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Complete GCP Monitoring for Cloud-Native Applications

Monitor your Google Cloud Platform infrastructure with comprehensive visibility into Compute Engine, Cloud Functions, Cloud Run, and GKE. Track performance, optimize costs, and ensure reliability across your GCP environment with real-time observability.

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OpenTelemetry nativeSaaS, on-prem, hybrid or BYOCNo per-user pricing
Challenges

Full-Stack Observability for GCP Workloads

End-to-end GCP coverage

Observe workloads running on Compute Engine, GKE, Cloud Run, App Engine, and managed databases with a unified operational view.

GKE workload visibility

Track pod behavior, node performance, and service communication inside Kubernetes clusters without losing application context.

Serverless execution clarity

Maintain visibility into Cloud Functions and Cloud Run executions where infrastructure is abstracted and short-lived.

Distributed request tracing

Follow requests across load balancers, APIs, background services, and data stores throughout GCP.

Application-aware infrastructure

Interpret CPU, memory, and network behavior in the context of real application traffic and workload demand.

Correlated telemetry timelines

Analyze logs, metrics, and traces together through a shared execution timeline during investigations.

Scale-ready observability

Maintain consistent visibility as services autoscale, traffic grows, and regions expand.

Shared operational context

Enable platform, SRE, and backend teams to operate from the same production view without data silos.

Unified GCP Monitoring

  • Monitor core Google Cloud services including Compute Engine, Cloud Storage, GKE, Cloud SQL, Cloud APIs, and other managed services from a single platform.
  • Centralize performance, availability, and health metrics across GCP services to eliminate monitoring silos.
  • Visualize real-time metrics through customizable dashboards aligned to your GCP architecture and workloads.
  • Configure service-specific metric collection to track uptime, performance, and reliability across cloud resources.
Unified GCP Monitoring

Operational Insights

  • Correlate metrics, logs, and traces to identify performance bottlenecks across distributed GCP workloads.
  • Track infrastructure resource usage such as CPU, memory, disk, and network I/O alongside application-level signals.
  • Gain visibility into request flows, dependencies, and latency contributors across microservices and cloud components.
  • Use actionable insights to improve reliability, reduce MTTR, and optimize day-to-day cloud operations.
Operational Insights

Seamless GCP Integration

  • Securely connect to Google Cloud Platform using IAM roles and service account impersonation for automated telemetry collection.
  • Enable monitoring across multiple GCP projects to support large-scale, multi-environment deployments.
  • Scale observability consistently as new projects, regions, and services are added without manual reconfiguration.
  • Maintain strong access control, governance, and security while collecting metrics, logs, and traces from GCP resources.
Seamless GCP Integration
Why Atatus

Why teams choose Atatus for GCP?

Teams running on GCP choose Atatus to maintain clear production visibility across managed services, containers, and serverless workloads.

01

Designed for GCP architectures

Atatus aligns with how GCP services interact across compute, networking, and managed platforms.

02

Fast production understanding

Engineers can reason about live system behavior without stitching data across multiple tools.

03

Works with ephemeral workloads

Visibility remains intact even when containers and serverless instances scale rapidly.

04

Clear cross-service context

Production issues are understood in terms of service interactions, not isolated signals.

05

Low adoption friction

Teams onboard quickly without restructuring existing GCP environments.

06

Built for engineering teams

Platform, SRE, and backend teams share a common operational view of production.

Teams

Unified Observability for Every Engineering Team

Atatus adapts to how engineering teams work across development, operations, and reliability.

Customers

Powering better performance for modern teams

"Solid Product even better support." The integration path is incredibly simple/easy and the overall interface is very intuitive. That said, I had a handful of odd use cases that the support team was incredibly responsive in helping me work through.

Wes DSite Reliability Engineer
FAQ

Questions Engineers Ask Before Buying

Pricing, deployment, data and the agent. If something is missing, a person will answer it on a demo call.

  • Atatus provides comprehensive monitoring for all major GCP services including:

    • Compute Engine - CPU, memory, disk, network metrics
    • Cloud Functions - invocations, duration, errors, cold starts
    • Cloud SQL - query performance, connections, replication lag
    • GKE clusters - pod health, node utilization, scaling events
    • Cloud Storage - request latency, error rates, storage metrics
    • Cloud Run - request counts, concurrency, cold starts
    • BigQuery - query performance, slot utilization, costs
    • Pub/Sub - message latency, subscription backlog

  • Atatus integrates with GCP through Cloud Monitoring API access via service accounts, direct agent installation on Compute Engine instances, and OpenTelemetry collectors for GKE and Cloud Run.

    Deploy quickly using our Deployment Manager templates or Terraform modules. Atatus automatically discovers GCP resources and provides immediate visibility.

  • Yes, Atatus tracks BigQuery query costs, slot utilization, and data scanned per query. Identify expensive queries, track cost trends, and set budget alerts before costs spiral.

    See which teams or projects consume the most BigQuery resources. Optimize query patterns, implement partitioning recommendations, and track the ROI of BigQuery workloads.

  • Atatus provides detailed Cloud Run monitoring including request latency, concurrency, container startup time, and autoscaling events. Track cold starts and optimize minimum instances.

    Distributed tracing shows the complete request flow through Cloud Run services, including calls to Cloud SQL, Firestore, and external APIs. Identify performance bottlenecks and optimize container configurations.

  • Yes, Atatus supports monitoring across multiple GCP projects and organizations. See all resources in a unified dashboard with project-level filtering and aggregation.

    Track cross-project networking, shared VPC performance, and inter-project dependencies. Get consolidated billing insights and compare resource utilization across projects.

  • Yes, Atatus provides deep Kubernetes monitoring for GKE clusters including Autopilot and Standard modes. Monitor workloads, track cluster autoscaling, and analyze container performance.

    Integrate with Artifact Registry for image tracking and vulnerability scanning. Monitor Anthos service mesh, track multi-cluster deployments, and correlate application traces with infrastructure metrics.

Get started

See the root cause first.

Start free trialRequest demo

Start free and send your first trace with OpenTelemetry or the Atatus agents. APM, logs, RUM, infrastructure and SIEM, all on one timeline.

  • SaaS
  • On-premises
  • Hybrid
  • BYOC
  • No per-user pricing