[tl;dr AWS CDK provides a means for developers to consume compliant, reusable cloud infrastructure components in a way that matches their SDLC, improving developer experience and reducing the risk of silo’ing cloud infrastructure development and operations .]
Some weeks ago, Amazon launched the AWS Cloud Development Kit, or CDK. This article provides my initial (neutral) thoughts on the potential impact and relevance of the CDK for organizations building and deploying solutions on the cloud.
First, does it work? As the CDK has been in beta for quite a while, when Amazon makes a product generally available, it means it meets a very high bar in terms of quality and stability, and that certainly is the case with the CDK. The examples all worked as expected, although the lambda code pipeline example took some mental gyrations to understand the full implications of what was actually being done – specifically, that the build/deploy pipeline created by the CDK can include running the CDK to generate templates that can be used as an input into that code-deployment pipeline – even if the resulting template is not deployed by the CDK.
All in all, the out-of-the-box experience for the CDK was excellent.
A polyglot framework
Secondly, the CDK is a software development framework. This means it uses ‘traditional’ programming languages (imperative, not declarative), it uses SDLC processes all application developers are familiar with (i.e., build/test/deploy cycles), and it provides many software abstractions that serve to hide (unnecessary) complexity from developers, while enabling developers to build ‘safe’ solutions.
So, the question is, should developers now learn to use the CDK or focus instead on language-specific frameworks?
What the CDK is – and what it is not?
To answer this question, we need to be clear on what the CDK is, and what it is not. CDK is a compiler to generate CloudFormation code. If one considers CloudFormation templates to be the ‘assembly language’ for the AWS cloud ‘processor’, then what is important is that CDK generates high-quality CloudFormation templates – period.
To that extent, the CDK only needs to be as efficient as it takes to generate valid CloudFormation templates. It does not execute those templates, so CDK code will never have run-time performance sensitivities (except perhaps, as with traditional compilers, in build toolchains).
For this reason, Typescript seems to have been a pragmatic choice to implement the CDK in. Run-time performance is not the key factor here – rather, it is the creation of flexible, adaptable constructs that avoids the need for developers to write CloudFormation YAML/JSON. Languages that use the CDK libraries should expect the same performance criteria to apply.
Why CDK is necessary
After working through several of the examples, and observing the complexity of the CloudFormation code the CDK generates – and the simplicity of the example code – it is clear that having developers write CloudFormation template is no more sustainable than having developers write assembly language. CloudFormation (as with Azure Resource Manager and GCP Cloud Deployment Manager) is excellent for small, well-defined projects, but rapidly gets complex when expanded to many applications with complex infrastructure inter-dependencies.
In particular, ensuring the security and compliance of templates becomes very complex when templates are hand-crafted. While services like CloudSploit offer to statically scan CloudFormation templates for security breaches, it would be much better to ensure secure CloudFormation code was written in the first place.
Through Constructs, Stacks, and Apps, the CDK allows enterprise engineering teams to provide libraries of secure, compliant infrastructure components to developers that can be safely deployed.
For this reason, as well as the familiarity of CDK constructs to developers, CDK is likely to end up being more popular than having developers hand-craft CloudFormation templates. The complexity of CloudFormation risks enterprises splitting teams into specialists and non-specialists, reverting organizations back to silo’d infrastructure anti-patterns.
However, having specialist engineering teams focused on building, publishing and maintaining high-quality reusable constructs is a good thing, and this is likely what most organizations enterprise engineering teams should focus on (as well as the larger global community of CDK developers).
With respect to language-specific frameworks, perhaps it is only a matter of time before these frameworks generate the cloud-native templates that the software level abstractions can map directly onto. This may mean that the application footprint for such applications could get much smaller in future, as the framework abstractions are increasingly implemented by cloud constructs. Indeed, as observed by Adrian Cockroft, many of the open-source microservice components developed by Netflix ended up being absorbed by AWS, greatly simplifying the Netflix-specific code-base.
If this outlook proves correct, the correct approach for organizations already committed to a microservices framework would be to stick with it, rather than have their business-facing application developers learn CDK.
With respect to Terraform, the most popular cross-cloud provisioning, deployment and configuration tool, its principle benefit is consistent SDLC workflow across cloud providers. Organizations need to decide if a single end-to-end SDLC for application and infrastructure developers on a single cloud (using CDK) provides more benefits than a single infrastructure SDLC across multiple cloud providers, but with a different SDLC for application developers.
CDK & Serverless
For architectures which are fundamentally not ‘serverless’ in nature, the CDK presents a conflict: by allowing infrastructure to be specified and built as part of the developer lifecycle, where does responsibility for managing infrastructure lie?
The reality is, most organizations still exist in a ‘serverful’ world – where infrastructure environments, even if it’s cloud-based, is a ‘pet’ and not ‘cattle’. Environments tend to be created and managed over the long-term, especially where datastores are involved. Stacks tend to be stable across environments, changing only with new releases of software. Separate teams (from developers) are responsible for the ongoing health, security and cost of environments. These teams are likely to be much more comfortable with configuration and scripting than outright coding, using tools like Chef, Puppet, Ansible or AWS OpsWorks. They may prefer developers or architects to request infrastructure components via tools like AWS Service Catalog or ServiceNow, so that infrastructure code is firmly managed away from developers, and the benefits of SDLC-friendly CDK may be less obvious to them.
Generating and maintaining safe, secure and compliant cloud stacks is a vibrant area of growth, and CDK is unlikely to monopolise this – rather, it may spur the growth of 3rd party solutions. 3rd parties that aim to simplify and standardize cloud infrastructure management (such as Pulumi) will have a role to play, particularly for polyglot language and multi-cloud environments, but ‘serverful’ platform and infrastructure teams need to decide what infrastructure building blocks to expose to developers, and how.
With serverless, this dynamic changes significantly, and the CDK can safely become part of the development team’s SDLC. Indeed, a potential goal for enterprise’s moving towards a serverless target state (i.e., applications consisting of composable services with no fixed/bespoke infrastructure) is to use CDK constructs to define those business-level services as infrastructure components. The concept of a platform-as-a-service to integrate software-as-a-service is a concept worth exploring as this space matures, particularly with the advent of services like AWS EventBridge.
In the meantime, behind every ‘serverless’ service lie many servers..teams have many options as to how best to automate this underlying infrastructure, and CDK is another tool in the toolbox to enable this.
AWS CDK is ground-breaking technology that is a big step towards improving the developer experience and capabilities on (AWS) cloud. Other polyglot cloud providers will likely follow suit or risk widening the gap between cloud infrastructure teams and application development teams. Organizations should consider investing in building and publishing CDK construct libraries to be used by application teams – constructs which can be verified to be secure and with sufficient guardrails to allow less-experienced engineers to safely experiment with solutions.
In the meantime, as cloud platforms extend their capabilities, expect language-specific microservices frameworks to get simpler and smaller (or at least more modular in implementation), enabling application developers to fully exploit a given cloud provider’s platform services. Teams relying on these frameworks should understand and drive the roadmap for how these frameworks leverage cloud-native services, and ensure they align with their wider platform cloud/infrastructure automation strategy.