Viewing docs for MongoDB Atlas v4.18.1
published on Tuesday, Oct 27, 2026 by Pulumi
published on Tuesday, Oct 27, 2026 by Pulumi
Viewing docs for MongoDB Atlas v4.18.1
published on Tuesday, Oct 27, 2026 by Pulumi
published on Tuesday, Oct 27, 2026 by Pulumi
mongodbatlas.getStreamProcessors returns all stream processors in a stream instance.
Example Usage
S
import * as pulumi from "@pulumi/pulumi";
import * as mongodbatlas from "@pulumi/mongodbatlas";
const example = new mongodbatlas.StreamInstance("example", {
projectId: projectId,
instanceName: "InstanceName",
dataProcessRegion: {
region: "VIRGINIA_USA",
cloudProvider: "AWS",
},
});
const example_sample = new mongodbatlas.StreamConnection("example-sample", {
projectId: projectId,
workspaceName: example.instanceName,
connectionName: "sample_stream_solar",
type: "Sample",
});
const example_cluster = new mongodbatlas.StreamConnection("example-cluster", {
projectId: projectId,
workspaceName: example.instanceName,
connectionName: "ClusterConnection",
type: "Cluster",
clusterName: clusterName,
dbRoleToExecute: {
role: "atlasAdmin",
type: "BUILT_IN",
},
});
const example_kafka = new mongodbatlas.StreamConnection("example-kafka", {
projectId: projectId,
workspaceName: example.instanceName,
connectionName: "KafkaPlaintextConnection",
type: "Kafka",
authentication: {
mechanism: "PLAIN",
username: kafkaUsername,
password: kafkaPassword,
},
bootstrapServers: "example.com:9092",
config: {
"auto.offset.reset": "earliest",
},
security: {
protocol: "SASL_PLAINTEXT",
},
});
const stream_processor_sample_example = new mongodbatlas.StreamProcessor("stream-processor-sample-example", {
projectId: projectId,
workspaceName: example.instanceName,
processorName: "sampleProcessorName",
pipeline: pulumi.interpolate`[
{\"$source\": {\"connectionName\": \"${example_sample.connectionName}\"}},
{\"$emit\": {\"connectionName\": \"${example_cluster.connectionName}\", \"db\": \"sample\", \"coll\": \"solar\", \"timeseries\": {\"timeField\": \"_ts\"}}}
]
`,
state: "STARTED",
tier: "SP30",
});
const stream_processor_cluster_to_kafka_example = new mongodbatlas.StreamProcessor("stream-processor-cluster-to-kafka-example", {
projectId: projectId,
workspaceName: example.instanceName,
processorName: "clusterProcessorName",
pipeline: pulumi.interpolate`[
{\"$source\": {\"connectionName\": \"${example_cluster.connectionName}\"}},
{\"$emit\": {\"connectionName\": \"${example_kafka.connectionName}\", \"topic\": \"topic_from_cluster\"}}
]
`,
state: "CREATED",
});
const stream_processor_kafka_to_cluster_example = new mongodbatlas.StreamProcessor("stream-processor-kafka-to-cluster-example", {
projectId: projectId,
workspaceName: example.instanceName,
processorName: "kafkaProcessorName",
pipeline: pulumi.interpolate`[
{\"$source\": {\"connectionName\": \"${example_kafka.connectionName}\", \"topic\": \"topic_source\"}},
{\"$emit\": {\"connectionName\": \"${example_cluster.connectionName}\", \"db\": \"kafka\", \"coll\": \"topic_source\", \"timeseries\": {\"timeField\": \"ts\"}}}
]
`,
state: "CREATED",
tier: "SP10",
options: {
dlq: {
coll: "exampleColumn",
connectionName: example_cluster.connectionName,
db: "exampleDb",
},
autoscaling: {
minTier: "SP10",
maxTier: "SP50",
},
},
});
const example_stream_processors = mongodbatlas.getStreamProcessorsOutput({
projectId: projectId,
workspaceName: example.instanceName,
});
const example_stream_processor = mongodbatlas.getStreamProcessorOutput({
projectId: projectId,
workspaceName: example.instanceName,
processorName: stream_processor_sample_example.processorName,
});
export const streamProcessorsState = example_stream_processor.state;
export const streamProcessorsResults = example_stream_processors.apply(example_stream_processors => example_stream_processors.results);
import pulumi
import pulumi_mongodbatlas as mongodbatlas
example = mongodbatlas.StreamInstance("example",
project_id=project_id,
instance_name="InstanceName",
data_process_region={
"region": "VIRGINIA_USA",
"cloud_provider": "AWS",
})
example_sample = mongodbatlas.StreamConnection("example-sample",
project_id=project_id,
workspace_name=example.instance_name,
connection_name="sample_stream_solar",
type="Sample")
example_cluster = mongodbatlas.StreamConnection("example-cluster",
project_id=project_id,
workspace_name=example.instance_name,
connection_name="ClusterConnection",
type="Cluster",
cluster_name=cluster_name,
db_role_to_execute={
"role": "atlasAdmin",
"type": "BUILT_IN",
})
example_kafka = mongodbatlas.StreamConnection("example-kafka",
project_id=project_id,
workspace_name=example.instance_name,
connection_name="KafkaPlaintextConnection",
type="Kafka",
authentication={
"mechanism": "PLAIN",
"username": kafka_username,
"password": kafka_password,
},
bootstrap_servers="example.com:9092",
config={
"auto.offset.reset": "earliest",
},
security={
"protocol": "SASL_PLAINTEXT",
})
stream_processor_sample_example = mongodbatlas.StreamProcessor("stream-processor-sample-example",
project_id=project_id,
workspace_name=example.instance_name,
processor_name="sampleProcessorName",
pipeline=pulumi.Output.all(
example-sampleConnection_name=example_sample.connection_name,
example-clusterConnection_name=example_cluster.connection_name
).apply(lambda resolved_outputs: f"""[
{{\"$source\": {{\"connectionName\": \"{resolved_outputs['example-sampleConnection_name']}\"}}}},
{{\"$emit\": {{\"connectionName\": \"{resolved_outputs['example-clusterConnection_name']}\", \"db\": \"sample\", \"coll\": \"solar\", \"timeseries\": {{\"timeField\": \"_ts\"}}}}}}
]
""")
,
state="STARTED",
tier="SP30")
stream_processor_cluster_to_kafka_example = mongodbatlas.StreamProcessor("stream-processor-cluster-to-kafka-example",
project_id=project_id,
workspace_name=example.instance_name,
processor_name="clusterProcessorName",
pipeline=pulumi.Output.all(
example-clusterConnection_name=example_cluster.connection_name,
example-kafkaConnection_name=example_kafka.connection_name
).apply(lambda resolved_outputs: f"""[
{{\"$source\": {{\"connectionName\": \"{resolved_outputs['example-clusterConnection_name']}\"}}}},
{{\"$emit\": {{\"connectionName\": \"{resolved_outputs['example-kafkaConnection_name']}\", \"topic\": \"topic_from_cluster\"}}}}
]
""")
,
state="CREATED")
stream_processor_kafka_to_cluster_example = mongodbatlas.StreamProcessor("stream-processor-kafka-to-cluster-example",
project_id=project_id,
workspace_name=example.instance_name,
processor_name="kafkaProcessorName",
pipeline=pulumi.Output.all(
example-kafkaConnection_name=example_kafka.connection_name,
example-clusterConnection_name=example_cluster.connection_name
).apply(lambda resolved_outputs: f"""[
{{\"$source\": {{\"connectionName\": \"{resolved_outputs['example-kafkaConnection_name']}\", \"topic\": \"topic_source\"}}}},
{{\"$emit\": {{\"connectionName\": \"{resolved_outputs['example-clusterConnection_name']}\", \"db\": \"kafka\", \"coll\": \"topic_source\", \"timeseries\": {{\"timeField\": \"ts\"}}}}}}
]
""")
,
state="CREATED",
tier="SP10",
options={
"dlq": {
"coll": "exampleColumn",
"connection_name": example_cluster.connection_name,
"db": "exampleDb",
},
"autoscaling": {
"min_tier": "SP10",
"max_tier": "SP50",
},
})
example_stream_processors = mongodbatlas.get_stream_processors_output(project_id=project_id,
workspace_name=example.instance_name)
example_stream_processor = mongodbatlas.get_stream_processor_output(project_id=project_id,
workspace_name=example.instance_name,
processor_name=stream_processor_sample_example.processor_name)
pulumi.export("streamProcessorsState", example_stream_processor.state)
pulumi.export("streamProcessorsResults", example_stream_processors.results)
package main
import (
"fmt"
"github.com/pulumi/pulumi-mongodbatlas/sdk/v4/go/mongodbatlas"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
example, err := mongodbatlas.NewStreamInstance(ctx, "example", &mongodbatlas.StreamInstanceArgs{
ProjectId: pulumi.Any(projectId),
InstanceName: pulumi.String("InstanceName"),
DataProcessRegion: &mongodbatlas.StreamInstanceDataProcessRegionArgs{
Region: pulumi.String("VIRGINIA_USA"),
CloudProvider: pulumi.String("AWS"),
},
})
if err != nil {
return err
}
example_sample, err := mongodbatlas.NewStreamConnection(ctx, "example-sample", &mongodbatlas.StreamConnectionArgs{
ProjectId: pulumi.Any(projectId),
WorkspaceName: example.InstanceName,
ConnectionName: pulumi.String("sample_stream_solar"),
Type: pulumi.String("Sample"),
})
if err != nil {
return err
}
example_cluster, err := mongodbatlas.NewStreamConnection(ctx, "example-cluster", &mongodbatlas.StreamConnectionArgs{
ProjectId: pulumi.Any(projectId),
WorkspaceName: example.InstanceName,
ConnectionName: pulumi.String("ClusterConnection"),
Type: pulumi.String("Cluster"),
ClusterName: pulumi.Any(clusterName),
DbRoleToExecute: &mongodbatlas.StreamConnectionDbRoleToExecuteArgs{
Role: pulumi.String("atlasAdmin"),
Type: pulumi.String("BUILT_IN"),
},
})
if err != nil {
return err
}
example_kafka, err := mongodbatlas.NewStreamConnection(ctx, "example-kafka", &mongodbatlas.StreamConnectionArgs{
ProjectId: pulumi.Any(projectId),
WorkspaceName: example.InstanceName,
ConnectionName: pulumi.String("KafkaPlaintextConnection"),
Type: pulumi.String("Kafka"),
Authentication: &mongodbatlas.StreamConnectionAuthenticationArgs{
Mechanism: pulumi.String("PLAIN"),
Username: pulumi.Any(kafkaUsername),
Password: pulumi.Any(kafkaPassword),
},
BootstrapServers: pulumi.String("example.com:9092"),
Config: pulumi.StringMap{
"auto.offset.reset": pulumi.String("earliest"),
},
Security: &mongodbatlas.StreamConnectionSecurityArgs{
Protocol: pulumi.String("SASL_PLAINTEXT"),
},
})
if err != nil {
return err
}
stream_processor_sample_example, err := mongodbatlas.NewStreamProcessor(ctx, "stream-processor-sample-example", &mongodbatlas.StreamProcessorArgs{
ProjectId: pulumi.Any(projectId),
WorkspaceName: example.InstanceName,
ProcessorName: pulumi.String("sampleProcessorName"),
Pipeline: pulumi.All(example_sample.ConnectionName, example_cluster.ConnectionName).ApplyT(func(_args []interface{}) (string, error) {
example - sampleConnectionName := _args[0].(string)
example - clusterConnectionName := _args[1].(string)
return fmt.Sprintf("[\n {\\\"$source\\\": {\\\"connectionName\\\": \\\"%v\\\"}},\n {\\\"$emit\\\": {\\\"connectionName\\\": \\\"%v\\\", \\\"db\\\": \\\"sample\\\", \\\"coll\\\": \\\"solar\\\", \\\"timeseries\\\": {\\\"timeField\\\": \\\"_ts\\\"}}}\n]\n", example_sampleConnectionName, example_clusterConnectionName), nil
}).(pulumi.StringOutput),
State: pulumi.String("STARTED"),
Tier: pulumi.String("SP30"),
})
if err != nil {
return err
}
_, err = mongodbatlas.NewStreamProcessor(ctx, "stream-processor-cluster-to-kafka-example", &mongodbatlas.StreamProcessorArgs{
ProjectId: pulumi.Any(projectId),
WorkspaceName: example.InstanceName,
ProcessorName: pulumi.String("clusterProcessorName"),
Pipeline: pulumi.All(example_cluster.ConnectionName, example_kafka.ConnectionName).ApplyT(func(_args []interface{}) (string, error) {
example - clusterConnectionName := _args[0].(string)
example - kafkaConnectionName := _args[1].(string)
return fmt.Sprintf("[\n {\\\"$source\\\": {\\\"connectionName\\\": \\\"%v\\\"}},\n {\\\"$emit\\\": {\\\"connectionName\\\": \\\"%v\\\", \\\"topic\\\": \\\"topic_from_cluster\\\"}}\n]\n", example_clusterConnectionName, example_kafkaConnectionName), nil
}).(pulumi.StringOutput),
State: pulumi.String("CREATED"),
})
if err != nil {
return err
}
_, err = mongodbatlas.NewStreamProcessor(ctx, "stream-processor-kafka-to-cluster-example", &mongodbatlas.StreamProcessorArgs{
ProjectId: pulumi.Any(projectId),
WorkspaceName: example.InstanceName,
ProcessorName: pulumi.String("kafkaProcessorName"),
Pipeline: pulumi.All(example_kafka.ConnectionName, example_cluster.ConnectionName).ApplyT(func(_args []interface{}) (string, error) {
example - kafkaConnectionName := _args[0].(string)
example - clusterConnectionName := _args[1].(string)
return fmt.Sprintf("[\n {\\\"$source\\\": {\\\"connectionName\\\": \\\"%v\\\", \\\"topic\\\": \\\"topic_source\\\"}},\n {\\\"$emit\\\": {\\\"connectionName\\\": \\\"%v\\\", \\\"db\\\": \\\"kafka\\\", \\\"coll\\\": \\\"topic_source\\\", \\\"timeseries\\\": {\\\"timeField\\\": \\\"ts\\\"}}}\n]\n", example_kafkaConnectionName, example_clusterConnectionName), nil
}).(pulumi.StringOutput),
State: pulumi.String("CREATED"),
Tier: pulumi.String("SP10"),
Options: &mongodbatlas.StreamProcessorOptionsArgs{
Dlq: &mongodbatlas.StreamProcessorOptionsDlqArgs{
Coll: pulumi.String("exampleColumn"),
ConnectionName: example_cluster.ConnectionName,
Db: pulumi.String("exampleDb"),
},
Autoscaling: &mongodbatlas.StreamProcessorOptionsAutoscalingArgs{
MinTier: pulumi.String("SP10"),
MaxTier: pulumi.String("SP50"),
},
},
})
if err != nil {
return err
}
example_stream_processors := mongodbatlas.GetStreamProcessorsOutput(ctx, mongodbatlas.GetStreamProcessorsOutputArgs{
ProjectId: pulumi.Any(projectId),
WorkspaceName: example.InstanceName,
}, nil)
example_stream_processor := mongodbatlas.GetStreamProcessorOutput(ctx, mongodbatlas.GetStreamProcessorOutputArgs{
ProjectId: pulumi.Any(projectId),
WorkspaceName: example.InstanceName,
ProcessorName: stream_processor_sample_example.ProcessorName,
}, nil)
ctx.Export("streamProcessorsState", example_stream_processor.State())
ctx.Export("streamProcessorsResults", example_stream_processors.ApplyT(func(example_stream_processors mongodbatlas.GetStreamProcessorsResult) ([]mongodbatlas.GetStreamProcessorsResult, error) {
return example_stream_processors.Results.([]mongodbatlas.GetStreamProcessorsResult), nil
}).(pulumi.ArrayOutput))
return nil
})
}
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Mongodbatlas = Pulumi.Mongodbatlas;
return await Deployment.RunAsync(() =>
{
var example = new Mongodbatlas.StreamInstance("example", new()
{
ProjectId = projectId,
InstanceName = "InstanceName",
DataProcessRegion = new Mongodbatlas.Inputs.StreamInstanceDataProcessRegionArgs
{
Region = "VIRGINIA_USA",
CloudProvider = "AWS",
},
});
var example_sample = new Mongodbatlas.StreamConnection("example-sample", new()
{
ProjectId = projectId,
WorkspaceName = example.InstanceName,
ConnectionName = "sample_stream_solar",
Type = "Sample",
});
var example_cluster = new Mongodbatlas.StreamConnection("example-cluster", new()
{
ProjectId = projectId,
WorkspaceName = example.InstanceName,
ConnectionName = "ClusterConnection",
Type = "Cluster",
ClusterName = clusterName,
DbRoleToExecute = new Mongodbatlas.Inputs.StreamConnectionDbRoleToExecuteArgs
{
Role = "atlasAdmin",
Type = "BUILT_IN",
},
});
var example_kafka = new Mongodbatlas.StreamConnection("example-kafka", new()
{
ProjectId = projectId,
WorkspaceName = example.InstanceName,
ConnectionName = "KafkaPlaintextConnection",
Type = "Kafka",
Authentication = new Mongodbatlas.Inputs.StreamConnectionAuthenticationArgs
{
Mechanism = "PLAIN",
Username = kafkaUsername,
Password = kafkaPassword,
},
BootstrapServers = "example.com:9092",
Config =
{
{ "auto.offset.reset", "earliest" },
},
Security = new Mongodbatlas.Inputs.StreamConnectionSecurityArgs
{
Protocol = "SASL_PLAINTEXT",
},
});
var stream_processor_sample_example = new Mongodbatlas.StreamProcessor("stream-processor-sample-example", new()
{
ProjectId = projectId,
WorkspaceName = example.InstanceName,
ProcessorName = "sampleProcessorName",
Pipeline = Output.Tuple(example_sample.ConnectionName, example_cluster.ConnectionName).Apply(values =>
{
var example-sampleConnectionName = values.Item1;
var example-clusterConnectionName = values.Item2;
return @$"[
{{\""$source\"": {{\""connectionName\"": \""{example_sampleConnectionName}\""}}}},
{{\""$emit\"": {{\""connectionName\"": \""{example_clusterConnectionName}\"", \""db\"": \""sample\"", \""coll\"": \""solar\"", \""timeseries\"": {{\""timeField\"": \""_ts\""}}}}}}
]
";
}),
State = "STARTED",
Tier = "SP30",
});
var stream_processor_cluster_to_kafka_example = new Mongodbatlas.StreamProcessor("stream-processor-cluster-to-kafka-example", new()
{
ProjectId = projectId,
WorkspaceName = example.InstanceName,
ProcessorName = "clusterProcessorName",
Pipeline = Output.Tuple(example_cluster.ConnectionName, example_kafka.ConnectionName).Apply(values =>
{
var example-clusterConnectionName = values.Item1;
var example-kafkaConnectionName = values.Item2;
return @$"[
{{\""$source\"": {{\""connectionName\"": \""{example_clusterConnectionName}\""}}}},
{{\""$emit\"": {{\""connectionName\"": \""{example_kafkaConnectionName}\"", \""topic\"": \""topic_from_cluster\""}}}}
]
";
}),
State = "CREATED",
});
var stream_processor_kafka_to_cluster_example = new Mongodbatlas.StreamProcessor("stream-processor-kafka-to-cluster-example", new()
{
ProjectId = projectId,
WorkspaceName = example.InstanceName,
ProcessorName = "kafkaProcessorName",
Pipeline = Output.Tuple(example_kafka.ConnectionName, example_cluster.ConnectionName).Apply(values =>
{
var example-kafkaConnectionName = values.Item1;
var example-clusterConnectionName = values.Item2;
return @$"[
{{\""$source\"": {{\""connectionName\"": \""{example_kafkaConnectionName}\"", \""topic\"": \""topic_source\""}}}},
{{\""$emit\"": {{\""connectionName\"": \""{example_clusterConnectionName}\"", \""db\"": \""kafka\"", \""coll\"": \""topic_source\"", \""timeseries\"": {{\""timeField\"": \""ts\""}}}}}}
]
";
}),
State = "CREATED",
Tier = "SP10",
Options = new Mongodbatlas.Inputs.StreamProcessorOptionsArgs
{
Dlq = new Mongodbatlas.Inputs.StreamProcessorOptionsDlqArgs
{
Coll = "exampleColumn",
ConnectionName = example_cluster.ConnectionName,
Db = "exampleDb",
},
Autoscaling = new Mongodbatlas.Inputs.StreamProcessorOptionsAutoscalingArgs
{
MinTier = "SP10",
MaxTier = "SP50",
},
},
});
var example_stream_processors = Mongodbatlas.GetStreamProcessors.Invoke(new()
{
ProjectId = projectId,
WorkspaceName = example.InstanceName,
});
var example_stream_processor = Mongodbatlas.GetStreamProcessor.Invoke(new()
{
ProjectId = projectId,
WorkspaceName = example.InstanceName,
ProcessorName = stream_processor_sample_example.ProcessorName,
});
return new Dictionary<string, object?>
{
["streamProcessorsState"] = example_stream_processor.Apply(example_stream_processor => example_stream_processor.Apply(getStreamProcessorResult => getStreamProcessorResult.State)),
["streamProcessorsResults"] = example_stream_processors.Apply(example_stream_processors => example_stream_processors.Apply(getStreamProcessorsResult => getStreamProcessorsResult.Results)),
};
});
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.mongodbatlas.StreamInstance;
import com.pulumi.mongodbatlas.StreamInstanceArgs;
import com.pulumi.mongodbatlas.inputs.StreamInstanceDataProcessRegionArgs;
import com.pulumi.mongodbatlas.StreamConnection;
import com.pulumi.mongodbatlas.StreamConnectionArgs;
import com.pulumi.mongodbatlas.inputs.StreamConnectionDbRoleToExecuteArgs;
import com.pulumi.mongodbatlas.inputs.StreamConnectionAuthenticationArgs;
import com.pulumi.mongodbatlas.inputs.StreamConnectionSecurityArgs;
import com.pulumi.mongodbatlas.StreamProcessor;
import com.pulumi.mongodbatlas.StreamProcessorArgs;
import com.pulumi.mongodbatlas.inputs.StreamProcessorOptionsArgs;
import com.pulumi.mongodbatlas.inputs.StreamProcessorOptionsDlqArgs;
import com.pulumi.mongodbatlas.inputs.StreamProcessorOptionsAutoscalingArgs;
import com.pulumi.mongodbatlas.MongodbatlasFunctions;
import com.pulumi.mongodbatlas.inputs.GetStreamProcessorsArgs;
import com.pulumi.mongodbatlas.inputs.GetStreamProcessorArgs;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var example = new StreamInstance("example", StreamInstanceArgs.builder()
.projectId(projectId)
.instanceName("InstanceName")
.dataProcessRegion(StreamInstanceDataProcessRegionArgs.builder()
.region("VIRGINIA_USA")
.cloudProvider("AWS")
.build())
.build());
var example_sample = new StreamConnection("example-sample", StreamConnectionArgs.builder()
.projectId(projectId)
.workspaceName(example.instanceName())
.connectionName("sample_stream_solar")
.type("Sample")
.build());
var example_cluster = new StreamConnection("example-cluster", StreamConnectionArgs.builder()
.projectId(projectId)
.workspaceName(example.instanceName())
.connectionName("ClusterConnection")
.type("Cluster")
.clusterName(clusterName)
.dbRoleToExecute(StreamConnectionDbRoleToExecuteArgs.builder()
.role("atlasAdmin")
.type("BUILT_IN")
.build())
.build());
var example_kafka = new StreamConnection("example-kafka", StreamConnectionArgs.builder()
.projectId(projectId)
.workspaceName(example.instanceName())
.connectionName("KafkaPlaintextConnection")
.type("Kafka")
.authentication(StreamConnectionAuthenticationArgs.builder()
.mechanism("PLAIN")
.username(kafkaUsername)
.password(kafkaPassword)
.build())
.bootstrapServers("example.com:9092")
.config(Map.of("auto.offset.reset", "earliest"))
.security(StreamConnectionSecurityArgs.builder()
.protocol("SASL_PLAINTEXT")
.build())
.build());
var stream_processor_sample_example = new StreamProcessor("stream-processor-sample-example", StreamProcessorArgs.builder()
.projectId(projectId)
.workspaceName(example.instanceName())
.processorName("sampleProcessorName")
.pipeline(Output.tuple(example_sample.connectionName(), example_cluster.connectionName()).applyValue(values -> {
var example-sampleConnectionName = values.t1;
var example-clusterConnectionName = values.t2;
return """
[
{\"$source\": {\"connectionName\": \"%s\"}},
{\"$emit\": {\"connectionName\": \"%s\", \"db\": \"sample\", \"coll\": \"solar\", \"timeseries\": {\"timeField\": \"_ts\"}}}
]
", example_sampleConnectionName,example_clusterConnectionName);
}))
.state("STARTED")
.tier("SP30")
.build());
var stream_processor_cluster_to_kafka_example = new StreamProcessor("stream-processor-cluster-to-kafka-example", StreamProcessorArgs.builder()
.projectId(projectId)
.workspaceName(example.instanceName())
.processorName("clusterProcessorName")
.pipeline(Output.tuple(example_cluster.connectionName(), example_kafka.connectionName()).applyValue(values -> {
var example-clusterConnectionName = values.t1;
var example-kafkaConnectionName = values.t2;
return """
[
{\"$source\": {\"connectionName\": \"%s\"}},
{\"$emit\": {\"connectionName\": \"%s\", \"topic\": \"topic_from_cluster\"}}
]
", example_clusterConnectionName,example_kafkaConnectionName);
}))
.state("CREATED")
.build());
var stream_processor_kafka_to_cluster_example = new StreamProcessor("stream-processor-kafka-to-cluster-example", StreamProcessorArgs.builder()
.projectId(projectId)
.workspaceName(example.instanceName())
.processorName("kafkaProcessorName")
.pipeline(Output.tuple(example_kafka.connectionName(), example_cluster.connectionName()).applyValue(values -> {
var example-kafkaConnectionName = values.t1;
var example-clusterConnectionName = values.t2;
return """
[
{\"$source\": {\"connectionName\": \"%s\", \"topic\": \"topic_source\"}},
{\"$emit\": {\"connectionName\": \"%s\", \"db\": \"kafka\", \"coll\": \"topic_source\", \"timeseries\": {\"timeField\": \"ts\"}}}
]
", example_kafkaConnectionName,example_clusterConnectionName);
}))
.state("CREATED")
.tier("SP10")
.options(StreamProcessorOptionsArgs.builder()
.dlq(StreamProcessorOptionsDlqArgs.builder()
.coll("exampleColumn")
.connectionName(example_cluster.connectionName())
.db("exampleDb")
.build())
.autoscaling(StreamProcessorOptionsAutoscalingArgs.builder()
.minTier("SP10")
.maxTier("SP50")
.build())
.build())
.build());
final var example-stream-processors = MongodbatlasFunctions.getStreamProcessors(GetStreamProcessorsArgs.builder()
.projectId(projectId)
.workspaceName(example.instanceName())
.build());
final var example-stream-processor = MongodbatlasFunctions.getStreamProcessor(GetStreamProcessorArgs.builder()
.projectId(projectId)
.workspaceName(example.instanceName())
.processorName(stream_processor_sample_example.processorName())
.build());
ctx.export("streamProcessorsState", example_stream_processor.applyValue(_example_stream_processor -> _example_stream_processor.state()));
ctx.export("streamProcessorsResults", example_stream_processors.applyValue(_example_stream_processors -> _example_stream_processors.results()));
}
}
resources:
example:
type: mongodbatlas:StreamInstance
properties:
projectId: ${projectId}
instanceName: InstanceName
dataProcessRegion:
region: VIRGINIA_USA
cloudProvider: AWS
example-sample:
type: mongodbatlas:StreamConnection
properties:
projectId: ${projectId}
workspaceName: ${example.instanceName}
connectionName: sample_stream_solar
type: Sample
example-cluster:
type: mongodbatlas:StreamConnection
properties:
projectId: ${projectId}
workspaceName: ${example.instanceName}
connectionName: ClusterConnection
type: Cluster
clusterName: ${clusterName}
dbRoleToExecute:
role: atlasAdmin
type: BUILT_IN
example-kafka:
type: mongodbatlas:StreamConnection
properties:
projectId: ${projectId}
workspaceName: ${example.instanceName}
connectionName: KafkaPlaintextConnection
type: Kafka
authentication:
mechanism: PLAIN
username: ${kafkaUsername}
password: ${kafkaPassword}
bootstrapServers: example.com:9092
config:
auto.offset.reset: earliest
security:
protocol: SASL_PLAINTEXT
stream-processor-sample-example:
type: mongodbatlas:StreamProcessor
properties:
projectId: ${projectId}
workspaceName: ${example.instanceName}
processorName: sampleProcessorName
pipeline: |
[
{\"$source\": {\"connectionName\": \"${["example-sample"].connectionName}\"}},
{\"$emit\": {\"connectionName\": \"${["example-cluster"].connectionName}\", \"db\": \"sample\", \"coll\": \"solar\", \"timeseries\": {\"timeField\": \"_ts\"}}}
]
state: STARTED
tier: SP30
stream-processor-cluster-to-kafka-example:
type: mongodbatlas:StreamProcessor
properties:
projectId: ${projectId}
workspaceName: ${example.instanceName}
processorName: clusterProcessorName
pipeline: |
[
{\"$source\": {\"connectionName\": \"${["example-cluster"].connectionName}\"}},
{\"$emit\": {\"connectionName\": \"${["example-kafka"].connectionName}\", \"topic\": \"topic_from_cluster\"}}
]
state: CREATED
stream-processor-kafka-to-cluster-example:
type: mongodbatlas:StreamProcessor
properties:
projectId: ${projectId}
workspaceName: ${example.instanceName}
processorName: kafkaProcessorName
pipeline: |
[
{\"$source\": {\"connectionName\": \"${["example-kafka"].connectionName}\", \"topic\": \"topic_source\"}},
{\"$emit\": {\"connectionName\": \"${["example-cluster"].connectionName}\", \"db\": \"kafka\", \"coll\": \"topic_source\", \"timeseries\": {\"timeField\": \"ts\"}}}
]
state: CREATED
tier: SP10
options:
dlq:
coll: exampleColumn
connectionName: ${["example-cluster"].connectionName}
db: exampleDb
autoscaling:
minTier: SP10
maxTier: SP50
variables:
example-stream-processors:
fn::invoke:
function: mongodbatlas:getStreamProcessors
arguments:
projectId: ${projectId}
workspaceName: ${example.instanceName}
example-stream-processor:
fn::invoke:
function: mongodbatlas:getStreamProcessor
arguments:
projectId: ${projectId}
workspaceName: ${example.instanceName}
processorName: ${["stream-processor-sample-example"].processorName}
outputs:
# example making use of functions
streamProcessorsState: ${["example-stream-processor"].state}
streamProcessorsResults: ${["example-stream-processors"].results}
terraform {
required_providers {
mongodbatlas = {
source = "pulumi/mongodbatlas"
}
}
}
data "mongodbatlas_stream_processors" "example-stream-processors" {
project_id = projectId
workspace_name = mongodbatlas_stream_instance.example.instance_name
}
data "mongodbatlas_stream_processor" "example-stream-processor" {
project_id = projectId
workspace_name = mongodbatlas_stream_instance.example.instance_name
processor_name = mongodbatlas_stream_processor.stream-processor-sample-example.processor_name
}
resource "mongodbatlas_stream_instance" "example" {
lifecycle {
create_before_destroy = true
}
project_id = projectId
instance_name = "InstanceName"
data_process_region = {
region = "VIRGINIA_USA"
cloud_provider = "AWS"
}
}
resource "mongodbatlas_stream_connection" "example-sample" {
lifecycle {
create_before_destroy = true
}
project_id = projectId
workspace_name = mongodbatlas_stream_instance.example.instance_name
connection_name = "sample_stream_solar"
type = "Sample"
}
resource "mongodbatlas_stream_connection" "example-cluster" {
lifecycle {
create_before_destroy = true
}
project_id = projectId
workspace_name = mongodbatlas_stream_instance.example.instance_name
connection_name = "ClusterConnection"
type = "Cluster"
cluster_name = clusterName
db_role_to_execute = {
role = "atlasAdmin"
type = "BUILT_IN"
}
}
resource "mongodbatlas_stream_connection" "example-kafka" {
lifecycle {
create_before_destroy = true
}
project_id = projectId
workspace_name = mongodbatlas_stream_instance.example.instance_name
connection_name = "KafkaPlaintextConnection"
type = "Kafka"
authentication = {
mechanism = "PLAIN"
username = kafkaUsername
password = kafkaPassword
}
bootstrap_servers = "example.com:9092"
config = {
"auto.offset.reset" = "earliest"
}
security = {
protocol = "SASL_PLAINTEXT"
}
}
resource "mongodbatlas_stream_processor" "stream-processor-sample-example" {
lifecycle {
create_before_destroy = true
}
project_id = projectId
workspace_name = mongodbatlas_stream_instance.example.instance_name
processor_name = "sampleProcessorName"
pipeline = <<-JSON
[
{\"$source\": {\"connectionName\": \"${mongodbatlas_stream_connection.example-sample.connection_name}\"}},
{\"$emit\": {\"connectionName\": \"${mongodbatlas_stream_connection.example-cluster.connection_name}\", \"db\": \"sample\", \"coll\": \"solar\", \"timeseries\": {\"timeField\": \"_ts\"}}}
]
JSON
state = "STARTED"
tier = "SP30"
}
resource "mongodbatlas_stream_processor" "stream-processor-cluster-to-kafka-example" {
lifecycle {
create_before_destroy = true
}
project_id = projectId
workspace_name = mongodbatlas_stream_instance.example.instance_name
processor_name = "clusterProcessorName"
pipeline = <<-JSON
[
{\"$source\": {\"connectionName\": \"${mongodbatlas_stream_connection.example-cluster.connection_name}\"}},
{\"$emit\": {\"connectionName\": \"${mongodbatlas_stream_connection.example-kafka.connection_name}\", \"topic\": \"topic_from_cluster\"}}
]
JSON
state = "CREATED"
}
resource "mongodbatlas_stream_processor" "stream-processor-kafka-to-cluster-example" {
lifecycle {
create_before_destroy = true
}
project_id = projectId
workspace_name = mongodbatlas_stream_instance.example.instance_name
processor_name = "kafkaProcessorName"
pipeline = <<-JSON
[
{\"$source\": {\"connectionName\": \"${mongodbatlas_stream_connection.example-kafka.connection_name}\", \"topic\": \"topic_source\"}},
{\"$emit\": {\"connectionName\": \"${mongodbatlas_stream_connection.example-cluster.connection_name}\", \"db\": \"kafka\", \"coll\": \"topic_source\", \"timeseries\": {\"timeField\": \"ts\"}}}
]
JSON
state = "CREATED"
tier = "SP10"
options = {
dlq = {
coll = "exampleColumn"
connection_name = mongodbatlas_stream_connection.example-cluster.connection_name
db = "exampleDb"
}
autoscaling = {
min_tier = "SP10"
max_tier = "SP50"
}
}
}
# example making use of functions
output "streamProcessorsState" {
value = data.mongodbatlas_stream_processor.example-stream-processor.state
}
output "streamProcessorsResults" {
value = data.mongodbatlas_stream_processors.example-stream-processors.results
}
Using getStreamProcessors
Two invocation forms are available. The direct form accepts plain arguments and either blocks until the result value is available, or returns a Promise-wrapped result. The output form accepts Input-wrapped arguments and returns an Output-wrapped result.
function getStreamProcessors(args: GetStreamProcessorsArgs, opts?: InvokeOptions): Promise<GetStreamProcessorsResult>
function getStreamProcessorsOutput(args: GetStreamProcessorsOutputArgs, opts?: InvokeOutputOptions): Output<GetStreamProcessorsResult>def get_stream_processors(instance_name: Optional[str] = None,
project_id: Optional[str] = None,
workspace_name: Optional[str] = None,
opts: Optional[InvokeOptions] = None) -> GetStreamProcessorsResult
def get_stream_processors_output(instance_name: pulumi.Input[Optional[str]] = None,
project_id: pulumi.Input[Optional[str]] = None,
workspace_name: pulumi.Input[Optional[str]] = None,
opts: Optional[InvokeOutputOptions] = None) -> Output[GetStreamProcessorsResult]func LookupStreamProcessors(ctx *Context, args *LookupStreamProcessorsArgs, opts ...InvokeOption) (*LookupStreamProcessorsResult, error)
func LookupStreamProcessorsOutput(ctx *Context, args *LookupStreamProcessorsOutputArgs, opts ...InvokeOption) LookupStreamProcessorsResultOutput> Note: This function is named LookupStreamProcessors in the Go SDK.
public static class GetStreamProcessors
{
public static Task<GetStreamProcessorsResult> InvokeAsync(GetStreamProcessorsArgs args, InvokeOptions? opts = null)
public static Output<GetStreamProcessorsResult> Invoke(GetStreamProcessorsInvokeArgs args, InvokeOptions? opts = null)
public static Output<GetStreamProcessorsResult> Invoke(GetStreamProcessorsInvokeArgs args, InvokeOutputOptions opts)
}public static CompletableFuture<GetStreamProcessorsResult> getStreamProcessors(GetStreamProcessorsArgs args, InvokeOptions options)
public static Output<GetStreamProcessorsResult> getStreamProcessors(GetStreamProcessorsArgs args, InvokeOptions options)
public static Output<GetStreamProcessorsResult> getStreamProcessors(GetStreamProcessorsArgs args, InvokeOutputOptions options)
fn::invoke:
function: mongodbatlas:index/getStreamProcessors:getStreamProcessors
arguments:
# arguments dictionarydata "mongodbatlas_get_stream_processors" "name" {
# arguments
}The following arguments are supported:
- Project
Id string - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - Instance
Name string - Label that identifies the stream processing workspace.
- Workspace
Name string - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- Project
Id string - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - Instance
Name string - Label that identifies the stream processing workspace.
- Workspace
Name string - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- project_
id string - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - instance_
name string - Label that identifies the stream processing workspace.
- workspace_
name string - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- project
Id String - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - instance
Name String - Label that identifies the stream processing workspace.
- workspace
Name String - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- project
Id string - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - instance
Name string - Label that identifies the stream processing workspace.
- workspace
Name string - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- project_
id str - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - instance_
name str - Label that identifies the stream processing workspace.
- workspace_
name str - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- project
Id String - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - instance
Name String - Label that identifies the stream processing workspace.
- workspace
Name String - Label that identifies the stream processing workspace. Conflicts with
instanceName.
getStreamProcessors Result
The following output properties are available:
- Project
Id string - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - Results
List<Get
Stream Processors Result> - Returns all Stream Processors within the specified stream instance.
- Instance
Name string - Label that identifies the stream processing workspace.
- Workspace
Name string - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- Project
Id string - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - Results
[]Get
Stream Processors Result - Returns all Stream Processors within the specified stream instance.
- Instance
Name string - Label that identifies the stream processing workspace.
- Workspace
Name string - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- project_
id string - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - results list(object)
- Returns all Stream Processors within the specified stream instance.
- instance_
name string - Label that identifies the stream processing workspace.
- workspace_
name string - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- project
Id String - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - results
List<Get
Stream Processors Result> - Returns all Stream Processors within the specified stream instance.
- instance
Name String - Label that identifies the stream processing workspace.
- workspace
Name String - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- project
Id string - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - results
Get
Stream Processors Result[] - Returns all Stream Processors within the specified stream instance.
- instance
Name string - Label that identifies the stream processing workspace.
- workspace
Name string - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- project_
id str - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - results
Sequence[Get
Stream Processors Result] - Returns all Stream Processors within the specified stream instance.
- instance_
name str - Label that identifies the stream processing workspace.
- workspace_
name str - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- project
Id String - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - results List<Property Map>
- Returns all Stream Processors within the specified stream instance.
- instance
Name String - Label that identifies the stream processing workspace.
- workspace
Name String - Label that identifies the stream processing workspace. Conflicts with
instanceName.
Supporting Types
GetStreamProcessorsResult
- Effective
Tier string - Tier the stream processor is currently running on. When autoscaling is disabled this equals
tier; when autoscaling is enabled it reflects the tier chosen by the autoscaler within the configured bounds. - Failover
Enabled bool - Indicates whether this stream processor is eligible for failover. When
true, an operator can trigger a failover event to migrate the stream processor to a secondary region configured in the workspace'sfailoverRegions. Requires an Atlas-to-Atlas or Atlas-to-Kafka pipeline withfailoverRegionsconfigured on the workspace. - Id string
- Unique 24-hexadecimal character string that identifies the stream processor.
- Instance
Name string - Label that identifies the stream processing workspace.
- Options
Get
Stream Processors Result Options - Optional configuration for the stream processor. Empty
optionsobjects are not supported. - Pipeline string
- Stream aggregation pipeline you want to apply to your streaming data, as a JSON string. MongoDB Atlas Docs contain more information. For more details see the Aggregation Pipelines Documentation. Field order matters: author this as a raw JSON string (heredoc or
file("pipeline.json")) and do not use jsonencode, which sorts object keys lexicographically, changing sort precedence, document-literal equality matches, and$addFields/$projectoutput field order. - Processor
Name string - Label that identifies the stream processor.
- Project
Id string - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - State string
- The state of the stream processor. Commonly occurring states are 'CREATED', 'STARTED', 'STOPPED' and 'FAILED'. Used to start or stop the Stream Processor. Valid values are
CREATED,STARTEDorSTOPPED. When a Stream Processor is created without specifying the state, it will default toCREATEDstate. When a Stream Processor is updated without specifying the state, it will default to the Previous state. - Stats string
- The stats associated with the stream processor. Refer to the MongoDB Atlas Docs for more information.
- Tier string
- Selected tier to start a stream processor on rather than defaulting to the workspace setting. Configures Memory / VCPU allowances. Valid options are SP2, SP5, SP10, SP30, and SP50. When
options.autoscalingis enabled, this is used only as the initial/baseline tier; the running tier is reported byeffectiveTier. - Workspace
Name string - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- Effective
Tier string - Tier the stream processor is currently running on. When autoscaling is disabled this equals
tier; when autoscaling is enabled it reflects the tier chosen by the autoscaler within the configured bounds. - Failover
Enabled bool - Indicates whether this stream processor is eligible for failover. When
true, an operator can trigger a failover event to migrate the stream processor to a secondary region configured in the workspace'sfailoverRegions. Requires an Atlas-to-Atlas or Atlas-to-Kafka pipeline withfailoverRegionsconfigured on the workspace. - Id string
- Unique 24-hexadecimal character string that identifies the stream processor.
- Instance
Name string - Label that identifies the stream processing workspace.
- Options
Get
Stream Processors Result Options - Optional configuration for the stream processor. Empty
optionsobjects are not supported. - Pipeline string
- Stream aggregation pipeline you want to apply to your streaming data, as a JSON string. MongoDB Atlas Docs contain more information. For more details see the Aggregation Pipelines Documentation. Field order matters: author this as a raw JSON string (heredoc or
file("pipeline.json")) and do not use jsonencode, which sorts object keys lexicographically, changing sort precedence, document-literal equality matches, and$addFields/$projectoutput field order. - Processor
Name string - Label that identifies the stream processor.
- Project
Id string - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - State string
- The state of the stream processor. Commonly occurring states are 'CREATED', 'STARTED', 'STOPPED' and 'FAILED'. Used to start or stop the Stream Processor. Valid values are
CREATED,STARTEDorSTOPPED. When a Stream Processor is created without specifying the state, it will default toCREATEDstate. When a Stream Processor is updated without specifying the state, it will default to the Previous state. - Stats string
- The stats associated with the stream processor. Refer to the MongoDB Atlas Docs for more information.
- Tier string
- Selected tier to start a stream processor on rather than defaulting to the workspace setting. Configures Memory / VCPU allowances. Valid options are SP2, SP5, SP10, SP30, and SP50. When
options.autoscalingis enabled, this is used only as the initial/baseline tier; the running tier is reported byeffectiveTier. - Workspace
Name string - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- effective_
tier string - Tier the stream processor is currently running on. When autoscaling is disabled this equals
tier; when autoscaling is enabled it reflects the tier chosen by the autoscaler within the configured bounds. - failover_
enabled bool - Indicates whether this stream processor is eligible for failover. When
true, an operator can trigger a failover event to migrate the stream processor to a secondary region configured in the workspace'sfailoverRegions. Requires an Atlas-to-Atlas or Atlas-to-Kafka pipeline withfailoverRegionsconfigured on the workspace. - id string
- Unique 24-hexadecimal character string that identifies the stream processor.
- instance_
name string - Label that identifies the stream processing workspace.
- options object
- Optional configuration for the stream processor. Empty
optionsobjects are not supported. - pipeline string
- Stream aggregation pipeline you want to apply to your streaming data, as a JSON string. MongoDB Atlas Docs contain more information. For more details see the Aggregation Pipelines Documentation. Field order matters: author this as a raw JSON string (heredoc or
file("pipeline.json")) and do not use jsonencode, which sorts object keys lexicographically, changing sort precedence, document-literal equality matches, and$addFields/$projectoutput field order. - processor_
name string - Label that identifies the stream processor.
- project_
id string - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - state string
- The state of the stream processor. Commonly occurring states are 'CREATED', 'STARTED', 'STOPPED' and 'FAILED'. Used to start or stop the Stream Processor. Valid values are
CREATED,STARTEDorSTOPPED. When a Stream Processor is created without specifying the state, it will default toCREATEDstate. When a Stream Processor is updated without specifying the state, it will default to the Previous state. - stats string
- The stats associated with the stream processor. Refer to the MongoDB Atlas Docs for more information.
- tier string
- Selected tier to start a stream processor on rather than defaulting to the workspace setting. Configures Memory / VCPU allowances. Valid options are SP2, SP5, SP10, SP30, and SP50. When
options.autoscalingis enabled, this is used only as the initial/baseline tier; the running tier is reported byeffectiveTier. - workspace_
name string - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- effective
Tier String - Tier the stream processor is currently running on. When autoscaling is disabled this equals
tier; when autoscaling is enabled it reflects the tier chosen by the autoscaler within the configured bounds. - failover
Enabled Boolean - Indicates whether this stream processor is eligible for failover. When
true, an operator can trigger a failover event to migrate the stream processor to a secondary region configured in the workspace'sfailoverRegions. Requires an Atlas-to-Atlas or Atlas-to-Kafka pipeline withfailoverRegionsconfigured on the workspace. - id String
- Unique 24-hexadecimal character string that identifies the stream processor.
- instance
Name String - Label that identifies the stream processing workspace.
- options
Get
Stream Processors Result Options - Optional configuration for the stream processor. Empty
optionsobjects are not supported. - pipeline String
- Stream aggregation pipeline you want to apply to your streaming data, as a JSON string. MongoDB Atlas Docs contain more information. For more details see the Aggregation Pipelines Documentation. Field order matters: author this as a raw JSON string (heredoc or
file("pipeline.json")) and do not use jsonencode, which sorts object keys lexicographically, changing sort precedence, document-literal equality matches, and$addFields/$projectoutput field order. - processor
Name String - Label that identifies the stream processor.
- project
Id String - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - state String
- The state of the stream processor. Commonly occurring states are 'CREATED', 'STARTED', 'STOPPED' and 'FAILED'. Used to start or stop the Stream Processor. Valid values are
CREATED,STARTEDorSTOPPED. When a Stream Processor is created without specifying the state, it will default toCREATEDstate. When a Stream Processor is updated without specifying the state, it will default to the Previous state. - stats String
- The stats associated with the stream processor. Refer to the MongoDB Atlas Docs for more information.
- tier String
- Selected tier to start a stream processor on rather than defaulting to the workspace setting. Configures Memory / VCPU allowances. Valid options are SP2, SP5, SP10, SP30, and SP50. When
options.autoscalingis enabled, this is used only as the initial/baseline tier; the running tier is reported byeffectiveTier. - workspace
Name String - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- effective
Tier string - Tier the stream processor is currently running on. When autoscaling is disabled this equals
tier; when autoscaling is enabled it reflects the tier chosen by the autoscaler within the configured bounds. - failover
Enabled boolean - Indicates whether this stream processor is eligible for failover. When
true, an operator can trigger a failover event to migrate the stream processor to a secondary region configured in the workspace'sfailoverRegions. Requires an Atlas-to-Atlas or Atlas-to-Kafka pipeline withfailoverRegionsconfigured on the workspace. - id string
- Unique 24-hexadecimal character string that identifies the stream processor.
- instance
Name string - Label that identifies the stream processing workspace.
- options
Get
Stream Processors Result Options - Optional configuration for the stream processor. Empty
optionsobjects are not supported. - pipeline string
- Stream aggregation pipeline you want to apply to your streaming data, as a JSON string. MongoDB Atlas Docs contain more information. For more details see the Aggregation Pipelines Documentation. Field order matters: author this as a raw JSON string (heredoc or
file("pipeline.json")) and do not use jsonencode, which sorts object keys lexicographically, changing sort precedence, document-literal equality matches, and$addFields/$projectoutput field order. - processor
Name string - Label that identifies the stream processor.
- project
Id string - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - state string
- The state of the stream processor. Commonly occurring states are 'CREATED', 'STARTED', 'STOPPED' and 'FAILED'. Used to start or stop the Stream Processor. Valid values are
CREATED,STARTEDorSTOPPED. When a Stream Processor is created without specifying the state, it will default toCREATEDstate. When a Stream Processor is updated without specifying the state, it will default to the Previous state. - stats string
- The stats associated with the stream processor. Refer to the MongoDB Atlas Docs for more information.
- tier string
- Selected tier to start a stream processor on rather than defaulting to the workspace setting. Configures Memory / VCPU allowances. Valid options are SP2, SP5, SP10, SP30, and SP50. When
options.autoscalingis enabled, this is used only as the initial/baseline tier; the running tier is reported byeffectiveTier. - workspace
Name string - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- effective_
tier str - Tier the stream processor is currently running on. When autoscaling is disabled this equals
tier; when autoscaling is enabled it reflects the tier chosen by the autoscaler within the configured bounds. - failover_
enabled bool - Indicates whether this stream processor is eligible for failover. When
true, an operator can trigger a failover event to migrate the stream processor to a secondary region configured in the workspace'sfailoverRegions. Requires an Atlas-to-Atlas or Atlas-to-Kafka pipeline withfailoverRegionsconfigured on the workspace. - id str
- Unique 24-hexadecimal character string that identifies the stream processor.
- instance_
name str - Label that identifies the stream processing workspace.
- options
Get
Stream Processors Result Options - Optional configuration for the stream processor. Empty
optionsobjects are not supported. - pipeline str
- Stream aggregation pipeline you want to apply to your streaming data, as a JSON string. MongoDB Atlas Docs contain more information. For more details see the Aggregation Pipelines Documentation. Field order matters: author this as a raw JSON string (heredoc or
file("pipeline.json")) and do not use jsonencode, which sorts object keys lexicographically, changing sort precedence, document-literal equality matches, and$addFields/$projectoutput field order. - processor_
name str - Label that identifies the stream processor.
- project_
id str - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - state str
- The state of the stream processor. Commonly occurring states are 'CREATED', 'STARTED', 'STOPPED' and 'FAILED'. Used to start or stop the Stream Processor. Valid values are
CREATED,STARTEDorSTOPPED. When a Stream Processor is created without specifying the state, it will default toCREATEDstate. When a Stream Processor is updated without specifying the state, it will default to the Previous state. - stats str
- The stats associated with the stream processor. Refer to the MongoDB Atlas Docs for more information.
- tier str
- Selected tier to start a stream processor on rather than defaulting to the workspace setting. Configures Memory / VCPU allowances. Valid options are SP2, SP5, SP10, SP30, and SP50. When
options.autoscalingis enabled, this is used only as the initial/baseline tier; the running tier is reported byeffectiveTier. - workspace_
name str - Label that identifies the stream processing workspace. Conflicts with
instanceName.
- effective
Tier String - Tier the stream processor is currently running on. When autoscaling is disabled this equals
tier; when autoscaling is enabled it reflects the tier chosen by the autoscaler within the configured bounds. - failover
Enabled Boolean - Indicates whether this stream processor is eligible for failover. When
true, an operator can trigger a failover event to migrate the stream processor to a secondary region configured in the workspace'sfailoverRegions. Requires an Atlas-to-Atlas or Atlas-to-Kafka pipeline withfailoverRegionsconfigured on the workspace. - id String
- Unique 24-hexadecimal character string that identifies the stream processor.
- instance
Name String - Label that identifies the stream processing workspace.
- options Property Map
- Optional configuration for the stream processor. Empty
optionsobjects are not supported. - pipeline String
- Stream aggregation pipeline you want to apply to your streaming data, as a JSON string. MongoDB Atlas Docs contain more information. For more details see the Aggregation Pipelines Documentation. Field order matters: author this as a raw JSON string (heredoc or
file("pipeline.json")) and do not use jsonencode, which sorts object keys lexicographically, changing sort precedence, document-literal equality matches, and$addFields/$projectoutput field order. - processor
Name String - Label that identifies the stream processor.
- project
Id String - Unique 24-hexadecimal digit string that identifies your project, also known as
groupIdin the official documentation. - state String
- The state of the stream processor. Commonly occurring states are 'CREATED', 'STARTED', 'STOPPED' and 'FAILED'. Used to start or stop the Stream Processor. Valid values are
CREATED,STARTEDorSTOPPED. When a Stream Processor is created without specifying the state, it will default toCREATEDstate. When a Stream Processor is updated without specifying the state, it will default to the Previous state. - stats String
- The stats associated with the stream processor. Refer to the MongoDB Atlas Docs for more information.
- tier String
- Selected tier to start a stream processor on rather than defaulting to the workspace setting. Configures Memory / VCPU allowances. Valid options are SP2, SP5, SP10, SP30, and SP50. When
options.autoscalingis enabled, this is used only as the initial/baseline tier; the running tier is reported byeffectiveTier. - workspace
Name String - Label that identifies the stream processing workspace. Conflicts with
instanceName.
GetStreamProcessorsResultOptions
- Autoscaling
Get
Stream Processors Result Options Autoscaling - Vertical autoscaling configuration for the stream processor. When present, the processor automatically scales its tier between
minTierandmaxTierbased on load;tieris used only as the initial/baseline tier and the running tier is reported byeffectiveTier. To disable autoscaling, remove this block. - Dlq
Get
Stream Processors Result Options Dlq - Dead letter queue for the stream processor. Refer to the MongoDB Atlas Docs for more information.
- Autoscaling
Get
Stream Processors Result Options Autoscaling - Vertical autoscaling configuration for the stream processor. When present, the processor automatically scales its tier between
minTierandmaxTierbased on load;tieris used only as the initial/baseline tier and the running tier is reported byeffectiveTier. To disable autoscaling, remove this block. - Dlq
Get
Stream Processors Result Options Dlq - Dead letter queue for the stream processor. Refer to the MongoDB Atlas Docs for more information.
- autoscaling object
- Vertical autoscaling configuration for the stream processor. When present, the processor automatically scales its tier between
minTierandmaxTierbased on load;tieris used only as the initial/baseline tier and the running tier is reported byeffectiveTier. To disable autoscaling, remove this block. - dlq object
- Dead letter queue for the stream processor. Refer to the MongoDB Atlas Docs for more information.
- autoscaling
Get
Stream Processors Result Options Autoscaling - Vertical autoscaling configuration for the stream processor. When present, the processor automatically scales its tier between
minTierandmaxTierbased on load;tieris used only as the initial/baseline tier and the running tier is reported byeffectiveTier. To disable autoscaling, remove this block. - dlq
Get
Stream Processors Result Options Dlq - Dead letter queue for the stream processor. Refer to the MongoDB Atlas Docs for more information.
- autoscaling
Get
Stream Processors Result Options Autoscaling - Vertical autoscaling configuration for the stream processor. When present, the processor automatically scales its tier between
minTierandmaxTierbased on load;tieris used only as the initial/baseline tier and the running tier is reported byeffectiveTier. To disable autoscaling, remove this block. - dlq
Get
Stream Processors Result Options Dlq - Dead letter queue for the stream processor. Refer to the MongoDB Atlas Docs for more information.
- autoscaling
Get
Stream Processors Result Options Autoscaling - Vertical autoscaling configuration for the stream processor. When present, the processor automatically scales its tier between
minTierandmaxTierbased on load;tieris used only as the initial/baseline tier and the running tier is reported byeffectiveTier. To disable autoscaling, remove this block. - dlq
Get
Stream Processors Result Options Dlq - Dead letter queue for the stream processor. Refer to the MongoDB Atlas Docs for more information.
- autoscaling Property Map
- Vertical autoscaling configuration for the stream processor. When present, the processor automatically scales its tier between
minTierandmaxTierbased on load;tieris used only as the initial/baseline tier and the running tier is reported byeffectiveTier. To disable autoscaling, remove this block. - dlq Property Map
- Dead letter queue for the stream processor. Refer to the MongoDB Atlas Docs for more information.
GetStreamProcessorsResultOptionsAutoscaling
GetStreamProcessorsResultOptionsDlq
- Coll string
- Name of the collection to use for the DLQ.
- Connection
Name string - Name of the connection to write DLQ messages to. Must be an Atlas connection.
- Db string
- Name of the database to use for the DLQ.
- Coll string
- Name of the collection to use for the DLQ.
- Connection
Name string - Name of the connection to write DLQ messages to. Must be an Atlas connection.
- Db string
- Name of the database to use for the DLQ.
- coll string
- Name of the collection to use for the DLQ.
- connection_
name string - Name of the connection to write DLQ messages to. Must be an Atlas connection.
- db string
- Name of the database to use for the DLQ.
- coll String
- Name of the collection to use for the DLQ.
- connection
Name String - Name of the connection to write DLQ messages to. Must be an Atlas connection.
- db String
- Name of the database to use for the DLQ.
- coll string
- Name of the collection to use for the DLQ.
- connection
Name string - Name of the connection to write DLQ messages to. Must be an Atlas connection.
- db string
- Name of the database to use for the DLQ.
- coll str
- Name of the collection to use for the DLQ.
- connection_
name str - Name of the connection to write DLQ messages to. Must be an Atlas connection.
- db str
- Name of the database to use for the DLQ.
- coll String
- Name of the collection to use for the DLQ.
- connection
Name String - Name of the connection to write DLQ messages to. Must be an Atlas connection.
- db String
- Name of the database to use for the DLQ.
Package Details
- Repository
- MongoDB Atlas pulumi/pulumi-mongodbatlas
- License
- Apache-2.0
- Notes
- This Pulumi package is based on the
mongodbatlasTerraform Provider.
Viewing docs for MongoDB Atlas v4.18.1
published on Tuesday, Oct 27, 2026 by Pulumi
published on Tuesday, Oct 27, 2026 by Pulumi