车讯情报一汽-大众2017年研发费“暴增”高达4

Get a single source of truth for frontend monitoring data

Companies have become increasingly reliant on web and mobile applications to meet their customers' needs, so it's important for them to proactively test key workflows and monitor real user sessions in order to deliver a consistent user experience. Other frontend monitoring solutions can help surface frontend issues, but they often require specialized knowledge of query languages and testing frameworks—and force users to pivot back and forth between tools throughout the troubleshooting process. These limitations make it difficult to assess an issue's context, onboard new team members, and collaborate with other stakeholders.

Run synthetic tests against different environments, devices, browsers, and locations

The agile development methodology enables teams to release new features quickly, but it also makes it harder for them to create and maintain tests that reliably detect regressions. With Datadog Synthetic Monitoring, teams can create scalable browser and API tests that can be executed in any environment, including CI pipelines. This enables them to catch issues such as slow response times, elevated error rates, and broken endpoints earlier in the development process—and prevent breaking changes from reaching production.

Eliminate data silos for improved UX collaboration

Real user data can help teams across an organization make informed decisions, but data silos in traditional tools can make it difficult to determine, for example, why users are abandoning their carts or struggling to navigate through an application. Datadog RUM enables developers, designers, marketers, and product managers to access the same user data, so they can monitor their applications' frontend performance holistically and collaborate on UX improvements.

Prioritize issues based on severity, frequency, and scope

Modern environments can generate thousands of errors in rapid succession, and these errors can affect users differently depending on their browser, location, and device. This makes it difficult for teams to assess the scale and impact of issues in order to prioritize their resolution. Datadog Error Tracking extracts error events from RUM data and automatically groups related errors into context-rich issues, which can be filtered by tags and facets such as service, environment, and application version. Users can also monitor each error's frequency in order to gauge its severity and appropriately prioritize its resolution. This enables engineers to triage and investigate more efficiently so they can focus their bandwidth on building new features and optimizing their applications.

Reduce MTTD and MTTR with full-stack visibility

Frontend errors and high latency can impact retention, churn rates, conversions, and revenue, but it can be challenging to pinpoint the source of these problems without a solution that provides full-stack visibility. Datadog unifies Application Performance Monitoring (APM) with Synthetic Monitoring and Real User Monitoring (RUM) to facilitate seamless, two-way correlation between frontend user sessions, synthetic test runs, and backend traces. This allows teams to troubleshoot with context so they can identify which part of the stack is responsible for user-facing issues. For instance, if a user sees a spike in their application's load time, they can pivot to related traces in a single click in order to pinpoint the exact source of the bottleneck. Traces are also automatically linked to relevant logs, which provide more granular insight into what occurred at each stage of a request.