What Are Monitoring and Debugging in Serverless Computing?

Monitoring and debugging in serverless computing are the processes of tracking and solving problems in the cloud functions and other services that they interrelate with. This is important because functions can only run at the time of invocation in a serverless architecture, which necessitates the ability to monitor the functioning, the resources consumed, as well as the errors that may be occurring.

The following are the main aspects of serverless monitoring and debugging;

• Distributed Tracing: Enables tracking of requests across multiple functions, services, and cloud resources.
• Real-time Logs and Metrics: It gives information on how the function has been performed, what resources have been utilized, and if there have been any errors.
• Error Tracking and Alerting: Identifies and reports errors, initiating workflows for analysis and correction. 
• Debugging and Troubleshooting: Tools that are used to detect and fix bugs that may be present in serverless applications.
• Performance Monitoring: Monitors and evaluates the user interactions within the application and the consumption of resources.

Practical Implementations

• A business to business e-commerce platform where most functionalities such as image processing, payment transactions and order processing. Monitoring is crucial for tracking customer engagement, identifying potential issues, and ensuring consistent service delivery.
• The IoT devices transmit data to a backend where it gets analyzed and stored for further use. Debugging helps maintain data accuracy and consistency, while minimizing potential discrepancies or errors.

The pros and cons include: 

장점:

• Proactive Issue Detection: Identify and assess potential problems and errors that could impact user experience.
• Optimizing efficiency: Gather and analyze resource performance data to potentially improve efficiency.
• Streamlined Troubleshooting: Employ distributed tracing and logging to expedite error identification and problem-solving.
• Observation Capabilities: Observing the internal workings and behavior of your application to enable better control and decision-making.

Limitations:

• 복잡성: As serverless solutions are typically multipurpose and highly diverse, it can take more time and efforts to identify problems with requests in comparison with simpler and less layered architectures.
• 비용: Monitoring and Debugging tools may be offered at additional cost, especially for large applications and development and this must be taken into consideration.
• Tooling: It can also be quite complex, at some point, to determine the appropriate tools to apply and how to apply them in your functioning.

Yes, debugging code in the serverless cloud can be challenging and may require different approaches compared to traditional methods, given the distribution and ephemeral nature of serverless functions.

There are several approaches to monitor serverless functions, such as the tools offered by the cloud provider, additional third-party tools, as well metrics and logs.

This approach may be effective due to its impact on the following reasons:

• Cloud Provider Tools: Provide fundamental PC monitoring and logging functions into your 클라우드 환경에서.
• Third-party offerings: Offering access to advanced features and integrations may relate to more in-depth application insights and statistics.
• Custom Metrics & Logs: It lets you track certain data as it relates to the functioning of your application.

To enhance observability:

• Implement Distributed Tracing: Track request across functions and services for optimization and visibility of an integrated system.
• Centralize Logging: Collect logs from various functions and services across the software and store them in a centralized logging area.
• Define and Collect Custom Metrics: Collect particular pieces of information regarding the application’s performance and behavior.
• Set Up Alerting and Anomaly Detection: Receive alerts of possible problems and analyze patterns that do not correspond to the norm using machine learning.
• Observability is key: This mode will help you get an idea of how the application runs and the problems that your application presents.