Review Summary
Users appreciate Datadog for its user-friendly interface, comprehensive observability features, and powerful real us ...
Users appreciate Datadog for its user-friendly interface, comprehensive observability features, and powerful real us ...
Datadog specializes in providing a comprehensive monitoring platform for cloud applications. It collects data from diverse sources such as servers, containers, databases, and third-party services, aiming to make the stack fully observable. By offering these features, Datadog assists DevOps teams in preventing downtime, addressing performance problems, and ensuring optimal user experience.
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I love that since I have come on board they have been very oriented on expanding the products around security. It is an extremely needed service in today's age, but also an incredibly difficult space to maintain full awareness of all the evolving risks and requirements across the tech stack. From monitoring to research, I love having Datadog as a sanity check that we are making the right choices and keeping a good posture.
All in one, easy to leverage one vendor for many services
I like the unified view of synthetics for API tests and APM for code traces. I can set up a synthetic test to hit our login endpoint every minute from 5 different global locations, and if latency spikes, I can click a button to see the exact SQL query or downstream microservice that caused the delay. CI/CD integration for quality gates is also top tier, and we can block deployment if the Datadog performance baseline isn't met.
The sheer amount of products and different ways of approaching pricing makes it sometimes hard to identify what is used where while keeping track of product offerings and how it relates to billing. Although there are many integrations, sometimes they do not cover my less popular choices. Things move around in the menus a bit too often.
Billing - line items / too many SKUs. All volume based and by range. Its also easy to turn on many things and then get a surprise bill at the end. also for how much our startup pays annually, i feel like the discounts should be larger / for any overages should be at the price we negotiated not list price
The log rehydration cost and the general pricing for custom metrics is painful. We often have to sample our traces aggressively (only keeping 1% of success logs) to keep costs down, which sometimes means we miss the context on rare edge case bugs. Also, the UI for building complex dashboards can be overwhelming for new hires compared to simpler tools.