Updated October 2026 · Written and maintained by the Progression Agency strategy team
Serverless app development services design and build applications on managed functions and services, such as AWS Lambda, Azure Functions and Google Cloud Run functions, with managed queues, databases and API gateways around them, so you pay for use and never patch a server. The provider still runs servers; you just do not manage them. It suits spiky, event-driven and API workloads and is the wrong choice for some steady or long-running ones, which we say before any build. Progression Agency is based in New York City and works with clients across the United States and worldwide.
On this page · 15 sections
- What is serverless app development?
- Our serverless app development services, from first sketch to steady running
- Serverless architecture examples: what we build
- Serverless architecture: the building blocks on each cloud
- Benefits of serverless, with the costs and limits beside them
- When should you use serverless architecture, and when is it a bad idea?
- Security for serverless functions
- Observability and testing: seeing a request across many functions
- How much does serverless cost? The pricing model explained
- Can you migrate an existing app to serverless?
- How to hire serverless developers: in-house, freelance or a serverless app development company
- Our process, stage by stage
- How CTOs ask AI assistants for serverless help, and which sources they cite
- How to choose a serverless development company
- Neighboring software and cloud services
The short answerServerless is worth choosing when traffic is uneven, work starts from events, and the team would rather ship features than run infrastructure. We draw the architecture against each provider’s published limits, build the riskiest path first, define every resource in code, give each function only the permissions it needs, and put alarms on errors, throttles and spend before launch. Success is judged on latency, error rate and the monthly bill against the targets in the scope. Pricing follows a written scope for each build, and the code, data and cloud accounts belong to you.
Provider limits, pricing models and product names are described from AWS, Microsoft, Google Cloud and OWASP documentation as read in October 2026 and change often; builds are priced only after a written scope.
What is serverless app development?
Serverless app development means writing your application as small pieces of code that a cloud provider runs on demand, plus managed services for storage, messaging and APIs. You are billed per request or per unit of compute used, and capacity grows and shrinks without anyone resizing machines.
How do serverless apps work?
A trigger fires: an HTTP request through an API gateway, a file landing in storage, a message on a queue or a timer. The platform starts an execution environment, runs your function with that event, and keeps the environment warm for a while in case another event arrives. State lives in a database or cache, never in the function itself.
Serverless application development in one sentence for your board
Serverless application development swaps a fixed monthly server bill and a patching rota for a usage-based bill and a set of provider limits you design around. That trade is excellent for some products and poor for others, which is why the first deliverable is an architecture note, not code.
What serverless does not mean
It does not mean no operations work. Someone still sets permissions, watches costs, tunes memory, reads traces and plans for quotas. The work moves from machines to configuration, and our DevOps team builds the pipelines and monitoring that carry it.
Our serverless app development services, from first sketch to steady running
We cover the whole path, and you can stop after any stage with something usable in hand. Our serverless app development services are delivered remotely by a team that writes the architecture, the code and the infrastructure definitions together.
| Engagement | What you receive | When it fits |
|---|---|---|
| Serverless consulting | An architecture note, a fit verdict and a list of provider limits that matter | Before money goes into a build |
| Proof of concept | The riskiest path built and load-tested on your cloud account | When a stakeholder needs evidence |
| New application build | APIs, functions, workflows, data stores and pipelines, all defined in code | Greenfield products and features |
| Serverless backend for mobile apps | Sign-in, sync, uploads, push notifications and an admin API | iOS, Android or cross-platform apps |
| Migration to serverless | One service or job moved at a time, with a rollback path | Older apps with painful hot spots |
| Cost and reliability review | A findings report on spend, retries, logging and alarms | Live apps whose bill or error rate surprises you |
| Ongoing support | Monitoring, dependency updates, quota reviews and tuning | Apps that have launched and need care |
Serverless application development services included in every build
Whatever the size of the engagement, the same working parts come with it, so nothing basic is left for a later invoice.
- An architecture note with the provider limits that matter marked on the diagram
- Infrastructure defined in code and kept in your repository
- A separate role and permission set for each function
- Secrets held in a managed store, never in code or logs
- Structured logs that carry a request ID across every function
- Alarms on errors, throttles, queue age and daily spend
- A deployment pipeline with tests that runs on every change
- Runbooks and a handover session for your own engineers
Serverless consulting before any code
Serverless consulting answers three questions in writing: does the workload suit functions, which provider limits shape the design, and what the running cost depends on. If the answer is containers or a plain server, the note says so and explains why.
AWS Lambda development services
AWS Lambda development is where most of our function work lands, usually with API Gateway, SQS, EventBridge, DynamoDB or Aurora and Step Functions around it. For AWS-heavy teams this is the default path; hosting a website on AWS covers the static front end that often sits beside these backends.
Azure Functions development
Azure Functions development suits teams already on Microsoft identity, .NET or Azure data services. New function apps go on the Flex Consumption plan, with Durable Functions for long or stateful workflows. Our guide to putting a site on Azure explains the web tier.
Google Cloud functions development on Cloud Run
On Google Cloud, functions now deploy as Cloud Run services built from source, so the same platform runs a quick function and a full containerized API. That makes it a natural choice when part of the app may outgrow a function later.
Serverless architecture examples: what we build
Most products are a few recurring patterns stitched together. These serverless architecture examples are the ones we design most often, each with the trigger that starts it and the managed pieces around it.
| Pattern | Trigger | Typical managed pieces | Watch out for |
|---|---|---|---|
| REST or GraphQL API | HTTP request through a gateway | Gateway, functions, a managed database, an auth service | Cold starts on rarely used routes |
| Serverless backend for mobile apps | App calls and push events | Auth, object storage, a document database, notifications | Chatty clients that multiply requests |
| File and media processing | Upload to object storage | Storage events, functions, a queue for heavy steps | Large files that exceed payload limits |
| Scheduled jobs | A timer or cron rule | Scheduler, functions, a workflow for multi-step jobs | Jobs that outgrow one invocation |
| Webhooks and integrations | Callbacks from payments, CRM or SaaS tools | Gateway, a queue to absorb bursts, idempotent functions | Duplicate deliveries from the sender |
| Real-time features | Messages and connection events | WebSocket or pub-sub service, functions, a fast store | Fan-out costs as users grow |
| AI inference steps | A queue message or workflow step | Workflow service, model API calls, a results store | Model latency longer than the gateway allows |
Serverless API development
Serverless API development starts with the contract: routes, request and response shapes, auth and rate limits, written before the first function. Each route gets its own function or a small set of routes shares one, chosen by how differently they scale and what permissions they need.
Serverless backend development for web and mobile
A serverless backend gives a web or phone app sign-in, data sync, file uploads and notifications without a server to keep alive overnight. It pairs with our web app development work and with native apps from our iOS and Android teams.
Serverless web app development and SaaS products
For a serverless web application, the front end is served from a CDN and every dynamic call goes to the API. Serverless SaaS adds tenant isolation in data and permissions; our SaaS development page covers billing, tenancy and onboarding around that core.
Serverless architecture: the building blocks on each cloud
Every serverless architecture uses the same five building blocks: functions, an API front door, queues or streams, workflow orchestration and managed data. The names differ by provider; the limits differ more, and they shape the design.
| Building block | AWS | Microsoft Azure | Google Cloud |
|---|---|---|---|
| Functions | AWS Lambda | Azure Functions on the Flex Consumption plan | Cloud Run functions |
| API front door | Amazon API Gateway | Azure API Management | API Gateway |
| Queues and events | SQS, SNS, EventBridge | Service Bus, Event Grid | Pub/Sub, Eventarc |
| Workflow orchestration | AWS Step Functions | Durable Functions | Workflows |
| Managed data | DynamoDB, Aurora Serverless | Cosmos DB, Azure SQL | Firestore, Cloud SQL |
| Infrastructure as code | AWS SAM, CDK, Terraform | Bicep, Terraform | Terraform |
To weigh the three clouds against each other first, read our cloud provider comparison, which has a section on serverless and edge; this page goes deeper on building with functions.
AWS Lambda limits that shape a design
AWS lists the numbers in its Lambda quotas page: a standard function invocation can run for up to 15 minutes, memory ranges from 128 MB to 10,240 MB, synchronous requests and responses are capped at 6 MB each and asynchronous events at 1 MB, and a new account’s default is 1,000 concurrent executions in each Region, a soft limit you can ask to raise. AWS also notes that API Gateway’s default throttle of 10,000 requests per second can outrun that default concurrency, so we load-test against both.
Azure Functions limits worth knowing
Microsoft’s hosting comparison for Azure Functions now labels the Consumption plan legacy and points new serverless apps to Flex Consumption, which scales out to as many as 1,000 instances with 512 MB, 2,048 MB or 4,096 MB instance sizes. Whatever the timeout setting, an HTTP-triggered function has 230 seconds to answer a request, so longer work moves to a queue or a durable workflow. Hosting Linux apps on the Consumption plan retires on 30 September 2028.
Google Cloud Run functions
Google’s Cloud Run functions comparison explains that the product formerly called Cloud Functions (2nd gen) is now Cloud Run functions: code is built into a container automatically and deployed as a Cloud Run service. That shared platform makes it easy to move a function to a full service later without changing clouds.
Workflow orchestration: Step Functions and Durable Functions
Multi-step processes belong in a workflow service, not in functions calling each other. AWS Step Functions offers Standard workflows that run for up to one year with exactly-once execution and Express workflows of up to five minutes at high event rates. On Azure, Durable Functions adds orchestrator, activity and entity functions, with the runtime handling state, checkpoints and retries.
Serverless architecture design and best practices
Our serverless architecture best practices are short: keep functions small and single-purpose, make every handler idempotent because events can arrive twice, put a queue in front of anything slow or fragile, store state outside the function, and set timeouts shorter than the caller’s so failures surface instead of hanging.
Planning an API or backend and wondering if functions fit?Describe the traffic you expect, the data it touches and the clouds you already pay for. We reply with a written architecture note that says whether serverless suits it, and why.
Benefits of serverless, with the costs and limits beside them
The benefits of serverless are real: no servers to patch, capacity that follows demand, billing that falls to near zero when nothing runs, and faster delivery for small teams. Each one has a matching cost, and an honest design lists both.
| Benefit | What it buys you | The matching cost or limit | How we contain it |
|---|---|---|---|
| No servers to manage | No OS patching, capacity planning or cluster upgrades | Less control over runtime, networking and hardware | Pick the plan or a container where control matters |
| Scales with demand | Bursts absorbed without pre-booking capacity | Concurrency quotas and downstream databases can be overwhelmed | Queues, reserved concurrency and load tests |
| Pay for use | Idle hours cost little or nothing | Steady heavy traffic can cost more than reserved machines | Model the bill at expected and peak volume first |
| Faster delivery | Small teams ship features without infrastructure work | More moving parts to wire, test and trace | Infrastructure as code and tracing from day one |
| Built-in availability | Providers run functions across zones by default | Cold starts after idle periods | Provisioned concurrency, SnapStart or always-ready instances |
| Managed integrations | Triggers from storage, queues and schedules out of the box | Vendor lock-in through triggers and services | Keep business logic in plain modules behind thin handlers |
Cold starts and how to soften them
A cold start is the delay while a new execution environment loads your code. On AWS, Lambda SnapStart resumes environments from a cached snapshot for Java 11 and later, Python 3.12 and later and .NET 8 and later, while provisioned concurrency keeps environments initialized and is billed separately. On Azure, always-ready instances are available on the Flex Consumption plan. We apply these only to the endpoints where latency is in the scope.
Vendor lock-in, contained rather than ignored
Lock-in lives in triggers, permissions and managed services, not in the function code. We keep business logic in ordinary modules that a thin handler calls, define infrastructure in code, and record which services would need replacing if you moved. That keeps a future move a project, not a rewrite.
Local testing and observability gaps
Functions are harder to run on a laptop than a monolith. Tools help: AWS SAM is an open-source framework whose CLI can test functions and simulate API endpoints locally. We still test against a real cloud stage before release, because permissions and event shapes are where local runs lie.
When should you use serverless architecture, and when is it a bad idea?
Use it when work is event-driven, traffic is uneven and the team is small. Avoid it, or limit it to the edges, when traffic is steady and heavy, jobs run long, latency must be tight on every call, or the work needs GPUs or persistent connections.
Where serverless is the right call
Strong candidates include public APIs with busy and quiet hours, mobile backends, document and image processing, scheduled reporting, payment and CRM webhooks, internal tools used during business hours, and new products whose traffic nobody can forecast yet.
When serverless is a bad idea
Weak candidates include video encoding farms running all day, high-frequency trading paths, chat servers that hold thousands of open sockets, and batch jobs that take hours. Our architecture guide on monoliths and microservices discusses a 2023 case where a serverless pipeline was consolidated into a single service to cut cost, a useful reminder that the pattern is a tool, not a goal.
Serverless vs microservices: what is the difference?
Microservices is a way to split an application into independently deployed services; serverless is a way to run code without managing servers. A microservice can run on functions, on containers or on a plain server. The questions are separate, and the linked guide covers the split; this page covers the runtime.
Will serverless replace Kubernetes?
Not for every workload. Serverless containers and functions now cover much of what small and mid-size teams once ran on clusters, but teams needing fine control of networking, scheduling or hardware still choose Kubernetes. Our cloud app development page compares serverless, containers and Kubernetes in one table.
Security for serverless functions
Each function is a small attack surface with its own permissions, so security is mostly about keeping those permissions narrow, keeping secrets out of code and keeping dependencies current. The provider secures the platform; you secure your code, configuration and data.
| Control | What it means in practice | Why it matters for functions |
|---|---|---|
| Least-privilege roles | One role per function, scoped to the tables, queues and keys it uses | A compromised function reaches only its own resources |
| Secrets management | Keys and tokens in a managed secrets store, read at runtime | No credentials in code, logs or environment dumps |
| Input validation | Every event checked against a schema before use | Events arrive from many sources, not only users |
| Dependency scanning | Libraries scanned in the pipeline and updated on a schedule | Small functions often carry large dependency trees |
| Gateway protection | Auth, rate limits and a web application firewall at the API front door | Stops abuse before it turns into a bill |
| Audit logging | Who changed which function, role or setting, and when | Configuration is where most serverless incidents start |
The OWASP view of serverless risk
The OWASP Serverless Top 10 project is still an incubator project; its published work is a 2018 serverless interpretation of the OWASP Top 10, with an official report planned from field data. We use it as a checklist of where function apps go wrong, alongside the provider’s own security guidance.
Compliance designed in
Audit trails, encrypted storage, periodic access checks and controlled releases cost far less when planned in the first sprint than when bolted on later. We build those technical controls; any certification stays between you and your auditor.
Observability and testing: seeing a request across many functions
One user request in a serverless app can touch a gateway, three functions, a queue and two data stores, so you need traces that follow it end to end. We set up structured logs, distributed tracing and alarms before launch, not after the first incident.
Structured logs with a request ID
Every log line is JSON with the request or correlation ID, function name, version and duration. That makes one search show the whole path of a failed order, and it lets you set retention per log stream so old debug output stops costing money.
Alarms on errors, throttles and spend
Alarms watch error rates, throttled invocations, queue age, workflow failures and daily spend against a budget. A throttle alarm is often the first sign that a quota needs raising or a downstream database is struggling.
The default alarm list
These alarms go live before launch on every app we build; thresholds are set from the load test and tightened after launch.
- Function error rate above the agreed threshold
- Throttled invocations on any function
- Oldest message age on each queue
- Failed or timed-out workflow executions
- Gateway 5xx responses and latency on key routes
- Database throttling or capacity warnings
- Daily spend above the budget line
Tests at three levels
Unit tests cover business logic in plain modules, integration tests run against a real cloud stage, and load tests push the riskiest endpoints past expected peak to find quota and database limits before customers do.
How much does serverless cost? The pricing model explained
Serverless running cost depends on requests, how long code runs and how much memory it holds, plus the services around it: the API gateway, queues, databases, data transfer and logs. Build cost depends on scope, so every serverless build is quoted after a written scope, with no figure before it.
| Cost line | What it is billed on | Common surprise |
|---|---|---|
| Function compute | Requests plus duration multiplied by configured memory | Over-sized memory on functions that wait on I/O |
| Cold-start mitigation | Provisioned or always-ready capacity, billed while configured | Left on for endpoints that do not need it |
| API gateway | Requests and data passed through | Chatty clients making many tiny calls |
| Queues and workflows | Messages, state transitions or workflow executions | Retries multiplying traffic during an outage |
| Databases | Reads, writes, storage or capacity units | Scans where a keyed lookup would do |
| Logs and traces | Data ingested and retained | Debug logging left on in production |
| Data transfer | Bytes leaving the cloud or crossing regions | Large responses served without a CDN |
What the provider pricing pages say
AWS Lambda pricing bills standard functions on requests and duration, with a monthly free tier of one million requests and 400,000 GB-seconds that does not apply to functions using provisioned concurrency. Google’s Cloud Run billing settings default to request-based billing, charging an instance only while it processes requests. Microsoft bills Flex Consumption on executions and active instance memory, plus any always-ready instances.
Is serverless cheaper than servers or containers?
Often for uneven traffic, rarely for steady heavy traffic. Why is serverless so expensive for some teams? Usually because a busy, constant workload pays per request for capacity that a reserved machine would provide flatly, or because logging and retries were never budgeted. We model both shapes before recommending one.
Serverless cost optimization for live apps
Typical fixes are right-sizing memory from measured duration, cutting log verbosity and retention, batching queue messages, caching at the edge, removing unused provisioned capacity and fixing retry loops. A cost review lists each fix with its expected effect before anything changes. Market price bands for app builds appear on our app development cost guide as US market figures, not a Progression rate card.
Running a serverless app that costs more than it should?Share a month of the bill and the function list. We point out the logging, retry and data-transfer lines that usually explain it, and scope the fixes.
Can you migrate an existing app to serverless?
Yes, usually one piece at a time. Serverless migration works best with the strangler pattern: route one endpoint or job to new functions, run it beside the old system, compare results, then move the next piece. A big-bang rewrite is rarely the cheaper path.
Which pieces to move first
Good first moves are scheduled jobs, file processing, webhooks and read-heavy endpoints with uneven traffic. Core transactional paths with tight latency come later, once tracing and alarms prove the new path. Wider moves between hosting and clouds are covered by our cloud migration team.
AWS serverless migration from servers or containers
On AWS, a common sequence is a gateway in front of the existing app, then routes peeled off to Lambda one by one, with a queue between old and new code where timing differs. Each step has a rollback: switch the route back.
How to hire serverless developers: in-house, freelance or a serverless app development company
Hire in-house when serverless is core to a product you will run for years and you can fill several roles. Use freelancers for a narrow, well-specified task. Choose a serverless app development company when you need architecture, build, security and operations covered together under one written scope.
| Option | Best for | Watch for |
|---|---|---|
| In-house serverless developers | Long-lived products with steady roadmaps | Hiring time and the breadth of skills one person lacks |
| Freelance serverless developer | A defined function, integration or fix | Who owns monitoring and on-call after the handover |
| Serverless development company | New builds, migrations and reviews end to end | Whether limits, costs and security are in the proposal |
| Team extension | Your engineers own the product but need capacity | Clear roles and a documented handover |
What serverless experts should show you
Ask for an architecture diagram with provider limits marked, a sample of their infrastructure code, how they set per-function permissions, their alarm list and how they would cap a runaway bill. Vague answers on cost and quotas are the tell.
Choosing a serverless application development company
A serverless application development company should put the fit verdict, the cost drivers, the security controls and the exit plan in writing. Our dedicated developer teams page covers the team-extension model if you only need hands on your own roadmap.
AWS serverless consulting without a badge claim
We do not hold out a partner tier or a certification here. What you get is the work: designs checked against each provider’s published limits and frameworks, code you own, and a review you can hand to any future team.
Our process, stage by stage
Our serverless app development services run in five stages, each ending with a document or a running artifact and a decision to continue. Timelines and prices are set in the written scope for your project, not on this page.
| Stage | What happens | What you keep |
|---|---|---|
| Discovery | Traffic, data, users, compliance and existing cloud accounts are mapped | A discovery summary |
| Architecture review | Services, limits, cost drivers and security controls are chosen | An architecture note and diagram |
| Proof of concept | The riskiest path is built and load-tested | Working code and a test report |
| Build | Features ship through pipelines with tests and infrastructure as code | The application and its repository |
| Launch and tune | Alarms go live, then memory and concurrency are tuned from real use | Runbooks, dashboards and a tuning log |
Inputs for the first call
Bring a plain description of what the app must do, who uses it and when, the data it holds, any compliance needs, and which cloud accounts you already have. Our software consulting page explains how discovery runs.
How CTOs ask AI assistants for serverless help, and which sources they cite
Engineering leads put questions to Claude, ChatGPT, Gemini, Perplexity, Google AI Overviews and Microsoft Copilot: who can build a Lambda backend for us, whether serverless is cheaper for a given workload, or how to move a cron job off a server. The answers lean on provider documentation, comparison pages and firms that publish specific, checkable engineering detail.
What assistants tend to cite
Provider docs for limits and pricing, independent comparisons of clouds and runtimes, open-source framework docs, and agency pages that state limits, trade-offs and process plainly. Pages that only list buzzwords rarely get named or linked.
What a software firm should publish to be named
Architecture notes with real limits, honest when-not-to-use sections, cost drivers explained, and FAQ answers that stand alone. We write our own pages that way, and our AEO services apply the same method to client sites.
How to choose a serverless development company
Before you sign for serverless app development services, choose the team that tells you where serverless will hurt your workload, shows the limits in its design, and puts cost controls and security in the proposal. Use these seven checks when comparing proposals.
| Requirement | How to check it |
|---|---|
| Honest fit verdict | Ask when they last advised against serverless, and why |
| Limits in the design | Ask which quotas and timeouts their proposed design is closest to |
| Cost model | Ask for the bill’s main lines at expected and peak traffic |
| Per-function permissions | Ask to see a sample role policy from their infrastructure code |
| Observability | Ask for their default alarm list and tracing setup |
| Ownership | Confirm you hold the code, data and cloud accounts outright |
| Exit plan | Ask which services would need replacing to change cloud |
Want a written verdict on whether serverless fits your app?
Send a short description of the workload and the clouds you use. We reply with an architecture note and a scope.
Neighboring software and cloud services
Serverless app development services often sit beside other builds. These pages cover the neighboring services.
- Cloud-native builds across the three major clouds
- Custom software development company
- App development agency
- Enterprise app development
- Backend development services
- API development
- MVP development for new products
- IoT app development with event-driven backends
- AI integration services
- Backend hosting options compared
- React Native app development
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Websites and design
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Frequently asked questions
Which deliverables come with serverless app development services?
What does serverless development mean for an engineering team?
How is a serverless web application put together?
How do serverless apps handle state if functions do not keep it?
When should you use serverless architecture?
What are the pros and cons of serverless architecture?
Is serverless cheaper than running servers or containers?
How much does a serverless app cost to run each month?
What sets the price of building a serverless application?
What is a cold start and does it matter for my app?
How long can a serverless function run?
Can a serverless backend support a mobile app with many users?
Should our functions run on Lambda, Azure Functions or Cloud Run?
Does serverless lock us into one cloud provider?
How do you secure serverless functions?
How do you test and monitor a serverless application?
Is it possible to shift a running application onto functions gradually?
Should I hire serverless developers in-house or work with an agency?
Are serverless and microservices competing choices?
Do you build serverless apps with AI features?
Who owns the code and cloud accounts after the build?
Do you build serverless apps for teams in other states and countries?
Planning an API or backend and wondering if functions fit?Describe the traffic you expect, the data it touches and the clouds you already pay for. We reply with a written architecture note that says whether serverless suits it, and why.
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