SQL Azure transient failure - sql

Question

I am using entity framework to connect to SQL Azure and data pushed from azure functions.
I noticed that at a particular time interval of 10 mins today there were errors like following thrown from function
An exception has been raised that is likely due to a transient failure. If you are connecting to a SQL Azure database consider using SqlAzureExecutionStrategy
When I looked at sql database statistics, it had reached 99% during that time and then it was good after that.
How can I find out how many transactions were executed during that timeframe using azure portal?
It can probably give me an idea about what caused this load on the server.

Answer 1

In this case what you are seeing may be throttling. When throttling occurs connections get affected but also bad programming may produce unwanted number of connections and every tier has limits of number connections. Below queries will help you monitor successful/terminated/throttled connections.
select *
from sys.database_connection_stats_ex
where start_time >= CAST(FLOOR(CAST(getdate() AS float)) AS DATETIME)
order by start_time desc
select *
from sys.event_log
where event_type <> 'connection_successful' and
start_time >= CAST(FLOOR(CAST(getdate() AS float)) AS DATETIME)
order by start_time desc
To monitor when your databases reach the DTU limit you can use below query:
SELECT
(COUNT(end_time) - SUM(CASE WHEN avg_cpu_percent > 80 THEN 1 ELSE 0 END) * 1.0) / COUNT(end_time) AS 'CPU Fit Percent',
(COUNT(end_time) - SUM(CASE WHEN avg_log_write_percent > 80 THEN 1 ELSE 0 END) * 1.0) / COUNT(end_time) AS 'Log Write Fit Percent',
(COUNT(end_time) - SUM(CASE WHEN avg_data_io_percent > 80 THEN 1 ELSE 0 END) * 1.0) / COUNT(end_time) AS 'Physical Data Read Fit Percent'
FROM sys.dm_db_resource_stats
When query above shows service level objective (SLO) of 99.9% <= go to next tier.
To identify queries creating high IO, high CPU usage, high resource usage you can use Query Store. There you can find queries creating the high DTU usage.
-- Top 10 long running queries
SELECT TOP 10 q.query_id, p.plan_id,
rs.count_executions,
qsqt.query_sql_text,
CONVERT(NUMERIC(10,2), (rs.avg_cpu_time/1000)) as 'avg_cpu_time_seconds',
CONVERT(NUMERIC(10,2),(rs.avg_duration/1000)) as 'avg_duration_seconds',
CONVERT(NUMERIC(10,2),rs.avg_logical_io_reads ) as 'avg_logical_io_reads',
CONVERT(NUMERIC(10,2),rs.avg_logical_io_writes ) as 'avg_logical_io_writes',
CONVERT(NUMERIC(10,2),rs.avg_physical_io_reads ) as 'avg_physical_io_reads',
CONVERT(NUMERIC(10,0),rs.avg_rowcount ) as 'avg_rowcount'
from sys.query_store_query q
JOIN sys.query_store_plan p ON q.query_id = p.query_id
JOIN sys.query_store_runtime_stats rs ON p.plan_id = rs.plan_id
INNER JOIN sys.query_store_query_text qsqt
ON q.query_text_id = qsqt.query_text_id
WHERE rs.last_execution_time > dateadd(hour, -1, getutcdate())
ORDER BY rs.avg_duration DESC