Google Updated Associate-Cloud-Engineer Exam Questions and Answers by jose

Comprehensive and Detailed In Depth Explanation:

The requirement is to export logs from Cloud Logging to a third-party SaaS tool with the least amount of delay possible. Let's analyze each option:

A. Cloud Scheduler, Cloud Function, and querying Cloud Logging: This approach introduces a delay based on the Cloud Scheduler's cron job frequency. The Cloud Function would periodically query Cloud Logging, which might not capture the logs in real-time. This does not meet the "least amount of delay possible" requirement.

B. Cloud Logging sink to Pub/Sub, SaaS tool subscribing to Pub/Sub: Cloud Logging sinks can be configured to export logs in near real-time as they are ingested into Cloud Logging. Pub/Sub is a messaging service designed for asynchronous and near real-time message delivery. By configuring the sink to send logs to a Pub/Sub topic, and having the SaaS tool subscribe to this topic, logs can be delivered to the SaaS tool with minimal delay. This aligns with the requirement for immediate export.

C. Cloud Logging sink to Cloud Storage, SaaS tool reading Cloud Storage: Exporting logs to Cloud Storage involves a batch-oriented approach. Logs are typically written to files periodically. The SaaS tool would then need to poll or be configured to read these files, introducing a significant delay compared to a streaming approach.

D. Cloud Logging sink to BigQuery, SaaS tool querying BigQuery: Similar to Cloud Storage, exporting to BigQuery is more suitable for analytical purposes. The SaaS tool would need to periodically queryBigQuery, which introduces latency and is not the most efficient way to achieve near real-time log delivery.

Therefore, configuring a Cloud Logging sink to Pub/Sub and having the SaaS tool subscribe to the Pub/Sub topic provides the lowest latency for exporting logs.

Google Cloud Documentation References:

Cloud Logging Sinks Overview: https://cloud.google.com/logging/docs/export/configure_export_v2 - This document explains how to create and manage Cloud Logging sinks, including the available destinations.

Pub/Sub Overview: https://cloud.google.com/pubsub/docs/overview - This highlights Pub/Sub's capabilities for real-time message delivery and its use cases in streaming data.

Exporting Logs with Cloud Logging: https://cloud.google.com/logging/docs/export - This provides a comprehensive guide to exporting logs from Cloud Logging to various destinations, emphasizing Pub/Sub for streaming.

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IAP controls access to your App Engine apps and Compute Engine VMs running on Google Cloud. It leverages user identity and the context of a request to determine if a user should be allowed access. IAP is a building block toward BeyondCorp, an enterprise security model that enables employees to work from untrusted networks without using a VPN.

By default, IAP uses Google identities and IAM. By leveraging Identity Platform instead, you can authenticate users with a wide range of external identity providers, such as:

Email/password

OAuth (Google, Facebook, Twitter, GitHub, Microsoft, etc.)

SAML

OIDC

Phone number

Custom

Anonymous

This is useful if your application is already using an external authentication system, and migrating your users to Google accounts is impractical.

https://cloud.google.com/iap/docs/u sing-tcp-forwarding#grant-permission

A tag is simply a character string added to a tags field in a resource, such as Compute Engine virtual machine (VM) instances or instance templates. A tag is not a separateresource, so you cannot create it separately. All resources with that string are considered to have that tag. Tags enable you to make firewall rules and routes applicable to specific VM instances.

https://cloud.google.com/compute/docs/instance-groups

https://cloud.google.com/load-bal ancing/docs/network/transition-to-backend-services#console

In order to enable auto-healing, you need to group the instances into a managed instance group. Managed instance groups (MIGs) maintain the high availability of your applications by proactively keeping your virtual machine (VM) instances available. An auto-healing policy on the MIG relies on an application-based health check to verify that an application is responding as expected. If the auto-healer determines that an application isnt responding, the managed instance group automatically recreates that instance.

It is important to use separate health checks for load balancing and for auto-healing. Health checks for load balancing can and should be more aggressive because these health checks determine whether an instance receives user traffic. You want to catch non-responsive instances quickly, so you can redirect traffic if necessary. In contrast, health checking for auto-healing causes Compute Engine to proactively replace failing instances, so this health check should be more conservative than a load balancing health check.