Amazon AWS vs Azure Cloud vs Kubernetes
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Here we will talk about cloud technology and when we hear the word cloud technology, Amazon Web Services, Microsoft Azure and Kubernetes.
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Amazon AWS vs Azure Cloud vs Kubernetes
- 1. Amazon Cloud V/S Azure Cloud V/S Kubernetes
- 2. AWS – Amazon Web Services Centralized Cloud Platform Offering Deck of Features from global data centres Features Enhance & Improve Business Operations By Integrating Amazon Powered Web Services Cache: Amazon Web Services uses elastic cache. Serverless Cloud Functionality: No more provisioning, administering or monitoring of backend services. Fault tolerance managed by AWS. Ubiquitous Database: Completely managed in-memory & graphical database. Compliance & Security: Filter traffic based on the AWS rules to protect infrastructure. Offerings AWS Has Low Ongoing Cost: • Pay-as-you-go pricing- Charged as Pay Per Hour • On-demand, on the spot models. Analytics: • AWS Amazon Kinesis is used for collecting, analyzing & streaming data. • Data stored in streams called shrads. • Data from shrads used by EC2 for different purposes. Storage: • Amazon Glacier: Aids long-term storage. • Amazon Simple Storage Service: scalable solutions for object storage facilitating archival, analytics along with data backup. • The Amazon EBS — Renders block level storage volumes to use • it with EC-2 instances. Secure: • Protocol and port level access • Filter traffic emerging out of EC2 instance.
- 3. Azure Cloud A public cloud computing platform tailored to map the needs of users while rendering the best in industry cloud offerings. Components Compute & Execution Model: This is used to determine the optimal interface for the execution of the application. SQL Server: This facilitates the management and storage of all data. Azure Traffic Manager: This is used to collect and then route the request of the user to the data center in the closest location. HDInsight: Hadoop based service that promotes seamless management of large data chunks, the ones that are not part of the relational database. Content Delivery Network: This helps in caching the blob data which further improves the speed and performance of the application. Multi-factor Access - Used for authentication and security purposes. Data Management: SQL Database, Import/Export, Storage Table, etc to adhere to data collaboration needs. Gateway Connectivity: IoTHub to draft a communication between the IoT devices to gather significant insights and facilitate smarter decisions. Streamline Data Transfer: Service Bus Feature to decouple services and applications. Robusts platform promoting asynchronous data transfer.
- 4. Azure Cloud Offerings • Azure Cloud promotes quick to build, deployment, and scaling of data using logic apps. • Azure Maps with robusts and secure location APIs that render geospatial context to every data • Connect public and private cloud environment with Service buses. • Create digital replicas of organizational infrastructure and spaces. • Azure Cloud extends its support to technologies such as machine learning and artificial intelligence helping you in unleashing the potential of data and make smarter decisions. • Seamless connection with customers all across with globe, anytime and through any device. Azure Cloud offers high-definition audio and video with the diverse distribution. • Deploy intelligent models so that you can draft a better engagement with your customers and drive significant insights using their data. • Azure Cloud offers different software models with software as a service (SaaS) being one. This is basically an on-demand software that helps you scale with the recent updates and software versions and give customers what they want and when they want. • Azure Cloud Platform helps connect billions of iot devices driving significant insights. Features • Run and Deploy on Linux Virtual Machine and Windows Server • Migrate both applications and the organizational infrastructure with ioTHub. • Lightning-fast speed with Caching • IoTHub for device connectivity • Service buses for asynchronous data transfer • Virtual Network • Business Analytics • Hadoop • Media Services
- 5. Kubernetes Components • Pods: Group of one or more containers which creates, schedule, and deploy on the node altogether. • Labels: Tags of key-value tags as assigned to identify services, pods, and replication controllers. • Services: Services name the group of pods, and act as a load balancer so as to redirect traffic into the running containers. • Replication controllers: Framework responsible to ensure that a significant number of pod replicas have been scheduled and can run at any given time. Offerings • Orchestrate containers on different hosts • Solve as many problems by deriving containers proliferation and organizing them in “pods”. • Higher portability due to containerization • Docket feature makes it easier to create several version of the container. • Deployment of multiple versions of same application or various instances of same version. • Auto-test and autocorrect applications - Kubernetes is production-grade container orchestration tool with automated deployment features.
- 6. Automates rollouts and rollbacks: Kubernetes Run everywhere: Open-source tool On-premises, hybrid, or public cloud infrastructure Automates manual processes: Kubernetes can control the server that will host the container. Interacts with different groups of containers: Kubernetes can manage multiple clusters at the same time Provides additional services: Container management Kubernetes offers security, networking and storage services Self-monitoring: Constant check on containers and the health of nodes Horizontal scaling: Kubernetes help scale resources both vertically and horizontally, Storage orchestration: Kubernetes mounts and adds storage system of your choice Container balancing: Places containers in the best location
- 7. Stridely Solutions +91 -79-4800-5566 info@stridelysolutions.com