AWS CloudWatch vs Datadog

Developers should use AWS CloudWatch when deploying applications on AWS to gain visibility into system performance, troubleshoot issues, and ensure reliability meets developers should learn and use datadog when building or maintaining distributed systems, microservices architectures, or cloud-based applications that require comprehensive observability. Here's our take.

AWS CloudWatch

Nice Pick

Developers should use AWS CloudWatch when deploying applications on AWS to gain visibility into system performance, troubleshoot issues, and ensure reliability

Pros

• It is essential for monitoring AWS services like EC2, Lambda, and RDS, setting up automated responses to events, and analyzing logs for debugging and compliance purposes
• Related to: aws-ec2, aws-lambda

Cons

• Specific tradeoffs depend on your use case

Datadog

Developers should learn and use Datadog when building or maintaining distributed systems, microservices architectures, or cloud-based applications that require comprehensive observability

Pros

• It is essential for DevOps and SRE teams to monitor application performance, detect anomalies, and resolve incidents quickly, particularly in dynamic environments like AWS, Azure, or Kubernetes
• Related to: apm, infrastructure-monitoring

Cons

• Specific tradeoffs depend on your use case

The Verdict

These tools serve different purposes. AWS CloudWatch is a tool while Datadog is a platform. We picked AWS CloudWatch based on overall popularity, but your choice depends on what you're building.

The Bottom Line

AWS CloudWatch wins

Based on overall popularity. AWS CloudWatch is more widely used, but Datadog excels in its own space.