Amazon Web Services
Compute
- AWS EC2
- EC2 Instance Types
- EC2 Pricing Models
- EC2 Auto Scaling
- Elastic Load Balancing-ELB
- AWS Lambda – Serverless Computing
- Amazon Lightsail
- AWS Elastic Beanstalk
- AWS Fargate
- Amazon ECS (Elastic Container Service)
- Amazon EKS (Elastic Kubernetes Service)
DynamoDB
- DynamoDB Global Table vs Regular DynamoDB Table
- DynamoDB Streams
- Athena query data to DynamoDB
- Athena Query Results with DynamoDB
- PySpark DataFrame to DynamoDB
Redshift
Lambda
Glue
Lambda
Storage
- S3 vs. EBS vs. EFS
- Amazon S3 (Simple Storage Service)
- Amazon S3 Storage Classes
- Amazon EBS (Elastic Block Store)
- Amazon EFS (Elastic File System)
- AWS Storage Gateway
- AWS Snowball
- Amazon FSx
- AWS Backup
Security
⚡ Mastering Concurrency in AWS Lambda: A Beginner-Friendly Guide
AWS Lambda is one of the most powerful serverless compute services offered by AWS. It allows you to run code without worrying about servers, scaling, or infrastructure. But one important aspect of using Lambda in production is managing concurrency.
When a Lambda function is triggered, AWS automatically creates an instance of that function to handle the request. If more requests arrive at the same time, Lambda scales out by creating more instances. This is great for scalability, but uncontrolled concurrency can cause:
- Throttling errors if concurrency limits are reached.
- Increased costs due to over-scaling.
- Database connection exhaustion if too many Lambda instances connect at once.
That’s why understanding and controlling concurrency is critical.
In this guide, we’ll break down:
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Types of Concurrency in AWS Lambda
- Unreserved Concurrency
- Reserved Concurrency
- Provisioned Concurrency
-
How to use each one (with examples).
-
Memory tricks for interviews & exams.
-
Why concurrency management is important.
🔑 Understanding Concurrency in AWS Lambda
Before diving into specific strategies, let’s clarify the basics.
- Concurrency = Number of Lambda instances running simultaneously.
- Each new request → new execution environment (if not already available).
- Account-level concurrency limit (default: 1000 per region, adjustable).
Types of Concurrency in AWS Lambda
-
Unreserved Concurrency
- Default behavior.
- Functions share concurrency pool.
- If one function uses too much, others may get throttled.
-
Reserved Concurrency
- You dedicate a fixed number of concurrent executions to a function.
- Ensures critical functions always have capacity.
- Also acts as a throttle (caps max usage).
-
Provisioned Concurrency
- Pre-warms Lambda instances so there’s no cold start latency.
- Ideal for latency-sensitive workloads (APIs, financial apps).
- Costs more than reserved concurrency.
🔥 1. Unreserved Concurrency
📌 What It Means
- Default concurrency pool shared by all Lambda functions.
- Scales up until account concurrency limit is reached.
- Risk: noisy neighbors (one function consumes all concurrency).
✅ When to Use
- For non-critical, batch, or experimental functions.
- When you don’t want to manage concurrency manually.
🖥️ Example Programs for Unreserved Concurrency
Example 1: Simple Function without Concurrency Settings (Python)
import json
def lambda_handler(event, context): return { "statusCode": 200, "body": json.dumps({"message": "Unreserved concurrency example"}) }
This runs in the default pool. AWS decides concurrency automatically.
Example 2: Trigger Multiple Concurrent Executions (SQS + Lambda)
import boto3
sqs = boto3.client('sqs')queue_url = "https://sqs.us-east-1.amazonaws.com/123456789/myQueue"
for i in range(50): # Send 50 messages sqs.send_message(QueueUrl=queue_url, MessageBody=f"Task {i}")
If this Lambda is subscribed to SQS, it will spin up multiple concurrent executions.
Example 3: Monitor Concurrency with CloudWatch
aws cloudwatch get-metric-statistics \ --namespace AWS/Lambda \ --metric-name ConcurrentExecutions \ --start-time 2025-08-26T00:00:00Z \ --end-time 2025-08-27T00:00:00Z \ --period 300 \ --statistics Maximum
🔥 2. Reserved Concurrency
📌 What It Means
- Assigns a fixed concurrency limit to a function.
- Guarantees availability.
- Prevents the function from consuming entire account concurrency.
✅ When to Use
- Mission-critical functions (payment processing, authentication).
- To throttle functions that should not scale endlessly.
🖥️ Example Programs for Reserved Concurrency
Example 1: Set Reserved Concurrency (CLI)
aws lambda put-function-concurrency \ --function-name criticalFunction \ --reserved-concurrent-executions 20
Example 2: Python Code to Configure Reserved Concurrency
import boto3
lambda_client = boto3.client('lambda')
response = lambda_client.put_function_concurrency( FunctionName='criticalFunction', ReservedConcurrentExecutions=20)
print("Reserved concurrency set:", response)
Example 3: Remove Reserved Concurrency
aws lambda delete-function-concurrency --function-name criticalFunction
🔥 3. Provisioned Concurrency
📌 What It Means
- Pre-initializes execution environments.
- No cold start → consistent low-latency performance.
- Costs extra (pay for provisioned capacity even if idle).
✅ When to Use
- Latency-sensitive APIs.
- Financial transactions or real-time analytics.
- Applications where cold starts are unacceptable.
🖥️ Example Programs for Provisioned Concurrency
Example 1: Configure Provisioned Concurrency (CLI)
aws lambda put-provisioned-concurrency-config \ --function-name fastAPI \ --qualifier 1 \ --provisioned-concurrent-executions 5
Example 2: Python Boto3 Example
import boto3
lambda_client = boto3.client('lambda')
response = lambda_client.put_provisioned_concurrency_config( FunctionName='fastAPI', Qualifier='1', ProvisionedConcurrentExecutions=5)
print("Provisioned concurrency configured:", response)
Example 3: Auto Scaling with Application Auto Scaling (YAML)
Resources: LambdaAutoScaling: Type: AWS::ApplicationAutoScaling::ScalableTarget Properties: MaxCapacity: 10 MinCapacity: 2 ResourceId: function:fastAPI:1 ScalableDimension: lambda:function:ProvisionedConcurrency ServiceNamespace: lambda
🧠 How to Remember for Interview & Exam
-
Unreserved Concurrency → Default, shared pool. (Think: “Unreserved = everyone shares.”)
-
Reserved Concurrency → Fixed per function, guarantees slots. (Think: “Reserved = reserved seats in a theater.”)
-
Provisioned Concurrency → Pre-warmed, no cold start. (Think: “Provisioned = always ready like a hot coffee.”)
🎯 Why It’s Important to Learn Concurrency Management
- Cost Control – Prevent unexpected high bills from uncontrolled scaling.
- Reliability – Ensure critical functions always run, even under heavy load.
- Performance – Reduce cold start latency for user-facing apps.
- Compliance – Some industries require guaranteed availability.
- Interviews & Exams – Common topic in AWS certifications and cloud job interviews.
📌 Conclusion
Concurrency in AWS Lambda is one of the most important topics for both real-world projects and certification exams. To recap:
- Unreserved Concurrency: Shared pool, automatic scaling.
- Reserved Concurrency: Guarantees capacity for critical functions.
- Provisioned Concurrency: Eliminates cold starts, best for latency-sensitive apps.
By mastering concurrency, you can build scalable, cost-effective, and highly reliable serverless applications.