# Cloud Monitoring

> Sisense Cloud employs a comprehensive monitoring and observability framework to ensure high availability, performance, and reliability of our platform. Our Cloud Operations team, including a dedicated Site Reliability Engineering (SRE) team, proactively monitors and optimizes system performance while ensuring a seamless experience for our customers.

*Source: https://docs.sisense.com/main/SisenseLinux/cloud-monitoring.htm*

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Last updated: June 10, 2026

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| [Tier](https://www.sisense.com/pricing/#pricing) | [Deployment](https://docs.sisense.com/main/SisenseLinux/introduction-to-sisense-cloud-managed-services.md#ComparisonofManagedCloudandSelfHosted) |
| Grow    Enterprise | Cloud |

Sisense Cloud employs a comprehensive monitoring and observability framework to ensure high availability, performance, and reliability of our platform. Our Cloud Operations team, including a dedicated Site Reliability Engineering (SRE) team, proactively monitors and optimizes system performance while ensuring a seamless experience for our customers.

## Monitoring & Observability

Sisense Cloud gathers Metrics, Events, Logs, and Traces (MELT) through a Single Pane of Glass (SPOG) platform, ensuring end-to-end visibility across all deployments.

- **Metrics Collection:** Every deployment includes Prometheus, which ships key metrics to local Grafana dashboards and SPOG.
- **Logging:** Fluentd collects logs locally and ships them to SPOG for centralized analysis.
- **Application Performance Monitoring (APM):** We actively integrate OpenTelemetry to enhance visibility into application-level performance.
- **Key Monitored Metrics:**

  - **Infrastructure:** CPU, memory, network, and disk usage.
  - **Kubernetes Cluster Health:** Node and pod-level status, and resource utilization.
  - **Application-Level Metrics:** In progress, with continuous expansion.
- **Alerting & Automated Remediation:**

  - Alerts are predefined for critical node and pod-level metrics.
  - Automated remediation techniques are in place to minimize disruptions.

## Proactive Incident Response

Sisense Cloud prioritizes a proactive approach to incident detection and resolution:

- **Incident Detection & Escalation:**

  - SPOG is used to manage business-critical alerts and ensure rapid response.
  - Automated monitoring detects application and performance issues before they impact users.
- **Automated Remediation:**

  - Self-healing mechanisms and automated scripts help resolve common failures.
  - Proactive scaling ensures optimal resource allocation.
- **Service Level Agreements (SLAs):**

  - Our SLAs are publicly available at [Sisense Support Types & Response Times](https://www.sisense.com/support/support-types-and-response-times/).
  - Service Level Objectives (SLOs) are planned for definition after full APM rollout.

## Site Reliability Engineering (SRE)

The Sisense Cloud Operations team is responsible for ensuring the reliability, scalability, and efficiency of the Sisense Cloud. The SRE team plays a crucial role in continuously improving platform performance and stability through engineering-driven operational excellence.

SRE Responsibilities:

- **Incident Prevention & Response:**

  - Implementing best practices for monitoring, alerting, and incident management.
  - Ensuring rapid incident resolution and postmortem analysis for continuous improvement.
- **Scalability & Reliability Enhancements:**

  - Proactively optimizing system performance and infrastructure capacity.
  - Adopting cloud-native reliability engineering practices.
- **Continuous Improvement:**

  - Automating manual operational tasks to reduce toil.
  - Enhancing observability through APM, logs, and telemetry data.

Sisense Cloud is committed to delivering a reliable, high-performing platform by continuously evolving our monitoring and SRE capabilities.

For more details on self-service monitoring, see [Monitoring Sisense on Linux](https://docs.sisense.com/main/SisenseLinux/monitoring-sisense-on-linux.md).