AWS Lambda is a function-oriented service that lets you store programs and run them on demand. It’s ideal for developers who need to scale up their usage of AWS Cloud resources.
AWS IoT Lambda functions can be set to run automatically in response to various events, enabling you to create powerful IoT experiences.
How Lambda works?
AWS Lambda is a serverless computing service that enables developers to create and run functions without worrying about managing servers. It automatically executes code when called upon, scaling according to the size of the workload.
Lambda offers support for various programming languages, such as Python, Go and Javascript. Each function is given its own environment and view of the file system that it runs within. When running, this function utilizes Amazon’s metered compute and storage resources at a cost based on requests made and time needed to execute code.
Users can manage their Lambda applications using the AWS console, CLI or SDK. Furthermore, they can list, delete, update and monitor functions from either the Lambda dashboard or AWS CloudWatch.
AWS Lambda provides users with the power to programmatically transform data, construct workflows and deliver content. Major League Baseball utilizes Lambda for game-play data enhancements that enhance its speed, scalability and fan engagement. Guardian News Media similarly utilizes Lambda for internal business processes that coordinate across different systems.
For instance, the company utilizes Lambda to manage HTTP responses and cookies, make network calls, and run A/B tests. Furthermore, it utilizes Lambda to send location-specific content through AWS CloudFront event-triggered services.
The AWS Lambda service provides an isolated computing environment for each function and its associated storage and compute resources. When a function is invoked, these resources spin up automatically and you are charged in 100 millisecond increments for compute time used.
Additionally, AWS Lambda provides a free tier that includes one million requests and 400 gigabytes of compute time per month. Additional charges may apply to associated AWS products like Amazon Simple Storage Service (S3).
Another way to utilize AWS Lambda is by connecting it with Amazon Simple Queue Service (SQS). SQS queue allows AWS Lambda to process multiple device messages simultaneously, cutting costs and improving performance. Furthermore, SQS provides message locking, auto-scaling, and 14 day message retention for added convenience.
SQS batching may cause a delay in processing, but this can be managed using an event source property that specifies how long AWS Lambda should wait before processing the batch. Ultimately, it’s the user’s prerogative whether this delay is tolerable or not. Table 2 compares the monthly costs of using SQS batching versus using just a Lambda function alone.
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Event-driven programming
Event-driven programming is a programming paradigm that utilizes a message queue to manage events. This approach has become especially popular in microservice-based software applications, which often have specific tasks triggered by some event.
Event-driven programming model relies on producers sending messages to a queue, while consumers either subscribe for new messages or poll periodically from that queue. This straightforward pattern works well for many applications due to its simplicity.
Another intriguing and useful pattern is one in which producers and consumers are distinct entities, each free to operate independently. This can be especially advantageous in cases where events produced by one party take longer to process than those consumed by the other.
It is also useful for handling sensitive data, such as personal identifiable information (PII), which could be compromised if handled incorrectly. Examples of sensitive data include customer names, social security numbers, driver’s license numbers and financial info.
Stateful programming is ideal for IoT devices with multiple states, such as “running,” “stuck,” or “off.” This enables software developers to link inputs, states and conditional logic together in order to launch actions when the device reaches certain conditions.
Thus, software applications can be kept running optimally at all times. This is especially essential in the context of IoT, where various devices might be sending and receiving telemetry data at different rates.
Event-driven programming presents an intriguing challenge compared to traditional sequential programs, like threads in an RTOS. This concept of inversion of control refers to where control resides – within the event infrastructure rather than outside the program itself.
Consequently, when the program attempts to block, it must quickly return control and enter the event loop. This contrasts with sequential programs which may block for extended periods while waiting for an event to occur.
As an alternative to message queues, Kinesis Data Streams can be used for IoT data routing to Lambda functions. With up to 365-day stream retention and multiple replay options without paying for expensive FIFO queues, this results in up to 68% cost savings compared to using AWS Lambda alone.
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Triggers
Triggers enable you to execute Lambda functions based on events or when conditions are met. AWS offers a vast library of triggers that can be utilized in your serverless applications.
Typically, triggers occur when a resource in your AWS account changes. This includes writing or uploading records to DynamoDB, sending messages through WebSocket channels, and more.
When a trigger event occurs, your Lambda function is automatically invoked. Your function can respond synchronously or asynchronously depending on the type of event.
An S3 event, for instance, is a synchronous trigger that requires your Lambda function to return a response. This response is sent back to the service that initiated it and can be used as confirmation that your Lambda function completed successfully.
DynamoDB table streams can also be used to trigger your Lambda function when an item in a specific table is updated. Unlike S3 events, DynamoDB table streams do not require your Lambda function to send back any response; rather, when an update occurs in a DynamoDB table, its changes are immediately published to its stream and your Lambda function is invoked instantly.
This asynchronous type of event is more frequently used and often the preferred choice for AWS Lambda applications. It allows you to batch multiple DynamoDB table changes into one Lambda event, decreasing the number of invocations your Lambda needs to process.
If your Lambda application triggers actions, it’s essential to monitor its health closely. Enabling CloudWatch and running reports on your lambda will give you valuable insight.
AWS has created the free tool Dashbird to assist with this task. It features an easy-to-use dashboard, enabling you to set alerts and gain insights into what’s happening with your serverless apps. Plus, with Dashbird’s cost tracking features built right in, there’s no need for code modifications!
With AWS IoT 1-Click, you can trigger Lambda functions from simple devices like an AWS IoT button or one connected through an MQTT broker. In this course, you’ll learn how to manage a single button or other device with 1-Click and how to launch Lambda functions on that same device from either the cloud or on-premises.
Discover the AWS Cloud Solutions Architect Professional Certificate, click here.
Monitoring
Lambda is an event-driven compute service that allows users to execute functions as needed. It’s ideal for applications requiring heavy computation and processing power, such as machine learning models.
AWS provides several ways to monitor your Lambda functions. You can use a dashboard for an overview of invocations from within the function, or dig through log messages for insights.
Monitoring is critical for quickly detecting issues with your application and pinpointing the underlying cause of failures. It allows you to optimize Lambda functions, leading to improved user experiences.
Configuring your AWS account to receive alerts from CloudWatch when an error occurs with your Lambda function is beneficial for tracking and diagnosing issues in real-time.
Another option is to utilize Coralogix’s log analytics tool for analyzing the log messages of your Lambda functions. This service offers features like automatic alerting and re-logging, which can greatly enhance monitoring capabilities.
If your applications are running on AWS EC2 instances, CloudWatch allows for easy monitoring of their performance to see the outcomes of Lambda invocations. This provides a convenient and straightforward way to keep an eye on how well your apps are performing.
With AWS Lambda, you only pay for the number of requests and time your functions take to execute. When running, Lambda assigns each function its own container with a certain amount of RAM and CPU capacity; it then executes the code inside that container until it runs out of memory.
AWS Lambda has some limitations compared to Amazon EC2. It may not be ideal for applications requiring high performance, such as those processing large amounts of data or those using machine learning. On the other hand, its scalability makes it ideal for small projects and its user-friendliness make it a popular choice among developers.
