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Cloud
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GCPLoggingPersistenceCloud
Last edited time
Jun 26, 2024 12:39 PM
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👉 Overview
👀 What ?
GCP Logging Persistence refers to the process of storing and managing logs generated within Google Cloud Platform (GCP). These logs provide valuable insights into the operation and performance of cloud applications and services, as well as potential security incidents.
🧐 Why ?
The importance of GCP Logging Persistence lies in its ability to offer visibility into the activities and performance of your applications and services running on GCP. It helps in identifying issues, troubleshooting, and enhancing the performance and security of your applications. Through log persistence, you can store and access logs over time, which is crucial for long-term analysis, meeting compliance requirements, and conducting detailed post-mortem investigations in case of security incidents.
⛏️ How ?
To use GCP Logging Persistence to your advantage, start by setting up a Cloud Logging agent for your services. This agent sends logs to the Cloud Logging service. From the Google Cloud Console, you can view, search, and filter these logs. To store logs persistently, you need to set up a sink, which is a mechanism to route logs to supported storage destinations including Cloud Storage, BigQuery, and Pub/Sub. You can set up sinks at the project, folder, billing account, or organization level.
⏳ When ?
The use of GCP Logging Persistence began when Google Cloud Platform started offering its Cloud Logging service. As businesses started moving their workloads to GCP, the need for a robust and reliable logging mechanism became apparent, leading to the adoption of logging persistence practices.
⚙️ Technical Explanations
From a technical standpoint, GCP Logging Persistence involves several components of Google Cloud Platform. Logs are generated by various services running on GCP, like App Engine, Compute Engine, and others. These logs are captured by the Cloud Logging agent and sent to the Cloud Logging service. Here, logs can be viewed and analyzed in real-time. For long-term storage and analysis, logs are sent to a sink. The sink routes logs to a storage destination like Cloud Storage (for long-term storage), BigQuery (for SQL-like querying and analysis), or Pub/Sub (for real-time processing). This entire process is governed by IAM roles and permissions, ensuring that only authorized personnel can access and manage logs.