What is Apache CloudStack and what are its top alternatives?
Top Alternatives to Apache CloudStack
- OpenStack
OpenStack is a cloud operating system that controls large pools of compute, storage, and networking resources throughout a datacenter, all managed through a dashboard that gives administrators control while empowering their users to provision resources through a web interface. ...
- 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. ...
- OpenNebula
It provides a simple but feature-rich and flexible solution for the comprehensive management of virtualized data centers to enable on-premise enterprise clouds in existing infrastructures. It can be primarily used as a virtualization tool to manage your virtual infrastructure in the data-center or cluster, which is usually referred as Private Cloud. It supports Hybrid Cloud to combine local infrastructure with public cloud-based infrastructure, enabling highly scalable hosting environments. ...
- Eucalyptus
Eucalyptus is open source software for building private, AWS-compatible IT, QA, and developer clouds. It makes it easy to deliver cloud computing, just like AWS, from within your data center. ...
- MaaS
MAAS (Metal as a Service) offers cloud style provisioning for physical servers. It is open source and free to use, with commercial support available from Canonical. ...
- VirtKick
Software as a service platform for hosting providers.
Apache CloudStack alternatives & related posts
- Private cloud56
- Avoid vendor lock-in38
- Flexible in use22
- Industry leader6
- Supported by many companies in top5004
- Robust architecture4
related OpenStack posts
Kubernetes
- Leading docker container management solution164
- Simple and powerful128
- Open source106
- Backed by google76
- The right abstractions58
- Scale services25
- Replication controller20
- Permission managment11
- Supports autoscaling9
- Cheap8
- Simple8
- Self-healing6
- No cloud platform lock-in5
- Promotes modern/good infrascture practice5
- Open, powerful, stable5
- Reliable5
- Scalable4
- Quick cloud setup4
- Cloud Agnostic3
- Captain of Container Ship3
- A self healing environment with rich metadata3
- Runs on azure3
- Backed by Red Hat3
- Custom and extensibility3
- Sfg2
- Gke2
- Everything of CaaS2
- Golang2
- Easy setup2
- Expandable2
- Steep learning curve16
- 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
related Kubernetes posts
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
https://eng.uber.com/distributed-tracing/
(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)
Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark
Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.
Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.
After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...
OpenNebula
related OpenNebula posts
related Eucalyptus posts
- Hardware Automation1
related MaaS posts
- Easy setup and simplicity in use5
- One Click Install1