Product and Engineering teams want to know how their software is performing, but it’s even more important that your paying customers (you know, those people who keep the lights on) are having good experiences. Don’t wait for the support ticket; be proactive about customer-level application performance monitoring.
Segment your application performance data by customer account attributes to understand how specific customers are experiencing your software.
Drill down to application usage for specific accounts to understand how features are performing and gaining adoption.
Identify the high volume transactions that are either creating too many database calls or spending a lot of time in the database layer.
Site owners rely on real user data to help troubleshoot incidents faster and optimize customer experience. For troubleshooting, developers or reliability teams responding to incidents can easily quantify customer impact. For longer-term customer experience, frontend and fullstack developers can leverage perceived performance metrics to benchmark and improve page performance, then visualize improved business outcomes from faster pages.
User-centric perceived performance
Measure how fast your page displays content, how quickly users can interact, and how quickly your marquee images and videos render.
Track the pageviews, response times, and sessions of specific accounts or users to give support and operations teams insight into customer experience.
Track digital customer experience
Determine the content, features, and funnels that your users are engaging to help prioritize which parts of your application that need optimization.
Mobile developers are constantly looking for ways to shave seconds off of their application load times. A poor first time user experience can mean deletion and abandonment for many apps. Using the combined power of New Relic dashboards and Mobile, you can create detailed interactions, screen-level performance reports, and dynamic user histories to understand what your users are doing, and how you can optimize your app to meet your goals.
Analyze sessions coming from your mobile application to understand core engagement metrics and how users are adopting different features.
Track core mobile KPIs such as average session time, average sessions per user, and daily active users.
Refine your analysis of mobile performance by pinpointing specific geographies, carriers, and networks and how those aspects impact mobile application performance.
Availability and performance matter. Visualize and report SLAs, SLOs, and the availability of URLs, APIs, third parties, and user funnels. Benchmark your page speed and performance against your competition to understand how your site compares in the market.
Visualize reliability metrics, SLAs, SLOs
Dashboard and report service level health to teams and management. Measure the change in uptime across your site, APIs, third parties, and services.
Understand the performance impact that 3rd party services have on your page load durations by drilling into your Synthetics data.
Track uptime and performance
Pinpoint failed test results tracked in Synthetics and group results by error messages to identify the root cause of the issue.
DevOps teams need to manage metrics emitted from multiple systems, including Prometheus, DropWizard, and more. With so many sources of metrics data, you need a single place to monitor, alert on, and take action.
Identify which of your clusters are experiencing performance issues so that you can address them before your customers notice degradation.
Analyze and set alerts for CPU time, memory utilization, or any other metrics your business tracks. Drill into the data and filter by time period, region, hardware, and any other key:value pair that your data contains.
Developers and IT Ops professionals often need the granular detail that’s only captured in log messages in order to determine the root cause of application and infrastructure incidents.
Granular log visibility
Logs, originating both in the cloud and on-prem, can be visualized in dashboards to track these detailed messages over time and help you take the right actions to reduce the mean time to detection (MTTD) and mean time to resolution (MTTR).