Struct aws_sdk_computeoptimizer::model::lambda_function_recommendation::Builder

pub struct Builder { /* private fields */ }

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: 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 generated.

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

The timestamp of when the function recommendation was last generated.

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: 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: 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 current_performance_risk(self, input: CurrentPerformanceRisk) -> Self

The risk of the current Lambda function not meeting the performance needs of its workloads. The higher the risk, the more likely the current Lambda function requires more memory.

pub fn set_current_performance_risk(
    self,
    input: Option<CurrentPerformanceRisk>
) -> Self

The risk of the current Lambda function not meeting the performance needs of its workloads. The higher the risk, the more likely the current Lambda function requires more memory.

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: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for Builder