Container Driven development is A serverless computing architecture helps build applications without using servers, thus enabling developers to focus on code without having to worry about traditional infrastructure. Serverless computing has applications running in stateless compute containers managed by a third party. Here, snippets of code carry out a single, short-lived task. Further, these self-contained blocks of code can be deployed and executed on demand.Amazon’s 2014 release, AWS Lambda is one such computing service that allows developers to create cloud-based functions on an existing fleet of managed instances. AWS also released an API Gateway service later, a public endpoint to invoke Lambda functions over HTTP. A leader in the serverless computing, AWS Lambda allows developers to run back-end code without having to manage their own server systems. Let’s take a look at how it enables serverless computing.
AWS Lambda makes it possible to build highly available application architectures easily. Application architectures can even be stretched across multiple regions to enable geographic redundancy.
One of the trickiest parts of building applications in the cloud is tuning the autoscaling configuration for virtual servers. The right balance has to be struck to scale out based on a spike in traffic and then scale back when things subside. With serverless computing, this gets offloaded to the provider, leaving the customer free to focus on the application. AWS Lambda runs on a fully managed fleet of Elastic Compute Cloud instances. The service thus scales your application based on the code executed and developers don’t need to manage virtual machines (VM) or autoscaling groups.
Elimination of idle resource
Serverless computing only charges for the time it takes the instances to run the code. Traditional servers see some resources left unused but serverless solves this issue by charging if someone uses the application. AWS Lambda also offers sub-second metering that charges only for every 100 milliseconds of code execution.
Enabling a serverless environment
Since the introduction of Lambda, serverless computing has gained huge popularity in the AWS ecosystem. Many organizations are 0the cost-effectiveness of managing a large set of workloads with AWS Lambda as the execution engine. Over 20% of companies on AWS today use AWS Lambda. Users of Lambda are also known to use other AWS services that can contribute to the key use cases enabled by a serverless environment.
AWS Lambda functions are triggered by events with the event source being another AWS service or a custom application. The events can include changes to data in Amazon S3 or DynamoDB, HTTP requests from Amazon API Gateway, detected records off an Amazon Kinesis stream or notifications from Amazon SNS.
Managing a serverless environment
A serverless environment allows the automatic provision and execution of code when a specific event occurs. Taking advantage of a serverless architecture needs the right tools to maintain quality.
Managing AWS Lambda requires a monitoring of the key set of performance metrics with the right tools. Key metrics are:
As the adoption of Lambda gains even more traction, the importance of the right tooling to manage and monitor these functions will become critical. An effective monitoring solution for AWS Lambda must include:
AWS Lambda is disrupting cloud application development and operations patterns. While serverless computing is still in its infancy, organizations are coming to understand the benefits of efficient execution of logic in environments without a VM or OS.
Keeping up with the rapid pace of innovation demands agility, speed, and responsiveness. Modern application developers are thus embracing architecture patterns that eliminate the need for traditional VMs. Breaking up applications into clusters of single functions that run on-demand is thus gaining traction. With AWS Lambda, organizations can achieve efficiency in serverless computing.
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