Key Highlights
Distributed tracing and auto-instrumentation follow each request from entry to execution. Single DaemonSet agent per Kubernetes node auto-instruments all workloads, no per-pod sidecars, capturing full application behavior beyond container health, spanning Kubernetes, Docker, OpenShift, and all major managed variants.
Instrument the whole cluster from one deployment. No sidecar, no per-service config, no version drift.
Single DaemonSet agent per Kubernetes node auto-detects languages and instruments cluster-wide.
No per-pod sidecar agents. One deployment covers all workloads across all nodes.
No per-service configuration. Language detection and agent injection happen automatically at cluster level.
No version drift. One agent version covers all instrumented services in the cluster.
Auto-instrumentation covers all major languages running inside containers, with one guardrail.
Auto-instrumentation for Java, .NET, Python, Go, Node.js, and PHP inside containers.
Auto-instrumentation for Java, .NET, Python, Go, Node.js, and PHP inside containers.
Instrumentation applied at runtime via MotaAgent, no code changes for supported languages and frameworks.
Spring Boot and ASP.NET are supported frameworks for Java and .NET respectively.
The same APM instrumentation, with consistent behavior across all deployment architectures you run.
The same APM instrumentation, with consistent behavior across all deployment architectures you run.
Fargate, OKE (Oracle Kubernetes Engine), GKE (Google Kubernetes Engine), and Rancher.
Consistent language agent behavior regardless of Kubernetes platform or container runtime.
Unified trace view spanning deployments. Follow application behavior through boundaries in one APM workspace.
The same distributed tracing, error tracking, and performance KPI coverage across all deployment targets.
Extend APM beyond automatic instrumentation with business-specific context at the container level.
Language-specific SDKs enable custom span creation for logic not covered by framework instrumentation.
Custom attributes and parameters inject business-critical context into traces from containerized services.
Tenant ID, transaction type, and feature flag value enrichment per span.
Custom metadata enrichment delivers deeper, environment-specific insights.
Enrichment works. No need to modify container images or deployment configurations.
Business context flows through each containerized-service trace, requiring no framework-level support.
Single Investigation Workspace for Containerized Applications
Navigate from container traces to errors, host metrics, logs, databases, and JVM insights in place.
Determine whether a container issue originates in application code, JVM, database, or infrastructure.
Aligned visual evidence makes the source clear.
Full-stack correlation through dashboards and widgets covers containerized performance.
The correlated view sits alongside the infrastructure picture in the same workspace.
All investigation paths are available for containerized services exactly as for host-based deployments.
Trace, error, endpoint, database, and JVM views all carry over.
Intelligence
Kubernetes breaks monitoring context. Pods reschedule mid-incident, disappear before investigation, and the deployment boundary shifts from host to cluster. Shallow Kubernetes labels lacking in-container instrumentation lose trace depth, and running separate container health and APM tools compounds the gap.
Motadata APM instruments the application code inside the container, capturing each trace, error, and performance indicator regardless of pod rescheduling. The DaemonSet model removes per-pod configuration overhead while auto-language detection removes per-service negotiation. Custom Views in APM Explorer, filtered by pod, namespace, or cluster, deliver cross-deployment investigation from one workspace.
How It Works
Deploy the Motadata APM DaemonSet. One agent per Kubernetes node auto-instruments all workloads automatically.
Auto-language detection applies agents for Java, .NET, Node.js, Python, PHP, and Go (Ruby: Host/VM and Docker only).
Agents collect distributed traces, metrics, and database call data directly from running container code.
SDKs and attribute enrichment inject custom business metadata into spans. No container image changes required.
Container traces, errors, and KPIs flow into one unified APM workspace alongside host-based services.
Single Investigation Workspace links container traces directly to host metrics, logs, databases, and JVM insights.
Each request traced. All containers covered. Every application performance signal captured from the code inside your cluster.
Role-Based Value
Reduce tooling complexity as workloads migrate to Kubernetes with one APM layer that covers application performance across all clusters and platforms.
Reduce tooling complexity as workloads migrate to Kubernetes with one APM layer that covers application performance across all clusters and platforms.
Give application and platform teams a shared view where containerized and host-based service data appears in the same APM workspace.
Give application and platform teams a shared view where containerized and host-based service data appears in the same APM workspace.
When an alert fires on a containerized service, see the full application trace beyond the container event.
When an alert fires on a containerized service, see the full application trace beyond the container event.
Validate each Kubernetes deployment’s impact on application performance instantly.
Validate each Kubernetes deployment’s impact on application performance instantly.
From Visibility to Control
Single DaemonSet agent per node auto-instruments the whole cluster: no sidecars, no per-service config, no drift.
Auto-instrumentation covers Java, .NET, Python, Go, Node.js, and PHP in containers.
Ruby is Host/VM and Docker only and is not deployed in Kubernetes contexts.
Deployment coverage: Kubernetes (on-premises), Docker, Host/VM, OpenShift, EKS, AWS EKS Fargate, OKE, GKE, and Rancher.
Consistent APM behavior across all supported environments.
Custom Instrumentation SDKs inject business-critical context into containerized traces, no image changes needed.
Single Investigation Workspace: navigate from container traces to errors, databases, JVM insights, and host metrics. One workflow, one platform.
Spring Boot (Java) and ASP.NET (.NET) are supported frameworks for containerized instrumentation.
All APM capabilities carry over for containerized services exactly as for host-based deployments.
That covers distributed tracing, error tracking, performance KPIs, database activity, and JVM visibility.
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