Class CfnTransformer

Creates or updates a log transformer for a single log group.

Inheritance

object

CfnElement

CfnRefElement

CfnResource

CfnTransformer

Implements

IInspectable

Inherited Members

CfnResource.IsCfnResource(object)

CfnResource.AddDeletionOverride(string)

CfnResource.AddDependency(CfnResource)

CfnResource.AddDependsOn(CfnResource)

CfnResource.AddMetadata(string, object)

CfnResource.AddOverride(string, object)

CfnResource.AddPropertyDeletionOverride(string)

CfnResource.AddPropertyOverride(string, object)

CfnResource.ApplyRemovalPolicy(RemovalPolicy?, IRemovalPolicyOptions)

CfnResource.GetAtt(string, ResolutionTypeHint?)

CfnResource.GetMetadata(string)

CfnResource.ObtainDependencies()

CfnResource.ObtainResourceDependencies()

CfnResource.RemoveDependency(CfnResource)

CfnResource.ReplaceDependency(CfnResource, CfnResource)

CfnResource.ShouldSynthesize()

CfnResource.ToString()

CfnResource.ValidateProperties(object)

CfnResource.CfnOptions

CfnResource.CfnResourceType

CfnResource.UpdatedProperites

CfnResource.UpdatedProperties

CfnRefElement.Ref

CfnElement.IsCfnElement(object)

CfnElement.OverrideLogicalId(string)

CfnElement.CreationStack

CfnElement.LogicalId

CfnElement.Stack

Namespace: Amazon.CDK.AWS.Logs

Assembly: Amazon.CDK.Lib.dll

Syntax (csharp)

public class CfnTransformer : CfnResource, IInspectable

Syntax (vb)

Public Class CfnTransformer Inherits CfnResource Implements IInspectable

Remarks

You use log transformers to transform log events into a different format, making them easier for you to process and analyze. You can also transform logs from different sources into standardized formats that contains relevant, source-specific information.

After you have created a transformer, CloudWatch Logs performs the transformations at the time of log ingestion. You can then refer to the transformed versions of the logs during operations such as querying with CloudWatch Logs Insights or creating metric filters or subscription filers.

You can also use a transformer to copy metadata from metadata keys into the log events themselves. This metadata can include log group name, log stream name, account ID and Region.

A transformer for a log group is a series of processors, where each processor applies one type of transformation to the log events ingested into this log group. The processors work one after another, in the order that you list them, like a pipeline. For more information about the available processors to use in a transformer, see Processors that you can use .

Having log events in standardized format enables visibility across your applications for your log analysis, reporting, and alarming needs. CloudWatch Logs provides transformation for common log types with out-of-the-box transformation templates for major AWS log sources such as VPC flow logs, Lambda, and Amazon RDS. You can use pre-built transformation templates or create custom transformation policies.

You can create transformers only for the log groups in the Standard log class.

You can also set up a transformer at the account level. For more information, see PutAccountPolicy . If there is both a log-group level transformer created with PutTransformer and an account-level transformer that could apply to the same log group, the log group uses only the log-group level transformer. It ignores the account-level transformer.

See: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-logs-transformer.html

CloudformationResource: AWS::Logs::Transformer

ExampleMetadata: fixture=_generated

Examples

// The code below shows an example of how to instantiate this type.
             // The values are placeholders you should change.
             using Amazon.CDK.AWS.Logs;

             var cfnTransformer = new CfnTransformer(this, "MyCfnTransformer", new CfnTransformerProps {
                 LogGroupIdentifier = "logGroupIdentifier",
                 TransformerConfig = new [] { new ProcessorProperty {
                     AddKeys = new AddKeysProperty {
                         Entries = new [] { new AddKeyEntryProperty {
                             Key = "key",
                             Value = "value",

                             // the properties below are optional
                             OverwriteIfExists = false
                         } }
                     },
                     CopyValue = new CopyValueProperty {
                         Entries = new [] { new CopyValueEntryProperty {
                             Source = "source",
                             Target = "target",

                             // the properties below are optional
                             OverwriteIfExists = false
                         } }
                     },
                     Csv = new CsvProperty {
                         Columns = new [] { "columns" },
                         Delimiter = "delimiter",
                         QuoteCharacter = "quoteCharacter",
                         Source = "source"
                     },
                     DateTimeConverter = new DateTimeConverterProperty {
                         MatchPatterns = new [] { "matchPatterns" },
                         Source = "source",
                         Target = "target",

                         // the properties below are optional
                         Locale = "locale",
                         SourceTimezone = "sourceTimezone",
                         TargetFormat = "targetFormat",
                         TargetTimezone = "targetTimezone"
                     },
                     DeleteKeys = new DeleteKeysProperty {
                         WithKeys = new [] { "withKeys" }
                     },
                     Grok = new GrokProperty {
                         Match = "match",

                         // the properties below are optional
                         Source = "source"
                     },
                     ListToMap = new ListToMapProperty {
                         Key = "key",
                         Source = "source",

                         // the properties below are optional
                         Flatten = false,
                         FlattenedElement = "flattenedElement",
                         Target = "target",
                         ValueKey = "valueKey"
                     },
                     LowerCaseString = new LowerCaseStringProperty {
                         WithKeys = new [] { "withKeys" }
                     },
                     MoveKeys = new MoveKeysProperty {
                         Entries = new [] { new MoveKeyEntryProperty {
                             Source = "source",
                             Target = "target",

                             // the properties below are optional
                             OverwriteIfExists = false
                         } }
                     },
                     ParseCloudfront = new ParseCloudfrontProperty {
                         Source = "source"
                     },
                     ParseJson = new ParseJSONProperty {
                         Destination = "destination",
                         Source = "source"
                     },
                     ParseKeyValue = new ParseKeyValueProperty {
                         Destination = "destination",
                         FieldDelimiter = "fieldDelimiter",
                         KeyPrefix = "keyPrefix",
                         KeyValueDelimiter = "keyValueDelimiter",
                         NonMatchValue = "nonMatchValue",
                         OverwriteIfExists = false,
                         Source = "source"
                     },
                     ParsePostgres = new ParsePostgresProperty {
                         Source = "source"
                     },
                     ParseRoute53 = new ParseRoute53Property {
                         Source = "source"
                     },
                     ParseToOcsf = new ParseToOCSFProperty {
                         EventSource = "eventSource",
                         OcsfVersion = "ocsfVersion",

                         // the properties below are optional
                         Source = "source"
                     },
                     ParseVpc = new ParseVPCProperty {
                         Source = "source"
                     },
                     ParseWaf = new ParseWAFProperty {
                         Source = "source"
                     },
                     RenameKeys = new RenameKeysProperty {
                         Entries = new [] { new RenameKeyEntryProperty {
                             Key = "key",
                             RenameTo = "renameTo",

                             // the properties below are optional
                             OverwriteIfExists = false
                         } }
                     },
                     SplitString = new SplitStringProperty {
                         Entries = new [] { new SplitStringEntryProperty {
                             Delimiter = "delimiter",
                             Source = "source"
                         } }
                     },
                     SubstituteString = new SubstituteStringProperty {
                         Entries = new [] { new SubstituteStringEntryProperty {
                             From = "from",
                             Source = "source",
                             To = "to"
                         } }
                     },
                     TrimString = new TrimStringProperty {
                         WithKeys = new [] { "withKeys" }
                     },
                     TypeConverter = new TypeConverterProperty {
                         Entries = new [] { new TypeConverterEntryProperty {
                             Key = "key",
                             Type = "type"
                         } }
                     },
                     UpperCaseString = new UpperCaseStringProperty {
                         WithKeys = new [] { "withKeys" }
                     }
                 } }
             });

Synopsis

Constructors

CfnTransformer(Construct, string, ICfnTransformerProps)

Creates or updates a log transformer for a single log group.

Properties

CFN_RESOURCE_TYPE_NAME	The CloudFormation resource type name for this resource class.
CfnProperties	Creates or updates a log transformer for a single log group.
LogGroupIdentifier	Specify either the name or ARN of the log group to create the transformer for.
TransformerConfig	This structure is an array that contains the configuration of this log transformer.

Methods

Inspect(TreeInspector)	Examines the CloudFormation resource and discloses attributes.
RenderProperties(IDictionary<string, object>)	Creates or updates a log transformer for a single log group.

Constructors

CfnTransformer(Construct, string, ICfnTransformerProps)

Creates or updates a log transformer for a single log group.

public CfnTransformer(Construct scope, string id, ICfnTransformerProps props)

Parameters

scope Construct

Scope in which this resource is defined.

id string

Construct identifier for this resource (unique in its scope).

props ICfnTransformerProps

Resource properties.

Remarks

You use log transformers to transform log events into a different format, making them easier for you to process and analyze. You can also transform logs from different sources into standardized formats that contains relevant, source-specific information.

After you have created a transformer, CloudWatch Logs performs the transformations at the time of log ingestion. You can then refer to the transformed versions of the logs during operations such as querying with CloudWatch Logs Insights or creating metric filters or subscription filers.

You can also use a transformer to copy metadata from metadata keys into the log events themselves. This metadata can include log group name, log stream name, account ID and Region.

A transformer for a log group is a series of processors, where each processor applies one type of transformation to the log events ingested into this log group. The processors work one after another, in the order that you list them, like a pipeline. For more information about the available processors to use in a transformer, see Processors that you can use .

Having log events in standardized format enables visibility across your applications for your log analysis, reporting, and alarming needs. CloudWatch Logs provides transformation for common log types with out-of-the-box transformation templates for major AWS log sources such as VPC flow logs, Lambda, and Amazon RDS. You can use pre-built transformation templates or create custom transformation policies.

You can create transformers only for the log groups in the Standard log class.

You can also set up a transformer at the account level. For more information, see PutAccountPolicy . If there is both a log-group level transformer created with PutTransformer and an account-level transformer that could apply to the same log group, the log group uses only the log-group level transformer. It ignores the account-level transformer.

See: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-logs-transformer.html

CloudformationResource: AWS::Logs::Transformer

ExampleMetadata: fixture=_generated

Properties

CFN_RESOURCE_TYPE_NAME

The CloudFormation resource type name for this resource class.

public static string CFN_RESOURCE_TYPE_NAME { get; }

Property Value

string

Remarks

You use log transformers to transform log events into a different format, making them easier for you to process and analyze. You can also transform logs from different sources into standardized formats that contains relevant, source-specific information.

After you have created a transformer, CloudWatch Logs performs the transformations at the time of log ingestion. You can then refer to the transformed versions of the logs during operations such as querying with CloudWatch Logs Insights or creating metric filters or subscription filers.

You can also use a transformer to copy metadata from metadata keys into the log events themselves. This metadata can include log group name, log stream name, account ID and Region.

A transformer for a log group is a series of processors, where each processor applies one type of transformation to the log events ingested into this log group. The processors work one after another, in the order that you list them, like a pipeline. For more information about the available processors to use in a transformer, see Processors that you can use .

Having log events in standardized format enables visibility across your applications for your log analysis, reporting, and alarming needs. CloudWatch Logs provides transformation for common log types with out-of-the-box transformation templates for major AWS log sources such as VPC flow logs, Lambda, and Amazon RDS. You can use pre-built transformation templates or create custom transformation policies.

You can create transformers only for the log groups in the Standard log class.

You can also set up a transformer at the account level. For more information, see PutAccountPolicy . If there is both a log-group level transformer created with PutTransformer and an account-level transformer that could apply to the same log group, the log group uses only the log-group level transformer. It ignores the account-level transformer.

See: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-logs-transformer.html

CloudformationResource: AWS::Logs::Transformer

ExampleMetadata: fixture=_generated

CfnProperties

Creates or updates a log transformer for a single log group.

protected override IDictionary<string, object> CfnProperties { get; }

Property Value

IDictionary<string, object>

Overrides

CfnResource.CfnProperties

Remarks

You use log transformers to transform log events into a different format, making them easier for you to process and analyze. You can also transform logs from different sources into standardized formats that contains relevant, source-specific information.

After you have created a transformer, CloudWatch Logs performs the transformations at the time of log ingestion. You can then refer to the transformed versions of the logs during operations such as querying with CloudWatch Logs Insights or creating metric filters or subscription filers.

You can also use a transformer to copy metadata from metadata keys into the log events themselves. This metadata can include log group name, log stream name, account ID and Region.

A transformer for a log group is a series of processors, where each processor applies one type of transformation to the log events ingested into this log group. The processors work one after another, in the order that you list them, like a pipeline. For more information about the available processors to use in a transformer, see Processors that you can use .

Having log events in standardized format enables visibility across your applications for your log analysis, reporting, and alarming needs. CloudWatch Logs provides transformation for common log types with out-of-the-box transformation templates for major AWS log sources such as VPC flow logs, Lambda, and Amazon RDS. You can use pre-built transformation templates or create custom transformation policies.

You can create transformers only for the log groups in the Standard log class.

You can also set up a transformer at the account level. For more information, see PutAccountPolicy . If there is both a log-group level transformer created with PutTransformer and an account-level transformer that could apply to the same log group, the log group uses only the log-group level transformer. It ignores the account-level transformer.

See: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-logs-transformer.html

CloudformationResource: AWS::Logs::Transformer

ExampleMetadata: fixture=_generated

LogGroupIdentifier

Specify either the name or ARN of the log group to create the transformer for.

public virtual string LogGroupIdentifier { get; set; }

Property Value

string

Remarks

You use log transformers to transform log events into a different format, making them easier for you to process and analyze. You can also transform logs from different sources into standardized formats that contains relevant, source-specific information.

After you have created a transformer, CloudWatch Logs performs the transformations at the time of log ingestion. You can then refer to the transformed versions of the logs during operations such as querying with CloudWatch Logs Insights or creating metric filters or subscription filers.

You can also use a transformer to copy metadata from metadata keys into the log events themselves. This metadata can include log group name, log stream name, account ID and Region.

A transformer for a log group is a series of processors, where each processor applies one type of transformation to the log events ingested into this log group. The processors work one after another, in the order that you list them, like a pipeline. For more information about the available processors to use in a transformer, see Processors that you can use .

Having log events in standardized format enables visibility across your applications for your log analysis, reporting, and alarming needs. CloudWatch Logs provides transformation for common log types with out-of-the-box transformation templates for major AWS log sources such as VPC flow logs, Lambda, and Amazon RDS. You can use pre-built transformation templates or create custom transformation policies.

You can create transformers only for the log groups in the Standard log class.

You can also set up a transformer at the account level. For more information, see PutAccountPolicy . If there is both a log-group level transformer created with PutTransformer and an account-level transformer that could apply to the same log group, the log group uses only the log-group level transformer. It ignores the account-level transformer.

See: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-logs-transformer.html

CloudformationResource: AWS::Logs::Transformer

ExampleMetadata: fixture=_generated

TransformerConfig

This structure is an array that contains the configuration of this log transformer.

public virtual object TransformerConfig { get; set; }

Property Value

object

Remarks

You use log transformers to transform log events into a different format, making them easier for you to process and analyze. You can also transform logs from different sources into standardized formats that contains relevant, source-specific information.

After you have created a transformer, CloudWatch Logs performs the transformations at the time of log ingestion. You can then refer to the transformed versions of the logs during operations such as querying with CloudWatch Logs Insights or creating metric filters or subscription filers.

You can also use a transformer to copy metadata from metadata keys into the log events themselves. This metadata can include log group name, log stream name, account ID and Region.

A transformer for a log group is a series of processors, where each processor applies one type of transformation to the log events ingested into this log group. The processors work one after another, in the order that you list them, like a pipeline. For more information about the available processors to use in a transformer, see Processors that you can use .

Having log events in standardized format enables visibility across your applications for your log analysis, reporting, and alarming needs. CloudWatch Logs provides transformation for common log types with out-of-the-box transformation templates for major AWS log sources such as VPC flow logs, Lambda, and Amazon RDS. You can use pre-built transformation templates or create custom transformation policies.

You can create transformers only for the log groups in the Standard log class.

You can also set up a transformer at the account level. For more information, see PutAccountPolicy . If there is both a log-group level transformer created with PutTransformer and an account-level transformer that could apply to the same log group, the log group uses only the log-group level transformer. It ignores the account-level transformer.

See: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-logs-transformer.html

CloudformationResource: AWS::Logs::Transformer

ExampleMetadata: fixture=_generated

Methods

Inspect(TreeInspector)

Examines the CloudFormation resource and discloses attributes.

public virtual void Inspect(TreeInspector inspector)

Parameters

inspector TreeInspector

tree inspector to collect and process attributes.

Remarks

You use log transformers to transform log events into a different format, making them easier for you to process and analyze. You can also transform logs from different sources into standardized formats that contains relevant, source-specific information.

After you have created a transformer, CloudWatch Logs performs the transformations at the time of log ingestion. You can then refer to the transformed versions of the logs during operations such as querying with CloudWatch Logs Insights or creating metric filters or subscription filers.

You can also use a transformer to copy metadata from metadata keys into the log events themselves. This metadata can include log group name, log stream name, account ID and Region.

A transformer for a log group is a series of processors, where each processor applies one type of transformation to the log events ingested into this log group. The processors work one after another, in the order that you list them, like a pipeline. For more information about the available processors to use in a transformer, see Processors that you can use .

Having log events in standardized format enables visibility across your applications for your log analysis, reporting, and alarming needs. CloudWatch Logs provides transformation for common log types with out-of-the-box transformation templates for major AWS log sources such as VPC flow logs, Lambda, and Amazon RDS. You can use pre-built transformation templates or create custom transformation policies.

You can create transformers only for the log groups in the Standard log class.

You can also set up a transformer at the account level. For more information, see PutAccountPolicy . If there is both a log-group level transformer created with PutTransformer and an account-level transformer that could apply to the same log group, the log group uses only the log-group level transformer. It ignores the account-level transformer.

See: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-logs-transformer.html

CloudformationResource: AWS::Logs::Transformer

ExampleMetadata: fixture=_generated

RenderProperties(IDictionary<string, object>)

Creates or updates a log transformer for a single log group.

protected override IDictionary<string, object> RenderProperties(IDictionary<string, object> props)

Parameters

props IDictionary<string, object>

Returns

IDictionary<string, object>

Overrides

CfnResource.RenderProperties(IDictionary<string, object>)

Remarks

You use log transformers to transform log events into a different format, making them easier for you to process and analyze. You can also transform logs from different sources into standardized formats that contains relevant, source-specific information.

After you have created a transformer, CloudWatch Logs performs the transformations at the time of log ingestion. You can then refer to the transformed versions of the logs during operations such as querying with CloudWatch Logs Insights or creating metric filters or subscription filers.

You can also use a transformer to copy metadata from metadata keys into the log events themselves. This metadata can include log group name, log stream name, account ID and Region.

A transformer for a log group is a series of processors, where each processor applies one type of transformation to the log events ingested into this log group. The processors work one after another, in the order that you list them, like a pipeline. For more information about the available processors to use in a transformer, see Processors that you can use .

Having log events in standardized format enables visibility across your applications for your log analysis, reporting, and alarming needs. CloudWatch Logs provides transformation for common log types with out-of-the-box transformation templates for major AWS log sources such as VPC flow logs, Lambda, and Amazon RDS. You can use pre-built transformation templates or create custom transformation policies.

You can create transformers only for the log groups in the Standard log class.

You can also set up a transformer at the account level. For more information, see PutAccountPolicy . If there is both a log-group level transformer created with PutTransformer and an account-level transformer that could apply to the same log group, the log group uses only the log-group level transformer. It ignores the account-level transformer.

See: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-logs-transformer.html

CloudformationResource: AWS::Logs::Transformer

ExampleMetadata: fixture=_generated

Implements

IInspectable