Serverless & Containers

How it works

How an event-driven app runs

An event arrives: an HTTP request, a file upload or a queue message. An event router filters it and sends it on, with retries and scheduling built in. A function handles short, event-driven work; a serverless container handles anything that needs a custom runtime or runs longer. A workflow engine coordinates multi-step processes, and all state lives outside in databases and queues.

The spectrum of control

From most managed to most control: functions, serverless containers, app platforms, then container orchestration. Moving right adds flexibility and operations work. The rule is to start as far left as the workload allows and move right only when you hit a real limit, such as run time, runtime support or networking needs.

AWS, Azure and Google Cloud compared

What makes each cloud different

Design decisions that matter

1. 01Default to the most managed option

   Pick functions or serverless containers until a concrete limit forces a change.

2. 02Keep compute stateless

   Store state in databases, caches and queues so any instance can be replaced.

3. 03Use events, not direct calls, between services

   Routers and queues absorb spikes and failures.

4. 04Orchestrate long processes

   Use a workflow engine for retries, waits and human approvals.

5. 05Scan every image

   Registries should block images with critical vulnerabilities.

Common mistakes we see

• Chains of functions calling functions. Hard to debug and expensive; use a workflow engine instead.
• Kubernetes for a simple web app. Operations cost outweighs the benefit for small teams.
• Ignoring cold starts. Latency-sensitive paths need warm capacity or a container.
• Unbounded concurrency. A traffic spike can overwhelm a database; set limits.

A practical 30-day plan

1. Week 1

   Classify workloads by run time, runtime needs and traffic pattern.

2. Week 2

   Move event-driven tasks to functions and stateless services to serverless containers.

3. Week 3

   Introduce an event router and a workflow engine for multi-step processes.

4. Week 4

   Add image scanning, concurrency limits and cost dashboards.

How NTS helps

NTS designs and builds serverless and container platforms on AWS, Azure and Google Cloud, from event-driven architectures and workflow orchestration to container platforms with secure supply chains. We help teams pick the right model per workload instead of one size for all.

How we work with you

1. 1Assess

   A focused review of your serverless and container platforms across AWS, Azure and Google Cloud. We look for the gaps we find most often: chains of functions calling functions, Kubernetes for a simple web app, ignoring cold starts and unbounded concurrency.

2. 2Design

   A target architecture and roadmap built on the decisions that matter most: default to the most managed option, keep compute stateless, use events, not direct calls, between services, orchestrate long processes and scan every image.

3. 3Build

   Hands-on delivery alongside your team. We classify workloads by run time, runtime needs and traffic pattern, move event-driven tasks to functions and stateless services to serverless containers, introduce an event router and a workflow engine for multi-step processes, and finally add image scanning, concurrency limits and cost dashboards.

4. 4Run and improve

   We tune memory, concurrency and scaling settings, and keep runtimes and base images current and secure.

Why teams choose NTS for serverless and container platforms

• The simplest platform that works

  We start with serverless where it fits and add Kubernetes only when it earns its complexity.

• Production patterns, not demos

  Idempotency, retries, observability and limits are designed in from the start.

• Developers move faster

  We give teams templates so a new service goes live in hours.