Prometheus for Quantifiable Data Collection
Updated November 07, 2022

Prometheus for Quantifiable Data Collection

Joshua Li | TrustRadius Reviewer
Score 6 out of 10
Vetted Review
Verified User

Overall Satisfaction with Prometheus

We use Prometheus as data metric collection source of our systems' many software services. Each service has their own Prometheus instances created to collect specific metrics. The metrics are displayed and manipulated in Grafana using the Prometheus data source. Prometheus supports these Grafana dashboard displays to aid system monitoring, performance troubleshooting, and statistics.

Pros

  • Store data metrics
  • Support code queries
  • Provide data source to any Grafana dashboard

Cons

  • Provide categorized metric lookup
  • Suggest certain code queries
  • Include metric descriptions
  • Universal Integration
  • Shareable data sources
  • Best for quantifiable metrics
  • Customer desires to see metric products which Prometheus directly supports
  • Most developers use Prometheus for service management anyways
  • Provides great value at every product level for internal and external use
Prometheus is great for quantifiable metrics. Loki is intended for log aggregation. Depending on project a different combination of data source types may be needed. However, quantifiable metrics are predominantly supported by Prometheus. Other data sources like elastic search are becoming deprecated and no longer supported by Grafana dashboards next update.

Do you think Prometheus delivers good value for the price?

Yes

Are you happy with Prometheus's feature set?

Yes

Did Prometheus live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Prometheus go as expected?

I wasn't involved with the implementation phase

Would you buy Prometheus again?

Yes

Prometheus is widely used for quantifiable data metric storage and is easy to use for including in any Grafana dashboard. Different services can share Prometheus data sources with each other in a complex software system architecture. However, a disadvantage is the Prometheus instance within a cluster is obviously dependent on the cluster status. If the cluster is offline, those Prometheus metrics will also be unavailable.

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