We have an IOT application. Application has to detect any sudden changes(anomaly) in the device battery voltage. We were planing on using anomaly function built into stream analytics in azure for accomplishing this task.
When I'm running anomaly function in stream analytics query as follows
SELECT ANOMALYDETECTION(BATTERYVOLTAGE) OVER( LIMIT DURATION(hour, 1))
as anomaly FROM [IotTelemetryStream]
it is returning the following error message:
unexpected error has occurred. Please open a support ticket to investigate and provide the following client request id:_______
But when running the same query after removing anomaly function works fine.
SELECT BATTERYVOLTAGE as anomaly FROM [IotTelemetryStream]
I cannot find any reference for this issue any where on web so any help would be much appreciated and thanks in advance.
Can you please send your email address in a direct message to https://twitter.com/azurestreaming ? We will reach out to you with details after that.
Related
Context: During performance evaluation we have noticed that there is a discrepancy in the response time between Postman and Application Insight.
During debugging we found that the response time given obtained from Postman Vs Application Insight are different for the same transaction. We noticed is for different transactions. Why it is so?
Current Configuration: We have application insight for an application which is running within an app service and "Adaptive Sampling" is enabled for Application insight.
Note: We are tracing the transaction with tracing ID.
Comparisions Chart:
Smaller Evaluation:
Medium Evaluation:
When the system is under stress the response time goes to min on postman, but in application insight the response time are change drastically.
May be the difference in the response time is lesser but when the number of transactions is more and when we see the 95th (refer the example below) and 99th percentile the game completely changed. Any suggestion on this? Am I missing something?
For example:
Postman Result:
Application Insight:
Posting the suggestion provided by Peter-Bonsas an answer so that it will be helpful for other community members.
From the below screenshot application insights won't take the actual latency of sending the request to the api and getting the response back. The time which we will be seeing in app insights is total execution time on the azure side
I have been using https://github.com/tappoz/azure-golang-iothub/ to read a device twin from azure iothub. Since yesterday it stopped working and giving me this error:
{"Message":"ErrorCode:ServerError;InternalServerError","ExceptionMessage":"Tracking ID:bd8489a3048d4fa3b7c655d2e5ea57a5-G:10-TimeStamp:03/20/2019 18:32:26"} 500 Internal Server Error
Any idea why it stopped working since yesterday and/or how can I resolve it?
Microsoft changed how Shared Access Signature is supposed to be computed. It used to take
".azure-devices.net/devices/?api-version=2016-11-14" for the computation, since March 18/19, the new way of computing would take just the "".azure-devices.net/devices/" part. I will submit a change to https://github.com/tappoz/azure-golang-iothub/ accordingly
I´m trying to grab Firebase analytics data from Google BigQuery with Azure Data Factory.
The Connection to BigQuery works but I have quite often timeout issues when running a (simple) query. 3 out of 5 times I run into a timeout. If no timeout occurs I recive the data as expected.
Can someone of you confirm this issue? Or has an idea what´s the reason for the.
Thanks & best,
Michael
Timeout issues could happen in the Azure Data Factory sometimes. It is affected by source dataset, sink dataset, network, query performance and other factors, etc. After all, your connectors are not azure services.
You could try to set timeout param follow this json chart. Or you could set retry times to deal with timeout issues.
If your sample data is so simple that can't be timeout,maybe you could commit feedback here to ask adf team about your concern.
We've been having a few issues with Azure IotHub. I have a stream analytics job listening to an IotHub. My stream analytics job which was working perfectly fine just started showing no input and output. On restart it came up with the following error "Stream Analytics job has validation errors: Querying EventHub returned an error: ProtocolName." Which sort of indicates to me that it can't listen to IotHub anymore. Has anyone else had similar issues?. Help on troubleshooting this would be great.
stream analytics job error
There was an issue with EventHub that has since been addressed which should fix this. If this problem persists, please contact support.
I'm outputting a Stream Analytics job to PowerBI.com. It successfully sends the first 11-100 messages just fine, but after which it fails. In the operational log it says the operation "failed to send events" and is categorized as a "PowerBIOutputAdapterTransientError" without much other information. What are the symptoms of this type of error?
Messages are still going through Event Hubs but all operations seem to be haulted on the PowerBI side.
Looks like this was a transient service issue.