Hyground vs Komodor

An AI SRE that goes beyond Kubernetes, inside your cluster

Komodor is a Kubernetes-only SaaS. Hyground runs entirely inside your cluster and covers cloud APIs, observability, ITSM, and your wikis alongside Kubernetes.

Different scope, different architecture

Komodor is a Kubernetes SaaS that adds self-healing and cost optimisation. Hyground runs investigation, multi-cluster, knowledge ingestion, and automation inside your cluster, across Kubernetes, cloud APIs, ITSM, and wikis.

Architecture

Where Hyground differs

Six choices that change what the platform can do and where your data lives.

Covers more than Kubernetes

Hyground correlates Kubernetes with cloud APIs (AWS, Azure, GCP), Loki, Elasticsearch, OpenSearch, ITSM (Jira, ServiceNow), and Confluence, all inside your cluster. Komodor stops at Kubernetes plus adjacent infrastructure that runs on Kubernetes; ITSM, cloud APIs, and customer wikis are out of scope.

Runs entirely in your cluster

Hyground deploys via Helm; logs, metrics, runbook ingestion, and AI inference all run inside your Kubernetes boundary, including air-gapped on-premises sites. Komodor's agent streams cluster metadata to its AWS-hosted control plane, with no self-hosted or on-prem option publicly offered.

Bring or self-host your LLM

Connect Hyground to Azure OpenAI, Anthropic, Google Gemini, or a self-hosted Ollama model via LiteLLM. Komodor is Bedrock-locked and Anthropic-dependent; customers cannot choose, swap, or self-host the underlying model.

Your knowledge stays sealed

Hyground ingests your Confluence, Git, PDFs, and runbooks into a knowledge base inside the cluster. Komodor's RAG runs over its own Kubernetes telemetry, not your wikis or runbooks; customer-doc ingestion was announced in March 2026 with no public detail on mechanics.

Read-only by default

Hyground observes and advises; it cannot restart pods or change configs unless you opt in. Komodor's Autonomous Self-Healing (GA Nov 2025) can remediate pod crashes, misconfigurations, failed rollouts, and right-size workloads automatically once guardrails are set.

Plugs into the stack you already run

Hyground ships first-party connectors for Loki, Elasticsearch and OpenSearch, plus bidirectional Jira and ServiceNow. Komodor relies on alert-ingestion webhooks for APM tools, has no first-party Loki, Elasticsearch, or OpenSearch connector, and offers no bidirectional ITSM.

Flat licensing across your fleet

Hyground licenses by deployment tier, not by vCPU. Komodor's AWS Marketplace SKU starts at $150,000 per year for the first 1,000 vCPUs and adds $132 per additional vCPU. The bill scales linearly with cluster size.

Decision

When each platform fits

Komodor and Hyground are different products: a Kubernetes-only SaaS, and an in-cluster AI SRE that reaches across your stack. The right fit depends on whether your investigation needs to leave Kubernetes.

Choose Hyground when

You need scope that goes beyond Kubernetes, sovereignty, or model choice in one platform.

You operate in regulated, sovereign, or air-gapped environments
You need to choose, swap, or self-host the LLM that runs your investigations
Read-only AI is a hard requirement for production access
You need investigation, multi-cluster, knowledge, and automation in one platform, not just Kubernetes

Choose Komodor when

Kubernetes-only scope with self-healing and cost optimisation on a SaaS control plane matches your operating model.

Kubernetes cost optimisation is a primary buying driver
You're comfortable with a SaaS data plane and vendor-managed inference
You want autonomous self-healing across pod crashes, misconfigurations, and right-sizing
You want Komodor's BYOA framework for custom Python investigation agents

See Hyground in action

Check out our sandbox or schedule a demo with our team and experience sovereign AI for DevOps firsthand.

Try our sandbox Book a demo