Cloud Platform Providers

Just tyring to collate what other cloud service providers had to offer apart from known: Microsoft Azure and Amazon AWS. List includes RackSpace, OpenStack, Google Compute Engine etc.

<hr> **Table of Contents** [TOCM] <hr> ## RackSpace [RackSpace](http://www.rackspace.com/) is the second largest public cloud after AWS. RackSpace clod runs from trunk of [OpenStack](https://www.openstack.org/). [OpenStack](https://www.openstack.org/) is one of the most popular APIs that lets your [APPs Control Your Cloud](https://www.openstack.org/software/) (**Bare Metals, Object/File/Block Storage, Compute, Networking, Data Analytics, Monitoring & Metering**). Provide machine, multi-cloud connector (**AWS, Azure & Google**).RackSpace had following offerings: - Dedicated Servers: Fully Managed Dedicated Server with Physical Firewall Configurations, True Single-Tenant Secure Backend (12C, 2.5GHz, 128GB RAM with Cisco Sec Firewall at $749pm) - VMWare Enviornments: Fully-Managed VMware-Powered Infrastructure with 100% Network and Hardware Uptime Gurantees on vSphere Platform - Multi-Cloud Connectivity: [RackConnect Global](https://www.rackspace.com/en-in/hybrid/rackconnect/global) provides highly available, secure, private network connectivity between Rackspace and your other data centers and the cloud provider of your choice, such as Microsoft Azure and Amazon Web Services for the ultimate in multi-cloud flexibility. Use cases are: disaster recovery and backup, Hybrid application across multi-cloud. - Database Services: Rackspace certified DBAs provide the deep expertise you need for MySQL, Oracle and MS SQL Server environments. Whether you’re running on dedicated hardware or on Rackspace Cloud Servers - it provides administration, monitoring and trobuleshooting. - Managed Storage: Products offered are DAS (**Direct Attached Storage**), SAN (**Storage Area Network**), NAS (**Network Attached Storage**), - Custom Networking: Cisco Firewalls, Custom Switches, Load Balancers, and DDoS Mitigation. ## Google Compute Engine [GCE]() is Google's IaaS offering. There are some reports that [GCE is faster than Amazon EC2](http://datacommunitydc.org/blog/2013/01/google-compute-engine-vs-amazon-ec2-part-2-synthetic-cpu-and-memory-benchmarks/). Google Compute Engine delivers virtual machines running in Google's innovative data centers and worldwide fiber network. Compute Engine's tooling and workflow support enable scaling from single instances to global, load-balanced cloud computing. You can find [price calculator](https://cloud.google.com/products/calculator/). It comparises of following products/calculator/ - [Google Compute Products](https://cloud.google.com/products/compute/): - [Compute Engine](https://cloud.google.com/compute/): High-performance scalable VMs (**Linux & Windows**) with tooling and workflow support enable scaling from single instances to global, load-balanced cloud computing. You can have **Custom Machine Type**, and upto 64vCPUs or 416GB memory on platter with 64TB storage. Lower cost [Preemptible VMs](https://cloud.google.com/preemptible-vms/) for Batch Processing needs and **per-minute billing**. - [APP Engine](https://cloud.google.com/appengine/): Build *scalable web and mobile backends* in any language on Google’s infrastructure. It includes - C#, Go, Python, Java, Ruby, Node.js, and PHP. Bring any library, custom software stack from language runtime to frameworks on-to App Engine by supplying a Docker container and let google take care of scalability and load balancing. For standard frameworks - *Just Add Code*, offload infrastructure concerns like scaling your app up or down to handle traffic, load balancing, health-checking and healing your instances, and applying updates to the underlying OS to Google. - [Container Engine](https://cloud.google.com/container-engine/): Google Container Engine is a powerful cluster manager and orchestration system for running your Docker containers. Container Engine schedules your containers into the cluster and manages them automatically based on requirements you define (such as CPU and memory). It's built on the open source Kubernetes system, giving you the flexibility to take advantage of on-premises, hybrid, or public cloud infrastructure. - [Cloud Functions](https://cloud.google.com/functions/): Fully serverless models of computing where logic can be spun up on-demand in response to events originating from anywhere. Applications from bite-sized business logic billed to the nearest 100 milliseconds. Serve users from zero to planet-scale, all without managing any infrastructure. Developers create micro-services (**independent units of functionality focused on doing one thind well**) and scale these functions and not **entire application, containers or VMs**. These functions can be connected by [Databse & Storage](https://cloud.google.com/storage-options/), [Cloud Pub/Sub](https://cloud.google.com/pubsub/) etc. Use case are: Mobile Backends, APIs & Microservices (**can be event-driven or invoked directly over HTTP/S**), Data Processing / ETL, Webhooks (** HTTP trigger, or respond to events**), IoT (**Pub & Sub Data At Scale**) - [Databse & Storage Products](https://cloud.google.com/storage-options/): - [Google Cloud Storage](https://cloud.google.com/storage/): A scalable, fully-managed, highly reliable, and cost-efficient *object / blob store*. It's good for images, pictures, video, objects, blobs, and unstructured data. Workloads cloud be: Storing and streaming multimedia; Storage for custom data analytics pipelines; Archive, backup, and disaster recovery; Host static site assets - HTML, CSs and JS in multi-regional Buckets; Run Cloud Machine Learning and BigQuery. - [Google Cloud SQL](https://cloud.google.com/sql/): A fully-managed *MySQL and PostgreSQL database service* that is built on the strength and reliability of Google’s infrastructure. It's good for Web frameworks, Structured data, OLTP workloads. Workloads cloud be: websites, blogs, and content management systems, BI applictions, ERP, CRM, eCommerce, Geospatial applications. Cloud SQL delivers high performance and scalability with up to 10TB of storage capacity, 25,000 IOPS, and 208GB of RAM per instance. - [Google Cloud BigTable](https://cloud.google.com/bigtable/): A scalable, fully-managed *NoSQL wide-column database* that is suitable for both **real-time access and analytics workloads**. It's good for Low-latency read/write access, High-throughput analytics, Native time series support. Workloads cloud be: IoT, finance, adtech, personalization, recommendations, monitoring, geospatial datasets, graphs etc. - [Google Cloud Spanner](https://cloud.google.com/spanner/): *One-of-a-Kind* mission-critical, relational database service with transactional consistency, global scale and high availability. It's good for mission-critical online transaction processing (OLTP) apps, high transactions, scale+consistency needs. Workloads cloud be: Adtech, Financial services, Global supply chain, Retail. Client libraries in Go, Java, Node.js, PHP, and Python, with more coming. JDBC driver for connectivity with popular third-party tools. - [Google Cloud DataStore](https://cloud.google.com/datastore/): A scalable, fully-managed *NoSQL Document Database* for your web and mobile applications. It's good for Semi-structured application data, Hierarchical data, Durable key-value data. Workloads cloud be: User profiles; Product catalogs. - [Persistant Disk](https://cloud.google.com/persistent-disk/): Fully-managed, price-performant block storage that is suitable for virtual machines and containers esp. for Google Compute Engine and Google Container Engine. Workloads could be: disks for VMs; sharing read-only data across VMs; rapid and durable VM backup. - [Networking: Products](https://cloud.google.com/products/networking/): - [Virtual Private Cloud(VPC)](https://cloud.google.com/vpc/): VPC networking for GCP instances - [Cloud Load Balancing](https://cloud.google.com/load-balancing/): Worldwide Autoscaling and Load Balancing with Single Anycast IP for HTTP(s), TCP/SSL, UDP, SSL Offload, etc - [Cloud CDN](https://cloud.google.com/cdn/): Caches at more than 80 sites around the world using Single Global IP Address with SSL - [Cloud Interconnect](https://cloud.google.com/interconnect/): Customers can work with Cloud Interconnect providers to achieve higher availability and lower latency connections to Google - [Cloud DNS](https://cloud.google.com/dns/): scalable, reliable and managed authoritative Domain Name System (DNS) service with low-latency, high availability. - [Big Data Products](https://cloud.google.com/products/big-data/) - [Google BigQuery](https://cloud.google.com/bigquery/): A scalable, fully-managed *Enterprise Data Warehouse (EDW) with SQL* and fast response times. It's good for OLAP workloads up to petabyte-scale, Big Data exploration and processing, Reporting via Business Intelligence (BI) tools. Workloads cloud be: analytical reporting on large data, data science and advanced analyses, Big Data processing using SQL. BigQuery can scan TB in seconds and PB in minutes. - [Cloud Pub/Sub](https://cloud.google.com/pubsub/) is a fully-managed global service for real-time and reliable messaging and streaming data. Cloud Pub/Sub is designed to provide “at least once” delivery at low latency with on-demand scalability to 1 million messages per second (and beyond). It supports one-to-one, one-to-many, or many-to-many communication, with push or pull delivery with Gurantee at Scale across Globe with End-to-End Acknowledgements, Encryption, REST APIs. **It's free for First 10GB Monthly Data Volume**. - [Cloud DataFlow](https://cloud.google.com/dataflow/): Fully-managed data processing service, supporting both stream and batch execution of pipelines. Dataflow is a unified programming model (**Via The Apache Beam SDKs: Java and Python **) and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. The Dataflow API enables you to express MapReduce like operations, powerful data windowing, and fine grained correctness control regardless of data source. - [Cloud DataProc](https://cloud.google.com/dataproc/): Google Cloud Dataproc, is an Apache Hadoop, Apache Spark, Apache Pig, and Apache Hive service, to easily process big datasets. With each cluster action taking less than 90 seconds on average. - [Cloud DataPrep](https://cloud.google.com/dataprep/): An intelligent cloud data service to *visually* explore, clean, and prepare data for analysis. You don't need to write code - visually explore and interact with data. Automatically identifies data anomalies and helps you to take corrective actions fast. serverless service, so you do not need to create or manage infrastructure. Process diverse datasets - structured and unstructured. Transform data stored in CSV, JSON, or relational table formats. Prepare datasets of any size, megabytes to terabytes, with equal ease. - [Cloud DataLab](https://cloud.google.com/datalab/): An easy to use interactive tool for data exploration, analysis, visualization and *machine learning*. Cloud Datalab is built on **Jupyter (formerly IPython)**, which boasts a thriving ecosystem of modules and a robust knowledge base. Cloud Datalab enables analysis of your data on Google BigQuery, Cloud Machine Learning Engine, Google Compute Engine, and Google Cloud Storage using Python, SQL, and JavaScript (for BigQuery user-defined functions). - [Google Data Studio](https://cloud.google.com/data-studio/): Google Data Studio **turns your data into informative dashboards** and reports that are easy to read, easy to share, and fully customizable. Easily access all the data sources you need. Transform your raw data into the dimensions, metrics, and calculations you need. - [ Google Genomics](https://cloud.google.com/genomics/): Ask bigger questions by efficiently processing up to petabytes of genomic data. - [IoT Products](https://cloud.google.com/iot-core/): - [Cloud IoT Core](https://cloud.google.com/iot-core/): A fully managed service to easily and securely connect, manage, and ingest data from globally dispersed devices. Process device data vis *Cloud Functions, Cloud Pub/Sub, Cloud DataFlow, BigTable, BigQuery, CloudML, Cloud Datalab, Data Studio, Analytics*. - [Machine Learning Products](https://cloud.google.com/products/machine-learning/): - [ML Engine](https://cloud.google.com/ml-engine/): Managed service that enables you to easily build machine learning models, that work on any type of data, of any size. Create your model with the powerful TensorFlow framework on managed scalable infrastructure. Trained model is immediately available for use with our global prediction platform. Build better performing models faster by automatically tuning your hyperparameters with HyperTune. Scalable training infrastructure that supports CPUs and GPUs. Models trained using Cloud Machine Learning Engine can be downloaded for local execution or mobile integration. - [Jobs API](https://cloud.google.com/jobs-api/): Power your job site with machine learning. Deliver relevant job search results etc. - [Natural Language API](https://cloud.google.com/natural-language/): Easy to use REST API to extract information about people, places, events and much more, mentioned in text documents, news articles or blog posts. You can use it to understand sentiment about your product on social media or parse intent from customer conversations happening in a call center or a messaging app. It includes **entity, sentiment, syntax analysis**. - [Speech API](https://cloud.google.com/speech/): Enables developers to convert audio to text by applying powerful neural network models in an easy to use API. The API recognizes over 80 languages and variants, to support your global user base. Real-time recognition, Cotext-aware recognition, Works on any device using REST. - [Translation API](https://cloud.google.com/translate/): Cloud Translation API provides a simple programmatic interface for translating an arbitrary string into any supported language using state-of-the-art Neural Machine Translation. Translation API is highly responsive, so websites and applications can integrate with Translation API for fast, dynamic translation of source text from the source language to a target language (e.g., French to English). - [Vision API](https://cloud.google.com/vision/): Google Cloud Vision API enables developers to understand the content of an image by encapsulating powerful machine learning models in an easy to use REST API. It quickly classifies images into thousands of categories (e.g., "sailboat", "lion", "Eiffel Tower"), detects individual objects and faces within images, and finds and reads printed words contained within images. Includes: Optical Character Recognition (OCR), Label Detection, Explicit Content Detection, Logo Detection, Landmark Detection, Face Detection, and Image Attributes. - [Video Intelligance](https://cloud.google.com/video-intelligence/): Makes videos searchable, and discoverable, by extracting metadata with an easy to use REST API.