Best Kubernetes Observability Tools (2026): Top 10 Compared

groundcover sells a full-stack observability platform built around an eBPF sensor. The sensor collects logs, metrics, traces and events from Kubernetes workloads with no code changes, and the platform also supports OpenTelemetry. Products listed on the site include infrastructure monitoring, application performance monitoring, log management, real user monitoring, synthetic monitoring and AI observability for LLM calls and agent pipelines.

The main architectural choice is Bring Your Own Cloud. The backend is deployed in the customer's own cloud account and managed by groundcover, while groundcover hosts the UI. A fully on-premises mode puts both the backend and the UI on the customer's servers. Agent Mode lets engineers ask questions in plain language, and an MCP server exposes the data to AI agents. A migration tool moves dashboards, monitors and integrations from other platforms.

Pricing is per host, counted as the monthly average of monitored nodes of any size. The platform is also sold through the AWS, Google Cloud and Azure marketplaces.

Coroot is an open-source observability platform that uses eBPF to capture metrics, logs, traces and continuous profiles with no code changes. It stores the data, builds service maps, tracks SLOs and deployments, and then runs AI-powered root cause analysis when something breaks. The GitHub repository is licensed under Apache 2.0, and the site cites more than 7,300 GitHub stars.

Installation on Kubernetes uses a Helm-installed operator and a custom resource, with ClickHouse as the store. Docker, Docker Swarm, Ubuntu, Debian and RHEL are also documented. Specific solution pages cover PostgreSQL, MongoDB and MySQL monitoring, GitOps observability, cloud cost monitoring and an MCP server.

The paid Standard edition is priced per monitored CPU core with no ingestion fees and no retention limits, so cost follows cluster size rather than log volume. Enterprise adds round-the-clock support, capacity planning and help with air-gapped installs.

Sysdig sells two platforms: Sysdig Secure for cloud and container security, and Sysdig Monitor for Kubernetes and cloud monitoring. Sysdig created the Falco runtime threat detection project and contributed it to the CNCF.

Sysdig Monitor is built on a managed Prometheus service. It offers automatic service discovery, a scalable data store, assisted integration deployment and full PromQL support, so teams can keep their queries and Grafana dashboards. For Kubernetes, it shows a prioritised list of issues with pod details, live logs and remediation steps. Out-of-the-box dashboards and configurable alerts connect to existing alert management.

Cost features show Kubernetes resource utilisation and savings estimates, and custom metrics can be ingested at what the vendor calls low cost. Cloud monitoring covers Amazon EKS, Google GKE and Azure AKS, serverless functions and other cloud resources, and the site carries guidance for monitoring OpenShift. Licensing is host-based or time-series-based, quoted by sales.

Apica sells the Ascent suite, which its documentation describes as a telemetry data management and observability platform. The suite has named parts: Flow controls and routes telemetry before ingestion, Lake stores it with InstaStore or S3-compatible storage, Observe correlates logs, metrics and traces, Fleet manages telemetry agents across hybrid environments, and Forge handles high-cardinality metrics with SLO views. Vanguard adds synthetic checks.

Apica's Kubernetes page frames the product as Kubernetes-native observability for platform engineering teams. It describes collection that adapts to short-lived pods, an architecture that handles millions of unique metric streams, and one view across AWS, Azure, Google Cloud and on-premises clusters. It also points to rising telemetry from AI agents deployed on Kubernetes as a reason to plan for high cardinality.

Pricing on AWS Marketplace is set by daily ingest volume and retention, with discounts for longer contracts. The same suite is covered on the observability platforms page.

Kubeshark describes itself as network observability for Kubernetes. It indexes cluster-wide traffic so engineers and AI agents can query it by Kubernetes, network or API terms, from TCP connections up to API payloads. The open-source repository on GitHub is licensed under Apache 2.0.

Its main features are TLS decryption for traffic such as MySQL, Postgres, Envoy and Traefik without exchanging keys or adding sidecars, real-time streaming and filtering, and cluster-wide PCAP snapshots that can be filtered by time, node, IP or workload and kept in cloud storage. The vendor positions these snapshots as a flight recorder for incident response and compliance. Full functionality is exposed through MCP tools and skills, including a security-audit skill for AI coding agents.

The Community tier is limited to small development and test clusters. Enterprise adds air-gapped clusters, SSO, authorisation, sensitive data redaction and dedicated support over Slack and Zoom. The official site is kubeshark.com.

Isovalent created Cilium, Tetragon and much of the eBPF tooling used in Kubernetes networking, and its site now lists its addresses as Isovalent at Cisco. Its enterprise platform covers networking for Kubernetes and virtual machines, runtime security and load balancing.

Observability in Cilium comes from Hubble. The Cilium documentation explains that Hubble gives visibility at node level by default, across a whole cluster once Hubble Relay is deployed, and across clusters in a Cluster Mesh setup. The Hubble CLI queries flows, and Hubble UI discovers the service dependency graph at layers 3, 4 and 7 and draws it as a filterable service map. Metrics export to Prometheus and Grafana, and a Hubble exporter writes flow logs.

Isovalent's observability page adds real-time golden signals, network flow data and service communication views without agents or sidecars, security observability tied to workload identity, and long-term storage of observability data for forensic review and audits.

Tigera sells commercial editions of Calico, the Kubernetes networking and security project. Calico Cloud is the SaaS edition and Calico Enterprise is self-managed. Both include observability alongside policy management, ingress and egress gateways and threat detection. Tigera also sells Lynx for AI agent security.

The observability and troubleshooting features are a Dynamic Service and Threat Graph that draws traffic flows and the security policies applied to them across namespaces, application-level observability that breaks service-to-service traffic down by response code and performance, and DNS dashboards for confirming or ruling out DNS as the cause of connectivity problems. Policy creation and testing lets teams stage policy changes against real-time traffic, and dynamic packet capture records traffic for a chosen workload.

Tigera lists support for Amazon EKS, Azure AKS, Google GKE, Red Hat OpenShift and SUSE Rancher. Calico Cloud pricing is published per vCPU hour, and the product is sold through all three major cloud marketplaces.

Komodor began as a Kubernetes troubleshooting tool and now sells the Komodor Agentic Operations Platform, which its documentation describes as a way to run AI agents on production operations work. The home page frames it as one platform to build, run, govern and optimise everything on Kubernetes.

Work is packaged as modules in three families. AI SRE covers incident management and troubleshooting, alert intelligence and proactive reliability. Cost Optimization covers Kubernetes, cloud and observability spend. AI Software Operations covers change risk, CI/CD health and production readiness. The agent catalog includes Komodor-built agents for Kubernetes, AWS, Azure, Google Cloud, Datadog, Grafana and GitHub, and teams can build their own with an SDK.

Each agent has its own identity and permissions, and credential values are masked before data leaves the worker. Governance features include RBAC, human approvals, budget enforcement, destructive action protection and auditing. The pricing page lists SOC 2 Type II and GDPR compliance.

Robusta began as an open-source project that its GitHub repository describes as better Prometheus alerts for Kubernetes, with smart grouping, AI enrichment and automatic remediation. The repository is MIT licensed. The commercial product is now presented as an AI SRE, and the home page carries an announcement that Robusta is joining Freshworks.

The documentation describes Robusta as an AI-powered SRE agent built on HolmesGPT. Every alert is investigated automatically, and HolmesGPT connects to existing monitoring, ITSM and cloud tools and MCP servers to gather evidence. Engineers can tag it in Slack or Microsoft Teams to ask follow-up questions.

The older Robusta Classic features remain documented: sending alerts to Robusta, tracking configuration changes, notification routing, playbooks for automated actions, managed Prometheus alerts and KRR, a tool for right-sizing Kubernetes resource requests. Install guides cover multi-cluster, GitOps, OpenShift and namespace-scoped deployments. The site states that Robusta is SOC 2 compliant.

Odigos generates distributed traces, metrics and logs from running services without code changes and exports them as OpenTelemetry to the destinations a team configures. The site now calls it a production context platform for engineers, AI agents and security teams.

The open-source edition, licensed under Apache 2.0, covers zero-code OpenTelemetry tracing on Kubernetes, the Odigos Collector, sampling and instrumentation actions. The documentation quickstart walks through tracing a microservices application written in Go, Java, Python, .NET and Node.js on a Kubernetes cluster, with Jaeger as the backend.

Enterprise adds out-of-process eBPF capture for Go, Java, Python and Node.js, extended database tracing for MySQL and Postgres, tracing on Linux virtual machines and bare metal, multi-cluster administration and 24/7 support. Live capture lets an engineer or AI agent record argument and return values from a chosen function in production, governed by RBAC and policy, with PII masking applied in the cluster. Odigos states it can run alongside an existing APM.