About 75% of businesses are presently emphasizing cloud-native applications. In this blog, we will delve into the realm of cloud-native applications and examine some of the prospects, difficulties, and trends that cloud-native application development entails. 

 

Opportunities of Cloud-Native Applications

1. Cost Reduction Through Scalability and Flexibility

Businesses usually find themselves grappling with inflated expenses on IT infrastructure. In that case, the adoption of cloud-native applications can provide a viable solution. Such applications have the capability to adjust resource utilization in accordance with the current workload, making them remarkably flexible and cost-effective. These applications can therefore accommodate sudden increases in traffic or adapt to reduced requirements to enable optimal cost savings. 

 

2. Greater Reliability and Resilience

Application crashes can be highly frustrating, particularly when they occur during crucial moments. However, cloud-native applications are designed to be highly resilient. They possess an exceptional ability to endure adverse conditions and continue to operate with unwavering consistency.

 

3. Better Security

The conventional concerns surrounding security and compliance are no longer a source of undue distress, thanks to the advent of cloud-native applications. These are equipped with a range of inbuilt security features, such as identity and access management, encryption, and network security, which effectively safeguards them against potential vulnerabilities. 

 

4. Faster Time-to-Market

In order to accelerate the introduction of products and services into the market, the adoption of cloud-native applications is paramount. These applications are specifically designed for expedited and efficient deployment, facilitating the swift launch of new products and services with unparalleled agility. The inherent rapidity of cloud-native apps lends the ability to swiftly test and incorporate novel concepts and features. 

 

Challenges of Cloud-Native Applications

1. Complexity in Building and Maintaining Cloud-Native Applications

Building cloud-native apps demands a comprehension of cloud infrastructure and specialized proficiency in software development, networking, and security. However, partnering with a technology expert can ward off this challenge.

 

2. Skills Gap and Talent Shortage

The current state of the job market presents a significant challenge for companies seeking an ideal candidate with the requisite knowledge and proficiency to competently manage cloud-native applications. Consequently, businesses grapple with escalating expenses incurred in staffing and training. 

 

3. Security Concerns with Cloud-Native Applications

Cloud-native applications, while offering numerous advantages, can introduce a fresh set of security challenges that demand careful consideration. These challenges include container security, network security, and access control, among others. It is crucial for businesses to prioritize and embed security into every stage of the application design and deployment process. By doing so, organizations can mitigate security risks and ensure the protection of valuable data and systems.

 

4. Vendor Lock-in

Leveraging cloud-native services presents a potential drawback in the form of vendor lock-in, wherein an enterprise may become unduly reliant on a singular cloud service provider for their entire gamut of infrastructure and services. Such a scenario can be highly precarious and could potentially prove to be a recipe for disaster. It is therefore prudent for organizations to maintain a certain degree of vendor agnosticism while adopting cloud-native services to avoid the pitfalls of vendor lock-in.

 

Trends in Cloud-Native Applications

1. Microservices Architecture

The utilization of microservices architecture has gained significant prominence. This approach involves the decomposition of an application into small, independent, and autonomously deployable services. Its inherent characteristics of flexibility, scalability, and resiliency render it a highly suitable choice for cloud-native applications.

 

2. Kubernetes as a De-Facto Standard for Container Orchestration

Kubernetes is a highly advantageous solution for orchestrating containers within cloud-native applications — furnishing a comprehensive and robust framework for deploying, scaling, and administrating containerized applications across diverse clusters and cloud environments.

 

3. Hybrid and Multi-cloud Environments

The proposition of embracing a hybrid and multi-cloud approach appears to be a promising trajectory towards the future. Rather than restricting oneself to a singular cloud infrastructure, a combination of public and private clouds, along with multiple cloud providers, can be strategically employed to attain heightened levels of scalability, flexibility, and resilience.

 

4. Serverless Computing

Serverless computing obviates the need for traditional servers, enabling the operation of applications without server management. Furthermore, it facilitates cost savings and enhanced scalability as one is only billed for the utilized computing resources.

 

How to Build Cloud-Native Apps? (A Step-by-Step Guide)

1. Define Your Requirements

Initiate the project by defining a comprehensive set of requirements. This should encompass functional, non-functional, compliance, and security requirements.

 

2. Choose Your Cloud Provider

It is imperative to carefully select a cloud service provider that aligns with the unique operational requirements of your enterprise. This should be taken care of by giving due consideration to crucial aspects such as expenses, capacity for expansion, dependability, and safeguarding against potential security breaches.

 

3. Design Your Architecture

Employing a microservices-based architecture and containerization methodology in the design of your application can confer upon you the benefits of enhanced flexibility, scalability, and resilience.

 

4. Develop Your Application

The implementation of a Continuous Integration and Continuous Delivery (CI/CD) pipeline has the potential to facilitate the development process of your application, enabling the swift and dependable deployment of updates.

 

5. Test Your Application

It is imperative to conduct comprehensive application testing to ensure its conformance with the prescribed requirements that encompass functional, performance, and security criteria.

 

6. Deploy Your Application

Deploy your app to your chosen cloud provider using Kubernetes or another container orchestration platform. This will allow you to manage and scale your app easily.

 

7. Monitor and Maintain Your Application

Keep an eye on your app to make sure it continues to meet the user’s and business’s needs. Monitor performance, security, and compliance, and make changes and updates as needed.

 

Best Practices for Building Cloud-Native Applications

1. Start with a Solid Architecture

A solid app architecture is key. Make sure it’s scalable, resilient, and flexible so you can adapt to changing business needs.

 

2. Use Containers to Enable Portability and Scalability

Containers are a valuable asset to leverage in facilitating portability and scalability, as they furnish a nimble and transportable methodology for encapsulating and distributing applications, ultimately contributing to increased scalability and decreased expenditure.

 

3. Employ a Microservices Architecture

Adopting microservices architecture is viable if one seeks to alleviate the cumbersome task of managing a single monolithic application. It offers the ability to partition and conquer, thereby simplifying the management process, enhancing business agility, and ensuring seamless scalability. The efficacy of microservices architecture empowers businesses to promptly adapt to the volatile modern business environment, thereby cementing their leadership in the market.

 

4. Embrace Automation

Automation stands as a pivotal aspect in the domain of cloud-native applications, owing to its ability to curtail errors, enhance productivity, and expedite the process of development and deployment. Furthermore, the reduction of the manual labor associated with this approach renders it an exceedingly desirable solution for businesses.

 

5. Ensure Security 

Security protocols must be considered when developing an application, irrespective of whether it is hosted on cloud-native infrastructure. To this end, diligent attention must be paid to the adoption of secure coding practices, access control measures, and vigilance in monitoring potential security vulnerabilities. A stringent approach toward safeguarding the application’s infrastructure is essential for protecting the interests of the business and its users.

Conclusion

Cloud-native applications present a promising future for businesses by providing boundless prospects for scaling, innovating, and gaining a competitive edge. But the adoption of such applications is not without challenges. 

 

It’s viable to connect with an expert like Sagacity to embark on this transformative journey. We help businesses effectively navigate and surmount challenges and realize better outcomes with their cloud-native initiatives. Get in touch with us today!

Mobile applications have become ubiquitous in modern society, revolutionizing the way people interact, access information, perform tasks, and communicate with others conveniently and efficiently. 

 

From fitness trackers to eCommerce applications, every modern-day app is being driven by data — data that’s collected across every touchpoint of a user’s journey and can power personalization initiatives. That’s precisely why we see:

• Fitness applications providing customized workout plans
• eCommerce applications recommending products based on users’ purchase history and browsing behavior
• Financial apps using predictive analytics to forecast users’ spending patterns and provide budgeting advice, etc.

 

What Exactly Is a Data-Driven Mobile Application?

Data-driven mobile applications utilize data analysis and machine learning algorithms to improve user experience and deliver personalized services. By collecting and analyzing user data, these apps can provide insights into user behavior and preferences, enabling businesses to make informed decisions and drive growth. From recommendation engines and targeted advertising to predictive maintenance and fraud detection, data-driven mobile apps are transforming the way businesses operate and interact with customers.

 

Social media, entertainment, productivity, commerce — mobile apps serve a variety of purposes, transforming the way people consume information and conduct transactions. All in all, data-driven applications help businesses profoundly connect with customers and deliver immense value.

 

Data-Driven Mobile Application Development Process

Developing a data-driven mobile application involves several steps as listed below:

 

• Define the Problem: The first step in developing a data-driven mobile application is to identify the problem that the application will solve. This involves understanding the target audience, their pain points, and the user experience that the application should provide.
• Collect Data: Once the problem is defined, the next step is to collect data that will be used to build the application. This includes data from various sources such as user inputs, sensor data, and external data sources.
• Choose the Right Data Storage: Choose the right data storage to store the collected data in a way that is easy to access and analyze. This can include cloud storage, databases, and other types of storage solutions.
• Data Cleaning and Preparation: Raw data collected from various sources might contain errors, inconsistencies, and incomplete data. Therefore, data cleaning and preparation are necessary to ensure data quality.
• Implement Data Analysis: Implement data analysis algorithms to analyze the data and extract meaningful insights. This can include the application of machine learning, data mining, and other data analysis techniques.
• Develop the Mobile Application: Develop the mobile application using the insights and data gathered in the previous steps. This involves designing the user interface, implementing data-driven features, etc.
• Test and Deploy: Test the application thoroughly to ensure that it works as expected, and then deploy it to the app stores for users to download and use.
• Monitor and Update: Monitor the application’s performance and update it regularly to ensure that it continues to provide a great user experience and stays relevant.

 

Data analysis plays a crucial role in the development process of a data-driven mobile application, as it provides insights that inform the application’s design. More profoundly, it helps to identify patterns, predict outcomes, and make recommendations based on data. Data analysis techniques such as data mining and statistical analysis enable developers to create personalized and engaging user experiences. Most importantly, data analysis helps to ensure that the data used in the application is accurate, relevant, and of high quality.

 

Tools for Building Data-Driven Mobile Applications

There are several tools and technologies available for building data-driven mobile applications. 

 

• For data storage and management, popular options include cloud-based services such as Amazon Web Services, Google Cloud Platform, and Microsoft Azure.
• For data analysis, machine learning libraries such as TensorFlow, PyTorch, and Scikit-learn can be used. 
• Development frameworks such as React Native, Flutter, and Xamarin can be used to create cross-platform applications. 
• For visualizing data, libraries such as D3.js, Plotly, and Matplotlib can be used. 

Additionally, there are various APIs and SDKs available for integrating with external data sources and services.

 

Challenges in Developing Data-Driven Mobile Applications (and Strategies to Overcome Them)

To overcome the challenges of developing data-driven mobile applications, here are some strategies that can be applied:

Data Security and Privacy Concerns

• Use secure data storage techniques and encryption protocols
• Implement access controls and authorization mechanisms
• Comply with data privacy regulations.

 

Ensuring Data Accuracy and Consistency

• Implement data validation checks
• Utilize data profiling and cleansing tools
• Establish data quality metrics and monitoring mechanisms

 

Managing and Processing Large Volumes of Data

• Use scalable and distributed data processing frameworks such as Apache Hadoop or Apache Spark
• Optimize data storage and retrieval
• Utilize cloud-based services to handle high volumes of data

 

Integrating Multiple Data Sources and APIs:

• Use standard data exchange formats, such as JSON or XML
• Utilize API management tools
• Establish data integration workflows

 

Providing Real-time Data Analysis and Insights

• Use real-time data processing and analytics frameworks, such as Apache Kafka or Apache Flink
• Implement streaming data pipelines
• Use data visualization tools.

 

Optimizing App Performance and User Experience while Handling Data

• Use efficient algorithms and data structures
• Optimize database queries
• Use caching mechanisms
• Implement efficient network communication protocols

 

Maintaining Data Quality and Ensuring Data Validity over Time

• Establish data governance policies
• Implement data versioning and lineage tracking mechanisms
• Regularly audit and monitor data quality metrics.

 

The Future of Data-Driven Mobile Applications

Some emerging trends in data-driven mobile application development include:

 

• Edge Computing: Edge computing is gaining popularity in mobile app development, as it allows processing and analyzing data closer to the source and reduces latency.
• AI and Machine Learning: AI and machine learning are being used to develop more intelligent and personalized mobile apps. These technologies can analyze user data to make recommendations and predictions, as well as automate tasks and processes.
• Augmented Reality: Augmented reality is becoming more prevalent in mobile app development, providing innovative ways to visualize and interact with data.
• Blockchain: Blockchain technology is gaining adoption, particularly in industries such as finance and healthcare, where data security and privacy are paramount.
• IoT Integration: Integrating Internet of Things (IoT) devices with mobile apps is becoming more common, allowing users to access and interact with data from various devices.
• Cloud Integration: Cloud computing is being used to store and process large volumes of data, enabling mobile apps to provide real-time data analysis and insights.
• Voice Recognition: Voice recognition technology is also providing a seamless way to interact with the application and perform tasks.

 

So there you have it! Interested in developing data-driven mobile applications? Let us help. At Sagacity, we have been assisting businesses in realizing significant ROI out of their mobile development initiatives. Get in touch with us today to learn more.

Today, businesses must be able to create and deliver high-quality, responsive digital experiences across different devices and platforms. Headless architecture makes this possible by decoupling the front-end and back-end of an application, making it easier to deliver content to different devices and channels.

The blog aims to explore the concept of headless architecture and its impact on modern application development. We will examine the benefits of headless, the problems it solves, and how it will shape the future of application development.

 

Understanding Headless Architecture

The headless architecture uses a CMS that delivers content to different devices and channels through an API. The application’s front-end is separated from the back-end, which means that the application can be delivered to different devices and channels, such as mobile apps, smartwatches, or even virtual reality headsets. 

The market for headless CMS is growing rapidly, with more and more businesses adopting this architecture to create cross-platform applications. As it stands, the headless CMS software market is expected to grow at a CAGR of 22.1% to reach $5,528.5 million by 2032, up from $751.6 million in 2022.

So, how is headless different from traditional architecture?

Traditional CMS is based on a monolithic architecture. The front-end and back-end are tightly coupled, and content is delivered through a website. This means that the website and the CMS are inseparable, limiting the application’s flexibility. With headless, on the other hand, the front-end and back-end are separated, which allows for greater flexibility and customization.

 

Headless Architecture for Mobile Application Development

Headless architecture is particularly advantageous for mobile application development. With the rapid growth of mobile devices, businesses must ensure that their mobile-responsive applications provide a seamless user experience across all devices.

The headless architecture allows developers to create mobile applications with a consistent cross-channel user interface and performance. Developers can easily make changes to the application’s presentation layer without affecting the back-end.

Here are some of the benefits of headless architecture for modern application development.

 

1. Improved User Experience 

One of the main benefits of headless architecture is that it allows for a more personalized and customized user experience. Developers can use different front-end frameworks to create unique user interfaces that meet the specific needs of their customers.

 

2. Increased Development Flexibility

Headless architecture offers greater flexibility and agility in application development. As elucidated above, developers can make changes to the presentation layer without affecting the back-end, which allows for easier maintenance and upgrades.

 

3. Better Performance and Scalability

Headless solutions ward off the architectural barriers of traditional CMSs, facilitating better site or application performance. The decoupled nature of the front-end and back-end allows the application to handle more traffic without impacting performance.

 

4. Seamless Integration with Different Devices and Platforms

With headless, developers can create content once and use it across multiple channels and platforms, including mobile applications, web applications, and digital signage.

 

5. Enhanced Security and Data Management

Headless architecture also provides enhanced security and data management. Again, since the back-end is separate from the presentation layer, it is easier to secure and manage data. This makes it easier to comply with data privacy regulations such as GDPR and CCPA.

 

How Headless Solves Common Issues of Traditional Architecture?

One of the main technical issues with traditional CMS for mobile application development is that it relies on a tightly-coupled architecture. This means that the front-end and back-end are closely integrated, making it difficult to adapt to changes in the mobile landscape. For example, if a new device or platform is released, it can be difficult to update the CMS to work with the new device or platform.

Since headless architecture uses a separate front and back-end architecture, it is easier to adapt to changes in the mobile landscape, as businesses can simply update the API to work with the new device or platform. 

Additionally, the headless architecture allows businesses to take advantage of the latest trends in the development space. For example, businesses can use headless architecture to create applications that work seamlessly with emerging technologies like augmented reality (AR) and virtual reality (VR). This allows them to create immersive, invaluable experiences.

 

The Future of Headless CMS and Modern Application Development

Headless architecture is expected to play an increasingly important role in application development as businesses look for more efficient and cost-effective ways to deliver high-quality digital experiences.

One of the emerging trends in headless CMS is the use of artificial intelligence (AI) and machine learning (ML) to optimize the performance and scalability of the application. This is expected to soar as businesses look for ways to improve the user experience, increase engagement rates, and lower costs.

 

Real-Life Examples of Mobile Application Development Problems Solved by Headless

Shopify, a popular eCommerce platform, uses headless architecture to provide a seamless shopping experience across multiple devices and platforms. Another example of a company successfully using headless architecture is the famous footwear and apparel brand Nike, which employs a headless architecture for its mobile-first site to accommodate better mobile experiences.

Many more companies have taken the leap to headless and will continue to do so as they realize its benefits, especially for providing unparalleled mobile-first experiences.

 

Conclusion

Headless architecture has emerged as a game-changer for modern application development. It has solved many problems associated with traditional CMSs and has brought forth greater developmental flexibility and agility.

Want to implement headless? We can help! Contact us today and let our experts guide you through the process.

Application development initiatives are becoming more distributed by the day. Security is being incorporated early in the pipeline. Automation (thanks to AI and ML) is finding its feet in the DevOps practice. In some way or the other, all of this is being made possible because businesses are inclining towards the use of microservices architecture and containers. In most cases, the combination of the two, i.e., containerized microservices, is driving development for good. 

This article serves as an early guide to microservices and containers and how they contribute to successful application development, especially in the age of cloud apps.

 

The What(s) and Why(s) of Microservices

The microservices architecture involves breaking up the application into small, independently functioning units or services. Usually, these services represent a specific business functionality or feature. Take the example of an eCommerce mobile application. It will have a dedicated service for each of these functions – inventory, product, checkout, cost, etc. 

Why microservices? Essentially, microservices are self-contained, independent modules of an application. They communicate via API calls, message brokers, or a service mesh. These services can be scaled and deployed separately, meaning you don’t have to worry about the performance and availability of other parts of the application when one microservice is having issues. Likewise, you don’t have to deploy the entire application in one go; you can deploy a service with all its applications and dependencies separately. Similarly, when you need to make changes, you can do so for one service at a time without worrying about having to bring down the entire edifice. This capability is also called loose coupling and serves as one of the main advantages of using microservices.

 

The What(s) and Why(s) of Containers

Containers are essentially packages that hold all the dependencies required to run an application. They work at the operating system level and include all the underlying settings, tools, libraries, etc., needed for the application to run in the desired state. This means, if you want to deploy a specific application to an environment, you don’t have to worry about the underlying infrastructure. The container would help in the deployment of applications regardless of the environment – be it a corporate data center, a personal computer, or a public cloud.

Why containers? Containers allow developers to make use of resources only as needed. Also, they have a smaller memory footprint compared to, say, virtual machines. Consider the case for Docker container images. These images are lightweight, executable packages that become containers during runtime. The images don’t occupy much space at rest and can be accommodated easily. 

 

Can Microservices and Containers Work Together?

The answer is a resounding yes. The whole point of using microservices and containers together is to make application development more streamlined. In general, microservices can be executed in different environments – for example, via Virtual Machines (VMs) and even physical servers. The latter, of course, isn’t always preferable in the wake of the heavy workloads of today’s cloud applications. VMs, too, aren’t usually favored because using an individual VM for each microservice would result in an expensive, inefficient deployment. 

Containers, therefore, become the default choice here. Because they are lightweight and can be supported by even a single OS instance, containers prove to be a perfect solution for microservices. They enable an environment where applications can be easily deployed, configured, run, and scaled. In simple words, containers help realize the full potential of microservices in terms of executing them in an isolated environment, thus, avoiding security issues to spread and allowing developers to tend to each service separately as needed. 

 

How Microservices and Containers Drive Application Development?

The 2022 State of Application Development report by Docker revealed that 60% of the back-end developers employ containers. While both containers and microservices have been on the rise for some time now, the recent surge in popularity is predominantly because of benefits they deliver for application development. Here’s a rundown of the same:

 

Separation of Concerns (and Independent Scaling)

Applications today are getting increasingly sophisticated owing to an increasing user base and technological integrations. Imagine how sophisticated an application like Netflix or Amazon would be – they’d have numerous microservices, each working in tandem to provide a seamless experience for their customers. But even if the application isn’t comprehensive, it’s necessary to be able to modify, evolve, and scale it according to needs – precisely where containerized microservices prove immensely viable. 

They allow developers to change or add features without affecting the rest of the application. This is especially useful when the application is undergoing development and testing. Additionally, microservices enable independent scaling of services, thus allowing businesses to modify scale requirements as needed. 

 

Language & Framework Flexibility

As mentioned above, development is highly distributed today. This means that different development teams are working on different business units. With microservices and containers, the teams can use their preferred languages and frameworks for the microservice under their control. This helps reduce the overall time to market and enables more focus on each microservice.

 

Iterative & Agile Development

Containerized microservices allow developers to define, design, and test a service independently. Containers, in particular, ward off the concerns pertaining to the environment and dependencies. This makes it easier for developers to iterate on their services and work in isolation. More profoundly, this:

• Complements modern-day development methodologies like DevOps and DevSecOps
• Automatic deployment of microservices to the respective environment once they have been tested

 

Cloud-Native Development

Both containers and microservices inherently complement the cloud-native development practice. Containerized microservices can be scaled independently (as mentioned above); they construct an additional security layer between the application and the environment and don’t get bogged down when one of the services is down. All these features, together with the inherent operational efficiencies of deploying microservices via containers, make a compelling case for developing cloud-native applications using containerized microservices.

So, there you have it! The burgeoning synergy between containers and microservices and its benefits for application development are hard to ignore. While both technologies have been on the rise for quite some time now, they couldn’t be more relevant today. Contact us to learn more about containerized microservices and how they can help you develop and modernize enterprise apps.

Serverless has gained traction over the past few years as more and more businesses realize the potential benefits that come with letting the cloud vendor handle the managing and provisioning of servers. 

As it stands, AWS, Azure, and Google Cloud Platform (GCP) are leading the way in the serverless category — with services like AWS Lambda and Azure Functions setting the new standard for building and deploying applications to the cloud. 

As per the State of Serverless report by Datadog, more than 70% of the organizations using AWS are now leveraging serverless. As for Google Cloud, around 55% of organizations are doing so. Azure’s serverless usage is almost on similar lines to Google, with just over 50% of enterprises using serverless on the cloud. 

But do these three vendors offer the same capabilities? Which one is a better choice for your organization? How do their serverless capabilities match up? Let’s discuss.

For the purpose of this article, we are going to look at the most prominent serverless offerings from each cloud vendor – AWS Lambda, Azure Functions, and Google Cloud Functions.

 

Programming Language Support

One of the special advantages of using serverless is that development teams can choose their preferred programming languages based on their skill set, functionality requirements, convenience, etc. But is this polyglot advantage facilitated by different cloud vendors? Let’s find out.

 

AWS Lambda

AWS Lambda allows teams to use common languages like Python, Java, Node.js, C#, Go, PowerShell, and Ruby code. However, developers can leverage the Runtime API to author functions in languages other than these. 

 

Azure Functions

Azure Functions accommodates two levels of language support – Generally Available (GA) and Preview. GA means fully supported, and Preview means “Not yet supported.” As far as GA is concerned, languages like C#, JavaScript, F#, Java, PowerShell, Python, and TypeScript fall into the purview. The language versions keep evolving, and Microsoft recommends not to pin the apps to a certain version.

 

Google Cloud Functions

Google Cloud Functions primarily supports these languages – Java, Python, Ruby, .Net, Node.js, and Go.

Altogether, the language support is quite comprehensive, with minor differences like Azure not supporting Go, which is supported by both GCP and AWS.

 

Scalability – Concurrency Potential

Scalability is the ultimate need today, with cloud-native applications having to adapt to changing demands and handle a massive number of concurrent requests. Let’s find out what the leading cloud vendors have to offer in this department.

 

AWS Lambda

Lambda provides the capability to instantly scale the application to handle the required load. A single request can quickly scale to thousands of requests. In fact, AWS defines how to consider the scalability potential in terms of two key metrics – concurrency and transactions or requests per second. 

Concurrency is the measure of concurrent requests for Lambda functions. Lambda, by default, puts the concurrency limit at 1000. However, this can be modified based on custom requests.

 

Azure Functions

Azure doesn’t explicitly outline the concurrency limit. However, it does provide information on the “maximum instances.” A single function app can support up to 200 instances. But each of these instances can support multiple requests.

 

Google Cloud Functions

Google’s definition of concurrency is a bit similar to Azure. Concurrency is representative of the concurrent requests being handled by a single function. By default, concurrency is set at 1. It can be increased as per demand – up to a value of 1000. 

In sum, all three vendors facilitate the utmost scalability. However, businesses must consult experts before choosing the vendor because the costs can vary, as the definitions of scalable requests and instances vary across each vendor. 

 

Security

Security is an important aspect when building applications on the cloud — especially for enterprises that handle sensitive data. Although serverless is essentially secure by design, a few measures can be taken to further protect the data. 

 

AWS Lambda

Lambda works on a shared responsibility model – segregating the security into two:

• Security of the cloud
• Security in the cloud

Security of the cloud is handled by AWS in accordance with AWS compliance programs. Security in the cloud revolves around the best practices that businesses must adopt to:

• Facilitate data protection
• Ensure robust identity and access management
• Perform configuration and vulnerability analysis
• Carry out compliance validation

 

Azure Functions

Azure, on the contrary, tasks the Azure App Service to ensure the security of function apps. This practice involves the usage of App Service to run continuous compliance checks and:

• Ensure the security of all the app resources
• Ensure that no communication between Azure resources crosses the network boundaries
• Facilitate 24-hour threat management
• Ensure encryption of connections with tools like REST APIs, Azure CLI, etc.

 

Google Cloud Functions

Security of Cloud Functions can be defined in terms of:

• Identity-based access control: This involves authenticating and authorizing the identity of the requesting entity.
• Network-based access control: Cloud Functions provide the capability to fine-tune the control over the traffic entering or exiting a network boundary.

All the vendors adopt a seemingly different approach to security, and it’s wise to consult with the technology partners about what’s viable based on the specific business requirements.

 

Pricing

The costs accrued across each of these vendors’ serverless offerings are dependent on the memory provisioned and the number of requests. For reference, here’s how the costs compare when talking in terms of executions or requests:

• AWS Lambda – $0.20 per 1 million requests
• Azure Functions – $0.20 per 1 million requests 
• Google Cloud Functions – $0.40 per 1 million requests

While Cloud Functions costs more, it gives 2 million monthly free requests compared to AWS and Azure’s 1 million.

 

What to Choose?

All these serverless offerings are extremely promising. The choice should be predicated on the budget, strategy, and project context. For instance, GCP might accrue more costs down the line, whereas Azure would not support a particular language like Go. Each vendor, however, promises high scalability, so the choice is not that cut-and-dry. It’s best to partner with a technology expert who can help you choose the right vendor and deploy the ideal serverless solution. That’s precisely where Sagacity can help. Reach out to us today!