Unravelling the Server vs. Serverless Conundrum: A Guide to Optimal Computing

In the ever-evolving realm of modern computing, the distinction between server and serverless architectures has emerged as a crucial consideration for businesses seeking to optimize their technological infrastructure. This profound divide presents both opportunities and challenges, shaping the way we deploy, manage, and scale our applications. In this comprehensive guide, we embark on an illuminating journey into the intricacies of server versus serverless computing, unravelling their fundamental differences, exploring their respective strengths and limitations, and providing invaluable insights to guide your decision-making process. Let us embark on this exploration and elucidate the path toward optimal computing architecture. Delving into their strengths, limitations, and strategic implications, we aim to empower software architects and engineers with the knowledge to make informed decisions. This discourse delves into the complexities of server-based and serverless architectures, providing valuable insights for organizations seeking to optimize their agile software development processes.

Traditional databases vs managed databases vs serverless databases

Traditional databases (Server Database)

Traditional databases are a type of database management that has been available for several decades. It requires setting up a physical or virtual server with the necessary hardware resources to act as a database server. However, this setup involves more than just installation and configuration. It requires ongoing management of the underlying infrastructure, such as hardware health, resource management, and network access. Additionally, the operating system must be kept up-to-date, stable, and secure, and the database management system must be configured, optimized, and managed.

Although traditional databases provide a high level of control and flexibility, they come with a greater management burden. Every part of the system must be maintained and optimized to provide optimal application performance while ensuring the system's availability and data security.

Serverless databases

Serverless databases are a novel approach offered by cloud providers that take on a significant part of the management responsibility from users. These databases separate the storage component from the one that runs queries. This means that both components can be scaled independently. The provider manages both of these components entirely in serverless databases.

In practical terms, serverless databases can be considered a limitless storage repository where data can be stored, processed, and retrieved. The backend storage is automatically scaled up as needed, and the number of query executors is adjusted based on demand. Users can access the database through an API-like interface that automatically routes commands to the appropriate components.

Compared to other options, serverless databases require the least amount of operational management. This allows users to use the database as an external service rather than as an infrastructure component that must be kept operational.

Managed databases

Managed databases are a popular product offered by most cloud providers as an alternative to managing your own infrastructure. With managed databases, the cloud provider manages the server configuration and database software and offers options to the user to configure and customize the behaviour as per their needs.

The provider takes responsibility for ongoing management of the underlying infrastructure, including hardware health, resource management, and network access. They also ensure that the operating system is up-to-date, stable, and secure, and manage certain aspects of the database system, like its health and functionality.

Nonetheless, the user retains the responsibility of determining the best configurations for their database and establishing guidelines for scalability, backups, and additional software-level settings. The provider exposes key configurable areas to the user so that they can tune behaviour as per their requirements.

Managed databases are a great option for organizations that want their developers to focus on customizing the parts of the database they care about without having to maintain in-house system administration expertise. However, it's important to note that this approach may not suit everyone. It's crucial to ensure that the level of control and automation offered by the provider aligns with your organization's needs.

Which Architecture to Choose? Server-Based Computing or Serverless Computing

Server-Based Computing

The traditional method of managing the entire stack of a database server, from hardware to database software, is best suited for those who require control, privacy, and high performance.

Pros:

• Control and customization
• Scalability and high performance
• Suitable for complex applications

Cons:

• High infrastructure costs
• Requires maintenance and management

High Level of Control:

A conventional database server requires continual monitoring, maintenance, and contingency planning to maintain availability, but it offers unparalleled levels of control. Users can choose the infrastructure architecture that suits their specific needs, from a single server to a complex cluster. They can deploy these assets wherever they want, whether on-premises, in data centres with their own or rented hardware, or by using standard compute assets from cloud providers. Users can upgrade and swap out any components as needed and tweak any software-level configuration without any limitations.

Data Privacy Focus:

If application data requires very high levels of privacy, traditional databases give users the most amount of control. They can dictate exactly who has access to the physical hardware where they are deployed, as well as any software-level access. Running their own database servers ensures that users can put the necessary levels of protection in place for their users and data. The data for different clients can be placed in different databases, on different servers, or in different physical locations to maintain strict separation. Users can decide on deploying to data centres that meet certain industry standards to ensure that physical access is restricted. On the software level, users also start from a place with no external access. No other parties have management oversight of their services by default. Users can protect their data by refraining from providing access and by setting up encryption and other safeguards to provide the level of protection they require.

High Performance:

If an application requires consistent high performance, a conventional database deployment might be the best strategy. By running database servers themselves, users can spot and mitigate contention for resources more easily since they have complete insight into the processes and clients competing. They don't have to worry about neighbouring customers taking too much of a shared resource, and they can provision additional assets as necessary. The peak performance of the system is limited only by the time and money allocated and the expertise in managing the systems.

Especially relevant when compared to serverless databases, the continual availability of server database resources is a significant advantage. There are no cold start problems, as there is no need to scale down layers of infrastructure whenever demand falls below peak demand. This can be important for those who require consistent performance regardless of the previous level of activity.

Serverless Computing

Serverless databases offer several advantages, provided they suit your use case. They are an excellent choice if you want an affordable database that can self-scale without requiring heavy management.

Pros:

• On-demand scalability
• Pay-as-you-go pricing model
• Reduces operational burden

Cons:

• Vendor lock-in
• Limited control and customization options

Low Operation Costs

Low-cost operation is one of the primary benefits of serverless databases. Since the storage and computational layers of the serverless database scale independently, you only pay for what you use. The storage layer scales according to the amount of data you manage, which is usually priced according to volume, making it relatively predictable if your application has consistent patterns. Since this storage backend is dynamically allocated, you never have to worry about running out of space or overpaying for storage. The computational layer scales independently, with the number of query executor instances provisioned being determined by the current traffic to the database. This means that during peak traffic, the service will spin up additional query processors to handle the requests, while during periods of low activity, the service can scale down to zero, removing the cost of processing entirely. Serverless databases are a good option if you are cost-sensitive, as the platform's resources and your costs scale precisely with your usage.

High scalability

High scalability is another significant advantage of a serverless database strategy. The separate scaling mechanisms for data storage and query execution allow you to handle varying levels of usage scenarios using the same service and configuration. The service can automatically adjust to accommodate most usage levels and can grow with your application without any change to the database service. High scalability also means that you can experiment with applications easily and move from testing to production without making changes to your database service. You can set up testing and staging databases that will scale down to zero when not in use. This can be especially useful when practising continuous integration and continuous delivery because your pipelines can use a database service that perfectly mirrors your production environment while only paying for the small amount of usage your tests require.

Reduced Management responsibility

Serverless databases can also help offload management responsibilities from your team. The platform manages the infrastructure, database management system software, resource allocation, and many of the policies for your databases. Instead of having to determine how much storage or how many database instances are required to serve your average traffic levels, the system can respond to the conditions it finds. You only need to configure thresholds for the cost and any specific tweaks to the scaling you want to make, and the system handles everything else to ensure that your application's database usage is always available, performing up to standards, and responding to the current request environment. This is different from managed databases, which require more administrative overhead.

Strategic Analysis for Agile Software Development

Benefits of Serverless for Agile Development:

Serverless computing is a cloud computing model that allows developers to build and run applications without having to manage servers. This model offers several benefits for agile development. Advantages of using a serverless database:

Cost-efficient

Using a serverless database can be very cost-effective due to its runtime model, which charges you only for the resources that you use. This means that when your application is idle, you only pay for storage, reducing your operational costs in the long run. In contrast, with traditional in-house servers, you pay a fixed amount for computing resources, which often go underutilized. This results in unnecessary expenses, as you have to pay for the full capacity regardless of how much you use.

Boosts productivity

Serverless databases offer a compelling alternative to traditional in-house servers since they free businesses from the burden of server maintenance. Unlike traditional servers, serverless databases don't require installation, provisioning, or any other type of maintenance. The service providers handle all the maintenance, allowing businesses to focus on building their applications. This translates into faster application development and deployment since development teams aren't bogged down by the stress of server management operations. Additionally, it eliminates the need for businesses to hire extra talent to manage their infrastructure, ultimately saving them both time and money.

Efficient scalability

A serverless database is a great solution for businesses that require scalability. This is because the database can easily expand to meet the growing needs of the business without requiring a switch to a more powerful server. By doing this, it ensures that the application is future-proof and can handle any unforeseen workload. Additionally, the automated scaling of the serverless database eliminates any risk of server overload, which can cause downtime in traditional servers. In-house servers have limited resources, which means that they can experience overload when traffic spikes. Therefore, a serverless database guarantees a smoother user experience compared to traditional servers.

Improved resilience and availability

A serverless database allows you to create multiple datasets distributed across a vast region. This means that if one node fails, all functions are automatically diverted to the nearby functional nodes until the faulty one is fixed. This makes your application more resilient to failures while also improving its availability. Additionally, functions are executed based on the closest dataset to the user, which reduces latency and provides a faster experience.

Simplicity

Serverless databases simplify the process of working with databases and offer a straightforward API for users to create and execute functions and computational logic. With these databases, developers can easily create clusters and manage operations with minimal effort, which helps streamline business operations. Furthermore, even teams without system administration experience can begin production quicker, as they do not have to hire dedicated experts to manage their infrastructure.

Challenges with Serverless for Agile Development:

When it comes to serverless computing, the development process can become more challenging if you're trying to follow the Agile methodology. Two of the major issues that can arise in this context are debugging and observability. However, the lack of a server can make it harder to capture and analyze the data. Another challenge is the dependence on third-party vendors, which can be a source of risks such as service disruptions or unexpected changes in API. It's essential to have a clear understanding of these challenges to develop effective strategies that mitigate the risks and ensure a smooth workflow.

Here are the disadvantages of using serverless databases:

Response latency

When a database isn’t being actively used, it goes into “idle mode” to save on resources. As such, when the app restarts, it may experience response latency as the database takes time to relaunch the underlying resources. This problem is commonly known as a "cold start", and can potentially impair user experience. If your application is performance-sensitive, serverless databases may not be an ideal choice for you. To solve this problem, you’ll have to pay to keep some resources pre-warmed for your application. Cumulatively, these expenses can exceed the cost of configuring in-house servers with a fixed throughput.

Difficulty in testing and debugging applications

A serverless database makes it almost impossible to monitor and diagnose an app’s performance. This is because it’s difficult to replicate a serverless architecture environment since most serverless databases aren’t open-source. However, you can use some third-party serverless tools to monitor your app’s performance.

Security

Serverless databases are often considered safe since the vendors are responsible for securing the system's vulnerabilities. However, it's a business's responsibility to configure its app's logic, data, and security-related layers that determine how an app interacts with the serverless database ecosystem. This introduces room vulnerabilities where every element can be an entry point for a hacker.

Vendor lock-in

It's easy for a business to be tied to a vendor's serverless database solution. This makes it difficult to switch to other alternatives since each vendor offers unique features and additional perks.

Comparison between Serverful and Serverless

Performance and scalability

When it comes to how quickly a computer can perform certain activities, using a long-running server, also known as serverful computing, can be quicker than using short-lived functionalities from serverless computing. This is because serverless computing requires the function to be started each time it is used. This is known as a cold start.?

When it comes to scalability, server computing may be slow and expensive. This is because it frequently requires more servers and IT staff to keep it working. However, serverless computing is designed to withstand large fluctuations in demand. The business does not need to take any more action because the cloud provider will ensure that there are enough resources to handle the request.

Cost-effectiveness

Overall, serverless computing is a lot more cost-effective. The reason is simple: you pay for what you use, and during the hours when you have low traffic, your serverless cost drops as well.

On the other hand, with servers, you need to anticipate the traffic and have some of the servers always running even when the traffic is low.

Caching

When users use the internet, they submit requests to servers to get information. These requests can be set up in either a serverful or serverless architecture.?

In server architecture, the server is always running processes requests saves data, and remembers previously used information. This implies that it can operate swiftly and efficiently, which is beneficial to those who use the server.?

Some businesses, however, rely on serverless architecture. In this setup, servers only run for a short time when someone needs them. This might cause issues since the server may not recall previously used information. This can make responding to requests take longer.

One way to fix this is to use a special database called Redis to store information.?

Another way to fix this problem is to store information on the user's computer or phone instead of on the server. The only concern is, it's important to make sure that the information being stored is safe and secure.

Database Connection Pooling?

Connection Pooling is a solution to prevent your application from exhausting all available database connections. It works by keeping some connections to the database open and available to use whenever needed. This also saves time and resources because opening and closing connections takes a lot of effort.?

Because server architecture has long-running servers, pooling connections is easier. On the other hand, in a serverless app, each user request usually results in a new function running in an isolated environment, you can easily exhaust all the database connections.

In serverless architecture, cloud providers like Amazon RDS or Azure SQL Database manage the connection pooling. They automatically take care of the connections for the application, making it easier to use a database in a serverless environment.

Moreover, as more apps are moving to serverless, companies have launched serverless drivers to seamlessly integrate database operations into your serverless apps.

Long-Running Tasks

Since server systems have long-running tasks, they can be managed by the server using background threads or worker processes. However, in serverless systems, long tasks can be handled using asynchronous functions. These functions act as mini-programs that can run independently, complete tasks, and not keep the user waiting. Additionally, cloud provider services such as AWS Lambda or Azure Functions can assist in managing these tasks.

However, if you have long-running tasks, the server makes more sense. Microservices have gained popularity in recent years due to their ability to improve scalability, security, and sharing in applications. However, too much componentization can lead to increased latency and operational complexity. Traditional microservices often grow larger and more similar to traditional services, while componentization limits the potential for transactional activity.

Combining server and serverless for optimal results

Uncover the advantages that result from coupling serverless with microservices, and see how cloud providers prepare for customers to use these technologies together.

Fortunately, a new approach has emerged that can trigger microservices more efficiently. This approach involves a convergence between microservices and serverless computing. While serverless was originally designed for event-triggered applications like IoT, it has evolved to encompass a wider range of applications.

The leading edge of both serverless and microservices is event-driven application and business process orchestration. This involves triggering events to mark progress and then using those events to activate processes and workflows. These workflows can be defined and imposed on stateless events and processes, resulting in more efficient and streamlined application performance.

To achieve this, applications must be capable of generating triggered events, and there must be a mechanism to activate processes according to those triggers. Additionally, a method must exist to define and impose workflows on stateless events and processes. Cloud providers now provide all three of these elements, making it easier for businesses to harness the power of serverless and microservices.

Orchestration and integration tools such as Amazon's Step Functions or Microsoft's Logic Apps can sequence application components, such as microservices and serverless, based on events generated by significant steps in other applications. Microsoft uses connectors that provide a trigger for things like document changes in Office, which can then kick off other applications and update databases. They can also trigger user-developed functions and microservices that run on demand as serverless components.

Both Amazon and Microsoft offer respective case studies to illustrate the use of step functions and logic apps in orchestration missions. These examples show that serverless and microservice components can play similar roles in distributed business applications and process orchestration that were traditionally played by service bus technology.

By adding more useful application-generated triggers, the granularity of the events generated improves. Instead of simply controlling what gets activated based on data examination, as BPL typically does, you can control processes based on signals from within other processes.

Microsoft's Power BI relates to its Office 365 suite and how Office tools can use connectors to generate events that Logic Apps can orchestrate. Microsoft has moved Logic Apps to a position directed much more at business integration. Amazon and Google both offer similar capabilities for their cloud-hosted features, and Google recently extended its support for hybrid applications when it extended its Cloud Platform to on-premises environments.

The idea that microservices and serverless could join to bind business processes and integrate business applications from desktops and data centres to the cloud is transformational. Event-driven serverless microservices could provide the perfect way to fulfil a multitude of business needs. How this happens depends on the ongoing cloud provider battle for control of business and application orchestration.

Enterprises were never the largest cloud users, as that honour goes to high-tech social media and content firms. But this will change. Microsoft already has a larger share of the enterprise cloud market, and both Amazon and Google want much larger pieces of the enterprise pie. Serverless and microservices will play a big role in the battle, and enterprises will be the real winners.

However, for businesses with unpredictable workloads and the need for automatic scaling, serverless computing may be a more effective solution. Serverless computing allows businesses to scale seamlessly and only pay for the resources they use, resulting in significant cost savings.

Additionally, serverless computing can be an ideal solution for businesses that need to quickly deploy new applications and services without the need for extensive IT management.