KubeSlice
Avesha Enterprise for KubeSlice
Service Connectivity Layer for managing fleet of clusters for better application performance
KubeBurst
On demand cloud capacity for datacenters
KubeTally
Multi - cluster chargeback by application and teams
KubeAccess
Service gateway for multi-cloud applications
Smart Scaler
Smart Scaler
Predictive autoscaling based on application behaviors
Smart Karpenter
Predictive autonomous scaling of pods and nodes
Elastic GPU Service
EGS
Single/Multi-cluster and multi-cloud GPU provisioning and management platform
KubeAgents
KubeAgents
KubeAgents adds intelligence and autonomy to Kubernetes
EGS Resources
Explore Resources for Elastic GPU Service
Analyst Reports
Navigating Key Metrics for Growth and Success
Blog
Source for Trends, Tips, and Timely Topics
Documentation
The Blueprint for Mastering Tools and Processes
Customer Case Studies
Success stories from our valued customers and partners
Autonomous, slice-aware AI agent that brings real-time intelligence and decision-making into Kubernetes operations.
KubeAgents adds intelligence and autonomy to Kubernetes by detecting issues, enforcing policies, and executing self-healing actions — all in real time.
AI Agent Layer
(Avesha KubeAgents)
Adds an intelligence layer on top of Kubernetes to power autonomous operations.
Detects and resolves issues autonomously (e.g., self-healing, noisy neighbor mitigation)
Enforces smart routing for compliance and performance
Surfaces observability-driven enforcement (cost, resource abuse, etc.)
Recommends actions based on policies, usage patterns, and behavior
Powers model-aware infrastructure for future GPU workloads (EGS readiness)
Automation Layer
(Current/Traditional Stack)
Executes zero-touch automation across your Kubernetes environments.
Zero-touch namespace and slice creation
Policy-as-code + RBAC integration with existing identity providers
Automated provisioning of services (DNS, Git, Redis, etc.)
Time-bound access controls and audit hooks for internal compliance
Seamless multi-cluster scaling
KubeAgents + Automation = Our Differentiator
Together, they enable truly autonomous cloud-native operation
KubeAgents brings actionability and intelligence.
Automation delivers speed and consistency.
Architecture Overview
KubeAgents sits on top of the Avesha platform, delivering autonomous monitoring, intelligent decision-making, and self-healing across
KubeAgents Workflow
Data Collection
Continuously collects metrics, logs, and events across Kubernetes clusters. Focus areas include:
- CPU, memory, performance
- Access patterns and latency
- Slice health and network traffic
- Resource utilization and cost
Pattern Recognition
AI engine analyzes data to:
- Establish performance baselines
- Detect policy violations or threats
- Forecast usage patterns
- Identify optimization zones
- Correlate patterns across environments
Decision-Making & Enforcement
Based on real-time insights:
- Enforces custom SLAs and policies
- Calculates risk scores
- Automates slice optimization and node actions
- Learns from prior decisions to improve outcomes
Autonomous Actions
Executes real-time decisions such as:
- Healing degraded slices
- Rebalancing workloads
- Improving performance
- Scaling resources
- Reducing costs through smart placement
