7 ways to build scalable platforms that serve high traffic
As businesses grow and add more users and demands increase, scalability and performance become critical aspects to consider when designing software architecture. Several techniques are available to help you scale and maintain high performance as traffic increases. We will walk through seven popular scaling techniques to design applications.
1. Load balancing
Load balancing is a technique for distributing incoming traffic over numerous servers so that no one server becomes overburdened. They operate as intermediaries between the client and the server, distributing load using various methods such as round-robin, least connections, and IP hash.
Load balancers come in two flavors: hardware-based and software-based. Hardware-based load balancers are physical devices that can deploy into data centers as part of network infrastructure. Software load balancers, as the name suggests, are installed on commodity servers to perform the load balancing. Software load balancers are generally cheaper, easier to manage, and dynamic to configure compared to hardware load balancer.
Load balancing algorithms
Algorithms for load balancing dictate how traffic is distributed among several servers. Several load balancing algorithms exist, including:
- Round-robin: This method distributes traffic evenly and sequentially across all available servers.
- Least active connections: This algorithm routes traffic to the server that has the fewest active connections.
- IP hash: This algorithm routes to appropriate servers based on the client's IP address, which allows the requests to be served by same server for a specific client.
- Weighted round-robin: This method distributes traffic by assigning weights to each server based on its capacity.
Load balancing best practices
- Monitor server health: Load balancers should monitor server health and remove unhealthy servers from the pool automatically.
- Use session persistence: Session persistence can ensure that requests from the same client are always handled by the same server.
- Implement caching: Caching should be used to minimize server load and enhance response time.
Auto-scaling is a technology that allows the system to respond to variations in traffic by dynamically adding and deleting servers. It ensures that the system can manage sudden traffic increases without the need for user intervention.
For example, autoscaling may be accomplished in cloud-based systems through cloud-provider services auto scalers. These services automatically monitor system performance and alter the number of virtual machines (VMs) or containers allotted to the system.
Types of autoscaling
There are two types of autoscaling: horizontal and vertical.
- Horizontal autoscaling: To address growing demand, horizontal autoscaling adds extra instances of the same resource, such as VMs or containers, to the system. When the workload can be divided among numerous instances, this form of autoscaling is advantageous.
- Vertical autoscaling: Increases the capacity of a single instance, such as expanding a VM's CPU or RAM. When the workload cannot be divided among numerous instances, this form of autoscaling is beneficial.
Autoscaling best practices
- Autoscaling relies on precise monitoring of system performance to modify the number of resources provided to the system. Check that the monitoring tools are properly configured and that the metrics being tracked are relevant to the system's performance.
- Define appropriate thresholds for autoscaling. The thresholds should be calculated and determined based on the traffic patterns and the capacity needs for the expected load.
- Enforce autoscaling policies to manage how system resources are distributed. Implement policies, for example, to guarantee that the system does not scale too rapidly or too slowly.
3. Asynchronous processing
Asynchronous processing is a technique for effectively handling many requests by running them in the background without interrupting the main thread. Threading, callbacks, and promises are some ways to implement asynchronous processing. Asynchronous processing has the potential to cut reaction time dramatically while improving overall system performance. Asynchronous processing allows activities to complete as another sub-task without blocking the main task. This instructs the main task or job not to wait for a subtask and start moving to another task.
Asynchronous processing has various advantages when dealing with large traffic:
- Better performance: Asynchronous processing enhances performance by allowing activities to be done concurrently. This indicates that the system can handle more queries while remaining responsive.
- Easier scaling: Asynchronous processing promotes scalability by allowing jobs to be queued and executed when resources become available. This means that the system can manage a growing number of requests without requiring more resources.
- Reliability: Asynchronous processing enhances reliability by guaranteeing that tasks are completed even if the system has faults or malfunctions.
4. Distributed database
A distributed database is comprised of many databases that are geographically spread over multiple sites. These databases are linked by a network, so they function as a single logical database. Data is partitioned and copied among various databases to achieve high availability and fault tolerance. With a well-designed distributed database architecture, businesses can handle heavy traffic and deliver a dependable user experience.
Using a distributed database to handle heavy traffic has various advantages:
- Scalability: By distributing data among numerous servers, databases can manage massive volumes of data and traffic. This enables horizontal scaling, meaning more servers may be added to the database cluster to manage the growing load.
- High availability: A distributed database may achieve high availability by duplicating data across different servers. If one server fails, another can take up its task, ensuring the system's availability.
- Better performance: This is achieved by storing data closer to the user.
How to design a distributed database architecture
- Partition the data: Distribute the data among many servers to boost scalability and speed. This can be done based on the properties of the data, such as geography or user.
- Data replication: To increase availability and fault tolerance, replicate the data across many servers. Techniques such as primary-replica and multi-primary replication can be used.
- Use a distributed file system: To ensure that data is preserved consistently across all servers, use a distributed file system. This allows for higher durability in case of server failures.
Caching is one of the most efficient ways to deal with excessive traffic on websites and applications. It's a strategy for reducing reaction time by keeping frequently requested data in memory. Caching may be accomplished through various methods, including in-memory, edge, and browser caching. This technique may dramatically increase overall system performance by reducing reaction time.
Caching temporarily stores frequently requested resources. The server may keep the response to a user's request for data when the user makes the request. The server may provide the same data from the cache storage rather than having to recalculate the answer when a user requests it again. Caching frequently requested data can considerably increase response time, reduce server load, and provide a cost-effective method for dealing with heavy traffic.
Benefits of caching
There are various advantages of employing caching to deal with excessive traffic:
- Improved response time: Caching may dramatically enhance a website's or application's response time. The server can avoid creating a new response by delivering data from the cache, lowering response time and improving user experience.
- Lessened server load: By using data from the cache rather than producing a new response, caching helps reduce server load. This increases the server's capacity while reducing the likelihood of server crashes brought on by high traffic.
How to include caching on your website
- Select cache options by use case: This works best for the use cases such as in-memory caching, disk-based caching, and distributed caching.
- Select and implement caching using a library or framework.
- Set the expiration time for the cache based on the use case. This ensures the cached data is not stale and can effectively solve the use case.
6. Content delivery network (CDN)
A CDN is a network of servers dispersed around the globe. The data requested is served from nearest server to requestor. This reduces network round trip time providing better performance and lower latencies.
Some benefits of using a CDN to handle significant traffic include the following:
- Improved performance: It may significantly speed up a website or application by reducing the distance data must travel from the server to the end user.
- Reduced server load: It can lower the strain on the server by reducing the number of requests made to the original server by caching and delivering the content from the closest server.
- Improved reliability: Improve the dependability of a website or service by providing backup servers in the event of server failure or outage.
Select a CDN provider based on your platform or application's requirements. Configure the CDN by setting up the caching rules, cybersecurity settings, and other settings based on your website or application's requirements.
Microservices architecture has become a well-liked method for managing heavy traffic brought on by the emergence of cloud computing and the rising demand for scalable and adaptable software systems. This software architectural style divides an application into several divides a large, monolithic program into many tiny, autonomous services.
Using a microservices architecture to manage heavy traffic has the following advantages:
- Scalability: Because each service can be scaled separately, microservices architecture is very scalable. It allocates extra resources to the required services so that the system can handle excessive traffic.
- Flexibility: Because each service can be created, tested, and deployed individually, microservices architecture offers greater flexibility in development and deployment.
- Robustness: Because services are created to be independent of one another, microservices architecture is built for resilience. This makes it simpler to recover from errors and guarantees the system's availability.
How ConnectWise takes advantage of these techniques
ConnectWise Asio™ is a scalable and resilient platform designed to meet the evolving needs of its customers. The platform employs various techniques and architectural patterns described above to ensure its services are robust, scalable, and performant. Continuous observability and monitoring by employing the open, AI-powered APM platforms as part of the framework ensure the Asio platform can operate efficiently and securely by predicting and resolving problems before they impact users in a precise and proactive manner.
One key aspect of Asio is its microservices architecture, which allows for infinite scalability where required. Each service is deployed to container clusters behind load balancers, and auto-scaling parameters such as CPU, memory usage, and latency are fine-tuned for each service. The platform also leverages geo-distributed cloud databases to enhance performance, scalability, and availability.
To improve fault-tolerance and automation capabilities, Asio uses appropriate caching mechanisms and Apache Kafka, as well as various cloud services for asynchronous processing. Cyberecurity is also a top priority, and the platform operates in a zero trust environment. To ensure each request is authenticated, every service uses the SSO authentication mechanism.
Designed to be highly extensible and integrable, Asio makes it easy for tech vendors to build on top of the platform, providing a set of tools, SDKs, and documentation that make it easy for vendors to develop, test, and deploy their integrations. The scrum teams within Asio develop their solutions with the ability to be extended by third-party vendors in mind, creating communication interfaces and providing them to vendors. This results in a highly versatile and customizable solution that can meet the diverse needs of a wide range of partners. Overall, Asio provides a flexible and scalable solution that can adapt to the changing needs of partners and their customers.