Your API backend is running on multiple cloud providers. You want to generate reports for the network latency of your API.
Which two steps should you take? (Choose two.)
Your API backend is running on multiple cloud providers. You want to generate reports for the network latency of your API.
Which two steps should you take? (Choose two.)
To generate reports on the network latency of an API running on multiple cloud providers, first, use the Zipkin collector to gather data. Zipkin is a distributed tracing system that helps collect timing data required to troubleshoot latency problems in service architectures. Then, use Stackdriver Trace to generate reports. Stackdriver Trace is a distributed tracing system that enables detailed analysis of how requests propagate through your application, providing crucial latency reports. These tools together will provide a comprehensive solution for gathering and analyzing network latency data.
for me the solution is A and C: https://cloud.google.com/trace/docs/zipkin
AC as Zipkin is used for to gather data for latency issues and SD trace purpose is to enable us to have a better view on the application code latency
AC A: to support multiple cloud providers https://cloud.google.com/trace Zipkin tracers to submit data to Cloud Trace. Projects running on App Engine are automatically captured. C: to generate reports for the network latency https://cloud.google.com/trace/docs/quickstart#analysis_reports_window
"latency" is the key word here so C is one of the answers; Stackdriver Trace https://cloud.google.com/trace/docs/zipkin: "receive traces from Zipkin clients and forward those traces to Cloud Trace for analysis." A is the other answer
I would go with BC
C is correct. But B is used for logging and not for monitoring.
A and C are correct solution.
https://cloud.google.com/trace/docs/zipkin#frequently_asked_questions use a Zipkin server to receive traces from Zipkin clients and forward those traces to Cloud Trace for analysis.
The two steps you should take to generate reports for the network latency of your API running on multiple cloud providers are: A. Use Zipkin collector to gather data: Zipkin is a distributed tracing system that helps you gather data about the latency of requests made to your API. It allows you to trace requests as they flow through your system, and provides insight into the performance of your services. You can use Zipkin collectors to collect data from multiple cloud providers, and then generate reports to analyze the latency of your API. C. Use Stackdriver Trace to generate reports: Stackdriver Trace is a distributed tracing system that helps you trace requests across multiple services and provides detailed performance data about your applications. It allows you to visualize and analyze the performance of your API and its dependencies. You can use Stackdriver Trace to generate reports about the network latency of your API running on multiple cloud providers. Therefore, the correct options are A and C.
for me it is C and E, as profiler is used for performance analysis
I think the answer is AC
CE. E for latency Cloud Profiler. For tracing can be use also zipkin but better tracing
BD are correct
A/C https://cloud.google.com/trace/docs/zipkin
The correct answer would be: A. Use Zipkin collector to gather data and C. Use Stackdriver Trace to generate reports. Using Zipkin collector will allow you to gather data from your instrumented application running on multiple cloud providers. Stackdriver Trace can then be used to generate reports based on this data. Option B, using Fluentd agent, is not related to generating reports on network latency for an API. Option D, using Stackdriver Debugger, is not related to generating reports on network latency for an API. Option E, using Stackdriver Profiler, is not related to generating reports on network latency for an API.
solution is AC: https://cloud.google.com/trace/docs/zipkin
For generating reports on network latency for an API that is distributed across multiple cloud providers, you would typically need to gather trace data and then analyze it: A. Use Zipkin collector to gather data: Zipkin is a distributed tracing system that helps gather timing data needed to troubleshoot latency problems in service architectures. You can use Zipkin collectors to gather trace data from your API backend regardless of where it's running. This trace data can provide insights into the latency of different service calls. C. Use Stackdriver Trace to generate reports: Stackdriver Trace (part of Google Cloud’s operations suite) allows you to analyze how requests propagate through your application and receive detailed latency reports for your API. If you are already using Stackdriver on Google Cloud, you can extend its usage to analyze trace data collected from other cloud providers as well.
The two steps you should take are: B. Use Fluentd agent to gather data. Fluentd is a great tool for collecting logs and metrics from various sources, including your API backend running on multiple cloud providers. It can be configured to collect network latency data and send it to a centralized location for analysis. C. Use Stackdriver Trace to generate reports. Stackdriver Trace is a distributed tracing system that helps you understand the performance of your applications. It can be used to collect and analyze network latency data, providing insights into bottlenecks and performance issues.
Here's why the other options are less suitable: A. Use Zipkin collector to gather data. While Zipkin is a popular distributed tracing system, it's not directly integrated with Stackdriver. Using Zipkin would require additional configuration and integration to send data to Stackdriver for reporting. D. Use Stackdriver Debugger to generate reports. Stackdriver Debugger is designed for debugging code, not for generating network latency reports. It focuses on inspecting the state of your application at specific points in time. E. Use Stackdriver Profiler to generate reports. Stackdriver Profiler is used for profiling your application's performance, focusing on CPU usage and memory allocation. It's not the ideal tool for analyzing network latency.