The middleware load balancer helps ensure a fast,
scalable, and secure application experience.
based Load balancer
10x faster by
based on usages
The Middleware Load Balancer operates on predictive modeling powered by artificial intelligence (AI). The system makes projections regarding load requirement and allocates the resources preemptively to maintain application uptime.
Middleware manages servers and resources effectively through its AI-powered load balancer. When paired with service discovery, it handles traffic across networks and protocols for multiple instances. Use it to auto-scale, containerize, and manage the cache of your microservices.
Middleware’s load balancer learns with every iteration by discovering usage patternsand anticipate requirements accordingly.
Middleware offers support to a number of applications, such as HTTP, TCP, and UDP, for effective load balancing.
Implement out-of-band application health checks with Middleware that offers slow-start functionality to add new or recovered servers.
Middleware balances load handling capacity and accommodates traffic to the extent of millions without compromising on real-time performance.
The following is a quick step-by-step guide on how to set up and configure load balancer using Middleware:
Middleware offers support to popular cloud-based service providers like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and Digital Ocean. Our autoscaler is compatible with various data centers, and we are also in the process of expanding support to other platforms and providers. For an in-house datacenter, contact our experts for an enterprise solution.
Service discovery in real-time shares actionable insights that allow the application to stay up at all times.
Create and delete virtual machines automatically to match with the load experienced.
Our no-code automated containerization system is a fitting competition to the likes of Kubernetes.