Datadog vs AWS Cloudwatch vs Grafana

  • Datadog
  • CloudWatch
  • Grafana

Datadog

Key Features of DataDog

Grafana

Key Features of Grafana

  • Data Source plugins
  • App plugins
  • Panel Plugins

AWS Cloudwatch

Key Features of CloudWatch

  • Logs published by AWS services Currently, over 30 AWS services publish logs to CloudWatch
  • Custom logs Using a CloudWatch agent, you can push logs from your application and on-premises resources.
  • Graph metrics and log data side by side
  • Graphs for cloud resources and applications in a unified view

Key Differences

  1. Getting started with
  • Prometheus
  • Jaeger
  • Zipkin
  • AWS CloudWatch
  • Graphite
  • Azure Monitor
By default, this is the landing page after you log in to Datadog
CloudWatch dashboard
Grafana dashboard example

Pros and Cons

Datadog

Pros

  • Support for log aggregation and analytics
  • Support for anomaly detection and alerts
  • Support for custom metrics and custom Datadog integrations

Cons

  • No self-hosted solution
  • Complex to use; can be overwhelming for new users
  • Limited log analytics due to lack of support for JSON log processing

AWS CloudWatch

Pros

  • It allows us to configure alarms to trigger a notification (like sending emails) when any specified condition is rendered satisfied.
  • CloudWatch provides the feature called Events, which is different from alerts. It makes the platform aware of the application’s operational changes as they happen in real-time. An Event can even automatically trigger a specified action.
  • Very advanced visibility and insights about other integrated AWS services.
  • Only pay for what you use.
  • Centralized storage and analysis for logs and metrics from all combined AWS resources and also allows executing queries on this data.

Cons

  • It can only be used for AWS services. There may be some good scripts made by third parties to get metrics for non-AWS servers but they aren’t an “official” solution.
  • Not enough customization of dashboards.
  • No metrics for memory usage by default. A custom metric has to be configured to have this basic indicator monitored.
  • Becomes very expensive at the enterprise level — can be over $50,000 per year.

Grafana

Pros

  • Free and open-source with a huge open-source community for support
  • Automatic service discovery and support for both push and pull metric scraping models
  • Support for custom metrics; a huge number of exporters available to export metrics to Prometheus from different sources

Cons

  • Complex and time-consuming to manage Prometheus instances; operational overhead if your staff is unfamiliar with the tool
  • Need to manually configure and manage Prometheus exporters
  • Manual setup required for graphs and alerts

Conclusion

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Anil Augustine Chalissery

Anil Augustine Chalissery

DevOps Engineer | AWS Enthusiast | Analyse -> Solve -> Automate