API Gateway vs. Load Balancer
API gateways also handle all of the interpretations and protocols that occur between various pieces of software. An API gateway, for example, connects micro-services, whereas load balancers redirect multiple instances of the same micro-service element as it scales out.
Most backend APIs are exposed via load balancers, whether they are exposed to the public or an internal audience. It appears that API gateways provide the same function: mapping HTTP queries to a backend service. What’s the difference between them? How well does API Gateway do at balancing loads? Who’s got the best one for server-less architectures?
Microservice-based architectures make it easy for developers to use services required for their client application areas by exposing a single endpoint to those apps. When it comes to applications and microservices, the API gateway is a connecting point.
What are load balancers are used for?
To smooth and balance demand across a group of resources is one of the critical goals of using an ALB.
Load balancers have traditionally been employed to distribute calls in a horizontally scaled infrastructure group, where services are duplicated across thousands of servers.
They also serve to decouple clients from services, which is a good approach from cloud security alliance.
Load balancing the API Gateway’s
The API gateway’s accessibility is critical to the application’s accessibility. There must be a load balancer for the API gateway that can adapt to changes in microservices, such as versioning and dynamic scaling. Additionally, the API gateway should have separate access controls for direct and indirect customers in addition to ensuring secure transportation and verification of data in transit. Aside from that, the API gateway must be protected from DDoS.
API response time directly impacts the end-user experience, so it’s essential to have a monitoring tool that can also provide complete API transaction logs.
How does API Gateway scale in response to load?
When used with AWS Lambda, the API gateway smoothly scales the network. According to its default settings, the API Gateway can handle up to 10,000 requests per second. It will scale to meet the demand of requests from API clients, and it will do so automatically.
Developers do not need to worry about configuring scalability criteria for API gateway or Lambda because there are none.
According to their own internal rules, both of their scale. As a result, when large spikes are anticipated, it may be appropriate to seek an increase in service quotas so that AWS doesn’t throttle user requests.
When compared to a load balancer, how does API Gateway perform?
A load balancer can control and balance network traffic, but API Gateway does it differently.
Requests can be directed to specific backend resources based on the destinations being requested instead of being distributed evenly over a group of resources (e.g., a cluster of servers).
API Gateway Vs Load Balancer –Which one is better?
If you do not use the features provided by API Gateway, it is feasible to employ a load balancer rather than an API Gateway. It’s difficult to compare because API Gateway pricing depends on the number of requests, while LB pricing is based on several factors, such as hours, new, and active connections.
A load balancer is more cost-effective for low traffic APIs than a gateway, which is more cost-effective for APIs with high traffic.
The 29-second duration is the API gateway’s main technical limitation. There will be an early error response if the request takes longer than expected to be processed by the backend resource. This number of requests per second is limited, but it can be increased depending on demand. A load balancer can indeed scale to thousands or even millions of requests per second.
A load balancer is better suited to low-cost, non-differentiated applications, long-running processes, or applications requiring ultra-high-throughput because of this. Access control logic and complex security measures make API Gateway a good fit for small teams looking to reduce time-to-market.
Microservice designs, for example, depend heavily on it. There is the possibility of connecting several services to the Gateway and mapping them to specific HTTP endpoint representations. A gateway can route each request to the correct backend service on demand.