AWS Lambda Managed Instances Offer Specialized Compute Configurations
AWS often promises us routes to simplicity; the ever-present specter of cloud complexity drives the organization to examine its toolsets and look for ways to make users’ lives easier and provide cloud engineers with functions that they know will be more performant, secure and predictable from a cost efficiency perspective.
Recent developments at AWS have seen the company work to uphold the operational simplicity offered by Lambda, the compute service that allows teams to runs code without the need to manage servers in a way that scales up and down automatically, with pay-per-use pricing.
Now aiming to carry ease-of-use forward, AWS Lambda Managed Instances enables teams to run Lambda functions on their Amazon EC2 instances, while maintaining Lambda’s operational simplicity.
Specialized Compute Configurations
With Lambda Managed Instances, cloud-native engineers get the chance to access specialized compute configurations and drive cost efficiency through EC2 pricing advantages, without managing infrastructure.
AWS doesn’t specify what these specialized compute configurations are, but we can infer that this means memory-optimized configurations (for workloads that process large datasets, often in memory), storage-optimized configurations (where apps require high sequential read and write access), compute-optimized configurations and those aligned for accelerated computing on GPUs and so on.
“Lambda Managed Instances fully manages all infrastructure tasks, including instance lifecycle, OS and runtime patching, built-in routing, load balancing and auto-scaling based on configurable parameters – so you can focus on writing code. This operational simplicity extends to the extensive EC2 instance catalog, giving you access to the latest-generation processors like AWS Graviton4 and high-bandwidth networking options,” details AWS, in a technical product statement.
Users can process parallel requests within each execution environment, a function that is intended to help maximize resource utilization and improve price-performance.
Steady-State As She Goes
Lambda Managed Instances are said to be ideal for customers requiring specialized hardware configurations, as well as those with steady-state or predictable workloads seeking to optimize costs while maintaining Lambda’s serverless experience.
That’s great news, of course, but it does mean the AWS simplicity promise is more realistically achievable in steady, repeatable, predictable, foreseeable workloads where customers can specify the amount and type of compute or analytics or storage they are going to require at the start of their (to use the AWS term above) instance lifecycle. So then, arguably somewhat not quite like the core promise of cloud computing flexibility in the first place.
Deliberate naysaying notwithstanding, the advantages on offer here will have different suitability, relevance and appeal for different customers, at least they do exist in the first place.
Straightforward Start-up
Getting started is straightforward, says AWS. Users can continue building functions with familiar development workflows, including Console or their preferred IDEs.
“First, create a capacity provider that defines your compute preferences, including VPC configuration, optional instance requirements and scaling policies. Then, attach your Lambda functions to the capacity provider via the AWS Lambda Console, APIs, or Infrastructure as Code tooling. Lambda Managed Instances integrates seamlessly with all Lambda event sources and tools like Amazon CloudWatch, AWS X-Ray and AWS Config. Latest versions of Java, Node.js, Python and .NET runtimes are supported,” notes AWS.
Lambda Managed Instances is now available in the U.S. East (N. Virginia), U.S. East (Ohio), U.S. West (Oregon), Asia Pacific (Tokyo) and Europe (Ireland) Regions.
