I wonder if it's possible in azure devOps to get the following work:
The user run a pipeline and enter 3 Macro-Variables: startDate, startTime, duration.
Based on the macro-variables, a pipeline-job should be scheduled to do something (e.g. a pipeline which set webpage in maintenance mode.
Or is the better way to solve this, to immediately run a pipeline, which create a scheduled command (e.g. via at on linux-bash) that will be executed in the future?
Related
My pipelines activities need the date of the run as a parameter. Now I get the current date in the pipeline from the utcnow() function. Ideally this would be something I could enter dynamically in the trigger so I could rerun a failed day and the parameter would be set right, now a rerun would lead to my pipeline being rerun but with the date of today not the failed run date.
I am used to airflow where such things are pretty easy to do, including scheduling reruns. Probably I think too much in terms of airflow but I can't wrap my head around a better solution.
In ADF,it is not supported directly to pass trigger date at which pipeline got failed to trigger.
You can get the trigger time using #pipeline().TriggerTime .
This system variable will give the time at which the trigger triggers the pipeline to run.
You can store this trigger value for every pipeline and use this as a parameter for the trigger which got failed and rerun the pipeline.
Reference: Microsoft document on System Variables on ADF
To resolve my problem I had to create a nested structure of pipelines, the top pipeline setting a variable for the date and then calling other pipelines passing that variable.
With this I still can't rerun the top pipeline but rerunning Execute Pipeline1/2/3 reruns them with the right variable set. It is still not perfect since the top pipeline run stays an error and it is difficult to keep track of what needs to be rerun, however it is a partial solution.
I have a configuration file for the Azure pipeline that is scheduled through the UI to run Mon to Fri. The file has different stages and each stage calls a different template. What I want to do is run different stages/templates in different days of the week.
I tried to save different schedules through the triggers UI, but they need to be applied to the entire file.
I was also reading this https://learn.microsoft.com/en-us/azure/devops/pipelines/process/scheduled-triggers?view=azure-devops&tabs=yaml but again, the schedule would be applied to the entire file.
Is there a way to apply a different schedule to each step?
No, there is an "out-of-box" way to do that. I think you may try to:
Divide your build into several and schedule them separately.
Or
Add a planning step that detects the day and sets an execution step variable like:
echo "##vso[task.setvariable variable=run.step1;]YES"
Set variables in scripts
Then use it in the conditions:
and(succeeded(), ne(variables['run.step1'], 'YES'))
Specify conditions
I have a requirement to incrementally copy data from one SQL table to another SQL table. The watermark or key column is an Identity column. My boss wants me to restart the load as soon as it's done...and as you know, the completion time may vary. In Azure Data Factory, the trigger options are Scheduled, Tumbling Window and Custom Event. Does anyone know which option would allow me to achieve this continuous running of the pipeline and how to configure it?
Create a new pipeline. Call it "run forever". Add an "until" activity with a never-true condition e.g. #equals(1, 2).
Inside the until execute the pipeline which copies between tables. Ensure "wait for completion" is ticked.
If the table copy fails then "run forever" will fail and will have to be manually re-started. You likely do not want "run forever" to be scheduled as the scheduled invocations will queue should it, in fact, not fail.
Pipeline in ADF are batch-based. You can set "micro batches" of 1 min with schedule trigger or 5 mins with tumbling window.
ADF will run in a batch. If you want to continuously load the data then you can go for Stream Analytics / Event Hub which would load real-time data
I need help with implementation for below requirement:
There is one ADF pipeline that runs every two hours (with Tumbling window trigger), now i need to create one more pipeline that will be used for performing maintenance job . This pipeline is scheduled to run once a month (with schedule trigger). Here is the requirement that i'm trying to implement:
Now before running the second pipeline i need to make sure the first pipeline is not running (basically get the status and if its running wait for its completion) and then disable the trigger associated with it.
Run the second pipeline and after its completion , enable the trigger that is associated with first pipeline
Please let me know if this can be achieved within ADF or some kind of custom scripting needed to achieve the result.
First, your idea is achievable.
Second, if you want to use built-in feature in Azure Datafactory, then there is no way.
Basically, you need to use azure function(simple httptrigger, dont give any input, then you can hit and execute it directly.) to achieve your requirement that ADF can't do. From your description, the executing of these two pipelines are mutually exclusive, so you can use sdk to check to status of another pipeline in azure function. If another pipeline is running, then wait a few seconds then re-check the status of another pipeline.(In short, put the main logic and code in the azure function.)
Simple azure function:
https://learn.microsoft.com/en-us/azure/azure-functions/functions-bindings-http-webhook-trigger?tabs=csharp
Use SDK to monitor:
https://learn.microsoft.com/en-us/azure/data-factory/monitor-programmatically#net
(The link I give is C#, you can choose other supported language.)
There is a solution if i want to run those piplines in the same time instead of doing it for each pipline
Just add a trigger at same time for all of your pipelines.
In the ADF portal:
Set the same time for trigger configuration:
If you want to execute them in the queue,you could use execute pipeline activity which allows you to invoke another pipeline.
You could also leverage the lookup activity to lookup the pipeline using meta data or a pipeline parameter table and then use the set the for each loop to parallel processing so that it will process upto 50 pipelines at once.
See ForEach Article for more info: https://learn.microsoft.com/en-us/azure/data-factory/control-flow-for-each-activity#parallel-execution