Best Microservices Tools for Amazon EKS

Find and compare the best Microservices tools for Amazon EKS in 2026

Use the comparison tool below to compare the top Microservices tools for Amazon EKS on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Control Plane Reviews

    Control Plane

    Control Plane Corporation

    Control Plane is the platform for running unbreakable apps and agents. It combines any cloud, neocloud, and bare metal, including AWS, Google Cloud, Azure, and your own Kubernetes clusters, into one Global Virtual Cloud. Every workload runs active-active across the locations you choose, and a global endpoint sends each request to the nearest healthy location, so a zone, region, or provider outage does not take your service down. It runs serverless, standard, stateful, cron, and VM workloads with no application changes. Workloads reach 600+ AWS, GCP, and Azure services through Universal Cloud Identity, with no long-lived cloud keys in code, and Cloud Wormhole connects them to private VPCs and data centers. Autoscaling, observability, mutual TLS, secrets, and an audit trail are built in, with no Kubernetes cluster to operate. Customers typically cut compute costs 30 to 50 percent compared with running directly on AWS, GCP, or Azure.
  • 2
    D2iQ Reviews
    D2iQ Enterprise Kubernetes Platform (DKP) Enterprise Kubernetes Platform: Run Kubernetes Workloads at Scale D2iQ Kubernetes Platform (DKP): Adopt, expand, and enable advanced workloads across any infrastructure, whether on-prem, on the cloud, in air-gapped environments, or at the edge. Solve the Toughest Enterprise Kubernetes Challenges Accelerate the journey to production at scale, DKP provides a single, centralized point of control to build, run, and manage applications across any infrastructure. * Enable Day 2 Readiness Out-of-the-Box Without Lock-In * Simplify and Accelerate Kubernetes Adoption * Ensure Consistency, Security, and Performance * Expand Kubernetes Across Distributed Environments * Ensure Fast, Simple Deployment of ML and Fast Data Pipeline * Leverage Cloud Native Expertise
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