Load Balancing Reinvented: Make your infrastructure Autonomous
Powered by Reinforcement Learning (RL)
End State is Infrastructure becoming autonomous
Works on requests ingressing into a cluster as well as requests going out
What isAvesha Smart Application Load Balancer?
Avesha Smart Application Load Balancer enriches service to service communication with defined objectives monitored continuously with programmable metrics and endpoints. This Load Balancing approach is a proactive measure for service availability and customer experience.
Path Selection Optimizedwith Telemetry Data
The shortest path for traffic is determined using AI and RL. The AI enables intelligent autoscaling of services.
Ultra low latency & Real-time Results
Applications that need ultra-low latency for eg. in medical, manufacturing, AR/VR, Drone technologies, AI object detections from video feeds need a Smart Load Balancer that continuously optimizes for real-time results.
Continuous Monitoring
There is no human intervention needed. The system continuously monitors and is adaptive to changing application behaviors. The metrics are programmable and adjust autonomously.
Autonomously optimize the weights to achieve desired state
Hand tuning of weights is not practical especially with dynamic workloads that can vary in minutes.
Ecosystems & Integrations
AWS, Azure, GCP, Istio, Envoy
What the Smart Application Load Balancer solves for you?
Avesha Smart Load Balancer can be trained to react to changes in server and network state and take actions to schedule requests for server resources in order to optimize the utilization.
Smart ApplicationInfrastructure
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Hybrid/MultiCloud Enablement
Extend KubeSlices for seamless, secure connectivity & workload placement between data center, any cloud, any edge.
EdgeEnablement
Give your applications the ability to autonomously determine the right edge to run, compute workloads on enabling superior user experiences.
Avesha Smart Application Load Balancer Overview
Avesha Smart Application Load Balancer uses several data points such as service dependency maps, service loading data, bandwidth, and latency metrics to optimize path selection with RL.
How to create a Smart Application Load Balancer?
Here are the steps on how to enable Avesha Smart Load Balancer for intelligent path selection for service to service communication across a cluster and optimize and rightsize resource utilization of POD in a cluster.
Step 1
Discover service endpoint across cluster / Multi-cloud and within a cluster. Configure telemetry servers or your favorite Application Performace tool (creds) in the Avesha portal. Avesha system provides you with required data sets to be enabled.
Step 2
Identify optimization objectives: Latency, bandwidth, cost, QoE, etc.
Step 3
Define tuning periodicity based on endpoints and WAN links for services and edge.
Step 4
Identify/configure your GitOps tools in the Avesha portal and visualize impact in KubeSlice metrics visualization.
Learn about our other products
Avesha KubeSlice consists of other products that enable automation, easy interconnectivity across a wide area network, and adaptive & autonomous configuration of the network based on the application's needs.
Avesha KubeSlice
Avesha KubeSlice is a platform that offers an easy and rapid way to isolate and segment your applications within and across K8s clusters. Improve your team's velocity by putting applications on Avesha KubeSlices!
Avesha Smart Application Mesh
Avesha Smart Application Mesh is a service that enables easy app to app connectivity for distributed application deployments (microservices or monolithic). Extend applications from the data center to cloud to edge networks using Avesha Mesh.