How to Understand Serverless vs Fully Managed Services: Complete Guide
By Braincuber Team
Published on April 4, 2026
What You'll Learn:
- What managed services are and how they fit into the PaaS (Platform as a Service) category
- What serverless means and how it fits into the FaaS (Function as a Service) model
- The key differences between server-oriented computing and serverless computing
- Advantages and disadvantages of serverless: scaling, cost, cold starts, and warm starts
- Real-world comparison: AWS Aurora managed vs Aurora serverless with cost analysis
- How to choose between serverless and managed services for your workload
If you are new to cloud technologies, you might be confused about the difference between serverless technologies and managed services. Both terms are used frequently in cloud computing discussions, and they share some interesting similarities. In this complete tutorial, we will break down exactly what each term means, how they differ, and when to use each approach. This step by step guide will help you make informed architectural decisions for your cloud applications. Whether you are a beginner or experienced developer, this beginner guide will show you exactly how these cloud computing models work.
What Are Managed Services?
A managed service lets the end-user focus on using a service rather than setting up the service. Now, this does not mean that the cloud provider can read your thoughts. Rather, any input the service requires happens via a user-friendly form.
Managed services fit into the category of PaaS products (Platform as a Service). One of the most famous managed services around is Amazon's Elastic Beanstalk. In Elastic Beanstalk you can set up some parameters, provide a Docker image, and the service will set up the rest for you.
Virtual Machines
Elastic Beanstalk automatically provisions and configures EC2 instances to run your application.
Web Server Setup
Automatically configures web servers (Apache, Nginx) if needed for your application.
Public Exposure
Automatically exposes your application to the public with URL endpoints and DNS configuration.
Monitoring and Logging
Built-in monitoring, logging infrastructure, and semi-automated configuration management.
Elastic Beanstalk will handle things like load balancing, scaling, monitoring and logging infrastructure, and semi-automated configuration. You will be able to see the results of the Elastic Beanstalk operation, for example the virtual machines that were bootstrapped as a result. Usually, you will not be able to access and fiddle around with them. Otherwise, it is not a managed service -- you are the manager.
So a managed service is essentially an abstraction of a non-managed service. The abstraction is usually interfaced via web forms. And in a managed service as a user, you do not bother with updates, patches, and so on. This is because you have no access to the machines. Someone has to do the laundry. Usually, you have only limited choices, if any, on the underlying system. That might be the operating system or the version of the software used.
What Does Serverless Mean?
With the word serverless we are referring to a different computing model, one that is different from the "traditional" one which is server-oriented. In server-oriented computing (or serverfull if you like more sophisticated words), we use virtual or physical machines to set up and execute our application.
Qualities like the availability and the performance of your applications are strongly bound to the health of your machines. We have perfected clusterization solutions over time (and other tools) to make the decline of machines' health less and less important.
Key Question: Why Pay for Idle Servers?
If we need to scale a cluster of machines, why does this take time? Why do we still pay for idle or underutilized servers (either in money or in lost CPU cycles)? Here comes serverless.
Serverless fits in the category of FaaS products (Function as a Service). The name is a bit misleading, though -- the server where the code runs does in fact exist. You just do not need to care about it, just like in managed services. Serverless goes a bit further, however -- your application runs, when you need it, and for just as long as it should. There are no idle times.
You never get to see the server in your virtual machine dashboard and of course, you do not know any details about the server. Serverless implementations are usually event-driven. The instances are idle unless an event occurs.
Scale-to-One:
Servers are instructed to not be idle,
staying warm and ready for requests.
When busy: They get support from other
clones (horizontal scaling).
When done: They go idle again until
the next event occurs.
Advantages of Going Serverless
There are several benefits of serverless implementations. Let us explore each one in detail.
Easy and Effective Scaling
A big advantage is that serverless architectures scale easily and effectively. This is because they are usually based on lightweight installation media, like Docker images and containers, and you do not need to provision extra machines. In theory, with serverless computing, you have the whole cloud infrastructure of the provider at your feet.
Cost Benefits
Speaking about costs, serverless code is billed per second and at a higher rate than a machine lease. So it is recommended that you run it for relatively short workloads. Some providers put a hard limit on how long serverless code can run. This is to also avoid unpleasant surprises on your bill.
One notable example of full-stack serverless and the cost benefits that come with it is acloud.guru. The instructor mentioned that "We pay $400 per month with Serverless and it would be around $100,000 using servers." This dramatic cost difference demonstrates the power of serverless for the right workloads.
| Aspect | Serverless | Traditional Servers |
|---|---|---|
| Billing Model | Per second of execution | Per hour/month regardless of usage |
| Idle Cost | Zero cost when idle | Pay for idle time continuously |
| Scaling Speed | Instant horizontal scaling | Takes time to provision new machines |
| Infrastructure | No machine provisioning needed | Must provision and manage VMs |
Disadvantages of Serverless
One of the cons of serverless architecture relates to time-critical applications. Usually, newly deployed serverless functions experience some kind of latency also known as a "cold start". There are mitigations that can help you deal with cold starts, called "warm starts". But you may want to check other architectures for such requirements.
Cold Start:
Newly deployed or idle serverless functions
experience latency on first invocation.
The platform must initialize the runtime.
Warm Start:
Subsequent invocations are faster because
the runtime is already initialized and
the function instance is kept alive.
Mitigation:
Use scale-to-one, provisioned concurrency,
or periodic ping functions to keep warm.
Managed Services + Serverless: The Overlap
As you have probably figured out by now, serverless and managed services have some interesting similarities. We can sum them up like this: Do not worry about the infrastructure, focus on your business value.
By the way, serverless solutions provided by the cloud providers (like AWS Lambda, Azure Functions) are actually managed, too. That means you can set up your serverless architecture using high-level abstractions and input your preferences and configuration with the forms they provide.
Real-World Example: AWS Aurora Managed vs Serverless
There is a very interesting public service that comes with both flavors, managed and serverless. This is AWS Aurora. Aurora is a managed database, compatible with MySQL and PostgreSQL.
Aurora Managed (Serverfull)
In the managed option, you set up a database using a form, and it brings up a few virtual machines and takes care of their health. In this case, you can just focus on deploying a good database schema. In this managed method, the database is running 24/7/365. Or at least that is the goal, as it offers very high availability and otherwise works in the same way as any database server you have used in the past.
Aurora Serverless
There is also the serverless flavor, where Aurora is set up in a serverless way. In that case, you have the storage "deployed" 24/7/365 as above. You cannot have serverless storage, which is contradictory. But the processes that perform data manipulations on your data, like fetch and update, can be easily converted to serverless functions.
Aurora serverless often costs a lot less, as the data manipulations run on an as-needed basis. But if the database is fairly busy the costs might be higher than in a serverfull architecture. That being said, it is better to use Aurora serverless when your workload is intermittent and unpredictable.
| Workload Type | Recommended Aurora Flavor | Why |
|---|---|---|
| Intermittent and unpredictable | Aurora Serverless | Pay only when data manipulations occur, significant cost savings during idle periods |
| Consistent and heavy traffic | Aurora Managed (Serverfull) | Serverless per-second billing may exceed fixed server costs under heavy continuous load |
| Time-critical low-latency needs | Aurora Managed (Serverfull) | Avoids cold start latency, always-ready database connections |
| Development and testing | Aurora Serverless | Minimal cost during non-working hours when database is not actively queried |
What is OpenFaaS?
If you want to run serverless computing and FaaS without relying on a public provider, you can use OpenFaaS. This technology will not only give you more control over your architecture. It will also help you realize that the serverless model relies on clustering technologies like Kubernetes.
With OpenFaaS, you will learn how you can set up scaling rules and cold and warm starts. It is a great way to understand the underlying infrastructure that public cloud providers abstract away from you.
More Control
Run serverless on your own infrastructure without depending on public cloud providers.
Kubernetes-Based
Learn how serverless relies on clustering technologies like Kubernetes for orchestration.
Custom Scaling Rules
Configure your own scaling rules and cold/warm start behaviors for fine-grained control.
No Vendor Lock-In
Avoid dependency on a single cloud provider with an open-source serverless platform.
Key Differences Summary
| Aspect | Managed Services (PaaS) | Serverless (FaaS) |
|---|---|---|
| Category | Platform as a Service (PaaS) | Function as a Service (FaaS) |
| Visibility | Can see VMs and resources created | Never see servers or VMs |
| Execution Model | Always running (24/7/365) | Event-driven, runs only when needed |
| Billing | Pay for provisioned resources | Pay per second of execution |
| Idle Cost | Pay even when idle | Zero cost when idle |
| Scaling | Auto Scaling Groups (configurable) | Automatic horizontal scaling |
| Latency | Consistent, always-ready | Cold start on first invocation |
| Best For | Consistent workloads, full applications | Intermittent workloads, microservices |
| Examples | Elastic Beanstalk, Aurora Managed | AWS Lambda, Aurora Serverless |
How to Choose Between Serverless and Managed Services
Choose Serverless When
Your workload is intermittent and unpredictable. You want to minimize costs during idle periods. You are building microservices or event-driven architectures. You do not want to manage any infrastructure at all.
Choose Managed Services When
Your workload is consistent and heavy. You need predictable performance without cold start latency. You want to deploy full applications rather than individual functions. Serverless per-second billing would exceed fixed server costs.
Combine Both When
Many architectures benefit from both. Use managed services for consistent core infrastructure and serverless for burst workloads, event processing, and cost optimization on intermittent tasks.
Frequently Asked Questions
What is the difference between PaaS and FaaS?
PaaS (Platform as a Service) like Elastic Beanstalk manages the platform for running full applications 24/7. FaaS (Function as a Service) like AWS Lambda runs individual functions only when triggered by events, with no idle costs.
What is a serverless cold start?
A cold start is the latency experienced when a newly deployed or idle serverless function is invoked for the first time. The platform must initialize the runtime environment before executing your code.
Is serverless always cheaper than managed services?
Not always. Serverless is cheaper for intermittent workloads with idle periods. For consistently heavy workloads, managed services with fixed resource costs can be more economical than per-second serverless billing.
Can serverless services be managed too?
Yes. Serverless solutions from cloud providers like AWS Lambda and Azure Functions are themselves managed services. You configure them through web forms without managing any underlying infrastructure.
When should I use Aurora Serverless vs Aurora Managed?
Use Aurora Serverless for intermittent and unpredictable workloads to save costs. Use Aurora Managed for consistent heavy traffic and time-critical low-latency needs where cold start latency is unacceptable.
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