Cloud Load Balancer
High-performance Load Management
Scale your business with guaranteed bandwidth, unlimited transfer and backend servers to dynamically balance your application’s load across multiple nodes in real-time.
Kubernetes Interface
Cloud Affinity
Quick Deployment
IP Address Filtering
Increase The Reliability of Your Apps And Decrease Downtime
Load Balancer
- ACE network load balancer can reduce server disturbance by automatically dispersing the load over several servers.
- With our services, you can increase the redundancy of your cloud apps and prevent single points of failure by adding an extra layer.
- We help you to increase application availability by ensuring that the health of a single server has no influence on the overall condition of your service.
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Proxy Protocol
Incorporate Proxy protocol to maintain the sender's original address and execute critical tasks on the nodes such as producing statistics and analyzing logs.
HTTP(S) Load Handler
We help to distribute HTTP and HTTPS traffic across several backend instances and locations as your whole program is accessible through a single global IP address, thereby simplifying DNS configuration.
TCP/SSL Traffic Controller
We help to distribute TCP traffic over a pool of instances inside a compute engine area and send traffic to healthy instances only.
Advanced Support
We provide advanced support features such as IPv6 global load balancing, webSockets, user-defined request headers, and protocol forwarding for private VIPs.
Increase The Availability Of Your Application With Network Load Balancer
Extremely controlled, Extensively managed
Significant Uptime
Increase the uptime of your digital operations by deploying our one-click load balancer with your production clusters and get built-in health monitoring and automated failover.
Extremely Stable
Improve the performance and stability of your infrastructure by simply adding or deleting instances from your compute pool.
Health Monitoring
Perform health checks to keep track of the operating status of each of your backend servers and construct custom health check endpoints.
SSL Offloading
Our load balancer includes high-performance SSL termination, that allows you to swiftly encrypt and decrypt data to relieve a web server's processing stress.
Broadcast Traffic
Automatically distribute traffic according to freely specified rules by using different static and dynamic algorithms depending on the scenario.
Sitcky Sessions
ACE load balancer supports the Source IP hash balancing policy, which creates an affinity between the same client IP and same backend node, through which the former requests were routed.
Manage varying traffic loads on your application at an effective cost
Load Balancer
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Use Cases
Optimize application development process without the hassle of managing clusters
Business Expansion
Expand your business with a load balancer by adding extra backend servers to increase service quality while avoiding downtime.
Handle High Traffic
With our services, you can easily handle high volume of traffic in your application by adding additional nodes to your system with just a few clicks.
Regulate Activity
The number of visits can fluctuate quite quickly, but the ACE network load balancer adjusts the distributed traffic variations, whether increasing or decreasing.
Hassle-Free Upgrades
The Ace load balancer service is responsive, allowing you to upgrade your application nodes with little downtime utilising the rolling upgrade process.
Boost Availability
Leverage the primary/secondary architecture of ACE load balancer, construct a robust platform and ensure that traffic is allocated across healthy resources.
Control Peak Loads
Avoid performance dips by adding as many backend servers as needed to boost your processing capacity within minutes.
Knowledge Centre
How To Find The Best GPU For Deep Learning?
In deep learning, GPUs have been gaining massive popularity, and for data scientists struggling to carry out HPC codes, this processor is a known term. Going back to the history of GPU development, the combination of CPU and GPU led to the formation of GPGPU, which is the General-Purpose Graphics Processing Unit.
Why GPUs for Deep Learning? A Complete Explanation
The advent of AI has led to a paradigm shift in the industry. Deep learning, a technique that helps machines learn from large data sets, has provided a powerful reality-altering tool for businesses.
NVIDIA A30: The Workhorse of AI and HPC in the Data Center
Since their inception, GPUs have been the most powerful computing engines for accelerating compute workloads that drive innovations in business and science. The demand for GPU processing power is growing year on year with an expected CAGR of 33.6% by 2027, as per reports published by Allied Market Research.
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Frequently Asked Questions (FAQs)
Resources to help drive your business forward faster
What is a Cloud Network Load Balancer?
How does a Cloud Network Load Balancer work?
Why should I use a Cloud Network Load Balancer?
How does a Cloud Network Load Balancer improve application performance?
What types of traffic can a Cloud Network Load Balancer handle?
Is it feasible to add security to the ACE load balancer to restrict access to a URL or port?
Do your load balancers support external IPv6 connections?
Is a public IP address required for backend servers?
From where can I assign and delete instances?
Which protocols do you support?
Can I use a load balancer in one area with instances in another?
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