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installed add-ons are up-to-date. See documentation. === How do I configure NodePools in EKS Auto Mode? A new cluster will come pre-configured with two NodePools ==== general-purpose image:gp\_nodepool.png[General Purpose NodePool] This NodePool instructs Karpenter to launch nodes with the following characteristics: 1.... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/autoscaling/auto-mode.adoc | mainline | aws-eks-best-practices | [
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[."topic"] [[cas,cas.title]] = Kubernetes Cluster Autoscaler :info\_doctype: section :info\_title: Cluster Autoscaler :info\_abstract: Cluster Autoscaler :info\_titleabbrev: Cluster Autoscaler :imagesdir: images/autoscaling/ include::../attributes.txt[] TIP: https://aws-experience.com/emea/smb/events/series/get-hands-o... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/autoscaling/cluster-autoscaler.adoc | mainline | aws-eks-best-practices | [
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but work is done by a single replica at a time. It is not horizontally scalable. For basic setups, the default it should work out of the box using the provided https://docs.aws.amazon.com/eks/latest/userguide/cluster-autoscaler.html[installation instructions], but there are a few things to keep in mind. Ensure that: \*... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/autoscaling/cluster-autoscaler.adoc | mainline | aws-eks-best-practices | [
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for your use case. === Vertically Autoscaling the Cluster Autoscaler The simplest way to scale the Cluster Autoscaler to larger clusters is to increase the resource requests for its deployment. Both memory and CPU should be increased for large clusters, though this varies significantly with cluster size. The autoscalin... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/autoscaling/cluster-autoscaler.adoc | mainline | aws-eks-best-practices | [
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... --nodes=1:10:k8s-worker-asg-1 --nodes=1:10:k8s-worker-asg-2 --- metadata: name: cluster-autoscaler namespace: cluster-autoscaler-2 ... --nodes=1:10:k8s-worker-asg-3 --nodes=1:10:k8s-worker-asg-4 .... Ensure that: \* Each shard is configured to point to a unique set of EC2 Auto Scaling Groups \* Each shard is deploy... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/autoscaling/cluster-autoscaler.adoc | mainline | aws-eks-best-practices | [
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within `--max-node-provision-time`, it will attempt to scale an EC2 Auto Scaling group matching the name \_p2-node-group\_. This value defaults to 15 minutes and can be reduced for more responsive node group selection, though if the value is too low, it can cause unnecessary scale outs. === Overprovisioning The Cluster... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/autoscaling/cluster-autoscaler.adoc | mainline | aws-eks-best-practices | [
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`balance-similar-node-groups=true`. \* Node Groups are configured with identical settings except for different availability zones and EBS Volumes. === Co-Scheduling Machine learning distributed training jobs benefit significantly from the minimized latency of same-zone node configurations. These workloads deploy multip... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/autoscaling/cluster-autoscaler.adoc | mainline | aws-eks-best-practices | [
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|10 seconds |max-empty-bulk-delete |Maximum number of empty nodes that can be deleted at the same time. |10 |scale-down-delay-after-add |How long after scale up that scale down evaluation resumes |10 minutes |scale-down-delay-after-delete |How long after node deletion that scale down evaluation resumes, defaults to sca... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/autoscaling/cluster-autoscaler.adoc | mainline | aws-eks-best-practices | [
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//!!NODE\_ROOT [[cluster-autoscaling,cluster-autoscaling.title]] = Cluster Autoscaling :doctype: book :sectnums: :toc: left :icons: font :experimental: :idprefix: :idseparator: - :sourcedir: . :info\_doctype: chapter :info\_title: Best Practices for Cluster Autoscaling :info\_abstract: Best Practices for Cluster Autosc... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/autoscaling/index.adoc | mainline | aws-eks-best-practices | [
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//!!NODE\_ROOT [[hybrid,hybrid.title]] = Best Practices for Hybrid Deployments :doctype: book :sectnums: :toc: left :icons: font :experimental: :idprefix: :idseparator: - :sourcedir: . :info\_doctype: chapter :info\_title: Best Practices for Hybrid Deployments :info\_abstract: Best Practices for Hybrid Deployments :inf... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/index.adoc | mainline | aws-eks-best-practices | [
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[.topic] [[hybrid-nodes-host-creds,hybrid-nodes-host-creds.title]] = Host credentials through network disconnections :info\_doctype: section :info\_title: Host credentials through network disconnections :info\_titleabbrev: Host credentials :info\_abstract: Host credentials through network disconnections EKS Hybrid Node... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/network-disconnections/host-credentials.adoc | mainline | aws-eks-best-practices | [
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network disconnections typically occurs within seconds of network restoration, because the kubelet calls `aws\_signing\_helper credential-process` to obtain credentials on demand. Although not directly related to hybrid nodes or network disconnections, you can configure notifications and alerts for certificate expiry w... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/network-disconnections/host-credentials.adoc | mainline | aws-eks-best-practices | [
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[.topic] [[hybrid-nodes-network-disconnection-best-practices,hybrid-nodes-network-disconnection-best-practices.title]] = Best practices for stability through network disconnections :info\_doctype: section :info\_title: Best practices for stability through network disconnections :info\_titleabbrev: Best practices :info\... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/network-disconnections/best-practices.adoc | mainline | aws-eks-best-practices | [
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metrics to observe the network traffic into and out of your TGW or VGW. You can create alarms for these metrics to detect scenarios where network traffic dips below normal levels, indicating a potential network issue between hybrid nodes and the EKS control plane. The TGW and VGW metrics are described in the following ... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/network-disconnections/best-practices.adoc | mainline | aws-eks-best-practices | [
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functionality is integrated with the Cilium agent, and the Cilium agent will continuously restart when disconnected from the Kubernetes control plane. The reason for the restart is due to Cilium's health check failing because its health is coupled with access to the Kubernetes control plane (see https://github.com/cili... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/network-disconnections/best-practices.adoc | mainline | aws-eks-best-practices | [
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with `tolerationSeconds` for the unreachable taint is shown below. In the example, `tolerationSeconds` is set to `1800` (30 minutes), which means pods running on unreachable nodes will only be evicted if the network disconnection lasts longer than 30 minutes. [source,yaml,subs="verbatim,attributes,quotes"] ---- apiVers... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/network-disconnections/best-practices.adoc | mainline | aws-eks-best-practices | [
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//!!NODE\_ROOT [.topic] [[hybrid-nodes-kubernetes-pod-failover,hybrid-nodes-kubernetes-pod-failover.title]] = Kubernetes pod failover through network disconnections :doctype: section :info\_doctype: section :info\_title: Kubernetes pod failover through network disconnections :info\_titleabbrev: Kubernetes pod failover ... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/network-disconnections/kubernetes-pod-failover.adoc | mainline | aws-eks-best-practices | [
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number of retries allowed for the kubelet to post node status. |40 |40 |No |node-lifecycle-controller |large-cluster-size-threshold |The number of nodes at which the node-lifecycle-controller treats the cluster as large for eviction logic. `--secondary-node-eviction-rate` is overridden to 0 for clusters of this size or... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/network-disconnections/kubernetes-pod-failover.adoc | mainline | aws-eks-best-practices | [
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on any nodes during the disconnection and subsequent reconnection. === Scenario 3: Majority zone disruption \*Expected result\*: Pods on unreachable nodes are not evicted and continue running on those nodes. A majority zone disruption means that most nodes in a given zone are disconnected from the Kubernetes control pl... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/network-disconnections/kubernetes-pod-failover.adoc | mainline | aws-eks-best-practices | [
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to a network disconnection, it cannot retrieve the information needed to start the pods. In this scenario, local troubleshooting tools such as the `crictl` CLI cannot be used to start pods manually as a “break-glass” measure. Kubernetes typically removes failed pods and creates new ones rather than restarting existing ... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/network-disconnections/kubernetes-pod-failover.adoc | mainline | aws-eks-best-practices | [
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[.topic] [[hybrid-nodes-app-network-traffic,hybrid-nodes-app-network-traffic.title]] = Application network traffic through network disconnections :info\_doctype: section :info\_title: Application network traffic through network disconnections :info\_titleabbrev: Application network traffic :info\_abstract: Application ... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/network-disconnections/app-network-traffic.adoc | mainline | aws-eks-best-practices | [
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modes for load balancing: https://metallb.universe.tf/concepts/layer2/[L2 mode] and https://metallb.universe.tf/concepts/bgp/[BGP mode]. Reference the MetalLB documentation for details of how these load balancing modes work and their limitations. The validation for this guide used MetalLB in L2 mode, where one machine ... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/network-disconnections/app-network-traffic.adoc | mainline | aws-eks-best-practices | [
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:443: i/o timeout" logger="UnhandledError" "Unhandled Error" err="k8s.io/client-go/informers/factory.go:160: Failed to watch \*v1.EndpointSlice: failed to list \*v1.EndpointSlice: Get \"https:///apis/discovery.k8s.io/v1/endpointslices?labelSelector=%21service.kubernetes.io%2Fheadless%2C%21service.kubernetes.io%2Fservic... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/network-disconnections/app-network-traffic.adoc | mainline | aws-eks-best-practices | [
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//!!NODE\_ROOT [.topic] [[hybrid-nodes-network-disconnections,hybrid-nodes-network-disconnections.title]] = EKS Hybrid Nodes and network disconnections :doctype: section :sectnums: :toc: left :icons: font :experimental: :idprefix: :idseparator: - :sourcedir: . :info\_doctype: section :info\_title: EKS Hybrid Nodes and ... | https://github.com/aws/aws-eks-best-practices/blob/mainline/latest/bpg/hybrid/network-disconnections/index.adoc | mainline | aws-eks-best-practices | [
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# Bee Health Detection Example This repository contains example code detect if a bee is healthy. Specifically, given a picture and structured attributes about a bee, it predicts if the bee is healthy. The code leverages pre-trained TF Hub image modules and uses Google Cloud Machine Learning Engine to train a TensorFlow... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/cloudml-bee-health-detection/README.md | main | gcp-professional-services | [
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After you’ve built a successful prototype of a machine learning model, there’s still plenty of things to do. To some extent, your journey as an ML engineer only begins here. You’d need to take care about plenty of things such as operationalization of your model: monitoring, CI/CD, reliability and reproducibility, and m... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/tensorflow-unit-testing/README.md | main | gcp-professional-services | [
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we don’t check whether the training itself makes sense - i.e., whether a loss decreases to any meaningful value. But more about it later. Let’s have a look at a simple example of how to test a model from this [tutorial](https://www.tensorflow.org/tutorials/keras/regression). ```python class ExampleModelTest(tf.test.Tes... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/tensorflow-unit-testing/README.md | main | gcp-professional-services | [
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# JavaScript to QueryParam This example shows a basic proxy that converts a simple, single-level JSON document posted into the endpoint to a series of query parameters sent to the target. For example, if the following were posted: ```json { "foo": "bar", "baz": "quux" } ``` The resulting back end query would be: `GET h... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/apigee-json-to-queryparam/README.md | main | gcp-professional-services | [
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# Dataflow Flex Template: De-identify CSVs in GCS (DLP) → BigQuery A runnable Flex Template that takes CSVs in Cloud Storage, calls DLP to de-identify sensitive fields, and writes sanitized rows to BigQuery. > \*\*Prerequisites\*\* > - Google Cloud project with billing enabled > - You can run commands either in \*\*Clo... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/dataflow-dlp-flex-deid/README.md | main | gcp-professional-services | [
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mismatch\*\* → ensure headers match CSV columns and your DLP template. - \*\*Permission denied\*\* → verify runner service account roles listed in “One-time resources”. - \*\*Template not found\*\* → check `deidentify\_template\_name` and its location (`global` or regional). --- | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/dataflow-dlp-flex-deid/README.md | main | gcp-professional-services | [
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# gRPC Example This example creates a gRCP server that connect to redis to find the name of a user for a given user id. ## Application Project Structure ``` . └── grpc\_example\_redis └── src └── main ├── java └── com.example.grpc ├── client └── ConnectClient # Example Client ├── server └── ConnectServer # Initializes ... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/grpc_redis_example/README.md | main | gcp-professional-services | [
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# ABAP Utility for Bulk Creation of CDS Views ## Summary This ABAP utility program streamlines the creation of CDS views designed for capturing delta changes in SAP tables. These delta-enabled views are crucial for replicating data to BigQuery, enabling powerful data analytics on SAP data. By automating this process, t... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/sap-bigquery-cds-generator/README.md | main | gcp-professional-services | [
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the output, the same logs are saved in the table ZCDS\_CR\_LOG | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/sap-bigquery-cds-generator/README.md | main | gcp-professional-services | [
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# Distributed Load-Testing with Jmeter ## Build and Push jmeter-master docker File ```Dockerfile FROM justb4/jmeter:latest EXPOSE 60000 ``` ```bash docker build --tag="/jmeter-master:latest" -f Dockerfile-master . docker push /jmeter-master:latest ``` ## Build and Push jmeter-slave docker File ```Dockerfile FROM justb4... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/gke-distributed-load-test-jmeter/README.md | main | gcp-professional-services | [
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# Overview The purpose of this walkthrough is to create a [Dataflow](https://cloud.google.com/dataflow) streaming pipeline to read XML encoded messages from [PubSub](https://cloud.google.com/pubsub):  ## Pipeline This pipeline is developed with the [Beam Pyth... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/dataflow-xml-pubsub-to-gcs/README.md | main | gcp-professional-services | [
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# Dataflow PubSub XML to Google cloud storage sample pipeline ## License Copyright 2023 Google LLC Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at https://www.apache.org/licenses/LICENSE-2.0 Unless r... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/dataflow-xml-pubsub-to-gcs/python/README.md | main | gcp-professional-services | [
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Monitor the Dataflow Job Navigate to https://console.cloud.google.com/dataflow/jobs to locate the job you just created. Clicking on the job will let you navigate to the job monitoring screen. ## Debug the Pipeline \*\*Optionally\*\* This sample contains the necessary bindings to debug step by step and/or breakpoint thi... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/dataflow-xml-pubsub-to-gcs/python/README.md | main | gcp-professional-services | [
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# CloudML Deep Collaborative Filtering A simple machine learning system capable of recommending songs given a user as a query using collaborative filtering and TensorFlow. Unlike classic matrix factorization approaches, using a neural network allows user and item features to be included during training. This example co... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/cloudml-collaborative-filtering/README.md | main | gcp-professional-services | [
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absolute value to get a value between 0 and 1. 7. Calculate error using log loss and train the model. 8. Evaluate the model performance by sampling 1000 random items and calculating the average recall@k when each positive sample's item is ranked against these random items for the sample's user. 9. Export a `SavedModel`... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/cloudml-collaborative-filtering/README.md | main | gcp-professional-services | [
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# React single page app on Cloud Run + Cloud Storage ## Introduction This blueprint contains a simple React single page application created with [`create-react-app`](https://create-react-app.dev/) and necessary Terraform resources to deploy it in on Google Cloud. The blueprint also contains a very simple Python backend... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/react-spa-app/README.md | main | gcp-professional-services | [
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load balancers active in this configuration. ## Variables | name | description | type | required | default | | ---------------------------------- | ------------------------------------------------------------------------------------- | :-----------------------------------------------------------------------------------... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/react-spa-app/README.md | main | gcp-professional-services | [
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# NetApp Cloud Volumes Service (CVS) Terraform Example This example shows how to deploy NetApp CVS volumes using terraform (i.e. without using any external modules). This code also enables replication between volumes if \*replication\* variable is set as \*true\*. ## Prerequisites 1. You must have a recent version of T... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/tf-netapp-cvs/README.md | main | gcp-professional-services | [
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# Automated BigQuery Exports via Email This serverless solution enables users to regularly send BigQuery export results via email. The end users will get a scheduled email with a link to either a Google Cloud Storage [signed URL](https://cloud.google.com/storage/docs/access-control/signed-urls) or an [unsigned URL](htt... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/bq-email-exports/README.md | main | gcp-professional-services | [
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## Providers | Name | Version | |------|---------| | archive | n/a | | google | ~> 3.48.0 | ## Inputs | Name | Description | Type | Default | Required | |------|-------------|------|---------|:-----:| | bq\\_dataset\\_expiration | The default lifetime of all tables in the dataset in milliseconds. The minimum value is 3... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/bq-email-exports/terraform/README.md | main | gcp-professional-services | [
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| | sender\\_email\\_address | Email address of sender. | `any` | n/a | yes | | sendgrid\\_api\\_key | API key for authenticating the sending of emails through SendGrid API | `any` | n/a | yes | | service\\_acct\\_name | The service account used by the three BQ email export Cloud Functions | `any` | n/a | yes | | servi... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/bq-email-exports/terraform/README.md | main | gcp-professional-services | [
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\*\*Table of Contents\*\* - [Data Lake](#data-lake) - [Troubleshooting](#troubleshooting) - [Issues with destroying KMS Resources](#issues-with-destroying-kms-resources) - [Requirements](#requirements) - [Providers](#providers) - [Inputs](#inputs) - [Outputs](#outputs) # Data Lake This module is intended to spin up a b... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/kerberized_data_lake/README.md | main | gcp-professional-services | [
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qualified domain name for cluster on which to run presto / spark jobs | | gcs\\_encrypted\\_keytab\\_path | GCS path to keep keytabs | | kms\\_key | kms key for decrypting keytabs | | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/kerberized_data_lake/README.md | main | gcp-professional-services | [
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\*\*Table of Contents\*\* - [Template Bash Script Module](#template-bash-script-module) - [Example Usage](#example-usage) - [Requirements](#requirements) - [Providers](#providers) - [Inputs](#inputs) - [Outputs](#outputs) # Template Bash Script Module This module is responsible for handling replacement of variables in ... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/kerberized_data_lake/modules/template_bash_script/README.md | main | gcp-professional-services | [
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# Terraform Google Cloud IAM Deny and Organization Policies This Terraform configuration demonstrates how to implement a series of security guardrails within a Google Cloud organization. It leverages IAM Deny Policies and Organization Policies to restrict high-privilege permissions and enforce organizational standards.... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/iam-deny/README.md | main | gcp-professional-services | [
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directory of this example. ## Installation and Deployment 1. \*\*Clone Repository:\*\* If you haven't already, clone the repository containing this example to your local machine. ```bash # Example: Replace with the actual repository URL git clone https://github.com/kevinschmidtG/professional-services.git cd examples/ia... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/iam-deny/README.md | main | gcp-professional-services | [
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| List of principals exempt from the billing deny rule. | `list(string)` | `[]` | No | | `sec\_exception\_principals` | List of principals exempt from the security deny rule. | `list(string)` | `[]` | No | | `top\_exception\_principals` | List of principals exempt from the organization-level deny policy. | `list(string... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/iam-deny/README.md | main | gcp-professional-services | [
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# Data Format Description Language ([DFDL](https://en.wikipedia.org/wiki/Data\_Format\_Description\_Language)) Processor Example This module is a example how to process a binary using a DFDL definition. The DFDL definitions are stored in a Bigtable database. The application send a request with the binary to process to ... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/dfdl-bigtable-pubsub-example/README.md | main | gcp-professional-services | [
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needed to run this example. #### Topics To run this example two topics need to be created: 1. A topic to publish the final json output: "data-output-json-topic" 2. A topic to publish the binary to be processed: "data-input-binary-topic" #### Subscription The following subscriptions need to be created: 1. A subscription... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/dfdl-bigtable-pubsub-example/README.md | main | gcp-professional-services | [
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# A 'state-scalable' project factory pattern with Terragrunt ## Overview Resolves the problem of state volume explotion with project factory. Terragrunt helps with that by: 1. Providing a dynamic way to configure [remote\_state](https://terragrunt.gruntwork.io/docs/features/keep-your-remote-state-configuration-dry/#kee... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/terragrunt-project-factory-gcp/README.md | main | gcp-professional-services | [
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-> terragrunt.hcl terraform { # Pull the terraform configuration from the local file system. Terragrunt will make a copy of the source folder in the # Terragrunt working directory (typically `.terragrunt-cache`). source = "../..//src" # Files to include from the Terraform src directory include\_in\_copy = [ "main.tf", ... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/terragrunt-project-factory-gcp/README.md | main | gcp-professional-services | [
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Copyright 2023 Google LLC Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed un... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/terragrunt-project-factory-gcp/src/README.md | main | gcp-professional-services | [
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## DAG to DAG dependency between multiple Composer Clusters Dependencies between Airflow DAGs might be inevitable. Within a composer instance, one can define a dag to dag dependency easily using operators like TriggerDagRunOperator and ExternalTaskSensor, for example, when you have a task in one DAG that triggers anoth... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/multicluster-dag-dependencies/Readme.md | main | gcp-professional-services | [
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{ "environment\_name": "composer-env-1", "dag\_id": "dag\_id\_3\_downstream" } ] } } ``` Each upstream dag has an object in GCS bucket. The environment name to Airflow web UI URL mapping is stored in a configuration environment(`composer-url-mapping-{env}.json`). Make sure to replace the `proect\_id` and `url` in the m... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/multicluster-dag-dependencies/Readme.md | main | gcp-professional-services | [
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# Dataproc Persistent History Server This repo houses the example code for a blog post on using a persistent history server to view job history about your Spark / MapReduce jobs and aggregated YARN logs from short-lived clusters on GCS.  ## Directory structure - `... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/dataproc-persistent-history-server/README.md | main | gcp-professional-services | [
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Compute zone. ``` cd workflow\_templates sed -i 's/PROJECT/your-gcp-project-id/g' \* sed -i 's/HISTORY\_BUCKET/your-history-bucket/g' \* sed -i 's/HISTORY\_SERVER/your-history-server/g' \* sed -i 's/REGION/us-central1/g' \* sed -i 's/ZONE/us-central1-f/g' \* sed -i 's/SUBNET/your-subnet-id/g' \* cd cluster\_templates s... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/dataproc-persistent-history-server/README.md | main | gcp-professional-services | [
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# BigQuery Benchmark Repos Customers new to BigQuery often have questions on how to best utilize the platform with regards to performance. For example, a common question which has routinely resurfaced in this area is the performance of file loads into BigQuery, specifically the optimal file parameters (file type, # col... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/bq_benchmarks/README.md | main | gcp-professional-services | [
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will include the type of table, type of query, and the table properties. \*\*Table Type\*\*: \* `BQ\_MANAGED`: Tables located within and managed by BigQuery. \* `EXTERNAL`: Data located in GCS files, which are used to create a temporary external table for querying. \*\*Query Type\*\*: \* `SIMPLE\_SELECT\_\*`: Select al... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/bq_benchmarks/README.md | main | gcp-professional-services | [
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for both the File Loader Benchmark and the Federated Query Benchmark. They can be configured in the `FILE\_PARAMETERS` dictionary in [`generic\_benchmark\_tools/file\_parameters.py`](generic\_benchmark\_tools/file\_parameters.py). Currently, no file parameters can be added to the dictionary, as this will cause errors. ... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/bq_benchmarks/README.md | main | gcp-professional-services | [
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in the resized staging dataset: `100\_STRING\_10\_10MB`, `100\_STRING\_10\_100MB`, `100\_STRING\_10\_1GB`, `100\_STRING\_10\_2GB`. To run the process of creating staging and resized staging tables, run the following command: ``` python bq\_benchmark.py \ --create\_staging\_tables \ --bq\_project\_id= \ --staging\_datas... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/bq_benchmarks/README.md | main | gcp-professional-services | [
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combination of files, but where numFiles > 1. More specifically, it is copied 100 times for `numFiles`=100, 1000 times for `numFiles`=1000, and 10000 times for `numFiles`=10000. Copying is much faster than extracting each table tens of thousands of times. As an example, the files listed above are copied to create the f... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/bq_benchmarks/README.md | main | gcp-professional-services | [
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Before the tables are deleted, the tables and their respective files can be used to run the Federated Query Benchmark. If running the two benchmarks independently, each file will be used to create a BigQuery table two different times. Running the two benchmarks at the same time can save time if results for both benchma... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/bq_benchmarks/README.md | main | gcp-professional-services | [
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were loaded from before the tables are deleted. If results for both benchmarks are desired, this will save time when compared to running each benchmark independently, since the same tables needed for the File Loader Benchmark are needed for the Federated Query Benchmark. It has a value of `store\_true`, so this flag wi... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/bq_benchmarks/README.md | main | gcp-professional-services | [
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reason should be stored in a different bucket. `--results\_table\_name`: Name of the results table to hold relevant information about the benchmark loads. `--results\_dataset\_id`: Name of the dataset that holds the results table. `--bq\_logs\_dataset`: Name of dataset hold BQ logs table. This dataset must be in projec... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/bq_benchmarks/README.md | main | gcp-professional-services | [
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# BQ Translation Validator A utility to compare 2 SQL Files and point basic differences like column names, table names, joins, function names etc. ## Business Requirements 1. Validation of the SQL by comparing both the Legacy Source SQL and Bigquery SQL 2. Ability to quickly identify any translation errors, right at th... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/bigquery-translation-validator-utility/README.md | main | gcp-professional-services | [
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in `./config/functions.csv`. 3. Run the utility `python3 main.py -input-path=path/to/input/folder -output-path=path/to/output/folder` 4. Check the result in `validation-translation.xlsx` and `log\_files` Folder. ### Run with Test Files in GCS Below packages are need to run the script:pandas, sqlparse, XlsxWriter, googl... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/bigquery-translation-validator-utility/README.md | main | gcp-professional-services | [
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# gRPC Example This example creates a gRCP server that connect to spanner to find the name of user for a given user id. ## Application Project Structure ``` . └── grpc\_example └── src └── main ├── java └── com.example.grpc ├── client └── ConnectClient # Example Client ├── server └── ConnectServer # Initializes gRPC Se... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/grpc_spanner_example/README.md | main | gcp-professional-services | [
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# Home Appliances’ Working Status Monitoring Using Gross Power Readings The popularization of IoT devices and the evolvement of machine learning technologies have brought tremendous opportunities for new businesses. We demonstrate how home appliances’ (e.g. kettle and washing machine) working status (on/off) can be inf... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/e2e-home-appliance-status-monitoring/README.md | main | gcp-professional-services | [
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>> app.yaml echo " GOOGLE\_CLOUD\_PROJECT: '${GOOGLE\_PROJECT\_ID}'" >> app.yaml # deploy application engine, choose any region that suits and answer yes at the end. gcloud --project ${GOOGLE\_PROJECT\_ID} app deploy # create a pubsub topic "data" and a subscription in the topic. # this is the pubsub between IoT device... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/e2e-home-appliance-status-monitoring/README.md | main | gcp-professional-services | [
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# Workload Identity Federation This repository provides an example for creating a Workload Identity Federation (WIF) Component that could be used for authenticating to Google Cloud from a GitLab CI/CD job using a JSON Web Token (JWT) token. This configuration generates on-demand, short-lived credentials without needing... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/workload_identity_federation/README.md | main | gcp-professional-services | [
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## Ingesting CCAI-Insights Data to BigQuery using Cloud Composer [Contact Center AI (CCAI) Insights](https://cloud.google.com/solutions/ccai-insights?hl=en) can be used to generate insights from voice and chat conversations. This repo will walk you through how to leverage this tool to analyze call conversations and gen... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/ccai-insight-export-composer/Readme.md | main | gcp-professional-services | [
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3:\*\* Create a json varaible for ccai-insight configuration by navigating to Admin > Variables in Airflow UI. Below is the screenshot.  You can also add the variable using gcloud command line. ``` gcloud composer environments run $COMPOSER\_ENVIRONE... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/ccai-insight-export-composer/Readme.md | main | gcp-professional-services | [
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# Conversational Hotel Booking Agent The Conversational Hotel Booking Agent is a custom Generative AI (GenAI) agent specialized in handling hotel bookings through a conversational user experience (UX). This repository contains the agent's source code and deployment instructions. The integrated solution features: \* \*\... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/mcptoolbox-bq-claude-slack-agent/README.md | main | gcp-professional-services | [
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table.  This example demonstrates the power of a conversational UX implemented through a specialized Agent, MCP, and a well-defined toolset to accomplish complex tasks within a specific domain. The example da... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/mcptoolbox-bq-claude-slack-agent/README.md | main | gcp-professional-services | [
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Token; this token is typically handled by the Spring Boot Slack SDK and doesn't usually require manual configuration in this project's default setup. 4. \*\*Configure Bot Token Scopes\*\*: \* Return to "OAuth & Permissions". \* Scroll to "Scopes" and under "Bot Token Scopes", add the following: \* `app\_mentions:read`:... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/mcptoolbox-bq-claude-slack-agent/README.md | main | gcp-professional-services | [
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Deploys the MCP Toolbox service to Cloud Run. - Deploys the Slackbot service to Google Cloud Run, configuring it with the MCP Toolbox URL for tool discovery. After the script completes successfully, the Slackbot will be deployed and running on Cloud Run. Once these steps are completed and the application is deployed wi... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/mcptoolbox-bq-claude-slack-agent/README.md | main | gcp-professional-services | [
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# Terraform Configuration for Spring Boot Cloud Run Deployment This directory contains Terraform code to provision the necessary Google Cloud infrastructure for deploying the Spring Boot application to Cloud Run, along with supporting services like BigQuery, MCP Toolbox, and the needed permissions between components. B... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/mcptoolbox-bq-claude-slack-agent/infra/README.md | main | gcp-professional-services | [
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to assign specific values to the variables defined in `variables.tf`, such as your Google Cloud Project ID and preferred region. \*\*It is crucial to copy this file to `terraform.tfvars` and customize it before running `terraform apply`.\*\* - \*\*`bigquery.tf`\*\*: - \*\*Purpose\*\*: Manages all BigQuery-related resou... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/mcptoolbox-bq-claude-slack-agent/infra/README.md | main | gcp-professional-services | [
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- `artifact\_registry\_repository\_id`: The ID of the Artifact Registry repository. - \*\*Other Files in `infra/`\*\*: - `infra/bigquery/data.csv`: Sample data loaded into the BigQuery table. - `infra/mcptoolbox/tools.yaml.tpl`: Template for the MCP Toolbox configuration, which is stored in Secret Manager. ## Cleaning ... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/mcptoolbox-bq-claude-slack-agent/infra/README.md | main | gcp-professional-services | [
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## Summary Time series data is either not being reported or failing to be ingested. ## Impact We are not confident in the state of the application. ## Triage ### Case 1: All time-series absent 1. Check for any deployments that might indicate a change in the reporting logic. 2. Check whether Stackdriver Monitoring is re... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/alert-absence-dedup/policy_doc.md | main | gcp-professional-services | [
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# Stackdriver alerts for missing timeseries This example demonstrates creating alerts for missing monitoring data with Stackdriver in a way that duplicate alerts are not generated. For example, suppose that you have 100 timeseries and you want to find out when any one of them is missing. If one or two timeseries are mi... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/alert-absence-dedup/README.md | main | gcp-professional-services | [
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a few minutes the alert should resolve itself. Stop the process and restart it with only one partition: ```shell ./alert-absence-demo --labels "1" ``` Check that only one alert is fired. Stop the process and do not restart it. You should see an alert that indicates all time series are absent. | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/alert-absence-dedup/README.md | main | gcp-professional-services | [
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# Running End-to-End test for Dataflow pipelines We all know testing dataflow applications is important. But when building data ingestion and transformation, sometimes thing gets too technical and hence stakeholders like analyst, data scientist have no visibility on what test are being performed. In this sample code. W... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/e2e-test-dataflow/Readme.md | main | gcp-professional-services | [
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the dataflow and create buckets in GCS and create BigQuery dataset in the project. `export GOOGLE\_APPLICATION\_CREDENTIALS=<` `mvn test` | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/e2e-test-dataflow/Readme.md | main | gcp-professional-services | [
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## Cloud Composer Examples: This repo contains the following examples of using Cloud Composer, Google Cloud Platform's managed Apache Airflow service: 1. [Composer Dataflow Examples](composer\_dataflow\_examples/README.md) a. [Simple Load DAG](composer\_dataflow\_examples/simple\_load\_dag.py): provides a common patter... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/cloud-composer-examples/README.md | main | gcp-professional-services | [
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## Cloud Composer: Ephemeral Dataproc Cluster for Spark Job ### Workflow Overview \*\*\*  An HTTP POST to the airflow endpoint from an on-prem system is used as a trigger to initiate the workflow. At a high level the C... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/cloud-composer-examples/composer_http_post_example/README.md | main | gcp-professional-services | [
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[these](https://cloud.google.com/composer/docs/quickstart) steps to create a Cloud Composer environment if needed (\*cloud-composer-env\*). We will set these variables in the composer environment. | Key | Value |Example | | :--------------------- |:---------------------------------------------- |:----------------------... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/cloud-composer-examples/composer_http_post_example/README.md | main | gcp-professional-services | [
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# Airflow Metadata Export This repo contains an example Airflow DAG Factory that exports data from a list of airflow tables into a BigQuery location. The goal of this example is to provide a common pattern to export data to BigQuery for auditing and reporting purposes. ## DAG Factory Overview At a high-level the factor... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/cloud-composer-examples/airflow_metadata_export/README.md | main | gcp-professional-services | [
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## Cloud Composer workflow using Cloud Dataflow ##### This repo contains an example Cloud Composer workflow that triggers Cloud Dataflow to transform, enrich and load a delimited text file into Cloud BigQuery. The goal of this example is to provide a common pattern to automatically trigger, via Google Cloud Function, a... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/cloud-composer-examples/composer_dataflow_examples/README.md | main | gcp-professional-services | [
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| | input\_field\_names | \*comma-separated-field-names-for-delimited-file\*|state,gender,year,name,number,created\_date| | bq\_output\_table | \*bigquery-output-table\* |my\_dataset.usa\_names | | email | \*some-email@mycompany.com\* |some-email@mycompany.com | The variables can be set as follows: `gcloud composer env... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/cloud-composer-examples/composer_dataflow_examples/README.md | main | gcp-professional-services | [
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# bigquery-analyze-realtime-reddit-data ## Table Of Contents 1. [Use Case](#use-case) 2. [About](#about) 3. [Architecture](#architecture) 4. [Guide](#guide) 5. [Sample](#sample) ---- ## Use-case Simple deployment of a ([reddit](https://www.reddit.com)) social media data collection architecture on Google Cloud Platform.... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/bigquery-analyze-realtime-reddit-data/README.md | main | gcp-professional-services | [
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# 🚀 GCC Creative Studio has moved! This project has moved to a new repository: 👉 \*\*[https://github.com/GoogleCloudPlatform/gcc-creative-studio](https://github.com/GoogleCloudPlatform/gcc-creative-studio)\*\* ## What this means for you If you have already deployed Creative Studio from this repository, please follow ... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/creative-studio/README.md | main | gcp-professional-services | [
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# Using Batching in Cloud Pub/Sub Java client API. This example provides guidance on how to use [Pub/Sub's Java client API](https://cloud.google.com/pubsub/docs/reference/libraries) to batch records that are published to a Pub/Sub topic. Using [BatchingSettings](http://googleapis.github.io/gax-java/1.4.1/apidocs/com/go... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/pubsub-publish-avro-example/README.md | main | gcp-professional-services | [
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# Dataproc lifecycle management orchestrated by Composer Writing DAGs isn’t practical when having multiple DAGs that run similar Dataproc Jobs, and want to share clusters efficiently, with just some parameters changing between them. Here makes sense to dynamically generate DAGs. Using this project you can deploy multip... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/dataproc-lifecycle-via-composer/README.md | main | gcp-professional-services | [
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of Composer Environment provisioning, you should expect for successful completion along with a list of the created resources. ## Running DAGs DAGs will run as per \*\*Schedule\*\*, \*\*StartDate\*\*, and \*\*Catchup\*\* configuration in DAG configuration file, or can be triggered manually trough Airflow web console aft... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/dataproc-lifecycle-via-composer/README.md | main | gcp-professional-services | [
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# dataproc-job-optimization-guide ---- ## Table Of Contents 1. [About](#About) 2. [Guide](#Guide) 3. [Results](#Results) 4. [Next Steps](#Next-steps) ---- ## About This guide is designed to optimize performance and cost of applications running on Dataproc clusters. Because Dataproc supports many big data technologies -... | https://github.com/GoogleCloudPlatform/professional-services/blob/main/examples/dataproc-job-optimization-guide/README.md | main | gcp-professional-services | [
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