Observability tooling can get expensive and complex fast. This comparison looks at CloudWatch, Sentry, and Datadog through a startup lens: what each is good at, and a sensible place to start.
What each tool is built for
These three tools get compared as if they are interchangeable, but they were built to answer different questions. CloudWatch tells you what your infrastructure is doing. Sentry tells you what your application code is doing wrong. Datadog tries to tell you everything in one place. Understanding the boundaries saves you from paying three times for the same signal — or missing a signal entirely.
The honest framing for a startup is not which one to pick, but which question hurts most right now: are servers falling over, is code throwing errors, or are you blind across the whole stack? Start with the pain you actually have.
CloudWatch: the cloud-native baseline
CloudWatch is the native monitoring layer for your cloud platform, so it sees infrastructure metrics — CPU, memory, disk, database connections, queue depth — without any extra agents, and it collects your logs by default. If you are already on the cloud, a meaningful baseline is essentially free and already running.
Its limits show up at the application layer. CloudWatch will tell you a service is unhealthy or that errors are rising, but it is weaker at telling you which line of code failed for which user. The querying and dashboards are functional rather than delightful. As a foundation it is hard to beat; as your only tool it leaves gaps.
Sentry: application errors
Sentry is purpose-built for one job and does it very well: capturing application errors with the context you need to fix them. When an exception fires, you get the stack trace, the request, the release it appeared in, and how many users it hit — grouped so a thousand occurrences read as one issue, not a thousand alerts.
This is the layer CloudWatch is weakest at, which is exactly why the two pair so naturally. Sentry is affordable at startup volumes, quick to install, and tends to be the first place developers actually look when something breaks. It is not infrastructure monitoring, and it does not pretend to be.
Datadog: unified observability
Datadog brings metrics, logs, traces, and application performance monitoring into one correlated view. When you want to follow a slow request from the load balancer through your services to the database query that caused it, this kind of unified observability is genuinely powerful, and the integrations cover almost anything you might run.
The trade-off is cost and complexity. Datadog bills across several dimensions, and bills can climb quickly as you add hosts, custom metrics, and log volume. It rewards teams who have enough scale and enough operational maturity to use what they are paying for. For a small team early on, it can be more platform than the problem requires.
A starter stack for startups
For most early-stage SaaS, the sensible default is CloudWatch plus Sentry. CloudWatch gives you infrastructure metrics, logs, and basic alerts at little cost; Sentry gives you the application error visibility CloudWatch lacks. Together they cover the two questions that account for nearly every early incident, without a heavy bill or a steep learning curve.
Reach for Datadog when correlating across many services becomes a daily need and the unified view clearly earns its cost — usually as you grow, not on day one. Whatever you choose, the tool only matters if someone is watching it; our Cloud Production Care is built around alerts a human actually responds to.