Google Trace
Author: Ronald Fung
Creation Date: 13 June 2023
Next Modified Date: 13 June 2024
A. Introduction
Cloud Trace is a distributed tracing system for Google Cloud that collects latency data from applications and displays it in near real-time in the Google Cloud console. Learn more about Cloud Trace
B. How is it used at Seagen
As a biopharma research company, Seagen can benefit from using Google Cloud Trace for their application performance monitoring needs. Here are some ways Seagen can use Google Cloud Trace:
Migrating from Microsoft Azure: Seagen can migrate their existing application performance monitoring configurations from Microsoft Azure to Google Cloud Trace by exporting the configurations from Azure and importing them into Google Cloud Trace. This can be done using the Google Cloud Trace API or other migration tools.
Tracing performance data: Seagen can trace performance data from their applications, virtual machines, and other resources running on Google Cloud Platform. They can use Google Cloud Trace to collect and analyze traces, and can use Google Cloud Error Reporting to track and analyze errors.
Monitoring and alerting: Seagen can monitor their performance and receive alerts in real-time using Google Cloud Trace. They can set up custom alerts based on specific performance metrics or resource types, and can receive notifications via email, SMS, or other channels.
Managing access and permissions: Seagen can manage access and permissions to their performance data using Google Cloud IAM. They can define roles and permissions for different users and groups, and can control access to performance data based on resource type, location, or other attributes.
Integrating with other Google Cloud services: Seagen can integrate their performance data with other Google Cloud services, such as Google Cloud Pub/Sub, Google Cloud Storage, and Google BigQuery. They can build real-time data pipelines and analytics workflows using these services, and can store and analyze performance data at scale.
Overall, by using Google Cloud Trace, Seagen can benefit from a powerful and scalable solution for their application performance monitoring needs. With its support for migrating existing performance monitoring configurations, tracing performance data, monitoring and alerting, managing access and permissions, and integrating with other Google Cloud services, Google Cloud Trace provides a range of options that can meet the needs of a variety of workloads and use cases.
C. Features
Easy set up
All Cloud Run, Cloud Functions and App Engine standard applications are automatically traced and libraries are available to trace applications running elsewhere after minimal setup. All performance reports and analysis described above are available out of the box.
Performance insights
Each end point level trace is evaluated automatically for performance bottlenecks.
Automatic analysis
Automatic daily performance reports are created for each traced application. You can also generate reports on demand.
Extensibility for custom workloads
The Trace API and language specific SDKs are available to trace applications running on virtual machines and containers. Trace data can be consumed via the Cloud Trace UI through the Trace API.
Latency shift detection
Performance reports of your application are evaluated over time to identify latency degradation of your application over time.
D. Where Implemented
E. How it is tested
Testing Google Cloud Trace involves ensuring that the tracing infrastructure is properly configured and optimized for performance, reliability, and security. Here are some steps to test Google Cloud Trace:
Create a test environment: Create a test environment that mimics the production environment as closely as possible, including the applications, virtual machines, and other resources that generate performance data. Ensure that the tracing infrastructure is properly configured and that the security policies are in place.
Deploy the tracing infrastructure: Deploy the tracing infrastructure on Google Cloud Platform. Ensure that the infrastructure is properly configured and that it can communicate with other resources, such as applications or APIs.
Test tracing collection: Test the tracing collection by generating test performance data using performance generation tools, such as the Stackdriver Trace API or other performance generation tools. Ensure that the performance data is being collected properly and that there are no errors or missing data.
Test tracing search and analysis: Test the tracing search and analysis by using tracing search and analysis tools, such as the Stackdriver Trace Console or other tracing analysis tools. Ensure that the traces are searchable and that there are no errors or timeouts.
Test tracing monitoring and alerting: Test the tracing monitoring and alerting by setting up custom alerts based on specific performance metrics or resource types, and by receiving notifications via email, SMS, or other channels. Ensure that the alerts are triggered properly and that there are no false positives or false negatives.
Test tracing access and permissions: Test the tracing access and permissions by using Google Cloud IAM to define roles and permissions for different users and groups, and by controlling access to traces based on resource type, location, or other attributes. Ensure that the access control policies are working as expected and that there are no unauthorized access or data breaches.
Test tracing integration: Test the tracing integration with other Google Cloud services or third-party tools by using tracing integration testing tools, such as Google Cloud Pub/Sub or Microsoft Azure Event Grid. Ensure that the traces are integrated properly and that there are no integration issues or errors.
Overall, by thoroughly testing Google Cloud Trace, users can ensure that their tracing infrastructure is properly configured and optimized for performance, reliability, and security. Additionally, users can reach out to Google Cloud support for help with any technical challenges they may encounter.
F. 2023 Roadmap
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G. 2024 Roadmap
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H. Known Issues
While Google Cloud Trace is a reliable and widely used solution for application performance monitoring needs, there are some known issues that users may encounter. Here are some of the known issues for Google Cloud Trace:
Tracing data accuracy issues: Users may encounter issues with tracing data accuracy, such as missing or incomplete traces, especially for workloads that generate a high volume of traces. This issue can often be resolved by using the appropriate tracing configuration settings, such as trace sampling rates or trace exclusions, and by monitoring the tracing data accuracy.
Tracing performance issues: Users may encounter issues with tracing performance, such as slow traces or high latency, especially for workloads that require real-time tracing or low latency tracing. This issue can often be resolved by using the appropriate tracing configuration settings, such as trace aggregation or trace compression, and by optimizing the tracing performance.
Alerting issues: Users may encounter alerting issues, such as false positives or false negatives, especially for workloads that require high accuracy or low latency alerts. This issue can often be resolved by using the appropriate alerting policies, such as performance threshold values or alert conditions, and by testing the alerting policies in a test environment.
Security issues: Users may encounter security issues, such as unauthorized access or data breaches, especially for workloads that require high security. This issue can often be resolved by using the appropriate security policies and access controls, such as firewall rules and IAM roles.
Integration issues: Users may encounter integration issues with other cloud services or third-party tools, such as data pipelines or analytics platforms. This issue can often be resolved by using industry-standard protocols and APIs to enable interoperability between different cloud services and tools.
Overall, while these issues may impact some users, Google Cloud Trace remains a powerful and reliable solution that is widely used by businesses and organizations around the world. By monitoring their performance and security alerts and traces, reviewing their tracing configuration and policies, and using best practices and industry standards, users can ensure that their tracing infrastructure running on Google Cloud Trace is optimized for performance, reliability, and security. Additionally, users can reach out to Google Cloud support for help with any known issues or other technical challenges they may encounter.
[x] Reviewed by Enterprise Architecture
[x] Reviewed by Application Development
[x] Reviewed by Data Architecture