Why Datadog Costs Can Spike

Using a monitoring/observability platform like Datadog is great initially, but as your cloud usage, containers, metrics, and log volumes grow, costs can skyrocket. Key reasons include:

• Datadog pricing is often host- or container-based.
• Autoscaling nodes or containers without optimizing agent deployment can inflate bills.
• Uncontrolled logging, custom metrics, and tracing volumes can lead to high volume-based charges.
• Misconfigurations in cloud-native setups (like Kubernetes + FastAPI + React + Redis + Postgres) can accidentally increase host counts.

Verdict: Ignoring monitoring costs can quickly lead to surprise bills.

As businesses increasingly rely on cloud infrastructure, AWS remains the market leader, offering unmatched scalability, reliability, and a wide array of services. But with great power comes great responsibility — especially when it comes to controlling costs. Unoptimized cloud spending can quickly spiral out of control, eating into your budget and reducing ROI. The good news? AWS provides a host of tools, strategies, and best practices to optimize costs without compromising performance. Let’s explore them.