Build and operate the data processing systems behind analytics and ML on Google Cloud, including BigQuery, Dataflow, and Pub/Sub, and track your readiness for the Professional Data Engineer exam.
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Google Cloud service
Memorystore for Redis
Topic in 3 exam domains
- Memorystore for Redis · Service
- Memorystore for Redis · Feature
Also called: Cloud Memorystore Redis, managed Redis, Memorystore(Redis)
A fully managed in-memory data store service provided by Google Cloud.
Where this appears on the exam
1 objective in 1 of 5 domains
Related topics
FoundationsThis topicWorks alongsideBuilds on theseAppliedIdentity and Access ManagementServiceCloud RunServiceCloud LoggingServiceCompute EngineServiceVPC Service ControlsServiceFirestoreServiceCloud Run functionsService
Memorystore for RedisService
Google Cloud StorageServiceWorkflowsServiceCloud MonitoringServiceCommitted use discountsFeatureDataflowServicecustomer-managed encryption keysFeatureBigQueryServiceCloud SQLServiceArtifact RegistryServicePoints to what builds on itWorks with or alternative toHover or tap a line to see what connects the two
- Identity and Access Management secures Memorystore for Redis From the official documentation: “Management of Memorystore for Redis instances is secured using Identity and Access Management (IAM) role-based access control.”
- Cloud Logging works with Memorystore for Redis From the official documentation: “Redis produces logs that Cloud Logging captures.”
- Cloud Monitoring works with Memorystore for Redis From the official documentation: “Additionally, integration with Cloud Monitoring makes it easy to monitor your Redis instances.”
- Cloud Run works with Memorystore for Redis From the official documentation: “The Cloud Run service can cache data in the Memorystore for Redis instance.”
- Cloud Run functions works with Memorystore for Redis From the official documentation: “Demonstrates a Cloud Function that connects to a managed Redis instance.”
- Committed use discounts works with Memorystore for Redis From the official documentation: “The discount applies to any eligible usage of Memorystore for Valkey, Memorystore for Redis Cluster, Memorystore for Redis, or Memorystore for Memcached instances associated with the Cloud Billing account used to purchase the CUD, with the exception of Memorystore for Redis M1…”
- Compute Engine works with Memorystore for Redis From the official documentation: “You can connect to your Redis instance from Compute Engine VM instances that use the same authorized network as your Redis instance.”
- customer-managed encryption keys is part of Memorystore for Redis From the official documentation: “You can use CMEK on new Memorystore for Redis deployments only. You can't enable CMEK on existing Memorystore for Redis instances.”
- Dataflow works with Memorystore for Redis From the official documentation: “Combined with Dataflow, Memorystore for Redis provides a scalable, fast in-memory store for storing intermediate data that thousands of clients can access with very low latency.”
- VPC Service Controls secures Memorystore for Redis From the official documentation: “The API for Memorystore for Redis can be protected by VPC Service Controls and the product can be used normally inside service perimeters.”
- BigQuery works with Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
- BigQuery works with Dataflow From the official documentation: “Read from BigQuery to Dataflow”
- BigQuery works with Cloud SQL From the official documentation: “Add credentials to connect BigQuery to Cloud SQL.”
- Cloud Run works with Cloud SQL From the official documentation: “Learn how to connect to Cloud SQL from Cloud Run”
- VPC Service Controls secures BigQuery From the official documentation: “BigQuery data is protected with VPC Service Controls”
- Cloud Logging works with customer-managed encryption keys From the official documentation: “To use Cloud Logging with Customer-managed encryption keys (CMEK), you must complete the steps in the [Enable CMEK for an organization](/logging/docs/routing/managed-encryption#enable) page in the Cloud Logging documentation.”
- BigQuery works with Cloud Monitoring From the official documentation: “You can use Monitoring to export your metrics to BigQuery.”
- Cloud SQL works with Compute Engine From the official documentation: “Create a Compute Engine VM Instance to host a sample web app that connects to Cloud SQL.”
- BigQuery is an alternative to Google Cloud Storage From the official documentation: “The training data can be either a CSV file in Cloud Storage or a table in BigQuery.”
- BigQuery works with Cloud Run functions From the official documentation: “BigQuery supports external function calls through Cloud Run functions.”
- BigQuery works with Google Cloud Storage From the official documentation: “Load Cloud Storage data into BigQuery”
- Cloud Monitoring works with Cloud SQL From the official documentation: “You can also get more details by viewing the Cloud Monitoring logs for your Cloud SQL destination instance.”
- Cloud SQL works with Identity and Access Management From the official documentation: “This page describes how Cloud SQL is integrated with IAM .”
- Cloud Logging works with Cloud SQL From the official documentation: “Cloud SQL uses Cloud Logging.”
- Cloud Run works with Workflows From the official documentation: “Route Workflows events to Cloud Run”
- Cloud SQL depends on Compute Engine From the official documentation: “Cloud SQL uses Compute Engine virtual machines (VMs) with persistent storage disks.”
- customer-managed encryption keys secures BigQuery From the official documentation: “You can either create CMEKs manually to protect your BigQuery resources or use Cloud KMS Autokey.”
- customer-managed encryption keys secures Cloud SQL From the official documentation: “Enable CMEK for Cloud SQL Databases”
- Identity and Access Management secures Firestore From the official documentation: “This page describes the IAM permissions and roles for Firestore.”
- Artifact Registry works with Cloud Run From the official documentation: “Cloud Run recommends using Artifact Registry.”
- Cloud Monitoring works with Dataflow From the official documentation: “Dataflow is fully integrated with Cloud Monitoring.”
- Cloud Run is an alternative to Cloud Run functions From the official documentation: “To create remote functions, you must [grant required roles](/bigquery/docs/remote-functions#grant_permission_on_function) to Cloud Run functions or Cloud Run.”
- Cloud Run functions works with Workflows From the official documentation: “Use Workflows with Cloud Run and Cloud Run functions tutorial”
- customer-managed encryption keys secures Artifact Registry From the official documentation: “Artifact Registry also supports [organization policy constraints](/artifact-registry/docs/cmek#org-policy) that can require CMEK to protect resources.”
- Identity and Access Management secures BigQuery From the official documentation: “Access to BigQuery data from AlloyDB is managed through IAM.”
- Artifact Registry works with Compute Engine From the official documentation: “Compute Engine can pull containers directly from Artifact Registry repositories.”
- BigQuery depends on Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
- BigQuery works with Identity and Access Management From the official documentation: “BigQuery uses Identity and Access Management (IAM) for authorization.”
- Cloud Logging works with Compute Engine From the official documentation: “Compute Engine sends you Cloud Logging events for scheduled, started, or completed maintenance.”
- Cloud Run works with Firestore From the official documentation: “The Cloud Run app stores the result in Firestore.”
- Cloud Run works with Google Cloud Storage From the official documentation: “The Cloud Run function will receive syslog messages from FortiEDR via HTTP and write them to GCS.”
- Cloud Run functions works with Firestore From the official documentation: “The Cloud Run function stores the result in Firestore.”
- Cloud Run functions works with Google Cloud Storage From the official documentation: “Service account for Dataminr Alerts Cloud Run function to write alert data to GCS”
- Cloud SQL works with Google Cloud Storage From the official documentation: “Imports data into a Cloud SQL instance from a SQL dump or CSV file in Cloud Storage.”
- Compute Engine works with Google Cloud Storage From the official documentation: “The usage export bucket is a Google Cloud Storage bucket where Compute Engine usage reports are stored.”
- VPC Service Controls secures Artifact Registry From the official documentation: “If your VPC Service Controls settings are blocking access to Artifact Registry, you must add the Artifact Registry service to the service perimeter of your VPC Service Controls.”
- VPC Service Controls secures Cloud SQL From the official documentation: “VPC Service Controls perimeters protect the Cloud SQL Admin API.”
- BigQuery works with Cloud Run From the official documentation: “You can then use Cloud Run to transcode data present in the bucket and move it to BigQuery.”
- BigQuery works with Firestore From the official documentation: “You can load data from a Firestore with MongoDB compatibility export into BigQuery, but only if you specified a `collection-ids` filter.”
- BigQuery works with Workflows From the official documentation: “To learn more about using Workflows with BigQuery, see [Run multiple BigQuery jobs in parallel](/workflows/docs/tutorials/bigquery-parallel-jobs).”
- Cloud Logging works with Cloud Monitoring From the official documentation: “If a log entry matches the filter of the alerting policy, then Cloud Logging extracts labels and forwards the data to Cloud Monitoring.”
- Cloud Logging works with Cloud Run From the official documentation: “Cloud Logging captures, stores, and analyzes Cloud Run logs.”
- Cloud Logging works with Cloud Run functions From the official documentation: “Cloud Run functions is configured to use Cloud Logging automatically.”
- Cloud Logging works with Dataflow From the official documentation: “Information stored in [Cloud Logging](/logging/docs/region-support) is primarily generated by the code in your Dataflow program.”
- Cloud Logging is an alternative to Google Cloud Storage From the official documentation: “When you specify your own service account for builds, you must store your build logs in a Cloud Logging bucket, in a user-created Cloud Storage bucket, or in a Google Cloud-created and user-owned Cloud Storage bucket.”
- Cloud Monitoring works with Cloud Run From the official documentation: “Cloud Monitoring records metrics regarding the execution of Cloud Run.”
- Cloud Monitoring works with Cloud Run functions From the official documentation: “This hands-on lab shows you how to view your Cloud Run functions with their execution times, execution counts, and memory usage in the Google Cloud console. These metrics are also available in Cloud Monitoring.”
- Cloud Monitoring works with Compute Engine From the official documentation: “Many Google services like Compute Engine send telemetry to Cloud Monitoring.”
- Cloud Run works with Identity and Access Management From the official documentation: “Cloud Run also offers the ability to control access to a service with Identity and Access Management (IAM).”
- Cloud Run functions depends on Cloud Run From the official documentation: “Cloud Run functions (2nd gen) is based on Cloud Run and has a limit of 100 database connections per instance.”
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