Struct aws_sdk_computeoptimizer::model::lambda_function_recommendation::Builder

#[non_exhaustive]
pub struct Builder { /* fields omitted */ }

A builder for LambdaFunctionRecommendation

Implementations

impl Builder

pub fn function_arn(self, input: impl Into<String>) -> Self

The Amazon Resource Name (ARN) of the current function.

pub fn set_function_arn(self, input: Option<String>) -> Self

The Amazon Resource Name (ARN) of the current function.

pub fn function_version(self, input: impl Into<String>) -> Self

The version number of the current function.

pub fn set_function_version(self, input: Option<String>) -> Self

The version number of the current function.

pub fn account_id(self, input: impl Into<String>) -> Self

The Amazon Web Services account ID of the function.

pub fn set_account_id(self, input: Option<String>) -> Self

The Amazon Web Services account ID of the function.

pub fn current_memory_size(self, input: i32) -> Self

The amount of memory, in MB, that's allocated to the current function.

pub fn set_current_memory_size(self, input: Option<i32>) -> Self

The amount of memory, in MB, that's allocated to the current function.

pub fn number_of_invocations(self, input: i64) -> Self

The number of times your function code was applied during the look-back period.

pub fn set_number_of_invocations(self, input: Option<i64>) -> Self

The number of times your function code was applied during the look-back period.

pub fn utilization_metrics(
    self,
    input: impl Into<LambdaFunctionUtilizationMetric>
) -> Self

Appends an item to utilization_metrics.

To override the contents of this collection use set_utilization_metrics.

An array of objects that describe the utilization metrics of the function.

pub fn set_utilization_metrics(
    self,
    input: Option<Vec<LambdaFunctionUtilizationMetric>>
) -> Self

An array of objects that describe the utilization metrics of the function.

pub fn lookback_period_in_days(self, input: f64) -> Self

The number of days for which utilization metrics were analyzed for the function.

pub fn set_lookback_period_in_days(self, input: Option<f64>) -> Self

The number of days for which utilization metrics were analyzed for the function.

pub fn last_refresh_timestamp(self, input: DateTime) -> Self

The timestamp of when the function recommendation was last refreshed.

pub fn set_last_refresh_timestamp(self, input: Option<DateTime>) -> Self

The timestamp of when the function recommendation was last refreshed.

pub fn finding(self, input: LambdaFunctionRecommendationFinding) -> Self

The finding classification of the function.

Findings for functions include:

• Optimized — The function is correctly provisioned to run your workload based on its current configuration and its utilization history. This finding classification does not include finding reason codes.

• NotOptimized — The function is performing at a higher level (over-provisioned) or at a lower level (under-provisioned) than required for your workload because its current configuration is not optimal. Over-provisioned resources might lead to unnecessary infrastructure cost, and under-provisioned resources might lead to poor application performance. This finding classification can include the MemoryUnderprovisioned and MemoryUnderprovisioned finding reason codes.

• Unavailable — Compute Optimizer was unable to generate a recommendation for the function. This could be because the function has not accumulated sufficient metric data, or the function does not qualify for a recommendation. This finding classification can include the InsufficientData and Inconclusive finding reason codes.

  Functions with a finding of unavailable are not returned unless you specify the filter parameter with a value of Unavailable in your GetLambdaFunctionRecommendations request.

pub fn set_finding(
    self,
    input: Option<LambdaFunctionRecommendationFinding>
) -> Self

The finding classification of the function.

Findings for functions include:

• Optimized — The function is correctly provisioned to run your workload based on its current configuration and its utilization history. This finding classification does not include finding reason codes.

• NotOptimized — The function is performing at a higher level (over-provisioned) or at a lower level (under-provisioned) than required for your workload because its current configuration is not optimal. Over-provisioned resources might lead to unnecessary infrastructure cost, and under-provisioned resources might lead to poor application performance. This finding classification can include the MemoryUnderprovisioned and MemoryUnderprovisioned finding reason codes.

• Unavailable — Compute Optimizer was unable to generate a recommendation for the function. This could be because the function has not accumulated sufficient metric data, or the function does not qualify for a recommendation. This finding classification can include the InsufficientData and Inconclusive finding reason codes.

  Functions with a finding of unavailable are not returned unless you specify the filter parameter with a value of Unavailable in your GetLambdaFunctionRecommendations request.

pub fn finding_reason_codes(
    self,
    input: impl Into<LambdaFunctionRecommendationFindingReasonCode>
) -> Self

Appends an item to finding_reason_codes.

To override the contents of this collection use set_finding_reason_codes.

The reason for the finding classification of the function.

Functions that have a finding classification of Optimized don't have a finding reason code.

Finding reason codes for functions include:

• MemoryOverprovisioned — The function is over-provisioned when its memory configuration can be sized down while still meeting the performance requirements of your workload. An over-provisioned function might lead to unnecessary infrastructure cost. This finding reason code is part of the NotOptimized finding classification.

• MemoryUnderprovisioned — The function is under-provisioned when its memory configuration doesn't meet the performance requirements of the workload. An under-provisioned function might lead to poor application performance. This finding reason code is part of the NotOptimized finding classification.

• InsufficientData — The function does not have sufficient metric data for Compute Optimizer to generate a recommendation. For more information, see the Supported resources and requirements in the Compute Optimizer User Guide. This finding reason code is part of the Unavailable finding classification.

• Inconclusive — The function does not qualify for a recommendation because Compute Optimizer cannot generate a recommendation with a high degree of confidence. This finding reason code is part of the Unavailable finding classification.

pub fn set_finding_reason_codes(
    self,
    input: Option<Vec<LambdaFunctionRecommendationFindingReasonCode>>
) -> Self

The reason for the finding classification of the function.

Functions that have a finding classification of Optimized don't have a finding reason code.

Finding reason codes for functions include:

• MemoryOverprovisioned — The function is over-provisioned when its memory configuration can be sized down while still meeting the performance requirements of your workload. An over-provisioned function might lead to unnecessary infrastructure cost. This finding reason code is part of the NotOptimized finding classification.

• MemoryUnderprovisioned — The function is under-provisioned when its memory configuration doesn't meet the performance requirements of the workload. An under-provisioned function might lead to poor application performance. This finding reason code is part of the NotOptimized finding classification.

• InsufficientData — The function does not have sufficient metric data for Compute Optimizer to generate a recommendation. For more information, see the Supported resources and requirements in the Compute Optimizer User Guide. This finding reason code is part of the Unavailable finding classification.

• Inconclusive — The function does not qualify for a recommendation because Compute Optimizer cannot generate a recommendation with a high degree of confidence. This finding reason code is part of the Unavailable finding classification.

pub fn memory_size_recommendation_options(
    self,
    input: impl Into<LambdaFunctionMemoryRecommendationOption>
) -> Self

Appends an item to memory_size_recommendation_options.

To override the contents of this collection use set_memory_size_recommendation_options.

An array of objects that describe the memory configuration recommendation options for the function.

pub fn set_memory_size_recommendation_options(
    self,
    input: Option<Vec<LambdaFunctionMemoryRecommendationOption>>
) -> Self

An array of objects that describe the memory configuration recommendation options for the function.

pub fn build(self) -> LambdaFunctionRecommendation

Consumes the builder and constructs a LambdaFunctionRecommendation

Trait Implementations

impl Clone for Builder

fn clone(&self) -> Builder

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Builder

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for Builder

fn default() -> Builder

Returns the “default value” for a type.

impl PartialEq<Builder> for Builder

fn eq(&self, other: &Builder) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Builder) -> bool

This method tests for !=.

impl StructuralPartialEq for Builder