Alternatives to Google Cloud Managed Service for Prometheus

Amazon CloudWatch Logs

It suits teams monitoring workloads across AWS, on-premises, or other clouds, especially those needing centralized log analysis across accounts.

It suits software engineers who need to detect application anomalies and investigate root causes using service health and telemetry signals.

It suits teams responsible for cloud-native applications and microservices that need service-level views, correlated telemetry, and distributed tracing.

Nagios XI

Nagios XI suits teams that want to host monitoring on their own Linux infrastructure and need configurable checks, notifications and access controls.

Netdata lists platform engineers, DevOps teams, SREs, developers, system administrators, CISOs, DBAs, network engineers, and MSPs among its audiences.

Icinga

Icinga suits teams of any size that need self-hosted infrastructure monitoring, from small setups to large distributed environments.

InfluxDB

InfluxDB suits teams working with timestamped data for industrial operations, observability or AI applications.

Google Cloud Monitoring

It suits teams monitoring applications, infrastructure, Kubernetes workloads, or services across Google Cloud and hybrid or multicloud environments.

groundcover

It suits teams monitoring production environments that want to collect telemetry without manual instrumentation.

VictoriaMetrics

It suits teams that need metrics monitoring and storage, or organizations building observability across metrics, logs, and traces.

LogicMonitor

LogicMonitor suits enterprises, IT teams, and MSPs managing complex hybrid environments across Linux, Windows, cloud, and on-premises systems.

SigNoz

SigNoz suits engineering teams monitoring applications and infrastructure across logs, metrics, traces, and exceptions.

Prometheus

It suits teams that need open-source metrics collection, querying and alerting, including self-hosted deployments.

Zabbix

Zabbix suits organizations monitoring infrastructure, applications, networks or services across varied data sources.

It suits teams running load, stress, browser-based, distributed, or API tests on Linux, especially those needing the listed tracing, logging, or profiling features.