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Serverless & Edgeby SoftwareCrafting

Functions-as-a-service and edge compute for low-latency, infinitely scalable backends by SoftwareCrafting.

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NDA-Protected
48hr Kick-off
7 Engineers
Founder-led Delivery
Serverless & Edge Services

Delivery Time

2-4 weeks

Senior deliveryFounder-involved build team
From₹18,000

Service Overview

We design and build serverless and edge architectures for teams who want to stop paying for idle servers and stop being paged about capacity. That covers Vercel and Cloudflare Workers at the edge, AWS Lambda and Step Functions for backend workloads, and the supporting pieces that decide whether serverless is pleasant or painful: cold start budgets, connection pooling for databases that were never designed for thousands of ephemeral clients, idempotency for retried invocations, and observability that works when there is no server to log into. We are equally willing to tell you when serverless is the wrong shape for your workload. Long running jobs, sustained high throughput, heavy compute, and workloads needing large in memory state are frequently cheaper and simpler on containers. Where the fit is genuine, the payoff is real: scaling to zero, per request billing, and deployment that stops being an operational event.

Technologies we use

Cloudflare WorkersAWS LambdaVercel Edge Functions

Key Features

  • Serverless architecture design on AWS Lambda, Vercel, or Cloudflare Workers
  • Edge middleware for routing, authentication, personalisation, and A/B testing
  • Cold start measurement and reduction through bundling and runtime choice
  • Database connection pooling suited to ephemeral compute
  • Event driven workflows with SQS, EventBridge, and Step Functions
  • Idempotency keys and safe retry behaviour for at least once delivery
  • API routes and edge functions with sensible caching policies
  • Background and scheduled jobs without a persistent server
  • Infrastructure as code using CDK, SST, or Terraform
  • Observability with structured logs, traces, and per function metrics
  • Cost modelling and per invocation spend attribution
  • Staged rollout, canary deploys, and instant rollback
  • Secrets management and least privilege function permissions
  • Migration path from existing container or server based workloads

Pricing Snapshot

₹18,000

Starting from ₹18,000 for serverless architecture design and deployment

  • Model: project
  • Timeline: 2-4 weeks
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Step-by-step

Our Delivery Process

We use an agile, transparent process to ensure your project is completed on time and meets exactly your needs.

01

Workload assessment

Profile the workload for duration, concurrency, memory, and state, then determine where serverless genuinely fits.

3-5 days
02

Architecture design

Design function boundaries, event flows, data access, and the cold start and cost budgets.

1 week
03

Infrastructure as code

Build the deployment pipeline, environments, permissions, and secrets handling as reviewable code.

1 week
04

Implementation

Build the functions, event handlers, and workflows with idempotency and retry behaviour designed in.

2-5 weeks
05

Load testing and tuning

Test under realistic concurrency, tune memory and bundling, and verify the cost model against real numbers.

1 week
06

Cutover and handover

Migrate traffic progressively, verify observability and alerting, and hand over runbooks.

3-5 days
Why Us

Why Choose SoftwareCrafting?

  • No capacity planning and no paying for idle compute
  • Scale to zero on low traffic services and environments
  • Traffic spikes absorbed without manual intervention
  • Lower latency by running logic at the edge, close to users
  • Deployment that is routine rather than an operational event
  • Cold starts measured and budgeted instead of hoped about
  • Database connections that survive contact with serverless concurrency
  • Retries that do not double charge customers or duplicate records
  • Per function cost visibility, so spend surprises are caught early
  • An honest assessment of where serverless is the wrong choice
FAQ

Frequently Asked Questions

Is serverless actually cheaper?

For spiky, low duty cycle, or unpredictable workloads, usually yes, because you pay per request instead of for provisioned capacity. For sustained high throughput it is frequently more expensive than an equivalently sized container. The break even depends on your request pattern, and we model it with your real traffic numbers before recommending an architecture.

What about cold starts?

They are real but manageable. Bundle size, runtime choice, and dependency weight dominate. A lean function typically starts in tens to low hundreds of milliseconds. Where a path is latency critical we use provisioned concurrency or move that specific path to the edge, and we treat cold start as a budget with a number rather than an unknown.

How do serverless functions talk to a database?

Carefully, because traditional connection pools assume long lived processes. We use a connection proxy such as RDS Proxy or PgBouncer, a driver designed for serverless, or an HTTP based database interface, depending on the stack. Getting this wrong is the most common way serverless deployments fall over under load.

What is the difference between edge and serverless functions?

Edge functions run in many locations close to your users with a restricted runtime, very fast startup, and tight execution limits. They suit routing, authentication checks, personalisation, and header manipulation. Serverless functions run in a specific region with a full runtime and longer limits, suiting business logic and database work. Most architectures use both.

When should we not use serverless?

Long running jobs beyond the execution limit, sustained high throughput where provisioned capacity is cheaper, workloads needing large in memory state or local disk, heavy compute such as video processing, and anything requiring persistent connections such as a WebSocket server. We will say so rather than force the fit.

Can we migrate gradually?

Yes, and we normally recommend it. We route specific paths to serverless while the rest continues on existing infrastructure, verify behaviour and cost under real traffic, then expand. This avoids a single cutover event and gives you real data before committing further.
Ready when you are

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