Debug School

Rajesh Kumar Samal
Rajesh Kumar Samal

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Datadog –Day-4- 14-Sept–23- Assignment 1

1 Top 10 metrics/indicators for APM ?

Response Time: Measure the time it takes for your application to respond to user requests. This is crucial for user experience.
Latency: Measure the delay between a request and its corresponding response to identify network and application performance issues.
Transaction Tracing: Trace the path of transactions across various components of your application to pinpoint bottlenecks and slowdowns.
Error Rate: Monitor the frequency of errors occurring in your application. High error rates can indicate problems that need immediate attention.
Resource Utilization: Monitor CPU, memory, disk, and network usage to identify resource bottlenecks and optimize resource allocation.
Throughput: Track the number of transactions or requests your application can handle per unit of time. It helps gauge your system's capacity.
Apdex Score: Calculate the Application Performance Index (Apdex) score to assess user satisfaction with application response times.
Dependency Analysis: Analyze dependencies between different components and services to identify potential issues and optimize performance.
Error Details: Dig deeper into error data to understand the root causes of issues and prioritize debugging efforts.
Real User Monitoring (RUM): Collect real user data, such as page load times and interactions, to gain insights into how actual users experience your application.

2 Top 10 metrics/indicators for Synthetic monitoring ?

Error Rate: Keep an eye on the rate at which synthetic transactions encounter errors or failures.
Response Time: Measure the time it takes for synthetic transactions to complete and assess whether they meet predefined thresholds.
synthetics.test_run_steps (count): The number of Synthetic test steps.
Availability/Uptime: Monitor the percentage of time an application or website is accessible and available to users.
Transaction Success Rate: Track the percentage of synthetic transactions that complete successfully without errors.
Transaction Paths: Monitor the sequence of steps within synthetic transactions to identify bottlenecks or issues in critical user flows.
Transaction Completion Time: Monitor the time it takes for specific synthetic transactions (e.g., login, checkout) to finish successfully.
Page Load Time: Measure how long it takes for web pages to fully load, including all resources such as images, scripts, and stylesheets.
Geographic Performance: Assess how response times vary across different geographical locations to identify regional performance issues.
Content Validation: Verify the content displayed during synthetic transactions to ensure it matches expected results, helping to detect unexpected changes or defacements.
Third-Party Service Performance: Evaluate the performance of third-party services and APIs integrated with your application, as they can impact overall performance.

3 Top 10 metrics/indicators for RUM ?

Page Load Time: Measure the time it takes for web pages to fully load in a user's browser, including all resources (images, scripts, stylesheets).
Page Views: Track the number of pages viewed by users to understand engagement and navigation patterns.
First Contentful Paint (FCP): Monitor the time it takes for the first piece of content to be rendered on a web page, providing a user with visual feedback.
Bounce Rate: Monitor the percentage of users who leave the website after viewing only one page, which can indicate user dissatisfaction.
Time to Interactive (TTI): Measure how long it takes for a web page to become fully interactive, where users can interact with elements and content.
Conversion Rate: Measure the percentage of users who complete a desired action or conversion, such as signing up or making a purchase.
Error Rate: Keep an eye on the rate at which users encounter errors or experience issues while interacting with your application.
Geographic Performance: Assess how performance varies across different geographic locations to identify regional performance disparities.
Device and Browser Performance: Analyze how performance varies on different devices (e.g., desktop, mobile) and browsers (e.g., Chrome, Firefox).
User Segmentation: Segment users based on various attributes (e.g., location, device, browser) to identify performance differences among different user groups.

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