As of 2024, the global serverless computing market is projected to reach a value of USD 21.9 billion, with expectations to grow to USD 44.7 billion by 2029.
Around 70% of organizations using AWS have adopted at least one serverless solution. The adoption rates for Google Cloud and Azure are 60% and 49%, respectively.
These numbers affirm that serverless is here to stay, and the demand for platforms to create and run applications is higher than ever.
AWS Lambda is the most popular serverless platform. Maybe you’ve looked into it and found it too complex or restrictive.
In this bookmarkable guide, you’ll discover the best AWS Lambda alternatives. We’ll explore what each alternative offers that Lambda lacks or their similarities. Additionally, we’ll help you understand how serverless computing can also lead to cloud costs and how to control and optimize.
What Is AWS Lambda?
AWS Lambda is an Amazon serverless computing service that automatically runs your code in response to events. Like most serverless platforms, you don’t need to manage servers or infrastructure. Instead, you upload your code through Lambda or other services such as S3 or CI/CD pipelines, and AWS manages everything else. This includes provisioning resources, executing the code, scaling as needed, and maintaining the infrastructure.
With Lambda, developers can also deploy and run small, individual units of code (functions). These are often triggered by events such as API requests, uploads, or changes in databases and is what is known as Functions-as-a-Service (FaaS).
However, Lambda is stateless, meaning functions don’t retain data between executions, and it has execution time limits. While this can be ideal for short-lived tasks, it can be potentially complex for applications needing persistent state or long-running processes.
AWS Lambda limitations
In addition to being stateless and having execution time limits, AWS Lambda has several other drawbacks:
- Limited storage – Lambda offers 512 MB of temporary disk space, only accessible during the function’s execution. This can be restrictive for functions that need more disk space for temporary data processing.
- Limited memory and CPU – Lambda functions have a memory limit of 10 GB, and the amount of CPU allocated is directly tied to the memory size. For compute-intensive tasks or those that need more specialized resources, Lambda may not provide enough power.
- Cold start delays – When a Lambda function is triggered after a period of inactivity, it can experience a delay while the runtime environment is initialized. This is known as a cold start and can increase latency.
- Pricing – While Lambda follows a pay-as-you-go pricing model, it can become costly for high-frequency triggers or long-running tasks. The cost increases with the amount of memory allocated to the function, and extra charges apply for integrated AWS services such as S3 or API Gateway. For consistently low-latency performance, provisioned concurrency — a feature to reduce cold start delays — adds up costs. This makes Lambda expensive for some large-scale or high-traffic applications.
- Deployment package size – Lambda functions have a size limit of 50 MB (zipped) when uploaded via the AWS Management Console and 250 MB (unzipped) when stored in S3. This can impose limitations on applications that rely on large libraries or frameworks.
- Limited debugging and monitoring – While AWS offers tools like CloudWatch, monitoring and debugging in distributed environments demand more complex tooling and may not be as straightforward as traditional server-based applications.
With these limitations in mind, here are some of the top AWS Lambda alternatives to consider.
Note: You won’t find Docker here. While they share some similarities, Docker is not a direct alternative to Lambda. Docker itself does not provide serverless functionality out of the box like Lambda does. You need additional orchestration or services to get a serverless experience with Docker. In the context of containerization, the closest direct alternatives to Lambda would be OpenFaaS, Knative, and Google Cloud Functions, as you’ll see below.
Here is a comprehensive guide on the best Docker alternatives.
13 Lambda Alternatives To Consider
Consider the following.
1. Google Cloud Functions
There are many similarities between Lambda and Google Cloud Functions. However, Google Cloud Functions offers more flexible deployment options. Through Google Cloud Run, developers can use custom Docker containers that support any runtime or language, providing more control over the environment. AWS Lambda also supports custom runtimes but doesn’t offer the full flexibility of container orchestration like Google Cloud Run.
Google Cloud Functions also offers 2 million free monthly requests compared to AWS Lambda’s 1 million.
Google Cloud Functions features
- Flexible execution timeout – Google Cloud Functions has a maximum execution timeout of 9 minutes. It can also be extended to 60 minutes via Google Cloud Run, whereas AWS Lambda has a fixed limit of 15 minutes.
- Cold start performance – Google Cloud Functions often has lower cold start latency than AWS Lambda.
- Integrated tools – Supports development tools such as Cloud Build and Debugger.
- Stateless – Each function runs independently without retaining state between invocations.
- Multiple triggers – Supports Pub/Sub, Firebase, and more.
- Global availability – Deployed across multiple Google regions.
- HTTP/S endpoints – Directly accessible without additional infrastructure like API Gateway. In AWS Lambda, you need to use API Gateway, which adds both complexity and cost.
2. Azure Functions
Azure Functions is a cost-effective alternative for long-running or HTTP-heavy serverless workflows. Its native HTTP integration avoids the need for a separate API service. Azure Functions also features integrated development and debugging that minimizes operational overhead.
Azure Functions also support serverless on any Kubernetes cluster using Kubernetes-based Event Driven Autoscaling (KEDA).
Azure Function features
- Durable functions – They enable stateful workflows, orchestrating complex serverless processes.
- Integration with Azure Monitor – This monitors and optimizes serverless workloads for performance.
- Flexible hosting plans – The Consumption plan is pay-as-you-go with automatic scaling based on demand. The Premium plan supports pre-warmed instances, eliminating cold starts and offering more memory and CPU. The dedicated (App Service) Plan enables users to run functions on dedicated virtual machines.
- Timers and schedulers – Can be triggered at specific intervals using CRON expressions for recurring tasks.
- Binding Support – Can connect to other Azure services such as Cosmos DB, Event Hubs, or Blob Storage via input and output bindings, without additional boilerplate code.
3. DigitalOcean Functions
DigitalOceans Function is most suitable for small-medium organizations and developers. With its simplified command-line tool (doctl), you can develop, test, and deploy functions without the complex configuration or management seen in Lambda.
DigitalOcean Functions is also built on Apache OpenWhisk, which offers vendor-agnostic portability. It integrates IBM Cloud and Netlify, including Red Hat OpenShift and other platforms that support OpenWhisk.
DigitalOceans Functions features
- Developer tools – DigitalOcean’s doctl CLI is more user-friendly for managing functions and local testing than AWS Lambda’s more complex AWS-centric tools.
- Predictable pricing model – DigitalOcean charges solely based on GB-seconds of execution.
- PaaS integration – DigitalOcean’s App Platform simplifies complex serverless workloads.
- Monitoring and logging – Offers integrated logging directly within its dashboard. OpenSearch further supports this by enabling log forwarding from other DigitalOcean services.
Note: DigitalOceans also offers another serverless solution, DigitalOcean Kubernetes (DOKS). It leverages frameworks such as Knative and OpenFaaS to automate scaling and manage serverless workloads in a Kubernetes environment.
4. IBM Cloud® Code Engine
IBM Cloud previously offered IBM Cloud Functions, but the service was deprecated, and as of October 2024, it is no longer available for new deployments. IBM has shifted to IBM Cloud® Code Engine, a fully managed, serverless platform built on Kubernetes and Knative.
Code Engine is considered a cost-efficient deployment option as it enables auto-scaling to zero. This means you are only charged when workloads are running. The platform also supports both FaaS and PaaS models.
IBM Cloud® Code Engine features
- DevOps integration – Integrated with CI/CD pipelines for smooth deployments and management.
- Hybrid cloud flexibility – Works across hybrid cloud environments and other IBM Cloud services.
- Batch jobs support – Allows for running batch jobs, something Lambda does not support.
- Cron-like schedules – Can set up automated, timed triggers for functions or jobs.
- Cost control – Offers efficient cost management by billing only when workloads are actively running.
5. Oracle Functions
Unlike Lambda, Oracle Functions is open source. It is built on the Fn Project, a container-native serverless platform on which you can develop and test your functions locally and then deploy them to Oracle Cloud Infrastructure (OCI) or another environment.
OCI Functions also has several cost advantages over Lambda. It is 17-18% cheaper in common use cases and has a more generous free tier with 2 million requests compared to Lambda’s 1 million. It maintains consistent rates globally and saves on provisioned concurrency costs by only charging for unused capacity.
Oracle Functions features
- Container-native – Oracle Functions uses Docker containers, which means you can package any code as a function.
- Multi-language support – Oracle Functions supports any programming language that can run in a container.
- Function development tools – Developers can use the Fn Project CLI to create, test, and deploy functions locally before pushing them to the cloud.
- Pre-built functions – Oracle offers a catalog of ready-to-use functions for common tasks, eliminating the need to write custom code.
- Security – Oracle Functions integrates with OCI’s built-in security features.
6. Cloudflare Workers
Cloudflare Workers are best suited for high-throughput, low-latency, and globally distributed serverless workflows. They use a more efficient method with the Chrome V8 Engine, enabling them to avoid cold starts almost completely. Cloudflare achieves this by using “isolates,” a lightweight way to securely run different users’ code in the same environment without delay.
Cloudflare Workers also operate on a global network, so they can respond to requests from data centers closest to the user, reducing latency. In contrast, AWS Lambda needs to ensure that the function and the client are in the same region to minimize delays, which might limit flexibility.
Cloudflare Workers features
- Global edge network – Runs code in over 200 data centers worldwide, reducing latency.
- Instant deployment – Deploys code fast to the edge, available globally within seconds.
- Request-based billing – Charges based on requests, not execution time.
- Built-in key-value storage – Workers KV ensure fast data storage and retrieval at the edge.
- HTTP handlers – Ideal for handling, modifying, and proxying HTTP requests.
- Secure sandboxing – Runs code in isolated environments for security without much overhead.
7. Heroku
Heroku is a Platform-as-a-Service (PaaS) best known for its developer-friendly environment. It offers robust support for stateful applications and those involving long-running processes.
Users can also scale the entire application, including the database, web servers, and background jobs. Lambda, however, scales individual functions, which is great for microservices but may be complex for full application scaling.
Heroku features
- CI/CD integration – It integrates with GitHub and CI/CD tools to automate testing and deployment, speeding up development.
- Git-based deployment – Heroku can deploy fast by pushing code via Git, simplifying version control and deployment.
- Dynos for scaling – Easily scale applications by adding or removing isolated containers (dynos).
- Multi-language support – Supports Node.js, Python, Ruby, Java, Go, PHP, and more through buildpacks that set up the environment.
- Automated app management – Handles server management, scaling, and patching automatically.
- Customizable buildpacks – Developers can create or modify buildpacks for better control over the app-building process.
- Managed databases and add-ons – This company offers managed databases (PostgreSQL). The add-on marketplace offers services such as caching, logging, and monitoring.
8. Netlify Functions
For front-end developers looking to build full-stack applications, Netlify Functions is an ideal choice. It also offers edge functions that can run code closer to the user, reducing latency. AWS Lambda offers something similar with Lambda@Edge, but setting it up is more complex and requires using AWS CloudFront.
Netlify Functions features
- Continuous deployment – Every time you push a change to your Git repository, your functions and site are redeployed automatically. This ensures a smooth CI/CD workflow.
- Background functions – For long-running tasks, you can create asynchronous functions that can run in the background for up to 15 minutes.
- Built-in HTTP routing – Enables developers to create APIs without an external API gateway.
- On-demand builders – This feature enables you to pre-build pages or data on demand. By only generating content when it’s needed, it can reduce build times for large sites.
- Regional deployment – You can choose where your functions are executed geographically, optimizing latency. It also ensures data compliance for certain regions.
9. Vercel Functions
Like Netlify Functions, Vercel Functions is also tailored towards frontend-heavy deployments.
It is specifically ideal for JAMstack (JavaScript, APIs, and Markup) workflows. JAMstack separates the frontend (HTML, CSS, JavaScript) from the backend. It uses APIs to handle server-side tasks like form submissions, authentication, and dynamic content. Vercel improves this process by integrating serverless functions directly into front-end development, making it more efficient. Lambda is suitable for backend services.
Vercel Functions features
- Regional deployment – Provides 23 global regions for deploying functions and optimizing performance.
- In-function concurrency – Enables a single function instance to handle multiple requests, improving efficiency.
- Edge caching – Automatically purges and updates data across its global network for real-time content delivery.
- Server-Side Rendering (SSR) – Ideal for Next.js projects requiring server-side rendering.
- Support for API routes – You can create APIs to handle HTTP requests within your functions.
- Integrated logging – Built-in logging and error tracking for debugging functions.
10. Apache OpenWhisk
Apache OpenWhisk is open-source and can be deployed on any infrastructure (including Kubernetes). Compared to Lambda, Apache OpenWhisk is a cost-effective solution and offers more flexibility in runtime environments.
Apache OpenWhisk features
- Action chaining – Combine actions in sequences for complex workflows.
- Asynchronous – Run actions without waiting for results immediately.
- API Gateway – Create serverless APIs with authentication and routing.
- Triggers and rules – Set up events that trigger specific actions.
- Cloud-ready – Works on Kubernetes, OpenShift, and other cloud platforms.
- Service integration – Easily connect to Kafka, Slack, GitHub, and databases.
- Debugging – Includes tools for real-time action monitoring.
- Modular design – Components scale independently for better performance.
As you’ve seen above, most of these platforms support serverless containers. However, they do not use Kubernetes to orchestrate containers.
This is where Serverless Kubernetes comes in. It uses Kubernetes to orchestrate and manage containers automatically while still delivering all the benefits of serverless infrastructure.
AWS Lambda is not a serverless Kubernetes service. If you’re looking for serverless with Kubernetes on AWS, that would be AWS EKS (Elastic Kubernetes Service) with AWS Fargate.
The platforms that implement Serverless Kubernetes are:
11. Fission
Fission is an open-source Kubernetes-native serverless platform that operates as a FaaS. It runs short-lived, event-driven functions without the complexity of directly managing Kubernetes resources.
It also addresses the cold start issue in serverless by keeping a pool of pre-warmed containers. This enables functions to start executing faster than most serverless solutions, which have to initialize containers from scratch.
Fission features
- Custom resource definitions (CRDs) – Fission uses Kubernetes CRDs to define and manage functions. Users can treat functions like any other Kubernetes resource, using tools like `kubectl` for management.
- Built-in CLI – Fission features a command-line interface (CLI) that reduces the complexity of manual K8 management.
- HTTP and message queue support – Fission can expose functions over HTTP or trigger them through message queues like NATS or Kafka, enabling event-driven architectures.
- Environment reusability – Fission separates function code from runtime environments. This enables multiple functions to share the same environment, speeding up deployment.
12. OpenFaaS
Open Functions as a Service (OpenFaaS ) is a serverless framework that runs on top of Kubernetes and Docker. It enables developers to deploy containers as a function, offering the flexibility to run serverless workloads in multiple languages or runtimes.
OpenFaas features
- Automatic scaling – OpenFaaS uses Kubernetes’ Horizontal Pod Autoscaling (HPA) to automatically scale functions up or down based on demand. Check out What is Kubernetes HPA here for more details.
- Function templates – Pre-built templates for common languages and runtimes help developers get started quickly.
- Works with Docker – OpenFaaS also supports Docker Swarm, giving flexibility for teams not fully using Kubernetes.
- Monitoring and metrics – It integrates with Prometheus to monitor container health and performance. Here are more container monitoring tools you should know.
13. Knative
Knative is a set of Kubernetes-based components that extend Kubernetes to add serverless capabilities. It is also open source and a natural fit for complex, event-driven microservices architectures.
Knative features
- Knative serving – Manages rapid deployment and autoscaling of containers.
- Knative eventing – Enables event-driven architectures, allowing applications to produce and consume events from multiple sources.
- Traffic management – Splits traffic between different versions of an application.
- Revision control – Tracks every service deployment, enabling rollbacks and traffic management between versions.
- Kubernetes tool integration – Works with `kubectl` and integrates into existing CI/CD pipelines.
- Cloud-native – Runs on any Kubernetes platform, supporting hybrid or multi-cloud environments.
- Monitoring – Integrates with Prometheus and Grafana for real-time observability and performance tracking.
- Kubernetes operator – Automates Knative deployment and management on Kubernetes clusters.
What next?
How Serverless Computing Can Lead To High Cloud Costs (And How To Manage Them)
While serverless computing offers flexibility and cost efficiency by charging only for actual usage, unexpected high costs can still occur. How?
- Unpredictable scaling – Serverless platforms scale automatically with demand. If your application experiences spikes in traffic, the platform scales up resources. While this is efficient, it can lead to high costs if traffic is unpredictable.
- Long execution times – Serverless charges are based on how long a function runs. If a function takes longer than expected due to inefficient code or complexity, costs can spike.
- API Gateway costs – Serverless applications often depend on APIs to trigger functions. If you use APIs frequently or rely on third-party services, the combined cost of API requests can increase costs.
- High volume of requests – Each serverless request is billed. A small, lightweight function might seem cost-effective. However, if it’s invoked millions of times a month, costs can escalate.
- Idle resource charges – While serverless charges are based on execution time, some services require “reserved concurrency” to reduce latency. This means you may still incur charges even when no requests are being processed.
- Data transfer costs – Serverless functions often communicate with databases and other services. Moving data between regions or services incurs data transfer costs.
- Hidden fixed costs – Serverless might run alongside other cloud services such as VMs or databases. The efficiency of serverless may be overshadowed by fixed costs of these other services, inflating cloud bills.
- Cold start mitigation – To reduce cold start delays, developers often keep functions “warm.” Keeping them ready means paying for resources even when they’re not actively processing requests.
CloudZero can help you manage the complexities of serverless cost management.
- CloudZero offers real-time visibility into serverless costs, enabling immediate action when inefficiencies arise. For instance, if your AWS Lambda usage spikes unexpectedly, you can investigate and resolve the issue before it impacts your budget.
- CloudZero breaks down costs by service, function, or team. This granularity helps trace costs back to specific serverless components such as API Gateway or individual Lambda functions, providing clarity on what drives high costs.
- Using AI, CloudZero detects unusual spending patterns, such as prolonged function runtimes or excessive API calls, and sends alerts. This ensures you address potential cost spikes before they lead to overruns.
- CloudZero doesn’t just monitor costs; it provides actionable insights. It suggests optimizing underutilized resources or refining inefficient code to reduce execution times. This can lower your serverless costs while maintaining performance.
- CloudZero also helps forecast future serverless costs based on current usage patterns. You can set and track budgets in real-time, ensuring that you maintain financial control as your serverless applications scale.
to see how CloudZero can help your organization save on cloud costs with serverless services.
The Cloud Cost Playbook
The step-by-step guide to cost maturity
