orchestrator | MySQL replication topology management and HA | Continuous Deployment library

If I call IDurableOrchestrationClient.TerminateAsync on a running orchestrator that is currently sleeping and waiting on a durable timer created through IDurableOrchestrationContext.CreateTimer, will this result in a graceful shutdown of the entire process including the timer?

The documentation on timers has a very explicit warning regarding graceful cancellation of any timers that didn't activate in the orchestration:

• https://docs.microsoft.com/en-us/azure/azure-functions/durable/durable-functions-timers?tabs=csharp#usage-for-timeout

Warning

Use a CancellationTokenSource (.NET) or call cancel() on the returned TimerTask (JavaScript) to cancel a durable timer if your code will not wait for it to complete. The Durable Task Framework will not change an orchestration's status to "completed" until all outstanding tasks are completed or canceled.

Will calling Terminate respect these restrictions? The documentation on it doesn't make this clear at all.

I have a requirement where I need to "monitor" some instance for some time after it is created, and to stop monitoring it once the instance is deleted.

For now, my application raises EventGrid events on creation and deletion of entities, and I listen to those in my orchestration trigger activity: once a creation event is received, I start the orchestration that monitors that instance. Once the deletion event is received, I send an external event to the orchestrator to signal that it should stop monitoring that instance and terminate. Each creation/deletion pair is handled by its own monitor of course (they are isolated from one another, controlled by an explicit instance ID based on the entity ID).

The orchestrator logic basically fires 2 tasks and waits for the first to finish:

1. A timer, based on data in the created instance. This can be minutes, to months
2. A WaitForExternalEvent that waits until the trigger function notifies of a cancellation

If task 2 wins, I cancel the timer (as per the recommendation), and exit the function. If task 1 wins, I do the processing I need on the instance and ignore the external event.

The orchestrator itself looks something like this:

Running Android Instrumented Tests, the gradle task :app:connectedDebugAndroidTest now prints a red WARNING after a successful test run:

I've been trying to deploy my Azure Durable HTTP Function app to my Azure resource group which I seem to have successfully done, to a degree at least.

When I go to the 'functions' tab and click to get the execution link, it kicks off the HTTP Trigger which calls the Durable Orchestrator which seems to 'schedule' the first Activity method in my Orchestrator, but not even the first line prints which is just a log. It printed ONE time which I found extremely strange as I had only restarted the Function App and ran it again.

There are so many ID's (processId, instanceId, operationId, etc) and so many other interfaces / diagnostic tools that I'm over-inundated with info and don't know how to make heads or tails of what's happening here.

I have App insights hooked up and the CPU will cap out at 100% as if the function app is running but nothing is happening.

Thank you for your help!

I have Windows 10 and had Docker Desktop installed. After they changed terms of commercial use I decided to remove Docker Desktop installation and use just docker engine itself (as I didn't use GUI). I've installed docker on Ubuntu under WSL 2 and it works fine:

My code:

The current IotEdge deployment is missing a crucial component which is a rollback strategy, while searching in the documentation, nothing specifies how we can get the devices to a previous version.

There's 2 options I considered through my journey of searching for a solution, which one would you opt for and how are you handling this situation ?

Use kubernetes to manage IotEdge deployments, which is in my opinion over-engineered and not intended for managing only deployment, as K8s is an orchestrator with many useful components not essentially made for such scenarios (or am I wrong ?).

• Quick
• Centralized configuration
• Can target multiple iothubs

• Over-engineered
• K8s knowledge (learning curve)

The second option is to write custom scripts that handle the deployment/rollback..

• Lightweight solution
• Free (no additional costs)

• Maintenance is hard.
• Slow Build time
• Bug prone

I am trying to run some UI tests using espresso on AS Arctic Fox 2020.3.1 Patch 3 ARM preview. Following Google instructions for setting up these are my dependencies:

Let's say you are using either ServiceFabric or Kubernetes, and you are hosting a transaction data warehouse microservice (maybe a bad example, but suppose all it dose is a simple CQRS architecture consisting of Id of sender, receiver, date and the payment amount, writes and reads into the DB).

For the sake of the argument, if we say that this microservice needs to be replicated among different geographic locations to insure that the data will be recoverable if one database goes down.

Now the naïve approach that I'm thinking is to have an event which gets fired when the transaction is received, and the orchestrator microservice will except to receive event-processed acknowledgment within specific timeframe. But the question stays that what about the database ? what will happen when we will scale out the microservices and a new microservice instances will be raise up? they will write to the same database, no ?

One of solutions can be to put the database within the docker, and let it be owned by each replica, is this a good solution?

Please share your thoughts and best practices.

I have KubernetesClient code running my app on K3s Orchestrator.

I want to understand the difference(use-case) between two K3s APIs PatchNamespacedServiceWithHttpMessagesAsync and ReplaceNamespacedServiceWithHttpMessagesAsync [link to these APIs]. Apart from this link I cant find any place to read about K3s APIs use cases. Please help me here.

PS:

1. Basically I am trying to update the existing Service, so want to understand the difference between above two APIs, either of which I will be calling with updated Patch body (updated service deployment).
   
2. This que is extension of my previous que