Shopify, Salesforce, Adobe, Zoom — they are titans of the SaaS universe, each showcasing the power of resilient and scalable infrastructures. As the SaaS market rockets skyward, businesses must heed their lessons and shape robust, high-availability architectures. This article will lay out the steps and processes involved in building a similar type of architecture—complete with high availability for stakeholders.
What Is SaaS Architecture?
A SaaS architecture is where a provider keeps an application on a distant server. Then, they deliver the application’s abilities over the internet to a company’s users. The setup may involve different firms using the same settings and model. So, they use the same hardware, network, hosted application, and more.Companies can use the architecture as it comes. Or, they can use an Application Programming Interface (API) to make changes. This can help meet their software needs.
To use this ready SaaS solution, users pay a regular fee. They don’t buy a full copy ahead of time or put the software on every computer. The SaaS provider deals with all the technical parts like hardware, updates, and security.
SaaS is not like Infrastructure-as-a-Service (IaaS) or Platform-as-a-service (PaaS). In IaaS, a cloud service gives a company resources like servers, storage, and networking in the cloud. Some examples are Amazon Web Services (AWS), Digital Ocean, and Microsoft Azure. PaaS providers offer a place where a company can build, manage, and deliver its apps. Some examples are AWS Elastic Beanstalk, Red Hat OpenShift, and Force. In both of these, the cloud service deals with backend tasks like security, updates, backups, and operating systems.
What Is High Availability?
High availability means a system stays working for a long time without stopping. It is usually measured as a percentage. For example, 100% means the system had no breaks. But it’s tough to make a system that never stops. Even big names like Google, Amazon, and Microsoft aim for 99.9% uptime.
SaaS architecture availability depends on different factors. These include unexpected loads, how quickly it recovers, more users, planned and unplanned maintenance. All these are promised in service level agreements, or SLAs.
But, high availability and uptime are not the same. Availability talks about how many connections a server allows. Uptime talks about if a server is reachable by at least one service. So, uptime is about the system’s structure, and high availability is about the application. In a SaaS model, both need to work well together.
What Other Concepts Are Associated with High Availability?
- Load balancing: This involves making copies of machines, a method known as redundancy. The role of a load balancer is to manage and share the work among these machines. To create a straightforward and reliable load balancer, tools like Nginx and a round-robin algorithm can be used.
- Floating IP addresses: This addresses allow an external IP to be quickly attached to different machines. So, if a load balancer stops working, the floating IP can be attached to a backup machine instead.
- Celery workers: Analyzing clicks data is heavy work. To prevent this from impacting user experience, the analysis is done in the background. Celery is a tool that can manage these background processes efficiently.
- Databases: Databases may stop working due to various issues. To keep them accessible, replication is used. This means storing data in several locations instead of just one.
- Database replication: This can be done in two ways. Data is either spread among different machines or duplicated between machines. If it’s duplicated, then any change in one machine must be updated on all others.
- SQL and NoSQL databases: For different tasks, applications often use both SQL and NoSQL databases. PostgreSQL and Redis are examples of such databases. PostgreSQL works well with the Django web framework, and Redis is suitable for storing cache data and managing background processes.
How to Build a Reliable, Scalable SaaS Architecture
The best way to build a scalable SaaS architecture is to follow industry best practices. These include:
Embracing Microservices
Microservices architecture is a software development technique that structures an application as a collection of loosely coupled services. This architectural style is favored for its scalability and flexibility. For a growing SaaS application, microservices allow each service to be written, deployed, and scaled independently. This compartmentalization means a failure in one service does not affect the entire system, thereby promoting overall system resilience.
Implementing Multi-Tenant Architecture
A multi-tenant architecture is a principle in software architecture where a single instance of software serves multiple customers or “tenants”. It optimizes resource utilization by sharing computing resources among various users, improving overall system efficiency. However, bear in mind that not all users are created equal, and high-demand users may require more resources, which could impact the performance of others in a multi-tenant environment.
Enabling User Customization
Most SaaS users have unique needs and preferences. Enabling customization and self-service allows users to tailor your solution to fit their exact requirements. This includes providing robust, easy-to-use APIs and comprehensive documentation, which can help users adapt and integrate your SaaS offering into their existing workflows without having to write code. This encourages user retention and can open avenues for organic growth.
Designing with Data Security in Mind
As more business processes become digitized, data security is a non-negotiable aspect of any SaaS architecture. Role-Based Access Control (RBAC) is a great method to ensure this security. RBAC restricts users from accessing and modifying data unrelated to their role, thereby enhancing overall SaaS security. It allows you to specify exactly who can access what, ensuring sensitive data is only accessible by authorized personnel.
Ensuring Regulatory Compliance
Regulatory compliance is a critical aspect of any SaaS offering, especially for vertical SaaS applications designed for specific industries. Industry-specific regulations, along with cross-industry regulations such as the General Data Protection Regulation (GDPR), need to be built into the application from the get-go. Meeting compliance requirements from the beginning can save your organization from potential penalties and reputation damage in the future.
Minimizing Downtime
In the cutthroat environment, high availability and minimal downtime are paramount. Your customers rely on your service to be always available and any significant downtime can lead to customer churn and revenue loss. Regularly tested updates and a robust support system can mitigate downtime risks and maintain user satisfaction.
Planning for Scalability
Scalability should be a key consideration from the very early stages of SaaS architecture design. As your customer base grows, your SaaS application will need to handle an increasing number of transactions, queries, and metadata. Designing the architecture to easily scale both vertically (adding more power to existing machines) and horizontally (adding more machines) and can ensure your application continues to deliver optimal performance as it grows.
Addressing Vendor Lock-In Concerns
Vendor lock-in is a common concern for many organizations. They fear becoming overly dependent on a single vendor and facing difficulties should they need to switch providers. As a SaaS provider, assuaging these fears means ensuring your solution supports standard integration APIs, giving users the flexibility to connect your solution with other applications. This not only fosters trust but also encourages long-term partnerships.
Monitoring Costs
Tracking the costs associated with your SaaS solution is critical to maintaining profitability. Implementing cost monitoring allows you to understand which customers, products, teams, or units incur the most costs. This visibility into your cost structure can guide feature prioritization, budget allocation decisions, and pricing strategies.
How to Achieve High Availability For SaaS infrastructure
Once you’ve built your SaaS infrastructure, it’s time to remember the big picture: high availability. Several steps are required to put your endpoints, devices, networks, etc. in this state. Take the steps below to ensure high availability:
Balance Between Simplicity and Complexity
Striking a balance between simplicity and complexity is critical. While complex systems may offer greater capabilities, they are also more prone to failures, leading to reduced availability. Conversely, simpler systems may offer fewer features but have less downtime. Microservices architecture can help manage this balance, allowing individual system components to operate independently, reducing the risk of widespread failures.
Apply Autoscaling
Autoscaling dynamically adjusts the number of computing resources in a server based on the current workload. This ensures efficient use of resources and maintains system performance even during peak loads. Scalability can be achieved vertically by increasing the size of the machine to boost processing power or horizontally by integrating multiple independent computers into a system.
Utilize Monitoring Tools
Monitoring tools can track application performance, real-time functions, and error rates, providing insights into potential issues. By setting predefined thresholds for error rates, these tools can alert you to ongoing or potential problems, enabling you to take preventive measures and minimize downtime.
Leverage Load Balancers
Load balancers distribute network traffic across several servers to prevent overloading a single server. This increases the system’s capacity and reduces downtime. Using primary and secondary balancers to distribute workload across data centers can assure uninterrupted application delivery.
Adopt Multiple Application Servers
Deploying applications across multiple servers can prevent overburdening a single server, reducing the risk of system crashes and outages. It eliminates the risk of a single point of failure, ensuring that in the event of a server failure, traffic can be redirected to another server to maintain system availability.
Create a Failover Setup
Introducing network redundancy can prevent a single point of failure. Auto-failover solutions provide a standby host that can take over in the event of an active host failure, keeping connections active and minimizing downtime.
Implement Clustering Techniques
High availability server clusters are groups of servers supporting the same set of functions, thereby preventing downtime by detecting failures, performing failover, and restoring operations. These clusters improve performance, scalability, and availability. In the event of a server failure, critical services are immediately transferred to another server.
Ensure No Single Points of Failure
In a high availability system, there should be no single points of failure. Failover setups detect and handle failures, ensuring that if one instance fails, a standby option can take over, maintaining uptime and continuous operation of critical services.
Maintain Hardware Redundancy
Hardware redundancy is achieved by creating multiple physical copies of hardware components, such as servers, power supplies, and memory. Applying redundancy to high-level components reduces the risk of outages during high-load periods. A reliable crossover setup ensures that failover systems take over seamlessly when a server crashes or stops responding. This allows a backup component to replace a failed one without data loss or performance reduction.
Establish Software and Application Redundancy
Software and application redundancy, like hardware redundancy, provides backup elements to take over when another instance is affected. Redundancy helps achieve reliability goals subject to technological and economic constraints and supports self-healing programs.
Achieve Data Redundancy and Apply Self-Monitoring
High availability systems ensure data redundancy, storing the same data in multiple places. This safeguards against data loss and guarantees data recovery if a memory location or server fails.
High availability systems have self-healing and self-monitoring functionalities to detect unusual failure rates or affected instances. This enables rapid detection and rectification of errors, minimizing potential harm to the system’s functionality. Efficient self-monitoring can greatly increase system uptime.
Conclusion
High availability and scalability are fundamental for any SaaS architecture to operate successfully. The discussion thus far illustrates the importance of these two elements and their role in enhancing the reliabilit and overall performance of SaaS systems. Fortunately, there are several ways to improve upon these aspects and set your architecture up for big projects.
The takeaways are:
- Balancing simplicity and complexity is crucial, as it allows for reliability while still offering robust capabilities.
- Employing multiple servers and utilizing load balancers can prevent single points of failure, ensuring high availability and efficient traffic management.
- Implementing various redundancy measures across hardware, software, data, and applications ensures that backups are readily available to take over when failures occur, ensuring continuous operation and high availability.
- Autoscaling is vital for adjusting computing resources based on workload, ensuring system efficiency and maintaining performance during peak loads.
Remember, the strategies and practices to achieve high availability and scalability are numerous and varied. The ones list above should meet the specific requirements and context of your SaaS architecture.