Transitioning to cloud-native architecture is a key priority for many organizations today. Two of the most talked-about approaches within this space are containers and serverless. Both aim to increase flexibility, scalability and efficiency compared to traditional monoliths.
But containers and serverless work quite differently under the hood. So how do you know which one is the best fit for your workloads?
In this comprehensive guide, we’ll unpack the key differences between the two approaches to help you decide. We’ll look at ideal use cases, dive into real-world examples, and discuss how to integrate containers and serverless.
By the end, you’ll understand:
- Brief history and evolution of each technology
- Architectural contrasts between containers vs serverless
- Alignment to business goals like time-to-market
- Metrics comparisons on performance, scalability, costs
- Security considerations and risk profiles
- Impact on CI/CD pipelines and DevOps culture
- Industry use cases on major cloud platforms
- Hybrid integration patterns
- Emerging open standards and maturity outlook
- Key evaluation criteria through a business lens
- Practical recommendations on getting started
A Brief History
Before diving into the details, let’s quickly recap the evolution of these technologies.
Containers trace their roots back to 1979 with Unix V7 chroot feature for isolation. By 2000, FreeBSD introduced "jails" for partitioning systems into isolated subsystems.
Linux containers emerged in 2008 when Docker made them practical for mainstream use. This catalyzed the container industry with new tools for images, registries and standardization.
The Cloud Native Computing Foundation now champions open ecosystems around containers, with Kubernetes becoming the orchestration standard.
Serverless computing emerged in 2014 when AWS Lambda introduced the industry to Function-as-a-Service (FaaS) on the public cloud. This was quickly followed by rivals with Azure Functions and Google Cloud Functions.
Open source serverless platforms like OpenFaaS and Knative now extend the model to private cloud. And CI/CD platforms have integrated well with containers and serverless.
Adoption Trends
It’s clear these technologies are seeing massive growth:
- Containers: Expected to grow from $2.55 billion industry in 2021 to $9.25 billion by 2026 according to MarketsandMarkets
- Serverless: Projected to grow from $7.72 billion in 2020 to $21.11 billion by 2025 per MarketsandMarkets
- 94% of enterprises now have containers in production based on recent StackRox survey
- By 2025, Gartner predicts 75% of global organizations will run containerized applications in production
Businesses are rapidly embracing cloud-native approaches. Containers and serverless each help:
- Achieve agility through modular services
- Enable innovation and speed time-to-market
- Drive operational efficiency at scale
- Optimize infrastructure and licensing costs
Now let’s unpack how they differ…
Key Differences
While containers and serverless aim for similar benefits, they contrast across some fundamental areas:
Application Architecture
- Containers package code + dependencies into standardized units for running distributed microservices.
- Serverless functions focus on singular purpose for event-driven actions.
Resource Management
- Containers allow fine-tuned allocation but still occupy capacity when idle. Must scale out manually.
- Serverless auto-provisions resources per function invocation then tears down.
Service Granularity
- Containers handle multiple processes in a single standardized unit.
- Serverless functions individually scale to immense levels.
Infrastructure Abstraction
- Both minimize infrastructure visibility for portability.
- Serverless removes servers entirely from developer experience.
Performance
- Containers minimize overhead vs VMs with faster bootup. Keep pools ready.
- Serverless functions suffer cold starts but limitless scale potential.
Pricing Model
- Containers bill for allocated capacity regardless of usage.
- With serverless you only pay for execution duration.
Let‘s analyze some representative metrics for comparison:
| Area | Containers | Serverless |
|---|---|---|
| Cold Start Latency | 200 – 400ms | Avg 400 – 2000ms |
| Idle Capacity | Allocated 24/7 | None, pay-per-exec |
| Boot Time | Fast (persistent runtime) | Slow (new container) |
| Granularity | Multiple containers | Individual functions |
| Scaling Limit | Cluster resource bounds | Virtually limitless |
As shown above, containers excel at keeping consistent performance while serverless prioritizes infinite scale and event-driven usage.
Architectural Contrast
To visualize the architectural differences, here is a diagram contrasting containerized apps vs serverless:
With containers, developers must configure networking plus orchestrate scaling. Serverless abstracts cluster management away, auto-scaling discreet functions triggered by events.
Now let‘s explore ideal use cases for each approach…
When To Use Containers vs Serverless
When should you choose one over the other? Here are some general guidelines:
Containers Are Ideal For:
- Microservices architectures
- Workloads needing consistent low latency
- Applications requiring access to OS resources
- Portable deployment across environments
- Loosely coupled services with persistent runtime
Serverless Shines For:
- Event-driven functions
- Infrequent execution with idle periods
- No infrastructure management
- Instant scale to extreme levels
- Optimizing costs for uneven workloads
Real-World Use Cases
Let‘s look at some specific examples to clarify the sweet spots…
Container Success Stories
Popular platforms like Kubernetes, Docker Enterprise and Red Hat OpenShift manage containers at massive scale across industries:
Ride-Sharing – Ola Cabs built an in-house container platform to orchestrate microservices across 5,000 cars requesting rides daily.
Finance – JP Morgan Chase is containerizing legacy apps to improve resiliency, portability and scalability while saving $350 million annually.
Retail – Walmart uses containers to modernize their ecommerce architecture as they process over one million customer orders per day at peak volumes.
Gaming – Unity Games containerized their create suite for developing 3D interactive content across mobile, console and VR platforms.
Serverless Superstars
Meanwhile, serverless continues excelling for event-driven services:
Media – Netflix tapped AWS Lambda to encode thousands of video transcoding jobs in parallel upon content uploads.
Software – Splunk uses Azure Functions to scale out big data ingestion tasks elastically responding to terabytes of daily logs.
Advertising – Smart AdServer implemented real-time bidding on Google Cloud Functions with no standing capacity.
IoT – Cloudflare Workers serverlessly processes billions of device data events each day with instant scale.
As shown above, combining containers and serverless creates a powerful modern architecture.
Integrating Containers and Serverless
The great news is containers and serverless integrate nicely together in many cases:
Hybrid Apps
- Host an app‘s logic via containers while tapping serverless for stateless processes
Shared Services
- Implement core services in containers then glue microservices together using serverless
Overflow Scaling
- Handle regular load with containers then offload peaks transparently to serverless
CI/CD Pipelines
-
Containerize builds while deploying functions serverlessly post-image push
-
Spin up containers on-demand to package dependencies for serverless runtimes
The ability to fluidly apply either approach per workload aligns the best technology fit.
The Open Source Landscape
While serverless exploded through public cloud vendors initially, open source options do exist:
OpenFaaS – Deploy serverless functions onto Kubernetes or Docker Swarm
Knative – Kubernetes extension from Google for running serverless workloads
OpenWhisk – IBM-incubated, Apache-licensed serverless platform
And Kubernetes clearly dominates as the open source container orchestration standard – its ecosystem permeating both public clouds and private infrastructure.
Emerging Standards
Additionally, emerging open standards aim to prevent vendor lock-in as these technologies mature:
OCI – Open Container Initiative developing vendor-neutral specs
CNCF – Cloud Native Computing Foundation housing Kubernetes and adjacent projects
OpenAPI – Creating a vendor neutral API standard for function-as-a-service
So while AWS initially created proprietary models for Lambda and ECS, shared standards help sustain hybrid and multi-cloud capabilities going forward.
Evaluating the maturity of all components in relation to your needs is wise.
Assessing Maturity
As you consider open source and commercial solutions, assessing maturity is helpful:
Containers
- RunC, ContainerD emerging as standards
- Kubernetes dominates orchestration
- Integrates broadly with CI/CD dev stacks
Serverless
- AWS Lambda most mature, Azure following
- Cloudflare, Vercel lead edge development
- Open source still evolving
No model has yet pulled far ahead – hybrid solutions integrate strengths of each. But do validate production-readiness for your specific use case via trials.
The Security Angle
As with adopting any new technology, we must evaluate security:
Containers
- Isolate apps safely leveraging namespaces
- Limit potential damage if one container is compromised
- Can scan images and runtime memory for vulnerabilities
Serverless
- No OS for attacker foothold
- Functions independent by design via isolation
- Cloud vendor secures underlying infrastructure
- Reduce responsibilities and costs
Both limit blast radius due to microservice designs. Verify your provider‘s security stance regarding their implementation.
Impact on DevOps
How do these approaches affect DevOps processes?
Containers
- Engineer base images then construct multi-service apps
- CI/CD pipeline stages standardize around image builds
- Single immutable artifacts promote to higher envs
- Kubernetes YAML expertise required
Serverless
- Functions abstract infrastructure distractions
- Allows laser focus on business logic
- Reduced YAML configuration management
- Monitoring complexity increases
Integrating these approaches does compel new processes and skills. Take cultural adaptation into account.
Key Evaluation Criteria
With benefits clear and differences covered, how should teams evaluate choices?
Focus on your app architecture, business goals and constraints:
- Runtime requirements – CPU/GPU needs, latency thresholds
- Desired infrastructure abstraction level
- Current operations maturity & container expertise
- Security, compliance and governance demands
- Whether peak capacity is unpredictable
- Total cost of ownership targets
Measure each against critical non-functional requirements, not just ease of development.
Getting Started Tips
Ready to get hands-on? Here is guidance on getting started:
💡 Learn your cloud vendor options then try some basic functions
💡 Scope early PoCs to low-risk use cases before committing
💡 Choose open source building blocks where possible to prevent lock-in
💡 Instrument performance monitoring early, establish key metrics
💡 Focus architects/developers on expanding cloud-native skills
With core languages and patterns portable, developers can pivot across providers based on business needs rather than technical limitations.
Key Takeaways
We covered a lot comparing these technologies! Let‘s recap key learnings:
- Both containers and serverless simplify app deployment and scaling
- Containers package apps reliably and portably
- Serverless abstracts infrastructure management away
- Integrating them provides the best of both worlds
- Open standards continue maturing across these ecosystems
- Assess options based on architectural needs and constraints
- Prioritize business goals then fit solutions to suit
The rapid evolution provides welcome options. I hope these insights help you evaluate the path forward for your cloud native journey!
