance thresholds, so you or your team members get immediate notification if anything doesn’t look right. 

For example, if the average response time of an application is usually 200 milliseconds, a consistent response time of 500 milliseconds for more than five minutes would send an alert. Every alert should be integral to performance and actionable, so when one comes through, you know it’s important. 

Additionally, your thresholds should be precisely defined based on historical data to balance sensitivity and relevance. There should also be clear incident management protocols that kick in, in response to an alert, with assigned roles and documented procedures. Maintain DevOps best practices by regularly reviewing and adjusting thresholds to maintain the highest performance standards for your cloud application.

If you use a WordPress site for your business, incorporating a WordPress table plugin can help you effectively organize and display performance data in a clear and accessible manner.

Root Cause Analysis

Finding out the underlying cause of cloud application performance issues requires effective Root Cause Analysis (RCA). This way, you both fix the problem and stop it from happening again. One of the best techniques for identifying the root cause of an issue is log analysis, where you examine the logs to find errors and anomalies. 

Another effective technique is transaction tracing, which tracks the journey of a transaction through an application to discover where bottlenecks are occurring. Performance profiling is also useful, monitoring resource usage and revealing where the most resources are being consumed.  

CAPM tools have advanced features on their dashboards that provide real-time and historical data, so you can detect what may be a recurring theme or a one-off anomaly. With error tracking, you can capture in-depth information about errors, such as stack traces and user actions, which are integral for root cause diagnosis. 

Tools should also offer synthetic monitoring, which simulates user interactions to test performance issues without affecting real users. 

Optimise Application Responsiveness

You’re looking to optimise application responsiveness wherever possible to reduce latency, provide quicker user interactions, and prevent negative repercussions for users. Suppose, for example, high latency was occurring in a cloud-based CRM platform. This could slow down valuable tasks like sales discovery calls, leading to irritated users and missed opportunities. 

Combat slow load times by using content delivery networks (CDNs), employing efficient caching strategies, and optimising database queries. Improved performance will give users confidence that the application will always allow them to complete tasks without delay. 

Ensure Application Availability

Maintain high availability and reduce downtime by establishing redundancy and failover mechanisms. Redundancy involves duplicating all the critical components and systems so that if one fails, another can take over without disrupting service. For instance, cloud-based call centre software might use redundant servers to ensure continuous operation, even during hardware failures.

Failover mechanisms play a similar role, automatically redirecting traffic to backup systems when the primary system is unavailable. This is invaluable for applications that have a big impact on sales or customer service, where downtime can be seriously costly. 

There is also a benefit to adopting cloud-native practices like auto-scaling and load balancing. Auto-scaling adjusts resources in real-time based on demand and prevents the overloading of servers, while load balancing spreads the traffic evenly across servers, improving application availability. 

Remember, all these mechanisms should be tested regularly to make sure they are ready when a real problem arises.

The Future of Cloud Application Performance Monitoring

CAPM will continue to be an area that improves as technology evolves. The impact of generative AI has already made itself known, as AI and machine learning fuel predictive analytics in CAPM. This technology supports proactive performance management, discovering problems before they start to affect users. Edge computing allows for data to be processed close to the source, reducing latency and improving responsiveness.  

Transform User Experience with CAPM

Providing the best possible user experience for your cloud-based applications is a top priority for any developer, and cloud-based performance monitoring is, without a doubt, one of the best ways to make it a reality. 

CAPM gives you the heads up as soon as anything deviates from acceptable standards, so you can take action immediately. The visibility it gives you means no delays or bugs will go unnoticed and you can both fix issues promptly and understand how to stop them happening again. 

Altogether, it’s the ideal approach to keep your application working perfectly and your users satisfied and happy.

Austin Guanzon – Tier 1 Support Manager

Austin Guanzon is the Tier 1 Support Manager for Dialpad, the leading AI-powered customer intelligence platform. He is a customer retention and technical support expert, with experience at some of the largest tech service companies in the US.You can find him on LinkedIn.

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9 Best Security Practices For REST API Development

If you work in any area of application programming interface (API) development, you’ll know that there are always concerns. Will the software manage errors effectively? How will it cope with large datasets? The list seems endless at times. One major concern many developers focus on is the security threats their APIs may face. 

With the cost of cybercrime expected to reach $13.82 trillion by 2028, the issue of cybersecurity is very real. If you are developing REST APIs, what threats might you face, and how should you be tackling them? Should you have a checklist of best practices during development to minimize any potential threats?

What is REST API?

Security Practices For REST API

An application programming interface (API) is a list of protocols and definitions developers use when building application software. To define it simply, it’s a ‘contract’ between the application user and the application. You could also see it as a communication conduit that communicates a request and allows for an exchange of information and/or data.

REST API (you may also hear the term RESTful API) is an application programming interface developers utilize when working in the REST (representational state transfer) architecture that allows for communication between RESTful web services. 

REST API security threats

Security Practices For REST API

To paraphrase Sun Tzu, knowing your enemy is crucial. By knowing what cyber security threats (especially the most common ones) your REST API may face, you can better plan for how to prevent those threats. 

We’ve listed some of them below:

  • Denial of Service (DoS): When a DoS attack occurs, the system is overloaded by an enormous amount of messages sent by a cybercriminal. If your REST API experiences a successful DoS attack, then it could be rendered non-functional and accessed by the attackers. 
  • Injection attack: This attack can allow cybercriminals access to often sensitive data and information. The attacker embeds a dangerous code into unsecured programs, often SQL injection or cross-site scripting. 
  • Sensitive data exposure: If there is a lack of encryption at any point in how your API handles data, then it may be exposed to attack. When you consider that a lot of data (health details, credit card info, etc.) is highly confidential, unsecured data can be a major risk. 
  • Broken authentication: If you have inadequate or missing authentication, you are leaving your API and app open to a cyberattack. From passwords to JSON web tokens to API keys, this can be a major weak point if not tackled. 
  • Parameter tampering: If a cybercriminal manipulates the parameters that are exchanged between user and server, they can modify various data in the application such as prices, product quantities, and user credentials. This can pose a major risk to enterprise collaboration systems
  • Man in the Middle (MITM): As the name suggests, with this type of attack, the cybercriminal positions themselves between two systems and intercepts the communications. This allows them to alter or steal any confidential data. There are two stages to MITM attacks; interception and decryption.
  • Broken access control: Access control (or authorization) is how you limit access to some functions or contents. If your access control is faulty or flawed, attackers can access data or take control of accounts. 

Moreover, Implementing proxy detection mechanisms can help identify and mitigate attacks originating from suspicious or anonymized sources, adding an essential layer to your security framework.

9 best security practices for REST API development

Security Practices For REST API

You are now aware of some of the most common security threats your REST API may face. You have to assume that any program or system is under threat, whether it is a banking app or an AI customer care program. In the development stage, what security measures should you implement or advise users to use?

1. TLS (transport layer security) encryption 

The data transferred by your API—such as B2B intent data—is important and can have varying degrees of confidentiality. If you use TLS for your API, then all communications between the end user and the application will be encrypted. 

TLS is not only good for your REST API but also for your web app. It will also secure any authentication credentials such as passwords, tokens, or API keys. 

2. Have a robust authentication and authorization model

You may use common techniques—such as security tokens or API keys—to manage access to your REST API. However, managing those keys and tokens can present its own challenges. 

The complexity of managing those access options can lead to security vulnerabilities for your REST API. You can reduce security risks in this area by integrating your API with an identity management system that will both issue and authenticate tokens and keys. You can also use a centralized gateway for your API that will protect your data.

3. Keep URLs free of sensitive information

One of the most common design flaws with REST APIs is the inclusion of sensitive information in the URL. This can include things such as API keys, user credentials, or tokens. Even if you are using TLS, cybercriminals can easily discover this information. 

You also have to consider that your URL may be logged frequently by the servers it passes through and any networking devices on the API’s data path. This can expose any sensitive information to further threats. Always ensure that any URL you use is free of all sensitive data and that you follow online security protocols.

4. Utilize the cloud for large API security datasets

Security Practices For REST API

If you operate your API security on-premises, then you will have a limit when it comes to analyzing activity. Not only are you limited to short windows, but that API data is then discarded. Given that many cyberattacks are ‘slow burn’ and can happen over weeks or months, this can render your security ineffectual. 

If you instead use the cloud for data from your API’s activity, you are accessing the computational power and scalability to analyze activity over longer periods. It also means you can conduct more detailed analyses and boost your security. 

5. Use behavioral analytics

The power afforded you by using the cloud for API activity data also means that, once you have accumulated enough activity data, you can use behavioral analytics. Behavioral analytics can be very useful when it comes to formulating an outbound sales strategy, but it can also be an important tool in your security strategy. 

Furthermore, incorporating tools like a cold emailing tool to enhance engagement can optimize your interactions with potential clients, leveraging the insights gained from your data analysis. This approach not only supports sales initiatives but is also an important tool in your security strategy.

The first benefit of applying behavioral analytics is that it identifies all the players and may include end users as well as legitimate business processes. You can then identify ‘normal’ patterns of usage and, from that, make it easier to identify any ‘abnormal’ behavior that may indicate a security threat.

6. Implement continuous discovery

It’s not always about the REST API you’re developing now. Even with the best security measures, developers can be caught out by ‘shadow’ APIs. These could exist in old legacy infrastructure or may have been implemented outside of your normal processes. Whatever their origins, they can pose a real threat to your API’s security. 

Utilizing collaboration software in this continuous discovery process can ensure that information about all APIs is shared and understood by all relevant teams, enhancing transparency and proactive management.

By implementing continuous discovery, you can build an inventory of all APIs. You should be looking at data from API activity that includes the following sources:

  • Any API gateways
  • Your content delivery networks (CDN)
  • Cloud provider logs
  • Log management systems

Analyzing the data collected from these sources will identify all APIs in use across your systems. If you find other REST APIs that are now defunct but causing issues, you can look to remove or decommission them.

7. Provide narrow definitions for requests and responses

Cybercriminals look to utilize APIs in malicious ways. This means that a request (or response) may not be what it purports to be. By providing narrow definitions for API requests—such as format, parameter types, length, etc.—you reduce the chances of an attack using requests to your API. 

It can also help if you extend these narrow definitions that your REST API is able to provide. Consider limiting the responses to content types such as GET or POST. 

8. Share and collaborate

It may seem obvious, but one of the best security practices you can follow is to share and collaborate. Highlighting how your REST API is being used, and what security threats it faces (or any vulnerabilities you may have identified) and sharing that information with your DevOps team and other relevant personnel can help mitigate risk. This can be especially helpful if you have teams using cross-platform development tools.

9. Be proactive and hunt for threats

Don’t wait till threats become a very real risk, seek them out so you can take action. If you do wait, then there is a chance that a risk becomes an incident, one that could damage your business. Implementing preventive maintenance for your systems and regularly updating security protocols can further strengthen your defenses against potential breaches.

If you go looking for threats, you may find there have been unsuccessful attempts but these can help you find weaknesses and shore them up. 

Close analysis of your API’s usage activity can also expose any previously undiscovered vulnerabilities before they are exploited. As the saying goes, prevention is better than cure.

Security Practices For REST API

The takeaway

As cyber criminals get cleverer and find new and innovative ways to mount attacks, you need to keep up with them or ideally ahead of them. These criminals often find APIs as a convenient way of gaining access to an app or system and stealing any data and information used and stored there. 

There will always be attacks and there will always be vulnerabilities with REST APIs, but developers have a responsibility to reduce and mitigate any identified risks. By following these best practices, you are taking an important step to making your API less prone to any attack.

Austin Guanzon – Tier 1 Support Manager

Austin Guanzon is the Tier 1 Support Manager for Dialpad, the leading AI-powered customer intelligence platform. He is a customer retention and technical support expert, with experience at some of the largest tech service companies in the US.You can find him on LinkedIn.

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What is Developer Experience and Why Should You Care?

With all the talk of users and customers, you’d be forgiven for thinking they were the only stakeholders who matter. However, the truth is that for any company producing software, their dev teams matter at least as much. Developer experience should be a top priority for businesses in 2024.

What is developer experience?

Developer experience (DX) is an umbrella term for everything affecting the way software developers work. It shares many of the same factors as user experience, such as accessibility and engagement. In fact, when it comes to applications for software development like APIs or SDKs, user and developer experience are one and the same.

However, developer experience often refers to the experience of the team creating software to be sold by your business. Say you have a team designing Contact Center as a Service (CCaaS) software. You’ll need a solid developer experience strategy for your team to work efficiently and support the product long-term.

Why it matters

Behind every successful app or web service are a vast number of work hours and the contributions of any number of people. Poor developer experience is rife with obstacles and inefficiencies. Perhaps there isn’t a quick way of mediating between different dev apps and data collection tools, for example.

It’s important to resist the “if it ain’t broke, don’t fix it” mentality with things like this. Even if your team is used to working around a given issue, it’s still a drain on time and energy, which means less left over for innovation or running additional product testing.

Of course, developer experience isn’t just about workflow or setup. It’s also about the support you provide your dev team as their employer. After all, it’s important to keep your people fresh if you want them to do their best work.

For a glimpse of what happens when dev teams don’t get this support, look at Developer Nation’s State of Developer Wellness report for 2024.

83% of surveyed developers reported experiencing burnout at some stage in their careers. 84% had to work overtime “at least occasionally.” 38% reported dissatisfaction with this, and a further 8% reported overwhelming dissatisfaction.

Of course, some overtime is inevitable in full-time work. It’s still important, however, to consider when it may be unnecessary or excessive.

It’s also important to remember that burnout isn’t merely being tired at the end of a long week. It’s the cumulative result of ongoing stress and exhaustion. If someone regularly gets given unreasonable workloads, they’ll still be there at the end of a weekend off.

The responsibilities of DX teams and specialists

Developer Experience

Developer experience hasn’t historically been considered to be as essential as user experience, but many tech companies have DX specialists or even dedicated teams nowadays. These personnel help to keep things running smoothly by maintaining support processes and identifying potential blockers.

Before we get into how to improve your company’s developer experience, let’s look at some of the core responsibilities for your DX team.

Technical documentation

Technical documentation may not be the most interesting thing in the world, but it’s essential for keeping your people on the same page. Think patch notes, user manuals, or any additional knowledge resources.

To further empower developers, incorporating self-service resources within this documentation can be a game changer. This acts as a knowledge base from which developers can find solutions and learn independently, enhancing their ability to handle challenges more efficiently and reducing downtime.

Each iteration of your platform could include any number of changes, large or small. As such, technical documentation is essential for your people to keep track of them. This helps to standardize their approaches and keeps different devs from accidentally working against each other.

Proper documentation is also the best tool for getting new members of your team up to speed on how the product works.

Let’s say you’re designing a platform as part of plans to start a virtual call center, and you’ve designed your own proprietary VoIP system. New hires need a working knowledge of the digital architecture before they can meaningfully contribute to the development process. Otherwise, they’ll be operating on potentially incorrect assumptions, which is a quick path to bugs and incompatibility errors.

Establishing efficient workflow procedure

While all roads may lead to Rome, some definitely get there more quickly than others. As such, another key developer experience responsibility is to define workflow.

You need to set up efficient procedures for everything, from stack management and testing to the documentation underpinning everything. This helps to prevent internal bottlenecks, as well as mistakes and oversights.

For example, let’s say you want to include more stringent review processes for work on the stack. Let’s see how that might look using a product landing page as an example:

  • Product landing page ready for the stack.
  • The page is queued for review by two or more colleagues (they check the code for errors, similar to how you might proofread a written document).
  • In case of errors, the landing page returns to the stack for alterations.
  • Queued for re-review.
  • A/B testing queue.
  • Final report.

Choosing the best tools and programming languages

The saying “a poor craftsman blames their tools” arguably doesn’t apply when it comes to the developer experience. Between APIs, SDKs, and programming languages, devs have all sorts of options for how to start building virtual apps and interfaces.

Add to that all the secondary and tertiary applications, like data analysis AI or stack management software, and the sheer volume of tools and techniques for developers is mind-boggling.

Effective internal tools streamline these processes by automating routine tasks, ensuring that developers can focus more on creativity and less on cumbersome workflows.

Whichever options you choose, it’s important to keep things standardized across your business to prevent compatibility issues.

The best ways to support and improve developer experience

If you thought DX work began and ended with the above responsibilities, then think again. There’s so much more you can do to create an innovative, supportive developer experience for your business.

Enable innovation and creativity

Designing a virtual product can so often feel like an exercise in hitting points on a checklist. Customer portal login? Check. Product search function? Check. Personalized recommendation system? Check.

To further enhance our team’s ability to innovate, we encourage developers to pursue further education, such as a certificate in data science, equipping them with advanced analytical skills that are essential in today’s tech landscape.

The importance of upskilling cannot be overstated, as it ensures developers stay current with emerging technologies and industry standards, which is crucial for maintaining competitive and innovative teams.

But a solid developer experience offers countless opportunities to experiment and think outside the box. Compare a product that was rushed out the door to one which had time to breathe, and the difference is like night and day.

Let’s revisit our example of developing for a virtual call center. Your major checklist might include:

  • VoIP functionality.
  • Customer or client database.
  • Product or service knowledge database.

That might be all call center workers need, strictly speaking. Given the time and resources to innovate, however, you can come up with all kinds of functions and features, like a call center quality monitoring scorecard to help track worker performance and customer attitudes.

Support developer wellbeing

Employee wellbeing is an essential priority for any successful business. It’s influenced by things like workload, working conditions, employer supportiveness, and even employer ethics. After all, people want to think they’re working for the good guy. ESG reporting can help companies stay on top of their moral and societal obligations like fair pay and green practices (if you find yourself asking, “what is an ESG report?” take this as a sign to look into them!).

We’ve already mentioned the prevalence of developer burnout, but it’s important to understand the consequences of letting it go on unchecked. Burnout can deal serious, lasting damage to a person’s mental and even physical health.

Victims of burnout often need a long time to recover. Many end up quitting their role, or even their entire industry or sector altogether. As such, if you don’t want attrition to claim your top dev talent, you need to take preventative measures. These include:

  • Minimizing overtime wherever possible.
  • Appropriate, reasonable goal-setting (such as SMART Goals).
  • Hiring enough people to handle projects and absences.
  • Providing sick days and PTO, and encouraging their use.
  • Enabling job flexibility for developers.

Provide job flexibility

If your experience as a manager has been more traditional, learning how to manage remote developers effectively can seem quite daunting. However, the COVID-19 pandemic showed that remote work and other types of job flexibility… well, work.

After all, everyone has some sort of life outside of work, whether it’s family commitments, side hustles, or active social lives. Job flexibility allows people to more effectively maintain their work/life balance. This helps to prevent personal problems from spilling into the workplace.

It’s never been easier for businesses to support hybrid or remote teams, making for a far more flexible developer experience.

Make web analytics and app stats front and center

It’s often not just a product or service’s initial launch you’ve got to worry about. You also need to consider how it’ll be supported going forward. For this, a steady supply of web analytics is absolutely essential.

Accessible KPIs, like CTRs, conversions, ad engagement, and general traffic help devs to see what is and isn’t working. Of course, monitoring these things over time can turn into busy work unless you make them easy to find.

Develop a system to display them in real-time, or periodically update documentation on your developer portal. Either way, it’s in your best interests to serve that info up on a silver platter.

A great developer experience gives you an edge on competitors

If you’ve read this far, then you know that prioritizing developer experience isn’t just great for your dev team. It’s essential if you want your software brand to succeed.

DX is now an essential aspect of any tech company’s workplace culture, particularly useful for keeping your team fresh enough to offer their best. On top of that, standardized tools and practices help to prevent conflicting efforts, wasted resources, and issues with compatibility.

In other words, if you don’t have a dedicated DX team, or even a single specialist, then that absolutely needs to change.

Austin Guanzon – Tier 1 Support Manager

Austin Guanzon is the Tier 1 Support Manager for Dialpad, the leading AI-powered customer intelligence platform. He is a customer retention and technical support expert, with experience at some of the largest tech service companies in the US. You can find him on LinkedIn.

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Scaling Laravel Applications: Handling High-Traffic and Performance Challenges

The Laravel application is known for its elegance and efficient framework; scaling up to meet the demands of a growing user base is both a challenge and an opportunity. With the help of a Laravel development company, you can enhance your website and application in an effortless manner. 

In this exploration of scaling Laravel applications, we delve into the intricacies of managing surges in traffic and overcoming performance bottlenecks. Join us as we uncover proven strategies and best practices that empower developers to not only tackle the complexities of high-traffic scenarios but also to create robust systems that provide optimal user experiences. 

Whether you’re a seasoned Laravel developer or just starting out, the insights shared here will equip you to navigate the scaling journey with confidence and finesse.

#1: Understanding Scalability and Performance

Scalability refers to a web application’s ability to handle increasing workloads, traffic, or data without compromising its performance or responsiveness. In simpler terms, a system can gracefully grow and adapt to higher demands as the user base, data volume, or concurrent users increase.

Scalability is important for businesses that expect their user base to expand over time or experience unpredictable traffic patterns. By planning for scalability from the early stages of application development, developers can future-proof their systems and reduce the risk of outages or performance degradation during peak usage periods.

Performance and user satisfaction are closely linked when it comes to web applications. The performance of a web application is typically measured by factors such as response time, load time, latency, and throughput. These metrics directly impact how users perceive and interact with the application.

#2: Identifying Performance Bottlenecks

Laravel is a popular PHP framework known for its elegant syntax, developer-friendly features, and robust ecosystem. However, like any other web application, Laravel applications can experience performance bottlenecks that hinder their responsiveness and scalability.

Poorly optimized or overly complex database queries can significantly slow down the application. This may occur using Laravel’s ORM (Eloquent) or raw SQL queries. Resource-intensive operations or computations, such as complex data manipulations or algorithms, can lead to high CPU usage and slow down the application’s response times. 

Inefficient database queries that result in the N+1 query problem, where multiple queries are executed for each record fetched, can slow down the application.

#3: Optimizing Database Performance

Optimizing database performance ensures your web application runs efficiently and can handle increasing workloads. The experienced Laravel development company uses several techniques and strategies to improve database performance. Additionally, using Redis for caching can significantly enhance performance in read-heavy scenarios.

Indexing is a way to improve the speed of database queries by creating data structures that allow the database to quickly locate and access specific rows. With indexes, the database could scan through the entire table to find the desired data, which can be extremely slow, especially for large datasets.

Database sharding is a technique that distributes data across multiple database instances or servers (shards) based on a specific criterion, such as user ID or geographic location. This approach helps in horizontal scaling, ensuring that data is evenly distributed and read/write operations are distributed across multiple servers.

#4: Leveraging Caching Mechanisms

Laravel provides several built-in caching mechanisms that can significantly improve the performance of your web by reducing the need to regenerate data or execute repetitive operations. These caching mechanisms include route caching, query caching, and view caching.

Route caching in Laravel involves converting the application’s route definitions into a cached file, allowing the web server to quickly determine the appropriate route for incoming requests without parsing the route definitions on every request. This can significantly reduce the time taken to resolve routes and, consequently, faster response times.

View caching in Laravel involves storing the rendered HTML output of views so that the application does not have to re-render the views on every request. This can lead to faster response times for views that don’t change frequently.

#5: Scaling Web Servers

Scaling web servers involves increasing the capacity of your server infrastructure to handle increased user traffic and demand. There are two primary approaches to scaling web servers: vertical scaling and horizontal scaling.

Horizontal scaling, also known as scaling out, involves adding more servers to distribute the load across multiple machines. Each server works independently in this approach, and requests are distributed among them. This can be achieved through load balancing, which evenly distributes incoming requests to different server instances.

Vertical scaling, involves increasing an existing server’s resources (CPU, RAM, disk space, etc.) to handle increased demand. This can be done by upgrading the hardware or the virtual machine that hosts the server.

#6: Database Replication and Clustering

Database replication is a process of creating and maintaining copies of a database on multiple servers or nodes. The primary goal of database replication is to achieve read scalability and high availability for the application. In this setup, one server acts as the primary or master database, handling both read and write operations. In contrast, the replicated servers, known as replicas or slaves, are responsible for serving read-only queries.

However, it’s important to note that database replication does not provide automatic load balancing for write operations, as all writes must be sent to the primary server to maintain data consistency.

Database clustering is a technique that distributes data across multiple nodes or servers to achieve better performance, fault tolerance, and scalability. Clustering allows multiple database instances to work together as a single logical unit, providing a seamless view of the data to the application.


#7: Content Delivery Networks (CDNs)

A Content Delivery Network (CDN) is a distributed network of servers strategically located worldwide to deliver web content more efficiently and reliably to users. CDNs work by caching and serving static assets, such as images, CSS files, JavaScript files, and videos, closer to the end-users, reducing the load on the origin server and improving the delivery speed of these assets.

With assets cached on CDN servers, subsequent requests for the same content can be served directly from the nearest CDN edge server, eliminating the need for requests to travel back to the origin server. This leads to faster load times and improved user experience.

Laravel development companies can use CDNs to make highly perforation solutions for your business. Since content is distributed across multiple CDN edge servers, if one server experiences issues or downtime, the CDN automatically routes requests to other available servers, ensuring the high availability of content.

#8: Queueing Systems for Asynchronous Processing

Laravel’s queueing system allows Laravel development companies to perform time-consuming and resource-intensive tasks asynchronously, offloading them from the main application and improving responsiveness. It enables background processing of tasks, such as sending emails, processing large data sets, and interacting with external APIs, without making users wait for the task to complete.

The basic idea behind queues is to add jobs to a queue and process them in the background by dedicated workers. This decoupling of tasks from the main application ensures that users receive faster responses while the time-consuming tasks are processed independently.

#9: Optimizing Code and Application Architecture

When developing a Laravel application, there are several best practices you can follow to write efficient and performant code. Eager loading allows you to fetch related data along with the primary data, reducing the number of database queries. Use with() or load() to eager load relationships in your queries and avoid the N+1 query problem.

The N+1 query problem occurs when a query is executed to fetch a list of records, and then, for each record, additional queries are executed to fetch related data. This can result in a large number of database queries, leading to performance issues. Eager loading and careful use of lazy loading can help avoid N+1 queries.

Implement caching for frequently accessed data to reduce the load on the database and improve response times. Laravel provides various caching mechanisms, including query caching and Redis-based caching.

Conclusion

In this blog, we explored several vital strategies for scaling Laravel applications to handle increased user traffic and ensure optimal performance. As Laravel applications grow in popularity and user traffic increases, proactive monitoring and continuous improvement become crucial. Regularly monitor application performance, database queries, server health, and user experience. 

Keep an eye on key performance metrics and address performance bottlenecks as they arise. Make use of tools like New Relic, Datadog, or custom logging to gain insights into application behaviour.

Moreover, continuously review and optimize the application codebase and architecture. Stay vigilant for opportunities to implement caching, improve database queries, and adopt scalable architectural patterns. Regularly test the application under simulated high-load scenarios to ensure it can handle peak traffic. You can also get help from a Laravel framework development company that offers you complete Laravel development solutions.

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Community Tips

Building a Multilingual Website with Drupal: Tips and Tricks

Imagine your website speaking the languages of the world, welcoming visitors from every corner of the globe. A multilingual site can open up exciting new markets and create lasting connections with diverse audiences. And with Drupal as your partner, this dream becomes an achievable reality.

Building a multilingual website is no small feat, but Drupal makes it a breeze. From selecting the right translation tools to optimizing content organization based on sound design principles, we’ll share insider tips to help you navigate the process with confidence. Get ready to break down language barriers, embrace cultural nuances, and craft an online experience that truly resonates across borders.

Whether you’re a seasoned Drupal pro or just starting your multilingual journey, this guide has something for everyone. Let’s embark on this global adventure together and unlock the full potential of your brand identity on the world stage!

Planning Your Multilingual Drupal Website

Defining Your Languages

The first step in building a multilingual website is identifying the target languages for your content. Consider factors like audience demographics, market reach, and potential growth opportunities. Research your target regions and prioritize languages based on business goals and user demand.

Content Strategy for Multilingual Websites

When it comes to multilingual content, you have two main options:

1. Content Duplication: Translate and duplicate content across all languages, ensuring consistency across versions.

2. Unique Content per Language: Create unique content tailored to each language and cultural context.

The choice depends on your goals, resources, and target audiences. Plan for ongoing content translation and maintenance, ensuring a seamless experience across languages. Establish clear translation workflows and quality assurance processes.

User Experience and Language Detection

For a seamless user experience, you’ll need to decide on language detection and switching mechanisms. Options include:

  • URL Prefixes: Use language codes in URLs (e.g., example.com/en/, example.com/fr/).
  • Subdomains: Create separate subdomains for each language (e.g., en.example.com, fr.example.com).
  • Language Detection: Automatically detect the user’s preferred language based on browser settings or geolocation.

Regardless of the approach, ensure clear language switching options and a consistent user experience across all language versions of your site.

Translation Workflow

Determine your translation workflow early on:

  • Manual Translation: Rely on human translators for high-quality, context-aware translations.
  • Automated Translation: Leverage machine translation tools for efficient, cost-effective translations (with potential quality trade-offs).

Consider integrating translation tools directly with Drupal for streamlined workflows and collaboration.

Setting Up Your Multilingual Drupal Website

Enabling Multilingual Features in Drupal

Drupal comes equipped with powerful modules to enable multilingual functionality right out of the box. To get started, you’ll need to enable the following core modules:

  • Content Translation Module: Allows you to translate all types of content, including nodes, taxonomy terms, and more.
  • Configuration Translation Module: Translates Drupal’s configuration settings, ensuring a consistent experience across languages.
  • Language Module: Manages the available languages on your site and provides language negotiation capabilities.

Once enabled, these modules lay the foundation for your multilingual Drupal website.

Adding Languages

With the necessary modules enabled, it’s time to add your desired languages. Navigate to the “Languages” configuration section in the Drupal admin area. Here, you can:

  • Add new languages by selecting from Drupal’s extensive list of supported languages.
  • Configure language codes (e.g., “en” for English, “fr” for French) for each language.
  • Set the default language for your site.
  • Determine the order in which languages should be displayed.

Take the time to review and configure your language settings carefully, as they will impact the entire multilingual experience. If you find the process complex, you might want to hire a Drupal developer to ensure everything is set up correctly.

Translating User Interface and Configuration

To provide a truly localized experience, you’ll want to translate not only your content but also the user interface elements and configuration settings. The Configuration Translation Module comes to the rescue here.

  • Use Drupal’s built-in translation interface to translate configuration strings, such as menu items, form labels, and more.
  • Alternatively, integrate with external translation platforms or services for a streamlined translation workflow.
  • Leverage Drupal’s robust translation capabilities to ensure a consistent and user-friendly experience across all languages.

Setting Up Language Detection and Selection

Ensuring a smooth language experience for your visitors is crucial. Drupal offers several options for language detection and selection:

  • Language Detection: Configure language detection based on user preferences, browser settings, or geolocation.
  • Language Switcher:  Add a language switcher block to your site, allowing visitors to manually select their preferred language.
  • URL-based Language Selection: Use language prefixes in URLs (e.g., example.com/en/, example.com/fr/) for easy language switching.
  • Subdomain-based Language Selection: Create separate subdomains for each language (e.g., en.example.com, fr.example.com).

Choose the approach that best suits your website’s needs and provides the most seamless experience for your multilingual audience.

Setting Up Your Multilingual Drupal Website

Enabling Multilingual Features in Drupal

Ready to make your Drupal site speak multiple languages? Start by enabling these core modules:

  • Content Translation: This module is your translator for all content types—articles, blog posts, you name it.
  • Configuration Translation: It handles the behind-the-scenes stuff, translating menus, labels, and settings.
  • Language: Think of this as your site’s language manager, handling available languages and user preferences.

To enable them, go to “Extend” in your admin menu, find these modules, and click “Install.” It’s that simple! With these tools in place, your Drupal site is ready to embrace its multilingual destiny.

Adding Languages

Now that your site is multilingual-ready, let’s add some languages. Head over to “Configuration” > “Regional and language” > “Languages” in your admin menu.

Here’s what you’ll do:

  1. Click “Add language” to see a list of options.
  2. Choose your desired languages (e.g., Spanish, French).
  3. Set language codes (like “es” for Spanish) for clean URLs.
  4. Pick a default language for your site.
  5. Arrange languages in your preferred order.

Don’t rush this part—your choices here shape how users will interact with your multilingual site. Take your time and make smart decisions!

Translating User Interface and Configuration

Your content’s ready for translation, but what about buttons, menus, and other site elements? That’s where Configuration Translation shines.

  1. Go to “Configuration” > “Regional and language” > “User interface translation.”
  2. Search for the string you want to translate (like “Submit” or “Read more”).
  3. Enter translations for each language.

For faster work:

  • Use Drupal’s import feature to upload pre-translated files.
  • Try services like Lokalise or Transifex that integrate with Drupal.

This step ensures every part of your site speaks the right language, making users feel right at home.

Setting Up Language Detection and Selection

Your site’s multilingual, but how does it know which language to use? Let’s set that up:

  1. Visit “Configuration” > “Regional and language” > “Detection and selection.”
  2. Choose detection methods:
    – Browser settings (most seamless)
    – User account preferences
    – Session-based choices
    – URL prefixes (like example.com/es/)
  1. Add a language switcher:
    – Go to “Structure” > “Block layout”
    – Place the “Language switcher” block in a visible area.

This way, your site automatically detects the user’s language or lets them choose. It’s all about making their experience smooth and personalized.

Building and Managing Multilingual Content

Creating and Translating Content

With the Content Translation Module, crafting multilingual content is a breeze:

  1. Create new content in your default language.
  2. Click “Translate” next to your content.
  3. Select the target language and hit “Add.”
  4. Fill in the translated version—it’s that simple!

For existing content:

  1. Find the piece you want to translate.
  2. Click “Translate” and choose a language.
  3. Edit and adapt the content for your target audience.

Remember, it’s not just about word-for-word translation. Tailor your content to resonate with each culture’s unique preferences and expectations.

Translating Menus and Navigation

Clear navigation is key, no matter the language. You have two options:

1. Separate Menus:

  • Create a menu for each language (e.g., “Main Menu – English,” “Main Menu – Spanish”).
  • Set language visibility in menu settings.

2. Multilingual Menus:

  • Use one menu structure for all languages.
  • Translate each menu item:
  • Go to “Structure” > “Menus” > [Your Menu].
  • Click “Edit” on an item, then “Translate.”
  • Add translations for each language.

Pro tip: Keep menu structures similar across languages to maintain a consistent user experience.

Handling Images, Media, and Files 

Visual content speaks volumes, but it needs the right context:

1. Images:

  • Use descriptive alt text in each language.
  • Translate captions to provide context.
  • Consider culturally relevant images for each region to create photos that resonate deeply with local communities.

2. Media:

  • For language-specific media (e.g., videos with narration):
  • Create separate media libraries.
  • Tag media with appropriate language.

3. Files:

  • Offer downloads in multiple languages.
  • Use clear, translated file names.

Remember, visuals can carry different meanings across cultures. Choose and describe them thoughtfully to ensure they resonate universally.

Managing User Roles and Permissions

Who can edit what in which language? Let’s set that up:

1. Go to “People” > “Roles” > “Add role.”

   – Create roles like “French Content Editor,” and “Spanish Translator.”

2. Set permissions:

  • Click “Edit” on a role.
  • Under “Content Translation,” check boxes like:
  • “Translate any entity”
  • “Create translations”
  • “Delete translations”

3. Assign language-specific permissions:

  • “Translate content to [Language]”
  • “Edit original values”

This way, you ensure that the right people have access to translate and edit content in their specialized languages, maintaining quality and consistency.

Advanced Considerations for Multilingual Drupal Websites

SEO for Multilingual Websites

Want your multilingual site to shine in search results? Here’s how:

1. Use hreflang tags:

  • They tell Google which page targets which language.
  • Drupal’s SEO modules can handle this automatically.

2. Optimize for each language:

  • Don’t just translate keywords—research them for each locale.
  • Write unique, culturally relevant meta descriptions.

   For example: “football” means soccer in the UK, but not in the US.

3. Build local backlinks:

  • Engage with region-specific blogs or forums.
  • This boosts your site’s authority in each language market.

Right-to-Left Language Support

Arabic, Hebrew, or Urdu on your site? You’ll need right-to-left (RTL) support:

1. Enable RTL in Drupal:

  • Go to “Configuration” > “Languages” > [RTL Language].
  • Check the “Right to left” option.

2. Theme Compatibility:

  • Use a responsive, RTL-ready theme like Bartik or Olivero.
  • For custom themes:

     – Mirror layouts and sidebars.

     – Flip icons and directional elements.

3. Test Thoroughly:

  • Check text alignment, forms, and tables.
  • Ensure RTL content doesn’t break your design.

With these steps, your RTL content will feel as natural as any other language.

Localization Best Practices

The translation is just the start. True localization means adapting content to each culture:

1. Cultural Nuances:

  • Avoid idioms or humor that doesn’t translate.
  • Example: “Piece of cake” means nothing in many languages.

2. Regional Variations:

  • Spanish in Spain differs from Mexico’s.
  • Choose the right dialect for your audience.

3. Format Differences:

  • Dates: 15/06/2024 (UK) vs 6/15/2024 (US)
  • Currency: Use local symbols (£, €, ¥)
  • Measurements: km vs miles, liters vs gallons

Drupal’s localization features help manage these differences, ensuring your content feels truly local.

Ongoing Maintenance and Updates

A multilingual site is a living entity. Keep it thriving with:

1. Regular Content Updates:

  • Schedule updates for all language versions.
  • Use Drupal’s content calendar for tracking.

2. Translation Workflows:

  • Set up states: “Needs Translation,” “In Review,” “Published.”
  • Assign tasks to translators or agencies.

3. Leverage Tools:

  • Try the TMGMT (Translation Management Tool) module.
  • It integrates with services like Lingotek or Smartling.
  • Features: Translation memory, job management.

4. Monitor Analytics:

  • Track engagement per language.
  • Low metrics might signal outdated content.

With these practices, your multilingual site stays fresh, accurate, and engaging in every language.

Conclusion

Building a multilingual Drupal website isn’t just a technical task—it’s a journey into global connection. We’ve explored everything from basic setup to cultural nuances, showing that Drupal’s robust tools make this journey smoother. Yes, there are challenges: maintaining content across languages, ensuring cultural relevance, and keeping up with updates. But the rewards? Exponentially larger audiences, deeper user engagement, and a truly global brand presence.

Remember, a great multilingual site speaks not just the language, but to the heart of each culture. For more insights, dive into Drupal’s multilingual guide, join the polyglot initiative, or explore case studies. Your World Wide Web adventure starts now—embrace it!

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Community

Everything You Need To Know About AI Tech Stack

AI Tech Stack: Explained In Detail

Over a narrow span, AI technology experienced a paradigm shift from novelty to an all-imperative aspect for businesses. With exponential growth in AI solution development, businesses are trying to maintain a pace with evolving AI tech stack, ensuring the adoption of the latest AI trends.

Before stepping in it’s essential to understand the AI tech stack, the technical breakdown of the AI tech stack, the stages of AI tech stack development, and how AI development companies select the best one. Let’s walk through all of them to ensure AI solutions are built using the advanced AI tech stack.

A brief overview of the AI tech stack

The AI tech stack is a structural framework that’s created with a layered approach and comprises components such as APIs, ML algorithms, data processing, data storage, visual data recognition, and data ingestion. The three layers- application layer, model layer, and infrastructure layer act as a foundation of the AI tech stack.

AI tech stack architecture includes multifaceted frameworks that provide programming paradigms that easily adapt AI technology evolutions. Vertex AI, LangChain, Fixie, and Semantic Kernel are the popular frameworks leveraged by AI engineers to build AI solutions quickly.

Technical breakdown of AI tech stack

The overview of the AI tech stack determines the importance of every component and element, which enables the creation of the best AI tech stack. Here’s the breakdown:

·        Machine learning frameworks: ML frameworks such as Keras, TensorFlow, and PyTorch provide a range of tools and APIs enabling ML model creation that are necessary for AI training and interference.

·        Programming languages: Python, R, and Julia are widely used programming languages for creating complex functionalities such as high-performance computational tasks, statistical analysis, etc. that are highly accessible.

·        Cloud services: Cloud services such as AWS, Azure, GCP, or other integrations provide ML platforms and configurable resources. Scalability ensures AI solutions perform to the notch despite variations in workload.

·        Data manipulation utilities: Data normalization, encoding, and preprocessing are important, and they are enabled using Hadoop, an Apache-like data manipulation utility. It helps to manage huge datasets and to analyze data to uncover valuable insights.

Different phases of building AI tech stack

For effective development and deployment of AI solutions, the layered AI tech stack is divided into two phases followed by multiple stages, which we will discuss in detail.

Phase 1: Data management

As data is the crux of ML algorithms and impacts decision-making, data handling is vital. Data management involves data acquisition, transformation, storage, processing, and monitoring.

Stage 1: Data acquisition

·        Data aggregation: Data collection involves moving through databases and writing queries to extract data. The data is further analyzed to gain actionable insights.

·        Data annotation: Manual labelling or auto-labelling using tools like- ImgLabs or V7Labs helps with data labelling so that ML solutions can identify the relationships among data in a supervised environment.

·        Synthetic data generation: When the data is not available for specific use cases, the data is generated using different libraries (SymPy and Pydbgen) and tools (Tensorflow and OpenCV) supporting data generation from images, texts, tables, and others.

Stage 2: Data transformation and storage

·        Data transformational mechanism: Data transformation is enabled in two types- ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform). The former is a traditional method that uses data processing as a priority, and the latter is preferred when data preservation and faster processing are required.

·        Storage modalities: Three types of data storage facilities are available based on data volume, interaction frequency, and data structure. Data lakes store unstructured data and organize them in a flexible format, while data warehouses store and process structured data across multiple touchpoints. Databases store and process structured, filtered data, which is good for interactions.

Stage 3: Data processing

·        Analysis: This stage converts raw data into meaningful data that Machine Learning models consume. NumPy, Pandas, and Apache Spark are the popular libraries used for data analysis at speed. Business intelligence tools provide business insights that are useful during stakeholder interactions.

·        Features handling: Feature store solutions (Iguazio, Tecton, Feast, and Hopsworks) make invaluable contributions to feature storage, computing, management, and versioning across ML solutions.

Stage 4: Data versioning lineage

Continuously changing and updating data makes it difficult to generate results unless data is versioned optimally. DVC is a popular data versioning tool that’s language-agnostic and enables seamless integrations with data, code, files, and storage. Data lineage helps view data version evolution over time and find out the logical connections between every data touchpoint.

Stage 5: Data monitoring

Data surveillance is essential to identify whether the data passed to ML models is flawless. Automated monitoring tools such as Censius, Fiddler, etc, help monitor millions of data points to check quality issues or abnormalities. Conceptual pattern and traffic monitoring through intelligent tools ensures data is completely error-free.

Phase 2: Model architecting and performance metrics

Data management and modelling are cyclic, wherein developers move back and forth to make changes and get optimal results. Model development starts with data gathering, storage, analysis, and transformation into usable form. After that, various aspects of the process are involved, from algorithm selection to final evaluation.

·        Algorithm selection: Every ML library has its strengths and offers a range of advantages, including customization level, speed, adoption, and flexibility. Post-library selection and model-building activities are executed.

·        Integrated Development environment: IDE facilitates code, compiler, debugger, and integration of other features that are essential for software development. PyCharm, VS code, Jupyter, and MATLAB are the popular IDEs leveraged at scale.

·        Tracking: AI solution development involves experimenting with feature combinations, models, and data to find the best result. These experiments are executed multiple times and tracked using tools like MLFlow, Neptune, and Layer for faster analysis and selection.

·        Evaluation: The results of different experiments are monitored and compared using AI tools. Correlating performance evaluations helps find the root cause of issues.

Phase 3: Model Deployment

The deployment phase ensures the solution becomes available to end users and is automated so that no incompatibility issues exist.

Stage 1: Model serving

Model serving enables AI solutions to be hosted by different hosting service providers. It ensures that end users can access the application. Model serving tools such as Cortex, TensorFlow Serving, Seldon, and Torchserve have multiple options to ease production.

Stage 2: Resource virtualization

It supports the isolated environment and experiments for model training and deployment. Virtual machines and containers help best manage development and deployment activities. 

Stage 3: Model testing

Model testing helps filter all the issues across various environments and containers, ensuring the right model reaches the customers. Testing tools compatible with a range of infrastructures enable faster testing.

How do you select the best AI tech stack?

The AI tech stack is overwhelming for beginners, but connecting with one of the top AI companies helps you create the best tech stack. However, consideration of a few criteria and milestones allows businesses to select the right AI tech stack.

·        Specifications for functionality and technology: The number of features and their complexity determine programming languages, frameworks, libraries, tools, and APIs to select. Data modality, computational complexity, scalability, and execution speed must be evaluated to determine tech stack specifications.

·        Strategic selection of assets: Resource availability plays a vital role in AI tech stack selection. So, tech stack selection must be strategic and based on team expertise, resource accessibility, budget, and maintenance complexity.

·        Scalability is important to consider: Adaptability is key in AI applications, so the AI tech stack must be scalable, ensuring longevity and high performance. 

·        Security and compliance can change the game: Critical data handling and management in a secure data environment require nation-specific compliances to be followed. Data integrity, authentication mechanisms, infrastructure defence, and regulatory adherence are paramount, ensuring data remains safe forever.

Partner with the reliable AI development company

Building scalable, dynamic AI solutions rests on the shoulders of a powerful AI tech stack that further helps businesses stay current and stand out in the competition. Building a robust AI tech stack requires connecting with the top AI companies with rich expertise and experience in AI solution development, leveraging the right mix of AI tools, techniques, and libraries. Collaborate with the right partner to create futuristic AI solutions. 

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Community Enterprise Developers Interviews

Meet the Enterprise Developers – Interview Series #4: Cloud Infrastructure DBaaS domain

Enterprise developers play a critical role in driving innovation, maintaining security, and ensuring the smooth operation of large-scale IT systems within organisations. Despite their importance, we have seen a noticeable decline in the number of enterprise developers across various domains. Particularly within the data analytics and business intelligence sectors, this drop is significant, decreasing from approximately 20% last year to around 14% this year (source: Q1 2024 Pulse Report).

In our ongoing Enterprise Developer Series, we’re striving to provide insights from professionals in the field. Our latest interviewee, who wishes to remain anonymous, will be referred to as Dev C. Dev C. shares their experiences and perspectives on working as an enterprise software developer at Oracle, offering valuable insights into the benefits, challenges, and evolving landscape of the industry.

Q. Can you briefly describe your Job as an Enterprise Software Developer?

Dev C. I work in Oracle Cloud Infrastructure – Database as a Service team where we get to work in developing many cloud related services and platforms that help customers.

Q. What are some of the challenges and benefits of working at a large company compared to a start-up?

Dev C. I would say there are no such benefits now, earlier my answer would have been job security but recent trends have proven this wrong, one benefit could be the culture and flexibility you get at least in Oracle. 

Challenges come in the form of financial increments and growth potential in some teams.

Transparency is needed

Q. If you could change one thing about how your organisation operates, what would it be?

Dev C. I would like a more transparent view about the growth of an individual rather than just be dependent on the manager and I think I would like to hire more people.

Using AI for education

Our latest Pulse Report shows that almost 55% of developers have used AI-assisted development tools for code generation tasks in the past 12 months, however, how does a company like Oracle view AI? Here is what Dev C has to say about Oracle’s policies.

Q. How is AI impacting your day-to-day life? Is there a policy regarding the use of AI tools in your company?

Dev C. Yes there is. But it’s related to not using it to generate code and use company proprietary code there, we can use it to educate ourselves or learn about different services.

Dependency on tools

Q. How much of your work depends on specific tools, frameworks, programming languages or cloud providers?

Dev C. A lot of it is using different frameworks.

Skill Development

Q: How do you keep your skills and knowledge up-to-date?

Dev C. Mostly by working on different projects, but sometimes if I find something interesting out of the scope of my work, I use youtube and other learning tools to update myself.

Mutual decision making

Q: How much influence do you’ve when it comes to procuring a new tool or service to support the projects at work?

Dev C. It’s a mutual team-wide discussion.

Through our conversation with Dev C., we’ve gained a good understanding of the dynamic role enterprise developers play within large organizations like Oracle. From navigating the challenges of growth and financial increments to leveraging AI for educational purposes, their insights highlight the evolving landscape of enterprise development. 

Do you want to shape the future and influence decisions of the largest tech companies? Get in our NEW Developer Nation survey! Everyone completing the survey gets instant access to our cool, virtual goody bag!

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How to Improve the Mobile App Onboarding Process

First impressions matter, especially for mobile apps. The onboarding process is the first interaction users have with your app, and it can make or break their decision to stick around.

A smooth and engaging onboarding experience helps users understand your app’s value and sets the stage for long-term engagement and retention. So, how can we make this experience great?

That’s what we’re going to discuss in this article. Before we explore some strategies, let’s first identify some factors that make an onboarding process memorable and pleasing for users.

What Makes a Mobile App Onboarding Great?

An onboarding process must be educative and informative, but we must not forget the visual appeal. Both an informative and appealing onboarding process can improve engagement and keep users coming back. 

When you create onboarding content for a mobile app, consider the following elements:

Simplicity and clarity: Aim to highlight the core features and benefits of your app with clear and concise instructions to help users get started without frustration.

Interactive elements: Use interactive tutorials or walk-throughs to allow users to learn by doing. This can help them better understand how to use your app.

Progress indicators: Let users know how far they’ve come and how much is left can keep them motivated. Progress indicators also provide a sense of accomplishment. 

Seamless transition: Use a smooth transition from onboarding to regular app use. Get users to a point where they feel comfortable using the app on their own.

Onboarding users are best using animated explainer videos. You can use screencast animations to provide tutorials and highlight features on your app. Videos are not only engaging but also visually appealing to engage users.For example, a furniture company, Multimo, can create an onboarding process on its mobile app to guide customers through making a purchase or pre-ordering customized products. The onboarding process in such apps can prevent confusion and may lead to higher sales.

How to Elevate the Mobile App Onboarding Process

Creating your mobile app onboarding process requires a well-structured plan. You can communicate concepts with your app developer team and find the best strategies to elevate the onboarding process.

Build trust and credibility before asking for permission.

Before requesting access to sensitive information or device features (like location, contacts, or camera), building trust and credibility with your users is crucial. Building trust must be gradually done to avoid bombarding users with multiple permission requests right at the start.

First, you can clearly communicate why you need certain permissions and how they enhance the user experience. For example, explain that access to location data will help provide personalized content or services.

You must also highlight any security measures you have in place to protect user data. To gain trust and credibility, consider including testimonials, user reviews, or endorsements from trusted sources.

Use clear language when explaining what the app does.

Clear messages are key when introducing your app to new users. However, making sure your explanations are easy to understand can be a real challenge and requires a deep understanding of your users.

We recommend never using jargon, as it can be irrelevant to users. Instead, use simple, everyday language rather than technical terms or industry jargon. Your goal is to ensure users of all backgrounds understand what your app does.

While guiding users to your app, get to the point quickly. Users want to understand your app’s value without wading through lengthy descriptions. Focus on the main functionalities and use images, icons, or short videos to illustrate how your app works.

Include a visible “skip” button.

Providing an onboarding process is great, but respecting user preferences must also come first. Giving users control over their onboarding experience can lead to higher satisfaction and retention. A way to do this is by offering a visible “skip” button.

Some users prefer to explore the app on their own without a guided tutorial. Moreover, mandatory onboarding can be a barrier for experienced users or those who are already familiar with similar apps.

A “skip” button reduces this friction. Make sure your “skip” button is easy to find and clearly labeled. This makes it convenient for users to opt out of the onboarding process if they choose to.

Show off the best features first.

The best comes first. Prioritize key features and highlight your app’s most impressive and valuable features right from the start to capture users’ interest.

Show users how your main features work. It’s best to explain them with engaging visuals, short videos, or interactive demos. This will help users learn icons and tools quickly and grasp your app’s functionality more effectively.

While highlighting key features, use engaging language and visuals to build excitement. For example, if your target users are young generations, use straightforward descriptions with friendly intonation to keep them hooked.

Don’t ask for too many things at once.

Overloading users with requests and information can be overwhelming. As a result, users may close your app, leading to higher dropout rates. To avoid this, use the step-by-step approach by breaking down the onboarding process into manageable steps.

Focus on the most important information and actions users need to take initially. As users become more comfortable with the app, additional features and requests can be introduced later.

In addition, simplify user actions. You can make each step simple and easy to complete. Avoid asking for too much information or too many permissions at once, which can be off-putting.

Use animations and visual cues to guide users.

Animations and visual cues can make the onboarding process more intuitive and engaging. You can use explainer videos to demonstrate how to use key features. For example, an animated hand or arrow can show users where to tap or swipe.

In other cases, you can also use visual cues like highlighting, zooming, or flashing to draw attention to important elements and actions. This helps users quickly understand what to do next.

However, keep in mind that when you use animations, ensure you show smooth transitions. Implement smooth transitions between steps to create a seamless experience. This reduces cognitive load and keeps users engaged.

Wrapping Up

A mobile app onboarding process must be effective to deliver maximum understanding for users. This process is necessary to ensure users understand the value of your app and feel confident using it. 

The above points are strategies for creating a mobile app onboarding process. Ensure users understand the value of your app and feel confident using it. Your goal is to make users feel welcomed and informed when using your app from the very first interaction.

Author Bio

Andre Oentoro is the founder of Breadnbeyond, an award-winning animation video company. He helps businesses increase conversion rates, close more sales, and get positive ROI from explainer videos (in that order). 

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Demystifying DevOps: Best Practices for Seamless Deployment

With hundreds of coding languages in existence and the number continuously rising, modern software development is a challenging subject to tackle. However, there is a way to make it more understandable by considering the role of DevOps in the entire development lifecycle.

That’s exactly what this article covers, all while offering insights into best practices for seamless deployment in DevOps.

Let’s take a closer look.

Understanding DevOps

A simple way to understand what DevOps means is to look at the previous way in which development processes were structured. In the past, developers would work on a project and then send it to the operations team for feedback and testing. Plus, it’s important to use team calendar software to facilitate coordination, ensuring seamless collaboration between development and operations teams.

While the operations team was doing this, the development team would move onto the next project. It was only natural that this created long delays in the development and testing process and that’s where DevOps came into existence.

Instead of separating development and operations, DevOps brings the two together in one infinity loop that helps streamline processes. In general, it starts with the development team planning, coding, building, and testing, and the ops team deploying, operating, and monitoring. 

So, what does this mean for software development teams? DevOps practices in such environments are absolutely indispensable. They help with some of the following aspects, among many others:

  • Collaboration
  • Improved quality
  • Cost reductions
  • Faster software development
  • Satisfied customers
  • Reliable solutions
  • Enhanced security
  • Better agility
  • Improved automation
  • Breaks down silos
  • Improves efficiency
  • Increases revenue
  • Greater innovation
  • Seamless communication

Key Components of DevOps

Before we touch on the best practices for seamless deployment, it’s a good idea to explore some of the key components of DevOps, which are the following:

  • Continuous integration (CI): The less controversial of the continuous integration/continuous delivery (CI/CD) approach, CI looks at how several developers merge code changes to a shared repository, early and often, for smooth operations. What happens next is that this information is automatically sent to a separate server, which checks if the new additions are safe to merge into the “main branch”. 
  • Continuous delivery (CD): Continuous delivery is the next piece of the CI/CD puzzle. Above, we mentioned that it is more controversial. Why? Because it is much harder to implement. When releasing a new feature, for example, it’s relatively easy and risk-free to do CD for stateless systems. However, the challenge arises when you want to introduce a new feature for a stateful system where you may wish to test out on a smaller sample of users first before going full out with your release.
  • Automation: Automation comes into play with both CI and CD as previously manual and human-created and entered code is now being replaced with a range of important tools to streamline processes. With automation, development, testing, and deployment become that much faster and more efficient.
  • Computer System Architecture: Understanding the underlying computer system architecture is crucial for effective implementation of DevOps practices. It influences how infrastructure is designed, deployed, and managed, ultimately impacting the efficiency and scalability of the development lifecycle.

Best Practices for Seamless Deployment

And now, we present the leading best practices that improve and streamline your deployment process.

  • Automated testing: Automated testing and test-driven development in DevOps are essential in ensuring code quality and reliability. It can also offer increased test coverage and greater accuracy and precision. With automated testing, businesses and their clients can enjoy greater cost savings and better returns on their investments. This is because automated testing can detect bugs early, is a scalable process, and works as part of a feedback loop that saves time and improves time to market.
  • Infrastructure as Code (IaC): IaC streamlines deployment processes and enhances scalability. This is done by helping organizations define their desired state without necessarily defining each step that needs to be taken to achieve the final outcome.
  • Continuous monitoring: The significance of continuous monitoring for identifying issues and ensuring system stability cannot be overstated. It’s the only way to spot bugs before launching to market and take steps to address these issues before they manifest themselves during a more critical stage such as an end-user encountering problems with an app or one of its features.
  • Deployment pipelines: A major benefit of deployment pipelines is achieving efficient and error-free deployments. This is essential because it reduces the chances of costly rollbacks and deployment failures that could cost an organization significant amounts of time, money, and other resources.

The Human Element in DevOps

None of the CI/CD and automation processes would be achieved without two fundamental soft skills that DevOps teams should possess. These are collaboration and communication.

Whatever the software environment you may be operating in, using applicant management software to clarify expectations and communicate them clearly while managing cross-team responsibilities is challenging but essential.

Without team members at your side who are willing to communicate, collaborate and stay productive, most projects would ultimately fail. That’s why the human element should never be taken too far out of the DevOps equation.

Conclusion

The key DevOps components of CI/CD and automation would not be complete without following some of the leading industry best practices.

They’re an excellent starting point for any development team that seeks to introduce efficiencies in their processes and enhance workflows.

By adopting the best practices discussed in this article, you’re on the road to seamless deployment. This can help take your DevOps workflows to the next level.