Understanding system activities requires analyzing data from event logs and transaction logs. This comprehensive guide on interpreting data from event logs and transaction logs delves into the columns of each log type, offering practical analysis tips. From monitoring to billing tracking, it covers various use cases and helps you make informed decisions to drive business success.
Transaction Logs Spreadsheet
The transaction logs spreadsheet provides critical details related to transactions. Let’s break down its columns:
Transaction Id: A unique identifier for each transaction, helps in tracking and referencing individual transactions.
Final Request Id: Identifies the final request within a series of requests that constitute a transaction.
Type: Indicates the type of transaction (e.g., “verify” or “fetch”) based on the request made.
Billable: Determines whether the transaction is billable.
Transaction Status: Reflects the status of the transaction (e.g. “completed” or “Upstream error”).
Offering: Specifies the name of the API used.
Client Name: Displays the name of the organization associated with the credentials, verifying that the API request was made by the client.
Credential: Indicates the type of credential used (test-credential or live-credential) for the API.
Result Code: Provides a code indicating the outcome of the transaction. Codes are specific to the API.
Created Date (UTC): Records the date and time (in Coordinated Universal Time) when the transaction was created.
Started At (UTC): Captures the date and time (in UTC) when the transaction began.
Completed At (UTC): Marks the date and time (in UTC) when the transaction was successfully completed.
Event Logs Spreadsheet
The event logs spreadsheet complements transaction data. The data in the columns refer to:
Client: Displays the name of the client who made the API call.
Credential: Indicates the type of credential used (live-credential or test-credential) in the request.
Request Id: A unique identifier for each API request.
Created Date (UTC): Records the date and time (in Coordinated Universal Time) when the API request was created.
Started At (UTC): Captures the date and time (in UTC) when the API request started.
Completed At (UTC): Marks the date and time (in UTC) when the API call was successfully completed.
Transaction Id: A unique identifier for the transaction associated with the API request.
Offering: Specifies the name of the API offering used.
Request Type: Indicates the type of request (e.g., ‘verify’ or ‘fetch’ data) made in the API call.
Request Path: Represents the path or URL where the request was made.
Client Address: Provides the IP address of the client who initiated the request.
HTTP Status Code: Indicates the result of the HTTP request (e.g., success, error, etc.).
Result Code: Provides a response code indicating the outcome of the API request.
By combining insights from both the transaction logs and event logs spreadsheets, you can gain a comprehensive understanding of your system’s behavior. Here’s how:
Correlate Transaction and Event Data:
Link transaction records (using Transaction Id) to corresponding event logs.
Identify any discrepancies.
Performance Optimization:
Analyze transaction response times (from transaction logs) alongside API request details (from event logs).
Optimize workflows based on API performance.
Address bottlenecks or delays.
Security and Compliance:
Cross-reference credentials, and IP addresses.
Detect any unauthorized or suspicious activity.
Ensure compliance with billing and usage policies.
Business Insights:
Use aggregated data to inform business decisions.
Understand peak usage times, popular offerings, and client behavior.
How to Use the values available in the spreadsheet:
Filters: Focus on specific transaction types, clients, request types, or time ranges.
- Examples: Filter by transaction(e.g., “verify” or exclude “fetch” transactions), client, request type(e.g., “fetch” requests), or specific time period.
Pivot: Explore column relationships, e.g., request types vs. response codes or pivot by used APIs.
Aggregations: Derive insights like total requests/day, successful transactions/day, average response time per offerings, or request type distribution across clients.