How to log errors in sql server stored procedures is essential for reliable database programs. This quick fact: robust error logging lets you diagnose failures fast and keep users happy. In this guide, you’ll get a practical, end-to-end approach to logging errors in SQL Server stored procedures, plus tips, samples, and best practices that actually work in production.

Quick fact: Centralized error logging helps you triage production issues in minutes, not hours.
This post gives you a step-by-step framework to log errors from stored procedures, including:
- Basic TRY…CATCH patterns
- Logging to a table, a file, or a monitoring system
- Handling nested procedures and transactions
- Performance considerations and remedial tips
What you’ll get:
- Practical code samples you can drop into your project
- Real-world tips that save you time during incidents
- A checklist to ensure you’re not missing critical information
Useful resources and references:
- Microsoft Docs – Transact-SQL T-SQL – TRY…CATCH
- SQL Server error handling best practices
- SQL Server performance tuning guides
- SQL Server Agent job logging references
- Azure SQL Database error logging considerations

How error handling works in SQL Server

When a statement fails, control transfers to the CATCH block if the code is wrapped in TRY…CATCH.
In the CATCH block, you can capture error details using functions like ERROR_NUMBER, ERROR_SEVERITY, ERROR_STATE, ERROR_PROCEDURE, ERROR_LINE, and ERROR_MESSAGE.
To ensure you don’t leave transactions in a bad state, you canROLLBACK TRANSACTION inside CATCH for active transactions.
Common pattern: TRY { transactional work } CATCH { log error; ROLLBACK TRANSACTION if active; rethrow or swallow depending on your design }

Key patterns for logging errors from stored procedures

Pattern A: Log to a dedicated ErrorLog table
- Pros: Fast, queryable, centralized
- Cons: Requires discipline to populate the log consistently
Pattern B: Log to a file or Windows Event Log
- Pros: Useful for offline analysis, supports long-term retention
- Cons: Requires extended stored procedures or CLR integration careful with security
Pattern C: Log to a dedicated monitoring system e.g., Application Insights, Prometheus, or a custom API
- Pros: Centralized monitoring, alerting, dashboards
- Cons: Adds dependencies and latency
Pattern D: Hybrid approach log to table plus an external sink
- Pros: Reliability, observability, redundancy
- Cons: More code and maintenance

Recommended starter approach: Log to a table with optional external sink

This gives you fast, reliable local logging and the ability to push to external systems when needed.
Create a simple ErrorLog table:
- Columns: LogId PK, ErrorNumber, ErrorSeverity, ErrorState, ErrorProcedure, ErrorLine, ErrorMessage, LoggedAt, UserName, ConnectionId, SessionId, TransactionId, AdditionalInfo
Use a stored procedure wrapper pattern to standardize logging:
- A helper procedure that inserts a row into ErrorLog and, if configured, calls an external sink.

Code samples you can adapt

Create the error log table
- CREATE TABLE dbo.ErrorLog
  LogId BIGINT IDENTITY1,1 PRIMARY KEY,
  ErrorNumber INT NULL,
  ErrorSeverity INT NULL,
  ErrorState INT NULL,
  ErrorProcedure NVARCHAR200 NULL,
  ErrorLine INT NULL,
  ErrorMessage NVARCHARMAX NULL,
  LoggedAt DATETIME2 DEFAULT SYSUTCDATETIME,
  UserName NVARCHAR128 NULL,
  ConnectionId NVARCHAR64 NULL,
  SessionId NVARCHAR64 NULL,
  TransactionId NVARCHAR64 NULL,
  AdditionalInfo NVARCHARMAX NULL
  ;
Basic log procedure
- CREATE PROCEDURE dbo.usp_LogError
  @ErrorNumber INT,
  @ErrorSeverity INT,
  @ErrorState INT,
  @ErrorProcedure NVARCHAR200,
  @ErrorLine INT,
  @ErrorMessage NVARCHARMAX,
  @UserName NVARCHAR128 = NULL,
  @ConnectionId NVARCHAR64 = NULL,
  @SessionId NVARCHAR64 = NULL,
  @TransactionId NVARCHAR64 = NULL,
  @AdditionalInfo NVARCHARMAX = NULL
  AS
  BEGIN
  SET NOCOUNT ON;
  
  INSERT INTO dbo.ErrorLog
  ErrorNumber, ErrorSeverity, ErrorState, ErrorProcedure, ErrorLine, ErrorMessage,
  LoggedAt, UserName, ConnectionId, SessionId, TransactionId, AdditionalInfo
  VALUES
  @ErrorNumber, @ErrorSeverity, @ErrorState, @ErrorProcedure, @ErrorLine, @ErrorMessage,
  SYSUTCDATETIME, @UserName, @ConnectionId, @SessionId, @TransactionId, @AdditionalInfo;
  END
GO
Example TRY…CATCH usage in a stored procedure
- CREATE PROCEDURE dbo.usp_DoWork
  AS
  BEGIN
  SET NOCOUNT ON;
  
  BEGIN TRY
  BEGIN TRANSACTION;
  
  — Your main work here
  — Example: insert into a table
  INSERT INTO dbo.YourTable ColA, ColB VALUES 1, ‘example’;
  
  — More statements that could fail
  — …
  
  COMMIT TRANSACTION;
  END TRY
  BEGIN CATCH
  IF @@TRANCOUNT > 0
  ROLLBACK TRANSACTION;
  
  DECLARE @ErrorNumber INT = ERROR_NUMBER;
  DECLARE @ErrorSeverity INT = ERROR_SEVERITY;
  DECLARE @ErrorState INT = ERROR_STATE;
  DECLARE @ErrorProcedure NVARCHAR200 = ERROR_PROCEDURE;
  DECLARE @ErrorLine INT = ERROR_LINE;
  DECLARE @ErrorMessage NVARCHARMAX = ERROR_MESSAGE;
  
  — Optional: additional context
  DECLARE @UserName NVARCHAR128 = ORIGINAL_LOGIN;
  DECLARE @ConnectionId NVARCHAR64 = CONNECTION_ID;
  DECLARE @SessionId NVARCHAR64 = CASTSESSION_ID AS NVARCHAR64;
  
  — Log using the helper procedure
  EXEC dbo.usp_LogError
  @ErrorNumber = @ErrorNumber,
  @ErrorSeverity = @ErrorSeverity,
  @ErrorState = @ErrorState,
  @ErrorProcedure = @ErrorProcedure,
  @ErrorLine = @ErrorLine,
  @ErrorMessage = @ErrorMessage,
  @UserName = @UserName,
  @ConnectionId = @ConnectionId,
  @SessionId = @SessionId,
  @TransactionId = NULL, — populate if you have transaction context
  @AdditionalInfo = N’Context: DoWork procedure failed’;
  
  — Re-throw or swallow based on policy
  — Rethrow to caller
  THROW;
  END CATCH
  END
GO
Optional: external sink hook pseudo, adjust to your environment
- In CATCH, after logging to table, you could enqueue a message or call a CLR stored procedure that sends data to a monitoring service.
- Example: EXEC dbo.usp_SendLogToExternalSink @LogId = SCOPE_IDENTITY;
Performance tips
- Keep the ErrorLog INSERT lightweight: select only needed fields, avoid long string data unless necessary.
- Consider using a staging log table for bursts and batch-send to external sink to reduce contention.
- Add non-blocking logging: log asynchronously when possible e.g., via Service Broker, SQL Server Agent jobs, or an external queue.

How to structure logging for nested procedures

If a parent procedure calls child procedures, you can:
- Rely on a centralized logging helper dbo.usp_LogError from every CATCH block.
- Include the name of the failing procedure using ERROR_PROCEDURE to help trace the root cause.
Example pattern:
- In child proc: any error in TRY…CATCH logs via dbo.usp_LogError, including the current procedure name.
- In parent proc: if child fails, the CATCH in parent captures and logs the parent context as well, creating a chain for debugging.

Best practices for reliable error logging

Always include:
- Error number, severity, state
- The failing procedure and line
- The error message
- User, connection, and session context
- Optional: a few key business identifiers orderId, customerId, etc.
Don’t swallow errors silently. If you don’t rethrow, explicitly log and exit with an appropriate message.
Use TRY…CATCH around critical operations, especially:
- Data modifications INSERT/UPDATE/DELETE
- Complex business logic
- Calls to external services or CLR procedures
Keep the logging path resilient:
- If logging fails, don’t crash the main transaction. You can keep a minimal log or retry in a controlled way.
Monitor error patterns:
- Build dashboards to alert on spikes in ERROR_MESSAGE or high error severities.
- Track mean time to detect MTTD and mean time to repair MTTR using your logs.

Performance considerations and tips

Minimize impact by:
- Logging only essential data in hot paths
- Using a compact field for error messages with a longer, full message stored in a secondary table or blob
- Batch processing logs in a background job if you expect high volume
Keep log table indexed on common query patterns:
- Index by LoggedAt for time-based searches
- Include ErrorNumber and ErrorSeverity in a composite index if you query by those fields often
Archive old logs regularly to keep table sizes manageable
Consider using filtered indexes if you routinely filter by specific error types

Common pitfalls to avoid

Over-logging every minor warning, which creates noise
Including sensitive data in logs PII, credentials
Relying on a single sink without fallback options
Forgetting to handle nested transactions ensure you roll back correctly
Not updating the log schema when you add new error context

Real-world scenarios and examples

Scenario 1: Data import procedure fails due to a constraint
- Catch block logs the detailed error, including the offending constraint name, and then rethrows the error after rolling back, so the calling process can handle it gracefully.
Scenario 2: Web API calls from SQL Server fail
- You log the error and push a lightweight alert e.g., a message in a queue for the application to retry, while your stored procedure ends with a controlled error to the API caller.
Scenario 3: Long-running ETL job encounters intermittent deadlocks
- The log captures the error number and the deadlock graph is saved elsewhere for deep debugging, while the ETL job retries with exponential backoff.

Monitoring and maintenance

Create a simple monitoring view:
- CREATE VIEW dbo.vwRecentErrors AS
  SELECT TOP 1000 *
  FROM dbo.ErrorLog
  ORDER BY LoggedAt DESC;
Set up alerts:
- If ERROR_SEVERITY >= 20, or if ERROR_NUMBER not in expected numbers, trigger an alert to on-call engineers.
Review cadence:
- Weekly review of error logs to identify recurring issues and potential code changes.
Documentation:
- Maintain a runbook with common error scenarios and recommended remediation steps.

Comparison: logging to table vs. external sinks

Table logging:
- Fast, reliable, easy to query
- Best for baseline observability
External sinks:
- Great for centralized monitoring and alerting
- Adds complexity and potential latency
Best practice: use both hybrid approach to maximize reliability and visibility

From idea to production: implementation checklist

Define what you will log mandatory fields
Create the ErrorLog table with a clear schema
Implement a central logging stored procedure usp_LogError
Wrap critical operations in TRY…CATCH blocks
Log and rethrow or handle based on policy
Add optional external sink integration
Implement monitoring and alerting
Regularly archive old logs and tune indexes
Document error handling behavior and edge cases

Advanced tips for SQL Server environments

Use schema-based separation for logs e.g., logging schema to improve organization
Consider a separate filegroup for the log table to reduce IO contention
If you’re on Azure SQL Database, use built-in auditing and extended events for deeper insight alongside your own log
Use SQL Server Profiler or Extended Events to understand error hotspots and refine your logging strategy

Troubleshooting common logging issues

Issue: Logs aren’t appearing for certain errors
- Check if the code path is inside a TRY block and CATCH is reached
- Verify connection settings and permissions for inserting into the log table
Issue: Logging causes performance degradation during peak load
- Move logging to an asynchronous path or use a smaller, essential data set
Issue: Sensitive data appearing in logs
- Redact or mask PII and restrict how logs are accessed

Useful URLs and Resources

Microsoft Docs – TRY…CATCH Transact-SQL – en.wikipedia.org/wiki/Transact-SQL
SQL Server error handling best practices – sqlserverpro.com
SQL Server performance tuning guidelines – docs.microsoft.com
Azure SQL Database error logging considerations – docs.microsoft.com
SQL Server Agent logging and alerting – docs.microsoft.com

Frequently Asked Questions

Table of Contents

What is TRY…CATCH in SQL Server?

TRY…CATCH is a control-of-flow language construct that lets you capture and handle runtime errors. The code in TRY runs, and if an error occurs, control passes to CATCH where you can log the error, rollback transactions, and decide how to respond.

How should I structure my error log table?

Include fields for ErrorNumber, ErrorSeverity, ErrorState, ErrorProcedure, ErrorLine, ErrorMessage, LoggedAt, UserName, ConnectionId, SessionId, TransactionId, and AdditionalInfo. This gives you enough context for most debugging needs.

Should I log all errors or only severe ones?

Balance is key. Log all errors that affect business logic or data integrity. For noisy, low-severity messages, consider a targeted logging strategy or aggregation.

Can I log errors asynchronously?

Yes. Use mechanisms like Service Broker, a queue, or an external sink to offload logging work from the main transaction path. This reduces the chance of logging slowing your main process.

How do I handle nested stored procedures?

Always log from the CATCH block with as much context as possible, including the current procedure name. If a child procedure fails, the parent can catch and log as well to provide a full error trace.

What about security and privacy in logs?

Never log passwords or sensitive data. Mask or redact PII where possible. Use access controls to restrict who can view logs and consider encryption at rest for the log table.

How do I test error logging?

Write unit tests or integration tests that force errors e.g., violate constraints and verify that logs are created with the expected fields. Include tests for rollback behavior and for ensuring logs persist even when the main operation fails.

How can I monitor logging performance?

Track log write latency, log table growth, and the frequency of error events. Use dashboards to spot spikes and tune indexes or the logging path accordingly.

Is there a recommended way to rotate logs?

Yes. Implement archival processes that move older logs to an archive table or a separate storage, then truncate or purge as per your retention policy. Regular maintenance keeps read performance healthy.

Can I use stored procedures for logging in non-SQL Server systems?

The same principles apply in other systems, but adapt to the specific error handling and data access patterns of that system. Centralized, structured logging with a consistency pattern is the core idea.

How to log errors in sql server stored procedures: Best Practices, Error Handling Patterns, TRY…CATCH, RAISERROR, and THROW

Use TRY…CATCH blocks and log errors to a table or external store.

In this guide, you’ll get a practical, battle-tested approach to error handling in SQL Server stored procedures. We’ll cover patterns, concrete code you can copy, performance considerations, and how to monitor and alert on failures. Expect a mix of step-by-step instructions, code samples, checklists, and real‑world tips to keep your SQL layer reliable and observable.

Useful URLs and Resources text only:
– Microsoft Docs – Error Handling Transact-SQL
– Microsoft Docs – TRY…CATCH Transact-SQL
– Microsoft Docs – THROW Transact-SQL
– SQL Server Logging Best Practices
– Stack Overflow – Error Handling in SQL Server
– Simple Talk – Centralized Logging in SQL Server

Table of contents
– Why error logging matters
– Core concepts you’ll use
– Logging targets: table vs file vs external services
– Designing an error log table
– Implementing robust error handling in stored procedures
– Centralized vs local logging strategies
– Performance and security considerations
– Testing and validating error handling
– Real-world patterns and recipes
– Monitoring, alerts, and dashboards

Why error logging matters

Error logging isn’t just about catching bugs. it’s about making incidents diagnosable and preventing silent failures from cascading. When stored procedures fail in production, you want:
– Immediate visibility: who failed, when, and why
– Enough context to reproduce the failure locally
– A safe mechanism to prevent data corruption or inconsistent states
– A strategy to alert the right teammates without spamming on every error

Beyond that, mature teams implement a centralized approach so that a single error feed can be used across multiple databases and environments.

Core concepts you’ll use

– TRY…CATCH: The core pattern for handling errors in SQL Server.
– ERROR_NUMBER, ERROR_SEVERITY, ERROR_STATE, ERROR_PROCEDURE, ERROR_MESSAGE, ERROR_LINE: Useful error context inside CATCH.
– THROW vs RAISERROR: THROW is the modern, simpler option that preserves error stacks. RAISERROR is older but still used in some legacy code.
– Logging target: a dedicated ErrorLog table, a file, or an external system Azure Monitor/Log Analytics, SIEM, etc..
– Transactions and error handling: using XACT_STATE to decide whether to commit or rollback.

Logging targets: table vs file vs external services

– Table-based logging recommended for most SQL Server setups:
– Pros: Easy to query, joins with business data, durable, supports indexing and retention policies.
– Cons: Requires careful schema design and maintenance. may add some overhead.
– File-based logging:
– Pros: Simple append-only logs. good for quick debugging on a single server.
– Cons: Harder to query. not centralized. potential disk pressure.
– External services Azure Monitor, Log Analytics, SIEM:
– Pros: Centralized across environments. powerful alerting and dashboards. scalable.
– Cons: Requires network connectivity and cost. more complex setup.

Recommendation: start with a centralized ErrorLog table and a lightweight external log sink for long-term analytics.

Designing an error log table

A solid error log table should capture enough context to diagnose issues without exposing sensitive data. Here’s a pragmatic starter schema:

CREATE TABLE dbo.ErrorLog
LogId BIGINT IDENTITY1,1 PRIMARY KEY,
ErrorNumber INT NULL,
ErrorSeverity INT NULL,
ErrorState INT NULL,
ErrorProcedure SYSNAME NULL,
ErrorMessage NVARCHARMAX NULL,
ErrorLine INT NULL,
LoggedAt DATETIME23 NOT NULL DEFAULT SYSUTCDATETIME,
ServerName SYSNAME NULL,
DatabaseName SYSNAME NULL,
UserName SYSNAME NULL,
ApplicationName SYSNAME NULL,
AdditionalInfo NVARCHARMAX NULL
.

Tips:
– Use NVARCHARMAX for ErrorMessage to avoid truncation.
– Include LoggedAt, DatabaseName, ServerName, UserName, and ApplicationName for context.
– Consider partitioning by year or by a critical tenant if you’ve multi-tenant apps.
– Mask or redact sensitive data in AdditionalInfo if needed.

Implementing robust error handling in stored procedures

Here’s a practical pattern you can adapt. It demonstrates logging inside a TRY…CATCH and optionally rethrowing with THROW.

1 Basic pattern: log and rethrow

BEGIN TRY
— Your main logic here
INSERT INTO dbo.Sales… VALUES ….
— other statements
END TRY
BEGIN CATCH
— Log the error
INSERT INTO dbo.ErrorLog
ErrorNumber, ErrorSeverity, ErrorState, ErrorProcedure, ErrorMessage,
ErrorLine, LoggedAt, ServerName, DatabaseName, UserName, ApplicationName

VALUES
ERROR_NUMBER,
ERROR_SEVERITY,
ERROR_STATE,
ERROR_PROCEDURE,
ERROR_MESSAGE,
ERROR_LINE,
SYSUTCDATETIME,
CAST SERVERPROPERTY’ServerName’ AS SYSNAME,
DB_NAME,
ORIGINAL_LOGIN,
APP_NAME
.

— Optional: enrich the error and rethrow
THROW. — Re-raises the original error with the same stack
END CATCH.

2 Logging with a helper stored procedure centralized

CREATE PROCEDURE dbo.usp_LogError
@ErrorNumber INT,
@ErrorSeverity INT,
@ErrorState INT,
@ErrorProcedure SYSNAME,
@ErrorMessage NVARCHARMAX,
@ErrorLine INT,
@LoggedAt DATETIME23,
@ServerName SYSNAME,
@DatabaseName SYSNAME,
@UserName SYSNAME,
@ApplicationName SYSNAME,
@AdditionalInfo NVARCHARMAX = NULL
AS
BEGIN
INSERT INTO dbo.ErrorLog …
VALUES …. — map parameters to columns
END.
GO

Then in your main procedure:

— main work
EXEC dbo.usp_LogError
@ErrorNumber = ERROR_NUMBER,
@ErrorSeverity = ERROR_SEVERITY,
@ErrorState = ERROR_STATE,
@ErrorProcedure = ERROR_PROCEDURE,
@ErrorMessage = ERROR_MESSAGE,
@ErrorLine = ERROR_LINE,
@LoggedAt = SYSUTCDATETIME,
@ServerName = CAST SERVERPROPERTY’ServerName’ AS SYSNAME,
@DatabaseName = DB_NAME,
@UserName = ORIGINAL_LOGIN,
@ApplicationName = APP_NAME,
@AdditionalInfo = NULL.
THROW.

3 Handling nested calls and transactions

If your procedure calls other procedures, you can:
– Log at the top-level procedure only, to avoid duplicate logs.
– Or log in every layer if you need traceability across calls.
– Use XACT_STATE to decide whether you can rollback safely within CATCH.

BEGIN TRANSACTION.
— work that may cause errors
EXEC dbo.usp_DoWork.
COMMIT TRANSACTION.
IF XACT_STATE <> 0
ROLLBACK TRANSACTION.

EXEC dbo.usp_LogError …. — as above

4 Logging optional data and preventing log failures

– Wrap logging in its own TRY…CATCH to avoid log failures aborting business logic.
– Consider storing large error messages in a separate table or truncating with care.
– If you must log sensitive data, apply masking rules or use a secure logging channel.

Centralized vs local logging strategies

– Centralized logging:
– Use a single ErrorLog table or a central logging stored procedure that all databases call.
– Pros: consistent structure, easier monitoring, cleaner analytics.
– Cons: can be a single point of failure. require cross-database permissions.
– Local logging:
– Each database or schema maintains its own error log.
– Pros: simpler permissions, autonomy, offline resilience.
– Cons: harder to aggregate across environments.

Hybrid approach:
– Core errors are logged centrally, while domain-specific messages are stored locally with a reference to the central log entry.

Performance and security considerations

– Performance:
– Logging can add overhead. batch or asynchronous logging e.g., queue into a SQL Server Agent job or an asynchronous service can help.
– Use indexed columns on ErrorLog ErrorNumber, LoggedAt, DatabaseName, ServerName for faster querying.
– Security:
– Do not log password hashes, connection strings, or PII in plain text.
– Implement least-privilege permissions for the logging mechanism.
– If you expose logs to developers, consider row-level security or masked views.

– Reliability:
– Ensure log table has proper retention policies to prevent unbounded growth.
– Consider archiving old logs to a separate database or storage.

Testing and validating error handling

– Create a controlled set of failure scenarios deadlocks, constraint violations, timeouts.
– Use a test suite to simulate failures in different layers:
– Database-level errors
– Application-level errors
– Network-related errors
– Verify that:
– Errors are captured in ErrorLog with complete context
– Transactions roll back as expected when necessary
– Throw rethrows the original error or a sanitized version, if needed
– Use DBCC DROPCLEANBUFFERS to simulate realistic caching behavior during tests.

Real-world patterns and recipes

– Pattern A: Minimal logging with added context
– Log key details, but avoid verbose data. rely on application layers to enrich visuals or UI.
– Pattern B: Full-stack logging with correlation IDs
– Generate a CorrelationId at the start of a user request and thread it through all procedures. include in ErrorLog for traceability.
– Pattern C: Conditional logging
– Only log errors above a certain severity or those that occur in production vs development.
– Pattern D: Async/log batching
– Write to an in-memory queue and flush to ErrorLog periodically or via a background job to reduce latency impact.

Code snippet: correlation ID example

— At the start of a request
DECLARE @CorrelationId UNIQUEIDENTIFIER = NEWSEQUENTIALID.

— Perform operations, pass @CorrelationId through to all downstream calls
INSERT INTO dbo.ErrorLog ErrorNumber, …, AdditionalInfo
VALUES ERROR_NUMBER, …, CAST@CorrelationId AS NVARCHAR36.

Monitoring, alerts, and dashboards

– Alerts:
– Trigger when ErrorLog count exceeds a threshold in a given period.
– Alert on spikes in ErrorSeverity 20+ or repeated errors from the same procedure.
– Dashboards:
– Track top failing procedures, failure counts by database, and peak error times.
– Show mean time to detect and mean time to recovery if you have incident data.
– Observability tips:
– Include a human-friendly ErrorMessage prefix and a structured JSON field for AdditionalInfo if supported.

Practical step-by-step guide to implement now

1 Create an error log table or confirm you have one.
2 Create a centralized logging procedure optional but recommended.
3 Add TRY…CATCH to your stored procedures and call the logging routine.
4 Add optional correlation IDs and enrichment data.
5 Set up a light-weight monitoring/alerting rule on ErrorLog.
6 Review and adjust retention policies and security controls.
7 Test thoroughly with realistic failure scenarios.

Code example: complete integration

— Step 1: ensure log table exists
CREATE TABLE IF NOT EXISTS dbo.ErrorLog
CorrelationId UNIQUEIDENTIFIER NULL,

— Step 2: centralized logging procedure
CREATE OR ALTER PROCEDURE dbo.usp_LogError
@CorrelationId UNIQUEIDENTIFIER,
INSERT INTO dbo.ErrorLog
ErrorNumber, ErrorSeverity, ErrorState, ErrorProcedure, ErrorMessage, ErrorLine,
LoggedAt, ServerName, DatabaseName, UserName, ApplicationName, CorrelationId, AdditionalInfo
VALUES
@ErrorNumber, @ErrorSeverity, @ErrorState, @ErrorProcedure, @ErrorMessage, @ErrorLine,
@LoggedAt, @ServerName, @DatabaseName, @UserName, @ApplicationName, @CorrelationId, @AdditionalInfo.

— Step 3: sample stored procedure with logging
CREATE OR ALTER PROCEDURE dbo.usp_SampleProcedure
@CorrelationId UNIQUEIDENTIFIER = NULL
SET NOCOUNT ON.
BEGIN TRY
— Simulate some work
INSERT INTO dbo.Sales … VALUES ….
END TRY
BEGIN CATCH
IF @CorrelationId IS NULL
SET @CorrelationId = NEWSEQUENTIALID.

EXEC dbo.usp_LogError
@CorrelationId = @CorrelationId,

THROW.
END CATCH.

Note: adjust the example to your actual schema and environment. The goal is to keep errors observable, traceable, and fast to diagnose.

Frequently Asked Questions

# What is TRY…CATCH and why use it?
TRY…CATCH is SQL Server’s structure for handling runtime errors. It lets you run code and, if something goes wrong, jump to CATCH to log the error, clean up, and optionally rethrow or translate the error for the caller.

# How do I log errors to a table?
Create a dedicated ErrorLog table as shown and write error details inside the CATCH block using ERROR_NUMBER, ERROR_MESSAGE, and related functions. Consider a centralized logging stored procedure to standardize the format.

# Should I log every error or only critical ones?
Start by logging all unexpected errors ERROR_SEVERITY >= 11. You can add conditional logging for less severe errors, but ensure you don’t flood logs with benign messages.

# When should I use RAISERROR vs THROW?
THROW is the modern option in SQL Server 2012+. It preserves the original error and stack. RAISERROR is older and can be used for custom messages, but THROW is generally preferred for new code.

# Can I log errors without impacting performance?
Yes. Use lightweight logging on the hot path minimal columns, indexed log table. For high-volume systems, consider asynchronous logging or buffering logs to a queue for later processing.

# How do I handle nested procedure calls?
Log at the top level to avoid duplicate entries, or implement a centralized logger that’s idempotent. Use TRY…CATCH in each layer if you need granular visibility.

# How to protect sensitive data in logs?
Mask or redact sensitive fields in ErrorMessage or AdditionalInfo. Consider storing only non-sensitive metadata and keep sensitive details in secure systems with restricted access.

# How to log errors in Azure SQL vs on-prem SQL Server?
The approach is the same, but you might extend with Azure Monitor, Log Analytics, or Event Hubs for centralized observability. Ensure network and security configurations allow the logging path.

# How do I test error handling?
Write unit tests or integration tests that deliberately cause failures constraint violations, timeouts, deadlocks. Verify that errors land in ErrorLog with correct context and that transactions rollback correctly when needed.

# How can I automate alerts from error logs?
Hook ErrorLog updates to a monitoring tool or SQL Server Agent job that runs queries like “errors in last hour” and triggers alerts if thresholds are exceeded. Use dashboards to visualize trends over time.

# What about performance tuning for error logging?
Benchmark logging latency and throughput, especially under peak load. If you see contention on the ErrorLog table, add a dedicated filegroup or use partitioning and indexing strategies. Consider asynchronous pipelines for heavy workloads.

# How can I migrate existing error logging to this pattern?
Plan a staged rollout:
– Add the ErrorLog table and optional central logger.
– Refactor procedures to call the logger in CATCH blocks.
– Run parallel validation: compare pre- and post-logging behavior.
– Roll out gradually to avoid large, risky changes in production.

# How should I handle sensitive or regulatory data in logs?
Implement data masking or redaction policies. Store only non-sensitive metadata timestamps, error codes, procedures and route sensitive data to secure storage with proper access controls.

# Can I log errors for batch jobs or ETL processes?
Yes. Treat batch jobs like a single logical unit and capture error metadata with a correlation ID. Centralize logs so you can correlate job failures across multiple steps.

# Is logging required for performance-critical procedures?
Not always. Use a lightweight logging approach for hot paths, and defer deeper logging to off-peak windows or background processes if needed.

If you’d like more concrete examples tailored to your environment Azure SQL, on-prem, specific ER diagrams, or integration with a SIEM, tell me your stack and I’ll tailor the patterns and code snippets for you.

Sources:

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