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In this stage, you conduct a detailed discovery process to evaluate existing AWS Lambda workloads, including their configuration, dependencies, and usage patterns. The goal is to understand which AWS features and services your workload relies on.
Evaluate your current workload
Compile a comprehensive inventory of your AWS Lambda functions by using familiar AWS tooling like service-specific SDKs, APIs, and CloudTrail to assess the workloads on AWS. You should understand the following key aspects of your inventory.
Use cases
Identify the primary business or technical purposes that each Lambda function serves.
Categorize functions based on their use cases, such as event-driven workflows, data processing, real-time analytics, or API back ends.
Configuration
Document configuration settings for each function, including memory allocation, time-out settings, and environment variables.
Note versioning details, aliases, and any deployment-specific configurations, such as language runtime and architectures like x86 or ARM.
Security and networking setup
Assess the identity and access management roles and policies associated with each function to ensure proper access control.
Identify virtual private cloud configurations, including subnets, security groups, and NAT gateway dependencies, if applicable.
Tooling
List the continuous integration and continuous delivery tools and deployment frameworks that each function uses, such as AWS SAM, Serverless Framework, or custom pipelines.
Document build and packaging tools, including testing frameworks and staging workflows.
Monitoring, logging, and observability mechanisms
Evaluate the current monitoring and logging mechanisms, such as Amazon CloudWatch, AWS X-Ray, or partner tools.
Identify log retention policies and patterns for troubleshooting.
Document tracked metrics and alerts, such as error rates, invocation counts, and duration trends.
Dependencies
Determine which AWS services, like DynamoDB, S3, or API Gateway, and partner tools that your Lambda functions rely on. Document their configurations, interactions, and dataflows.
Map interdependencies, such as shared resources or invocation chains, between Lambda functions, and evaluate potential bottlenecks or latency problems.
Assess service limits, operational considerations, and monitoring tools like CloudWatch and X-Ray. Ensure that you understand how these dependencies affect the workload.
By the end of this stage, you should have a comprehensive inventory of your AWS Lambda functions, including their:
Use cases.
Configurations.
Security and networking setups.
Tooling, monitoring, logging, and observability mechanisms.
Dependencies.
This detailed inventory is the foundation for the next stage, where you assess the readiness and suitability of these functions for migration to Azure Functions.