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Establish a Data Lake from Cloud Logging to BigQuery with Apigee

Establish a Data Lake from Cloud Logging to BigQuery with Apigee

1 hora 30 minutos 5 créditos

GSP669

Google Cloud Self-Paced Labs

Introduction

Apigee Edge enables you to quickly expose backend services as APIs. You do this by creating an API proxy that provides a facade for the backend service that you want to expose. You only need to provide the network address for the backend service, along with some information that Edge uses to create the API proxy that is exposed to developers.

The API proxy decouples your backend service implementation from the API that developers consume. This shields developers from future changes to your backend services. As you update backend services, developers, insulated from those changes, can continue to call the API uninterrupted.

API proxies give you the full power of Apigee's API platform to secure API calls, throttle traffic, mediate messages, control error handling, cache things, build developer portals, document APIs, analyze API traffic data, make money on the use of your APIs, protect against bad bots, and more.

Apigee Extensions is a feature that can help you integrate external resources into your API proxies. For example, you could integrate Google Cloud services such as Google Cloud Storage, Cloud Logging (formerly Stackdriver Logging), BigQuery etc. with your API proxy running on Apigee Edge. At run time, an API proxy uses the extension to exchange requests and responses with the external resource.

In this lab, you will learn how to export Cloud Logging data to BigQuery for analysis, then provide access to this aggregated data via APIs using Apigee Edge.

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Puntuación

—/100

Create a sink

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Create a service account using IAM and service key

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Exporting logs in bigquery

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Testing the API Proxy in Apigee REST Client

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/ 25