Support Critical Care with Application Observability & Kafka Monitoring
When an EHR order fails to sync, a FHIR call times out, or a pod restarts mid-shift, your team has minutes, not hours to find out why. KLogic centralizes logs across your clinical, cloud, and API layers, correlates them with metrics and traces, and uses AI to surface the root cause before a slow query becomes a patient-facing incident.
Why Observability Matters in Healthcare & Life Sciences
Application reliability in healthcare isn't just an engineering metric. It touches patient care, clinical workflows, provider productivity, revenue cycle, and your ability to answer a regulator's question with evidence instead of a guess.
Downtime Reaches the Bedside
A slow EHR order screen or a stalled lab result isn't an inconvenience, it's a clinician waiting to make a decision. Application performance in healthcare is inseparable from clinical workflow speed and provider productivity.
Healthcare Architecture Is Distributed by Nature
EHR platforms, lab systems, PACS, pharmacy, scheduling, and claims processing all talk to each other over HL7 and FHIR interfaces. A single patient encounter can touch a dozen services any one of which can fail quietly.
Auditors Expect an Answer, Not a Guess
HIPAA audits and security investigations assume you can reconstruct exactly what happened, when, and who accessed what across application logs, infrastructure events, and integration traffic.
Two Products, One Healthcare Infrastructure Stack
Atatus and KLogic are built to work together, one covers your applications and infrastructure, the other covers the logs and integration traffic connecting them.
Full-Stack Observability & APM
Unified monitoring across your clinical, patient-facing, and backend applications, the layer where providers and patients interact with your platform.
- Application performance monitoring for clinical and backend services
- Real user monitoring for patient portals and provider-facing apps
- Infrastructure monitoring across cloud and Kubernetes environments
- Distributed tracing across microservices
AI-Powered Log Management & Investigation
Purpose-built visibility into the logs and integration traffic that carry patient, clinical, and claims data between systems where generic APM stops looking.
- HL7 and FHIR-aware log parsing and search
- AI-assisted root cause investigation
- Kubernetes and distributed system log correlation
- Structured, retained audit logs for compliance
Why Retail Engineering 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 pipeline connecting it.
Ranks likely root causes from correlated log, metric, and trace signals instead of leaving you to search manually.
Full-text and structured search across every service, with results in seconds, not minutes.
Ingest logs, metrics, and traces through a standard OpenTelemetry pipeline without vendor lock-in.
Follow a single patient-facing request across every microservice and integration it touches.
Repetitive, low-signal log lines are filtered and grouped so engineers see what actually changed.
Shorter time from alert to root cause reduces both MTTR and on-call fatigue.
Explore Our Products
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.
Frequently Asked Questions
Let's build something worth measuring
Evaluating full-stack observability or Kafka monitoring? Talk to the team building both, not a reseller of either.