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SLA-Aware Resource Allocation in Azure Kubernetes Service (AKS)

AKS

SLA-Aware Resource Allocation in Azure

  • Use Case: Cloud-native applications deployed on Azure Kubernetes Service (AKS) often serve users with strict SLAs (Service Level Agreements) such as response time, availability, and throughput. Inefficient resource allocation can cause SLA violations (e.g., latency spikes, downtime) while over-provisioning leads to unnecessary costs. SLA-aware resource allocation dynamically adjusts compute, storage, and networking resources in AKS clusters to balance performance vs. cost.

Objective

  • Design a resource allocation framework in AKS that ensures SLA compliance (low latency, high availability).

    Minimize over-provisioning and cloud costs.

    Enable auto-scaling of containers/pods based on workload demand and SLA thresholds.

    Integrate real-time monitoring and predictive analytics for proactive scaling.

Project Description

  • This project implements an SLA-aware resource allocation system in Azure Kubernetes Service (AKS).

    Define SLA parameters (e.g., CPU utilization < 70%, latency < 200 ms, availability ≥ 99.9%).

    Use Azure Monitor and Application Insights to track SLA metrics in real time.

    Implement Horizontal Pod Autoscaler (HPA) and Cluster Autoscaler with SLA-based scaling policies.

    Apply Azure Machine Learning models to forecast workload spikes and proactively allocate resources.

    Route alerts via Event Grid and trigger corrective actions using Azure Functions.

    Visualize SLA compliance, scaling actions, and resource usage in Power BI dashboards.

    The system ensures optimal use of Kubernetes resources while maintaining SLA guarantees for cloud applications.
  • Azure Services & Purpose :
    Azure Service Purpose in Project
    Azure Kubernetes Service (AKS) Deploy and manage containerized applications with built-in orchestration.
    Azure Monitor + Application Insights Collect SLA metrics (latency, response time, availability, resource usage).
    Azure Machine Learning Predict workload demand and optimize resource allocation.
    Azure Functions Automate SLA-based scaling or remediation actions (event-driven).
    Azure Event Grid Event routing for SLA alerts, failures, and scaling events.
    Azure SQL Database / Cosmos DB Store SLA compliance logs and application performance history.
    Power BI Visualize SLA metrics, scaling efficiency, and cost-performance tradeoffs.
    Azure Key Vault Secure storage of secrets, certificates, and scaling policy configs.