Resilience pipelines
The ResiliencePipeline
allows executing arbitrary user-provided callbacks. It is a combination of one or more resilience strategies.
Usage
The ResiliencePipeline
allow executing various synchronous and asynchronous user-provided callbacks as seen in the examples below:
// Creating a new resilience pipeline
ResiliencePipeline pipeline = new ResiliencePipelineBuilder()
.AddConcurrencyLimiter(100)
.Build();
// Executing an asynchronous void callback
await pipeline.ExecuteAsync(
async token => await MyMethodAsync(token),
cancellationToken);
// Executing a synchronous void callback
pipeline.Execute(() => MyMethod());
// Executing an asynchronous callback that returns a value
await pipeline.ExecuteAsync(
async token => await httpClient.GetAsync(endpoint, token),
cancellationToken);
// Executing an asynchronous callback without allocating a lambda
await pipeline.ExecuteAsync(
static async (state, token) => await state.httpClient.GetAsync(state.endpoint, token),
(httpClient, endpoint), // State provided here
cancellationToken);
// Executing an asynchronous callback and passing custom data
// 1. Retrieve a context from the shared pool
ResilienceContext context = ResilienceContextPool.Shared.Get(cancellationToken);
// 2. Add custom data to the context
context.Properties.Set(new ResiliencePropertyKey<string>("my-custom-data"), "my-custom-data");
// 3. Execute the callback
await pipeline.ExecuteAsync(static async context =>
{
// Retrieve custom data from the context
var customData = context.Properties.GetValue(
new ResiliencePropertyKey<string>("my-custom-data"),
"default-value");
Console.WriteLine("Custom Data: {0}", customData);
await MyMethodAsync(context.CancellationToken);
},
context);
// 4. Optionally, return the context to the shared pool
ResilienceContextPool.Shared.Return(context);
The above samples demonstrate how to use the resilience pipeline within the same scope. Additionally, consider the following:
- Separate the resilience pipeline's definition from its usage. Inject pipelines into the code that will consume them. This facilitates various unit-testing scenarios.
- If your application uses Polly in multiple locations, define all pipelines at startup using
ResiliencePipelineRegistry
or using theAddResiliencePipeline
extension. This is a common approach in .NET Core applications. For example, you could create your own extension method onIServiceCollection
to configure pipelines consumed elsewhere in your application.
public static void ConfigureMyPipelines(IServiceCollection services)
{
services.AddResiliencePipeline("pipeline-A", builder => builder.AddConcurrencyLimiter(100));
services.AddResiliencePipeline("pipeline-B", builder => builder.AddRetry(new()));
// Later, resolve the pipeline by name using ResiliencePipelineProvider<string> or ResiliencePipelineRegistry<string>
var pipelineProvider = services.BuildServiceProvider().GetRequiredService<ResiliencePipelineProvider<string>>();
pipelineProvider.GetPipeline("pipeline-A").Execute(() => { });
}
Empty resilience pipeline
The empty resilience pipeline is a special construct that lacks any resilience strategies. You can access it through the following ways:
ResiliencePipeline.Empty
ResiliencePipeline<T>.Empty
This is particularly useful in test scenarios where implementing resilience strategies could slow down the test execution or over-complicate test setup.
Retrieving execution results with Outcome<T>
The ResiliencePipeline
class provides the ExecuteOutcomeAsync(...)
method, which is designed to never throw exceptions. Instead, it stores either the result or the exception within an Outcome<T>
struct.
// Acquire a ResilienceContext from the pool
ResilienceContext context = ResilienceContextPool.Shared.Get();
// Execute the pipeline and store the result in an Outcome<bool>
Outcome<bool> outcome = await pipeline.ExecuteOutcomeAsync(
static async (context, state) =>
{
Console.WriteLine("State: {0}", state);
try
{
await MyMethodAsync(context.CancellationToken);
// Use static utility methods from Outcome to easily create an Outcome<T> instance
return Outcome.FromResult(true);
}
catch (Exception e)
{
// Create an Outcome<T> instance that holds the exception
return Outcome.FromException<bool>(e);
}
},
context,
"my-state");
// Return the acquired ResilienceContext to the pool
ResilienceContextPool.Shared.Return(context);
// Evaluate the outcome
if (outcome.Exception is not null)
{
Console.WriteLine("Execution Failed: {0}", outcome.Exception.Message);
}
else
{
Console.WriteLine("Execution Result: {0}", outcome.Result);
}
Use ExecuteOutcomeAsync(...)
in high-performance scenarios where you wish to avoid re-throwing exceptions. Keep in mind that Polly's resilience strategies also make use of the Outcome
struct to prevent unnecessary exception throwing.
Context vs State
In the previous example the ExecuteOutcomeAsync
was called with "my-state"
state object. You might wonder what's the point of the state
, or can't we just use the context
?
The state
object was introduced to be able to pass a parameter to the user callback without using a closure.
- It allows you to access any object of the
ExecuteOutcomeAsync
's caller method without any extra memory allocation - It also enables you to use static anonymous methods
So, it is a performance optimization tool. Of course you can pass more complex object than just a simple string like (instance: this, request)
.
While the state
object is accessible only inside the user callback, you can use the context
in many places.
For example in case of Retry the context
is accessible:
- inside the
ShouldHandle
delegate; - inside the
OnRetry
delegate; - inside the
DelayGenerator
delegate; - through the
Outcome
property.
As a rule of thumb:
- Use the
state
object to pass a parameter to your decorated method; - Use the
context
object to exchange information between delegates of an instance ofXYZOptions
or between invocation attempts (in the case of retry or hedging strategies).
Diagrams
Sequence diagram for a pipeline with retry and timeout
Let's create the following pipeline:
- the inner strategy is a timeout,
- the outer is a retry which is timeout-aware.
ResiliencePipeline pipeline = new ResiliencePipelineBuilder()
.AddRetry(new() { ShouldHandle = new PredicateBuilder().Handle<TimeoutRejectedException>() }) // outer
.AddTimeout(TimeSpan.FromSeconds(1)) // inner
.Build();
Let's suppose that the first request takes too long but the second is fast enough.
sequenceDiagram
autonumber
actor C as Caller
participant P as Pipeline
participant R as Retry
participant T as Timeout
participant D as DecoratedUserCallback
C->>P: Calls ExecuteAsync
P->>R: Calls ExecuteCore
R->>T: Calls ExecuteCore
Note over R, D: Initial attempt
Note over T: Wait start
activate T
T->>D: Invokes
activate D
D-->>D: Performs <br/>long-running <br/>operation
Note over T: Wait end
deactivate T
T-->>T: Times out
T->>D: Propagates cancellation
D-->>D: Cancellation of callback
D->>T: Cancellation finished
deactivate D
T->>R: Throws <br/>TimeoutRejectedException
R-->>R: Sleeps
Note over R, D: First retry attempt
R->>T: Calls ExecuteCore
Note over T: Wait start
activate T
T->>D: Invokes
activate D
D-->>D: Performs <br/>long-running <br/>operation
D->>T: Returns result
deactivate D
deactivate T
Note over T: Wait end
T->>R: Returns result
R->>P: Returns result
P->>C: Returns result
Sequence diagram for a pipeline with timeout and retry
Let's create the following pipeline:
- the inner strategy is a retry,
- the outer is a timeout which is overarching all retry attempts.
ResiliencePipeline pipeline = new ResiliencePipelineBuilder()
.AddTimeout(TimeSpan.FromSeconds(10)) // outer
.AddRetry(new()) // inner
.Build();
Let's suppose that the first and the second requests are failing. The third request is not awaited since the overarching timeout elapsed.
sequenceDiagram
autonumber
actor C as Caller
participant P as Pipeline
participant T as Timeout
participant R as Retry
participant D as DecoratedUserCallback
C->>P: Calls ExecuteAsync
P->>T: Calls ExecuteCore
Note over T: Wait start
activate T
T->>R: Calls ExecuteCore
Note over R, D: Initial attempt
R->>D: Invokes
activate D
D-->>D: Performs <br/>operation
D->>R: Fails
deactivate D
R-->>R: Sleeps
Note over R, D: First retry attempt
R->>D: Invokes
activate D
D-->>D: Performs <br/>operation
D->>R: Fails
deactivate D
R-->>R: Sleeps
Note over R, D: Second retry attempt
R->>D: Invokes
activate D
D-->>D: Performs <br/>operation
deactivate T
Note over T: Wait end
T-->>T: Times out
T->>R: Propagates cancellation
R->>D: Propagates cancellation
D-->>D: Cancellation of callback
D->>T: Cancellation finished
deactivate D
T->>P: Throws <br/>TimeoutRejectedException
P->>C: Propagates exception
Sequence diagram for a pipeline with timeout, retry and timeout
Let's create the following pipeline:
- the inner most strategy is a timeout (per attempt),
- the middle one is a retry which is timeout-aware,
- the outer most is a timeout which is overarching all retry attempts.
ResiliencePipeline pipeline = new ResiliencePipelineBuilder()
.AddTimeout(TimeSpan.FromSeconds(10)) // outer most
.AddRetry(new() { ShouldHandle = new PredicateBuilder().Handle<TimeoutRejectedException>() })
.AddTimeout(TimeSpan.FromSeconds(1)) // inner most
.Build();
Let's suppose that the first request fails and the second takes too long. The third request is not awaited since the overarching timeout elapsed.
sequenceDiagram
autonumber
actor C as Caller
participant P as Pipeline
participant TO as TimeoutOuter
participant R as Retry
participant TI as TimeoutInner
participant D as DecoratedUserCallback
C->>P: Calls ExecuteAsync
P->>TO: Calls ExecuteCore
Note over TO: Wait start
activate TO
TO->>R: Calls ExecuteCore
Note over R, D: Initial attempt
R->>TI: Calls ExecuteCore
Note over TI: Wait start
activate TI
TI->>D: Invokes
activate D
D-->>D: Performs <br/>operation
D->>TI: Fails
deactivate D
deactivate TI
Note over TI: Wait end
TI->>R: Propagate failure
R-->>R: Sleeps
Note over R, D: First retry attempt
R->>TI: Calls ExecuteCore
Note over TI: Wait start
activate TI
TI->>D: Invokes
activate D
D-->>D: Performs <br/>operation
TI-->>TI: Times-out
deactivate TI
Note over TI: Wait end
TI->>D: Propagates cancellation
D-->>D: Cancellation of callback
D->>TI: Cancellation finished
deactivate D
TI->>R: Throws <br/>TimeoutRejectedException
R->>R: Sleeps
Note over R, D: Second retry attempt
R->>TI: Calls ExecuteCore
Note over TI: Wait start
activate TI
TI->>D: Invokes
activate D
D-->>D: Performs <br/>operation
TO-->>TO: Times-out
deactivate TO
Note over TO: Wait end
TO->>R: Propagates cancellation
R->>TI: Propagates cancellation
TI->>D: Propagates cancellation
D-->>D: Cancellation of callback
D->>TO: Cancellation finished
deactivate TI
deactivate D
TO->>P: Throws <br/>TimeoutRejectedException
P->>C: Propagates exception