stackdriver

I am trying to optimise performance in an app-engine Java app using cloud sql gen2. It would help a lot if I could trace calls to cloud sql just like I can trace RPC calls to the datastore in the stackdriver trace details. Is this somehow possible, or maybe planned? Or is the only alternative to do log.info() calls with milliseconds? Or is there some other way to add event markers for tracing / profiling? There's now Google Cloud Trace for JDBC for exactly this use case. Google Cloud Trace for JDBC is a custom JDBC driver which intercepts calls to the actual JDBC driver (e.g. Cloud SQL's) and

I am using OpenCensus in Go to push tracing data to Stackdriver for calls involving a chain of 2 or more micro services and I noticed that I get many traces which contain spans only for certain services but not the entire end to end call. At the moment I attribute this to the fact that not all calls are traced (only a certain sample) and each service decides whether to trace its current span or not. Is this the way it is intended to work? Is there any way to make sure when a trace is sampled, it is done so by all services in the call chain? Architecturally I will say when you are developing

In Google App Engine Flexible environment many Logs are skipping, and not getting shown in the Logging console, and it is happening always, I am checking it on Stackdriver Logging section on Google Cloud dashboard, the Logs I am showing using console.log() are getting skipped but mongoose query logs are getting printed. Also, now currently sometimes my logs console.logs are getting shown but sometimes not, but previously they were getting shown every time. Why now is it not working every time? Can anyone please tell me why is this happening? Thank You Edit - I have added debugging points but

I have Google compute engine instances already up and running since recently. I have explored Google Cloud stackdriver for monitoring CPU Usage etc. I have installed Stackdriver agent on to one of the Compute Engine instance for testing. I have explored creating new chart on dashboard, tried with various metrics. But I could not find any metrics that can show disk usage of my instance. Yes there is list of plugins supported by Stackdriver agent to pump custom metrics but I could not find any specific metric that measure the instance disk usage. Please give me a pointer. Thanks Volume usage is

I'm currently trying to log errors to Stackdriver Error Reporting from Google Container Engine. I'm using the built-in fluentd-based Stackdriver Logging agent from GKE which works great. However, when I log an error according to the specification( https://cloud.google.com/error-reporting/docs/formatting-error-messages ), I do not see it appear in Stackdriver Error Reporting The payload I see in Stackdriver Logging is { insertId: "xatjb4fltv246" jsonPayload: { stream: "event" message: "path was incorrect" environment: "production" event_type: "RAILS_ERROR" context: { path: "/2", reportLocation:

Already created my filters with a specific value from the jsonPayload. I want to create a metric which plots the values of Process_time. Can anyone please help, how to create such metrics? Click on the "CREATE METRIC" button above the filter box and use jsonPayload.process_time as the Field name The other attributes are generally described in the instructions on https://cloud.google.com/logging/docs/logs-based-metrics/distribution-metrics 来源： https://stackoverflow.com/questions/56821181/gcp-stackdriver-logs-based-metrics-for-custom-payload-value

Since migration to V2 logs from Cloud ML jobs are not accessible on the Stackdriver logging console anymore. The last log displayed is Waiting for Tensorflow to start. The job is executed and completed successfully, I just can't access outputs in the logs All Stackdriver APIs are enabled for the project. There are no known issues with Cloud ML's Stackdriver logging. The fact that you see "Waiting for Tensorflow to start." indicates you are seeing log messages from Cloud ML. If logs from your Python/TensorFlow program are missing that usually indicates Cloud ML hasn't been authorized to send

I'm a bit confused at how to setup error reporting in kubernetes, so errors are visible in Google Cloud Console / Stackdriver "Error Reporting"? According to documentation https://cloud.google.com/error-reporting/docs/setting-up-on-compute-engine we need to enable fluentd' "forward input plugin" and then send exception data from our apps. I think this approach would have worked if we had setup fluentd ourselves, but it's already pre-installed on every node in a pod that just runs gcr.io/google_containers/fluentd-gcp docker image. How do we enable forward input on those pods and make sure that