Launched on November 13, 2014 — AWS Lambda has proved itself an integral tool in the cloud-based services realm. Serverless, or without a dedicated server, implies that AWS Lambda lets you run your applications without worrying about provisioning or managing servers.
It works on a pay-per-execution model. This contrasts with traditional hosting methods, where you’d have to pay for servers irrespective of their usage.
This event-driven and auto-scalable platform can natively run your code in response to changes in data or system state.
For instance,
In this article, we will delve deeper into how AWS Lambda works, its benefits, use cases, best practices, limitations/disadvantages, and lastly, pricing.
The short answer is via running its own container.
Whenever a particular event is triggered, AWS Lambda launches a container to execute the function.
One key aspect is that the container remains available to handle subsequent invocations, thus making the process more efficient by re-utilizing the existing containers and providing “warm starts.”
However, if a request is not triggered for a while, AWS takes down the container, resulting in “cold starts“.
Lambda leverages a VPC for secure system execution, and IAM roles add an extra layer of security to protect cloud operations. Users can customize the VPC for additional customization.
Moreover, AWS Lambda also automatically manages the infrastructure supporting your systems, scaling up or down the concurrency in response to incoming request traffic.
This eliminates the need for manual intervention when spikes in demand occur. The scalability is seamless and immediate, bringing in an enhanced user experience.
There are a host of benefits associated with implementing AWS Lambda. Let’s examine some of the key ones below:
The pay-per-execution billing model put AWS Lambda in the spotlight.
The charges are levied based on the actual amount of compute time used by your functions, not on pre-allocated capacity.
AWS’s billing policy stands out amongst other cloud providers; instead of rounding server time up to the nearest hour, they round up to the nearest 100 milliseconds.
Imagine a sudden surge in user traffic hitting your website; AWS Lambda will decisively adjust and scale your services to maintain optimal performance without needing to configure anything. The system dynamically fluctuates and can manage incoming requests, whether one or a million. This agility ensures minimal response time, achieving a high level of customer satisfaction.
From daily tasks, notifications, and processing S3 objects to chatbots — AWS Lambda can handle it all. This technology also supports real-time data processing, making streaming services such as Amazon Kinesis or AWS Glue viable. Due to its adaptability, AWS Lambda is not restricted to any background or industry. It offers solutions relevant to IoT, gaming, fintech and more.
Code can be shipped directly from the vendor console or Amazon API Gateway. This is all handled automatically without worrying about the underlying operating system, patches, or language runtimes. Quality assurance, security, and deployment processes are managed digitally to speed up the distribution, minimizing human error factors and increasing the productivity of your DevOps team.
Automatic scalability saves time and resources.
Tightening security protocols can eliminate the need for an administrator and result in cost savings, and technical staff can focus on product innovation and development.
Mass-mailing services, payment processors, or CRM tools, AWS Lambda’s compatibility with other AWS services enables the smooth integration and communication between all vital infrastructures within an ecosystem.
Even pairing combinations like Lambda & API gateway or Lambda & DynamoDB are simple to deploy and maintain.
From development to monitoring activities — everything can be organized using a single AWS control center.
UX is held up to a high standard with AWS Lambda.
Swift and seamless operations allow developers to prioritize UX design—meaning faster loading times, reduced latency, and generally more responsive interfaces.
With its easy integration, AWS Lambda enables versatile application features. This leads to improved customer experience, audience retention, and engagement.
There are nine distinctive use cases for AWS Lambda. Below is a brief summary of a few top ones.
There are several best practices that developers and companies should follow to get the most out of AWS Lambda:
Sure, AWS Lambda comes with a pack of benefits, but like all technologies, it has some potential limitations and downsides to consider before integration.
The issue of cold starts affects all serverless computing platforms, not just AWS Lambda. If a function isn’t invoked for some time, it goes into a state of ‘hibernation’ called a ‘cold start.’ This can delay the execution time of your Lambda function, where speed matters.
While not impossible, local testing of AWS Lambda functions is arduous and complex compared with traditional applications. More meticulous planning, tools, and time must be devoted to ensure the effective application of tests.
Be aware that AWS Lambda doesn’t support all programming languages. AWS Lambda provides native support for Java, Go, PowerShell, Node.js, C#, Python, and Ruby. However, if you use languages like R, Swift, PHP, or others, an AWS custom runtime may be required, complicating your setup process.
AWS Lambda functions must conclude within 15-minute windows; anything exceeding the limit causes an issue, particularly for long-batch processes. Concurrent AWS SQS service, for instance, would be more appropriate for such needs.
Configuring and managing environments for developers can be time-consuming and complicated as it implicates both national regions and multiple accounts.
The resources granted to each execution context of an AWS Lambda function are finite. The memory to execution time, networking bandwidth, and storage varies from function to function and can end up hitting limitations if not carefully managed.
AWS Lambda provides an indefinite free tier consisting of 1 million requests and 400,000 GB-seconds of compute time per month. If you surpass these limits, you will have to pay for any excess computing time and requests.
With the Lambda Free Tier, you get 400,000 GB seconds of compute time and 1 million free requests per month. That works out to 110 hours of compute time with 1 GB of function memory and 11 hours with 10 GB.
Once you have used up your free resources, you will need to pay for any further requests.
AWS Lambda charges users based on the number of requests for their functions and the duration required for it to execute.
A request is counted when code begins to run in response to an event. The total number of requests for all functions is charged.
Duration is calculated as the time elapsed between when the code begins executing and when it returns or is terminated, rounded up to the nearest millisecond.
The pricing for AWS Lambda depends on the memory allocated to the function.
For example,
If you have allocated 512 MB of memory to your function, which runs for 200 milliseconds to serve one request, then you’re charged for 200 ms of execution time.
This applies regardless of whether the function used all the allocated memory.
That means if your Lambda function only used 200 MB, you’re still charged the rate of 512 MB.
No matter how complex your use case is, AWS Lambda is an efficient, practical, and cost-effective choice. Strengthen its potential by integrating it with cutting-edge security solutions like Perimeter81 to provide an extra layer of security. Step into the future with Lambda’s simplicity, flexibility, and power – learn more here!
