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Decisions about FaaS and Kubernetes
Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 29 upvotes · 5.4M 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 FaaS
Pros of Kubernetes
Pros of FaaS
- Simple way to build serverless applications1
Pros of Kubernetes
- Leading docker container management solution162
- Simple and powerful127
- Open source104
- Backed by google75
- The right abstractions57
- Scale services24
- Replication controller19
- Permission managment10
- Cheap7
- Simple7
- Supports autoscaling7
- No cloud platform lock-in4
- Self-healing4
- Reliable4
- Quick cloud setup3
- Open, powerful, stable3
- Scalable3
- Promotes modern/good infrascture practice3
- Custom and extensibility2
- Cloud Agnostic2
- Captain of Container Ship2
- A self healing environment with rich metadata2
- Runs on azure2
- Backed by Red Hat2
- Golang1
- Expandable1
- Sfg1
- Everything of CaaS1
- Easy setup1
- Gke1
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Cons of FaaS
Cons of Kubernetes
Cons of FaaS
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Cons of Kubernetes
- Steep learning curve15
- Poor workflow for development15
- Orchestrates only infrastructure8
- High resource requirements for on-prem clusters4
- Too heavy for simple systems2
- Additional vendor lock-in (Docker)1
- More moving parts to secure1
- Additional Technology Overhead1
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What is FaaS?
FaaS is a platform for building serverless functions on Docker Swarm Mode with first class metrics. Any UNIX process can be packaged as a function in FaaS enabling you to consume a range of web events without repetitive boiler-plate coding.
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 FaaS?
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What tools integrate with FaaS?
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What tools integrate with FaaS?
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What are some alternatives to FaaS and Kubernetes?
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.
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.
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.
Google Cloud Functions
Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running
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.