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Decisions about Azure Functions and Kubernetes
Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 28 upvotes · 3.1M views
Our whole DevOps stack consists of the following tools:
- GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
- Respectively Git as revision control system
- SourceTree as Git GUI
- Visual Studio Code as IDE
- CircleCI for continuous integration (automatize development process)
- Prettier / TSLint / ESLint as code linter
- SonarQube as quality gate
- Docker as container management (incl. Docker Compose for multi-container application management)
- VirtualBox for operating system simulation tests
- Kubernetes as cluster management for docker containers
- Heroku for deploying in test environments
- nginx as web server (preferably used as facade server in production environment)
- SSLMate (using OpenSSL) for certificate management
- Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
- PostgreSQL as preferred database system
- Redis as preferred in-memory database/store (great for caching)
The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:
- Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
- Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
- Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
- Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
- Scalability: All-in-one framework for distributed systems.
- Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
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Learn MorePros of Azure Functions
Pros of Kubernetes
Pros of Azure Functions
- Pay only when invoked12
- Great developer experience for C#8
- Multiple languages supported6
- Great debugging support5
- Poor developer experience for C#2
- Easy scalability2
- Can be used as lightweight https service2
- WebHooks1
- Event driven1
- Azure component events for Storage, services etc1
Pros of Kubernetes
- Leading docker container management solution155
- Simple and powerful124
- Open source100
- Backed by google74
- The right abstractions56
- Scale services24
- Replication controller18
- Permission managment9
- Simple7
- Supports autoscaling7
- Cheap6
- Self-healing4
- Reliable4
- No cloud platform lock-in4
- Open, powerful, stable3
- Scalable3
- Quick cloud setup3
- Promotes modern/good infrascture practice3
- Backed by Red Hat2
- Runs on azure2
- Cloud Agnostic2
- Custom and extensibility2
- Captain of Container Ship2
- A self healing environment with rich metadata2
- Golang1
- Easy setup1
- Everything of CaaS1
- Sfg1
- Expandable1
- Gke1
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Cons of Azure Functions
Cons of Kubernetes
Cons of Azure Functions
- No persistent (writable) file system available1
- Poor support for Linux environments1
- Sporadic server & language runtime issues1
- Not suited for long-running applications1
Cons of Kubernetes
- Poor workflow for development13
- Steep learning curve11
- Orchestrates only infrastructure5
- High resource requirements for on-prem clusters2
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- No public GitHub repository available -
What is Azure Functions?
Azure Functions is an event driven, compute-on-demand experience that extends the existing Azure application platform with capabilities to implement code triggered by events occurring in virtually any Azure or 3rd party service as well as on-premises systems.
What is Kubernetes?
Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.
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What companies use Azure Functions?
What companies use Kubernetes?
What companies use Azure Functions?
See which teams inside your own company are using Azure Functions or Kubernetes.
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What tools integrate with Azure Functions?
What tools integrate with Kubernetes?
What tools integrate with Azure Functions?
What tools integrate with Kubernetes?
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Blog Posts
What are some alternatives to Azure Functions and Kubernetes?
AWS Lambda
AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.
Serverless
Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.
Cloud Functions for Firebase
Cloud Functions for Firebase lets you create functions that are triggered by Firebase products, such as changes to data in the Realtime Database, uploads to Cloud Storage, new user sign ups via Authentication, and conversion events in Analytics.
Google Cloud Functions
Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running
Google Cloud Run
A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.