Docker Compose vs Docker Machine vs Docker Swarm

Our whole DevOps stack consists of the following tools:

• @{GitHub}|tool:27| (incl. @{GitHub Pages}|tool:683|/@{Markdown}|tool:1147| for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
• Respectively @{Git}|tool:1046| as revision control system
• @{SourceTree}|tool:1599| as @{Git}|tool:1046| GUI
• @{Visual Studio Code}|tool:4202| as IDE
• @{CircleCI}|tool:190| for continuous integration (automatize development process)
• @{Prettier}|tool:7035| / @{TSLint}|tool:5561| / @{ESLint}|tool:3337| as code linter
• @{SonarQube}|tool:2638| as quality gate
• @{Docker}|tool:586| as container management (incl. @{Docker Compose}|tool:3136| for multi-container application management)
• @{VirtualBox}|tool:774| for operating system simulation tests
• @{Kubernetes}|tool:1885| as cluster management for docker containers
• @{Heroku}|tool:133| for deploying in test environments
• @{nginx}|tool:1052| as web server (preferably used as facade server in production environment)
• @{SSLMate}|tool:2752| (using @{OpenSSL}|tool:3091|) for certificate management
• @{Amazon EC2}|tool:18| (incl. @{Amazon S3}|tool:25|) for deploying in stage (production-like) and production environments
• @{PostgreSQL}|tool:1028| as preferred database system
• @{Redis}|tool:1031| 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.

We develop rapidly with docker-compose orchestrated services, however, for production - we utilise the very best ideas that Kubernetes has to offer: SCALE! We can scale when needed, setting a maximum and minimum level of nodes for each application layer - scaling only when the load balancer needs it. This allowed us to reduce our devops costs by 40% whilst also maintaining an SLA of 99.87%.

Hello, we have a bunch of local hosts (Linux and Windows) where Docker containers are running with bamboo agents on them. Currently, each container is installed as a system service. Each host is set up manually. I want to improve the system by adding some sort of orchestration software that should install, update and check for consistency in my docker containers. I don't need any clouds, all hosts are local. I'd prefer simple solutions. What orchestration system should I choose?