NamLabs
Manufacturing Logistics

Application Observability & Kafka Monitoring for Smart Manufacturing

When a conveyor line stalls, an ERP order fails to sync, or a Kafka topic backs up between your MES and your warehouse system, your engineering team has minutes to find out why. Atatus gives you full-stack observability across your applications, APIs, and infrastructure. KLogic gives you purpose-built monitoring for the Kafka pipelines moving telemetry, orders, and shipment events between them.

Why Modern Manufacturing Requires Both Observability and Kafka Monitoring

Manufacturing and logistics platforms are no longer a single monolith running in a plant office. They're a mesh of MES, ERP, SCADA, WMS, and TMS systems, stitched together by microservices and increasingly by Kafka. Application monitoring alone only shows you half the picture.

Downtime stops the line

Downtime stops the line

A slow API between your order system and your MES isn't an inconvenience. It's a stopped production line, a missed shipment window, or a warehouse pick that never gets released.

Systems are distributed by design

Systems are distributed by design

PLCs, industrial IoT sensors, cloud-native microservices, and Kubernetes clusters all report status independently. A single stalled Kafka partition can quietly delay every consumer downstream.

Inventory and shipment data must stay in sync

Inventory and shipment data must stay in sync

Order events, inventory events, and shipment events flow constantly between warehouse, fleet, and factory systems. When that event flow lags, the physical world and the system of record disagree.

Our Products

Two Products, One Manufacturing Infrastructure Stack

Atatus and KLogic are built to be used together, one covers your applications and infrastructure, the other covers the Kafka backbone connecting them.

Atatus

Full-Stack Observability & APM

End-to-end observability across your manufacturing applications, APIs, cloud services, containers, Kubernetes, distributed traces, and databases, the layer where MES, ERP, WMS, and TMS systems talk to each other.

  • Application performance monitoring (APM) for order, inventory, and fulfillment services
  • Distributed tracing across microservices connecting plant floor and cloud systems
  • Infrastructure and Kubernetes monitoring across cloud-native manufacturing platforms
  • Real user monitoring for driver, dispatcher, and warehouse-facing apps
  • Database and API performance monitoring for MES/ERP integrations
KLogic

Kafka Monitoring & Event Pipeline Intelligence

Purpose-built Kafka cluster monitoring for the event streams carrying machine telemetry, industrial IoT data, inventory events, order events, and shipment events across your supply chain.

  • Consumer lag monitoring across order, inventory, and shipment topics
  • Broker performance, partition health, and replication tracking
  • Kafka Connect and Schema Registry monitoring for factory-to-cloud pipelines
  • Event flow tracing for stalled, dropped, or out-of-order telemetry and IoT events
  • Kafka administration and troubleshooting for high-throughput streaming pipelines

Why Teams Choose Atatus + KLogic

Traditional log management tools were built to store and search text. Atatus and KLogic are built to answer the question engineers actually have during an incident: what changed, where, and why, whether it happened in the application or in the Kafka pipeline connecting it.

Speed
Speed

Both products get engineers from alert to root cause fast, not just to a pile of collected logs.

Context
Context

Application events and Kafka events are correlated automatically, not left in separate dashboards.

AI Root Cause Analysis
AI Root Cause Analysis

Surfaces the likely root cause directly, turning a 45-minute investigation into minutes.

Noise Reduction
Noise Reduction

Filters and groups repetitive, low-signal alerts so engineers see what actually changed.

Cost
Cost

Keeps the signal-to-cost ratio favorable as event volume and production scale grow.

Developer Productivity
Developer Productivity

Less context-switching between application tooling and Kafka-specific tooling during incidents.

We needed application monitoring (APM and client side) for some of our internal applications and have finally been able to check all the boxes with Atatus at an affordable price. Easy to deploy and configure, immediately valuable and detailed metrics, and bonus--no extra charges for integrations, 2FA, and SSO. Wins all around.

Whitney C
Whitney C Lead Architect

Frequently Asked Questions

Why use Atatus and KLogic together for manufacturing operations?
Atatus provides end-to-end application, infrastructure, and user experience monitoring, while KLogic delivers AI-powered log analytics and root cause investigation. Together, they help manufacturers detect, diagnose, and resolve production issues faster.
Can these platforms monitor ERP, MES, WMS, and supply chain applications?
Yes. Atatus monitors the performance of manufacturing applications and infrastructure, while KLogic centralizes logs from ERP, MES, WMS, TMS, APIs, and cloud services to provide complete operational visibility.
How do Atatus and KLogic reduce production downtime?
Atatus proactively detects performance anomalies across applications and infrastructure, while KLogic correlates logs, metrics, and traces to identify the exact root cause, reducing Mean Time to Resolution (MTTR).
Do Atatus and KLogic support Kubernetes and cloud-native manufacturing environments?
Yes. Both platforms support Kubernetes, containers, microservices, and hybrid cloud environments, making them ideal for modern manufacturing and logistics workloads.
Can these platforms improve supply chain reliability?
Yes. By continuously monitoring APIs, integrations, databases, and infrastructure, Atatus and KLogic help teams quickly resolve issues that could disrupt inventory, shipping, or production workflows.
Are Atatus and KLogic suitable for compliance and operational audits?
Yes. KLogic provides centralized log retention and audit trails, while Atatus offers performance insights and historical monitoring data to support operational reviews and compliance requirements.

Let's build something worth measuring

Evaluating full-stack observability or Kafka monitoring? Talk to the team building both, not a reseller of either.