Why AWS Lambda is a Great Companion for Salesforce: Addressing Storage and Execution Limits
Salesforce is a powerful platform, but it comes with certain limits, such as data storage limits and execution time constraints for Apex code. When your org grows and starts to push against these boundaries, AWS Lambda can be a game-changer.
AWS Lambda is a serverless computing platform that allows you to run code without provisioning or managing servers. It enables you to offload heavy operations, extend Salesforce capabilities, and stay within Salesforce’s limits while reducing costs.
Benefits of AWS Lambda with Salesforce
1. Avoid Salesforce Governor Limits
AWS Lambda can handle compute-intensive tasks like batch processing, external API calls, or data transformation outside of Salesforce’s 10-second Apex execution limits.
2. Handle Large Storage Needs
By storing large datasets in AWS services like S3 or DynamoDB, you can reduce Salesforce data storage usage and access them dynamically through Lambda functions.
3. Real-Time Scalability
AWS Lambda scales automatically based on your workload, making it perfect for use cases like real-time data integration, large file processing, and external system orchestration.
4. Cost-Efficiency
You only pay for the compute time used in AWS Lambda, making it highly cost-effective for handling occasional spikes in workload.
5. Seamless Integration with Salesforce
Using tools like Salesforce Connect, Platform Events, and Apex HTTP Callouts, you can seamlessly connect Salesforce with AWS Lambda to offload processing tasks.
Example Use Case 1: Handling Salesforce Storage Limits
Scenario:
You have large files or reports that need to be stored but don’t fit within Salesforce’s storage limits.
Solution:
1. Upload large files to AWS S3 via an Apex callout to a Lambda function.
2. Store only the metadata (file link, size, etc.) in Salesforce.
AWS Lambda Code:
import json
import boto3
def lambda_handler(event, context):
s3 = boto3.client('s3')
file_content = event['file_content']
file_name = event['file_name']
bucket_name = "your-s3-bucket"
s3.put_object(Bucket=bucket_name, Key=file_name, Body=file_content)
return {
'statusCode': 200,
'body': f"File {file_name} uploaded to {bucket_name}"
}
Salesforce Integration (Apex):
HttpRequest req = new HttpRequest();
req.setEndpoint('https://your-lambda-endpoint.amazonaws.com/dev/upload');
req.setMethod('POST');
req.setHeader('Content-Type', 'application/json');
req.setBody(JSON.serialize(new Map<String, Object>{
'file_content' => EncodingUtil.base64Encode(fileBlob),
'file_name' => 'report.csv'
}));
Http http = new Http();
HttpResponse res = http.send(req);
System.debug('Response: ' + res.getBody());
Example Use Case 2: Processing Large Data Sets
Scenario:
You need to process millions of records, but Salesforce’s batch jobs and limits won’t suffice.
Solution:
1. Export the data from Salesforce to AWS (e.g., S3 or DynamoDB) using Apex callouts or Platform Events.
2. Use Lambda to process the data and return the results to Salesforce.
AWS Lambda Code (DynamoDB Processing):
import boto3
def lambda_handler(event, context):
dynamodb = boto3.resource('dynamodb')
table = dynamodb.Table('SalesforceData')
# Process records
for record in event['Records']:
# Example processing
table.put_item(Item={
'recordId': record['Id'],
'processedValue': record['Value'] * 2
})
return {'statusCode': 200, 'body': 'Processing complete'}
Salesforce Integration (Platform Event Publisher):
PlatformEvent__e pe = new PlatformEvent__e();
pe.Record_Id__c = '123';
pe.Value__c = 100;
EventBus.publish(pe);
Conclusion
AWS Lambda complements Salesforce perfectly by offloading compute-intensive tasks and overcoming governor limits. Whether it’s processing large datasets, storing files, or orchestrating integrations, Lambda ensures seamless scalability and enhanced performance.
By combining Salesforce’s CRM capabilities with AWS Lambda’s power, you can achieve a more robust, scalable, and cost-effective system.
Got a use case where you’re hitting Salesforce limits? Try AWS Lambda and experience the difference! 🚀