Serverless or Kubernetes on AWS

Many AWS customers standardize on open source technologies that are broadly supported. Open-source can enable an organization to find the right skills - and avoid some risk around lock-in. Making the wrong choices in an open-source ecosystem, can lead to being locked into abstractions and homegrown integrations. Additionally, the responsibility for making different open-source components work together often sits with the organization making the choice. It's common for organizations to spend too much time on maintaining open-source integrations.

Notes:

• Consider community sources and backing from enterprises or foundations when making these investments. An investment in these projects is not just financial. You also need to invest in training and educating your team on the technologies used. 
• You may also incur some technical debt (due to the work involved in maintaining those integrations) as these components and associated integrations will typically need updating.
  
• Visit the AWS Open Source blog for ideas on open source implementations.
  

When selecting a modern app development strategy, it's important that your strategy accommodates a variety of workload patterns. You can more easily make architecture choices by understanding your workload patterns. For example, Web Applications, API-based microservices, Event-Driven Applications, Streaming and Messaging, Data Pipelines, IT Automations, and more. Some workloads will perform better or be more cost effective in one compute environment versus another type.

When building with AWS Serverless, services such as App Runner and AWS Batch are designed to readily support the demands of a given workload type. Workloads using this approach will be easier to build, perform better, or be more cost effective, although it comes at the expense of flexibility.

Kubernetes provides consistency across clouds and on-premises environments if required by your organization.

Workloads do not live in isolation. Workloads are supported by technologies such as databases, messaging, streaming, orchestration, and other services. An effective modern app development strategy requires integration with these services. Managed integrations simplify operational overhead as much as management of the underlying infrastructure.

AWS Serverless options are deeply integrated in the AWS ecosystem. AWS Lambda can subscribe to events from more than 200 other services. AWS Lambda extensions, for example, enable integration with monitoring, observability, security, and governance tools. Lambda invokes a given function in a run environment, which provides a secure and isolated runtime where the function code is run. 

AWS-managed offerings for Kubernetes provide integrations with managed offerings. Kubernetes itself has a rich partner ecosystem, offering integration with numerous other technologies.

Many customers need to create experiments to validate ideas. These prototypes might be the idea for a new application, and/or thrown away if it's unsuccessful. The ability to provide an environment where you can quickly write, deploy, and validate ideas is essential for a healthy environment. This environment is often overlooked when developing a modern app development strategy, but the ability to innovate within the company may depend on it. Enabling teams to use services that can be used to rapidly build, test, and iterate are invaluable in discovering new business opportunities.

Many customers want to ensure that their applications can run in and be easily migrated or moved to a different environment. They want to be able to preserve the choice to move cloud providers, or run an application both on-premises and in the cloud. This often includes the need for supporting popular language frameworks and development scenarios. For example, Java developers might want to use Spring or Python, and Data Engineers might want to use PyTorch. Selecting a modern development app approach will not be enough by itself. It will require best practices and architecture to achieve application portability. We recommend building competency in software architectures and build packaging that allows you to more readily port differentiating business logic between compute services.

Applications built using some technologies may run more effectively on some compute services than others. Container services are usually a better migration target for legacy applications than Lambda, which will require a change in architecture.

There should be a clear difference between application and automation portability. Most of the time, the choice between AWS Serverless or AWS Kubernetes actually has little to do with whether or not an application is portable. Instead, it is the tools used by Infrastructure teams and DevOps teams that are a key factor. Customers who choose the Kubernetes approach on AWS are often looking for portability of infrastructure and deployment tools.

The skills of your organization are a major factor when deciding on whether to take a serverless or container-based approach to modern app development. Both serverless and containers will require some investment in DevOps and Site Reliability Engineer (SRE) teams. Building out an automated pipeline to deploy applications is common for most modern applications.

Some choices elevate the amount of management. For example, some organizations have skills and resources to run and manage a Kubernetes implementation, because they invest in strong SRE teams to manage Kubernetes Clusters. These teams handle frequent cluster upgrades (for example, Kubernetes has three major releases a year, and deprecates old versions).

Organization size is a key factor, as smaller startups might have a small IT staff made up of people fulfilling multiple roles, while larger enterprises may support hundreds of workloads in production at once.

Architecture decisions come with tradeoffs, one of which is often cost. It's common to struggle with estimating the cost of modern applications due to the dynamic nature of the components involved. While the cost of a fixed set of servers is easier to estimate, you also pay for those servers even when they are not adding business value.

Both approaches offer multiple levers to meet cost targets for your workloads. The high-level choice between approaches should consider the cost around not just the resources but also the effort in creating and maintaining that strategy. The AWS Pricing Calculator can be useful in understanding costs of a given workload.

Building with both AWS Serverless and Kubernetes on AWS allow you to build performant, scalable, and resilient workloads. You can meet the technical requirements you need. Services with the highest levels of abstraction manage placement across AWS Availability Zones and scaling of the environment, improving performance and resiliency. Lower levels of abstraction allow you more control in how your workload scales. The primary tradeoffs are cost and management complexity.