AWS vs Azure vs Google Cloud: Which Cloud Platform is best for your organization?
Mayank Patel
Aug 10, 2021
4 min read
Last updated Apr 18, 2024
Table of Contents
1. Storage Capacity
2. Tools
3. Computing Services
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The adoption of cloud computing has become a major driving force for businesses. Today, applications to drive innovation, reduce costs and increase agility have gone beyond non-premises data centres.
Infrastructure-as-a-service (IaaS) is a model where third-party providers host and maintain basic infrastructure on behalf of the customer, including hardware, software, servers, and storage.
The cloud service provider in USA and India, typically involves hosting applications in a highly scalable environment, where customers are only charged for their infrastructure.
Early concerns about security and data sovereignty have been largely addressed by the ‘big three’ public cloud vendors – Amazon Web Services (AWS), Micro Azure services and the Google Cloud services– to be cautious when it comes to only highly regulated businesses in USA and India to adopt cloud services.
According to the latest figures from research firm Gartner, this will boost the IaaS market, valued at $ 33.2 billion in 2021.
When it comes to AWS vs Microsoft Azure cloud, AWS had dominated for over a year when it entered the segment in 2006.
Now, AWS is the clear market leader globally, accounting for 33% of public IaaS and PaaS market share in Synergy Research Group’s data for the third quarter of 2019. Microsoft follows it at 16 percent and Google at 8 percent.
1. Storage Capacity
As far as any cloud service is concerned, it offers good storage capabilities. Let’s take a look at how each cloud platform provides storage capacity:
AWS Storage System:
If you compare AWS vs Microsoft Azure cloud, you can get complete services like Simple Storage Services (SSS) for object budget storage in AWS.
Besides, you can also store your data in Elastic Block Storage (EBS) for persistent block storage and Elastic File System (EFS) for storing files.
Azure Cloud Platform:
With Microsoft Azure services, you get REST-based object budget storage, with unstructured data, queue storage for large amounts of data, file and disk storage, and data lac stores for large applications.
Azure offers a variety of database storage options. It offers three SQL-based options, Data Warehouse Service, CosmosDB, and NoSQL for table storage, Redis Cache, and Server Stretch databases designed specifically for businesses that want a solution to reach SQL server for their database access.
Google Cloud Platform:
Google Cloud services in USA and India offers an integrated object budget storage service with a permanent drive option. It offers other online transfer services as well as transfer tools like AWS Snowball.
As far as databases are concerned, GCP has an SQL-based Cloud SQL with a relational database called Cloud Spanner, designed specifically for mission-critical projects.
It offers two no-SQL choices: Cloud Bigtable and Cloud Datastore. GCP does not provide backup and archiving services.
2. Tools
AWS has been at the forefront of bringing artificial intelligence and the Internet of Things (IoT) to SageMaker to train employees and deploy machine learning.
It offers a serverless computing environment and the freedom to submit applications from its serverless repository. AWS lets you incorporate a range of IoT Enterprise Solutions for advanced customization.
AWS Tools:
As we have mentioned earlier, SSR loads application or web pages even more quickly, and thus it helps in improvising the position of the page on various search engines.
It happens because search engines like Google give preference to the online product that opens quickly.
Azure Tools:
Microsoft Azure services provide cognitive services to enhance artificial intelligence. Cognitive Services is a suite of API-supported mechanisms that give integration with on-premises Microsoft software and business pertinence.
Google Tools:
Google’s cloud-based enterprise offers natural language translation and speech benefits to transform global enterprise sync into ML application development.
Furthermore Google cloud services also offer TensorFlow, a large open-source library. Its IoT and serverless platforms are currently in the beta stage.
All platforms come with their advantages and disadvantages that can vary according to the needs of your enterprise. Let’s look at the comparison of AWS vs. Microsoft Azure cloud and Google for their computing.
AWS computing Features:
AWS offers Amazon Elastic Compute Cloud or E2C, which provides high compatibility and advanced level for customizing the cost of databases.
The cloud platform comes with increased scalability, allowing you to scale or down services according to a load of projects. Plus, you can add new patterns in a matter of seconds.
You can track your apps using AWS Auto-Scaling Monitor to measure their potential concerning your current needs without adding a price pad. They offer 99.99% availability in terms of their Service Level Agreement (SLA).
Microsoft Azure computing features:
Azure relies heavily on a network of AR and VR machines that enable computing solutions for development, testing, application deployment, and data center expansion.
Microsoft Azure services are based on open-source platforms that provide compatibility with Linux and Windows Server, SQL Server, Oracle and SAP.
Google Cloud computing Features:
Google Cloud specializes in Kubernetes containers and supports Docker containers. In the USA and India, Google cloud services offer resource management and application deployment to add or subtract in real-time environments.
You can also deploy code from Google Cloud, Firebase or Assistant.
When choosing a cloud platform for your enterprise or Organization, choose the right cloud service provider that fits your budget and offers you the right services.
Study all the features that each platform offers, see what can meet the needs of your enterprise, and then choose accordingly. Also, analyse your organizational needs to see which platform best fits your needs.
Uncertain about the best fit?
Mayank Patel
CEO
Mayank Patel is an accomplished software engineer and entrepreneur with over 10 years of experience in the industry. He holds a B.Tech in Computer Engineering, earned in 2013.
Being a leading cloud service provider in India, we always maintain quality and transparency throughout the development process. Prior to going for the difference between Docker and Kubernetes, you must understand these concepts individually.
What is Docker?
When it comes to containers, Docker is always there. It is a software platform that supports the development of the application through a small and lightweight environment.
It is open-source, and developers prefer it for the packaging and distribution of applications that need to be centralized.
Further, the concept facilitates a shared operating system kernel, and each process runs individually without any dependency on the other. If we go in history, Docker came into existence in the year 2013. and since then, the life of developers is a little easier.
Now they have a provision to create a package for the entire application and execute it on any machine. As far as, Linearloop is concerned, we have a talented team of DevOps and hire the best docker developers in India from here exclusively.
Further, the concept of Docker revolves around four points. Many people are not aware of these concepts, hence have a look. If you already know, it is incredible.
Docker Universal Control Plane facilitates concrete experience to their users through a single interface.
For resilient architecture, it has a single point failure.
Docker offers security through the automated certificate.
Backward compatibility is assured in Docker.
Important terms used in Docker Swarm: Knowing exact terminologies is always essential, and being a growing cloud service provider in India, we know its significance. So always pay attention to it.
Node: Node is one that operates instances of the docker engine.
Swarm: Basically, Swarm is the collection or network of various instances of docker-engine.
Worker Node: These are the instances of the Docker engine that executes applications inside the containers
Manager Node: Maintenance of cluster state and task scheduling are the primary responsibilities of Manager Node.
What is Kubernetes?
Google is behind the foundation of Kubernetes and is an open-source that fulfills the purpose of containers deployment, operations upscale, and cluster-wide embedding all automation.
Being a technocrat, you must be knowing that applications have thousands of containers, and each has its defined instance, control, and management. Management of all these tasks is not simple, and hence Kubernetes is involved to manage and up-scale the features.
Also, at Linearloop, we have the world’s best Kubernetes developers who analyze your project from ground level and build it accordingly. Next time whenever you want to hire a Kubernetes developer in India, we are here.
Let’s know some important terms used in Kubernetes:
Cluster: In Kubernetes, a set of nodes or networks execute containerized applications, and its name is the cluster.
Node: The worker machine in Kubernetes is called Node. It can either be a virtual machine or a physical machine. Further, the control plane manages each of the nodes.
Pods: The smallest execution unit of Kubernetes is called Pods. These pods are transient in nature. Whenever any pod fails, Kubernetes creates its replica to keep the process or operation working.
Container: Basically, the container has everything that is required for the execution of an application. It is a ready-to-run software package.
So far, we have understood the concept of Kubernetes and Docker in detail. Now we will move towards differences. So, the upcoming section will cover the detailed comparison of Docker Vs. Kubernetes.
Hence, if you are searching for the difference between Docker and Kubernetes, the below-mentioned section will be helpful. Further, if any point keeps you in doubt, contact us immediately. We will do our best to sort out the issue.
Terminologies used in Kubernetes:
We will analyze both concepts on various parameters. Comparison of different parameters is essential because each technology has its own significance.
Let’s have a look
Installation Process:
Kubernetes
Docker
Kubernetes need a manual installation process to set up worker nodes components and Kubernetes Master.
Docker needs only a single line command for installation on operating systems like Linux, Ubuntu, CentOS.
Various systems support Kubernetes and it can easily run on the personal laptop, virtual machines, and even bare metal servers
In order to install a single-node Docker Swarm, the user can deploy Docker for Windows or Docker for Mac
Here the support for Windows is under the Beta phase
Here developers get support for Windows 10 long with the server (windows) 2016 & 1709
A manual upgrade is needed for the client & server packages on all the systems
The up-gradation in Docker is easy. With a single click, you can upgrade docker-engine in mac as well as windows.
Installation becomes complex and challenging
Installation is easy and quick
Operations/Working on both the containers:
Kubernetes
Docker
The functioning of Kubernetes revolves around the application level rather than on hardware level.
Two editions are there, at which Docker platforms work. The first one is Docker Community Edition & the second one is Docker Enterprise Edition
It offers support for various workloads that include data-processing, stateful, stateless workloads.
Community-based support forums are for Docker Community and Docker Enterprise Edition is served as enterprise-class support having fixed SLAs.
If you know the CLI (command-line interface) you can run Kubernetes on the top of Docker.
Both the editions of Docker come with Docker Swarm mode by default. Further, Docker Enterprise Edition supports Kubernetes
Selection will depend on the requirement
Selection will depend on the requirement
Scalability:
Kubernetes
Docker
Kubernetes works as one size that fits all for the development methods having distributed structure. Further, several groups of APIs are behind the scene that guarantees the cluster state. As a result of the bigger size, the speed of deployment compromises and scalability suffers
Independent of the size of the cluster, the deployment process with Docker Swarm is always fast. With faster deployment, the response time of the application becomes quick and as a result, its scalability increases.
The scalability of an application degrades with Kubernetes
The scalability of an application enhances with Kubernetes
Load Balancing
Kubernetes
Docker
Kubernetes follow a manual approach and hence load balancing becomes challenging here. In order to initiate the load balancing you need to make the configurations manually
Docker follows automated processes and it performs exceptionally well for load balancing. Further, it comes with prebuilt features that support load balancing and it makes the concept more advantageous than Kubernetes.
Based on the defined containers pods as services, the process of load balancing is initiated by Kubernetes
Here containers have the flexibility to join any node of the application.
It follows the manual approach
It follows the automated approach
Conclusion
These are some major differences between docker and Kubernetes. As we have stated earlier, each technology has its own significance. Further, the selection of any technology is dependent upon the requirement of your project.
If you need any support regarding cloud computing services, feel free to get in touch.
How does DevOps work?
As we have mentioned above, bringing two business units (Development and Operations) in coordination is the primary job of DevOps Technologies.
The operations and development team work together during the entire software development process. It starts with design to development to production and finishes with support.
Following the best practices, the ultimate intent of each team and participating member is to achieve the desired goal.
Further, all the stakeholders, clients, and other parties will be in the loop because of continuous integration and continuous delivery.
Both the concepts give them the flexibility to share required feedback as early as possible. As a result, development costs and time, both are saved.
Advantages of DevOps
IT industries are aggressively shifting their focus towards DevOps technologies because it has a result-driven approach. Apart from that, DevOps is one of the most demanding technologies because of its versatile features.
Let’s have a look at the benefits of DevOps.
Smooth Coordination: The biggest benefit of DevOps, is well-coordinated communication between the development and operation team. It offers an independent environment to the teams by being in coordination.
Speed: DevOps ensures fast delivery because of Continuous Integration and Continuous Delivery and it is also based on Agile principles.
Increased Reliability: As we know, DevOps follows the best practices for Continuous Integration, Continuous Deployment, and Automation Testing. As a result, we get reliable and robust business application.
Security: DevOps ensures the security of a product by following process automation and compliance policies. Further, if an application is developed using DevOps technologies, its security will never be compromised.
Management of Risk: Another most important benefit of DevOps is the management of risks. It allows early detection of bugs that may create a big problem at the coming stages. Early bug detection saves time as well as cost.
DevOps Tools
Knowledge of leading DevOps tools is a must. We know programming is all about mindset, but if you have enough information about the tools, your performance will be more impactful.
The role of DevOps tools is not hidden, as we are aware of the advantages of DevOps technologies.
Code Repositories: Code repositories allow multiple developers to work on the code. Additionally, it gives flexibility to the developers to code in & out, and they will also be able to go back to the older versions.
The tool also keeps the record of modifications made in the code. Developers will be required to monitor the changes so that they can update themselves with the recent change.
Artifact Repositories: Artifact contains the compiled source code for testing. Further, it enables object-based and version-controlled output. Both these approaches made the concept more significant and best practice.
CI/CD Pipeline Engines: The software development process becomes more prominent because of CI/CD. It allows frequent validation and delivery of the application.
Following the approach of continuous integration (CI), developers can build test, and validate the code using a shared repository. No manual intervention is required.
With continuous delivery (CD), quick execution & configuration set up for the release can be achieved. And with continuous deployment, it goes one step ahead. It involves testing, configuration, monitoring, analysis, and provisioning.
Some familiar CI/CD tools are Jenkins, TeamCity, Circle CI, Bamboo, Gitlab, Buddy, Travis CI.
Containers: With the help of Containers, multiple developers get individual infrastructure for development, testing, production, support, etc.
One of the popular containerization software is Docker. However, Microsoft offers multiple options for windows containers. Linearloop has a strong command over Docker development services, and you can hire docker developers for your projects.
Cloud Environments: To execute automated deployment, DevOps follow cloud infrastructure. The most commonly used cloud providers are AWS & Microsoft Azure. Further, Linearloop is also your constant partner for the services.
Also, hire AWS experts in India & USA from here as we have great and experienced people in our team.
As far as, our cloud computing services are concerned, we came in top cloud computing companies in India.
What are the key challenges DevOps faces and how to overcome them?
Explore the key challenges that DevOps often face and we also explained how they overcome those challenges.
1. Cultural Resistance: One of the most common challenges in adopting DevOps is cultural resistance. You will see that traditional organizational structures often create silos where development, operations, and other departments work in isolation. Due to this separation “us vs them” culture starts and it can be very harmful for a company. You can overcome this cultural resistance by applying the points mentioned below.
Communication and Training: Regularly communicate the benefits of DevOps and provide training to help team members understand its value.
Cross-Functional Teams: You should create cross-functional teams that include members from development, operations, and other relevant departments. This integration helps build trust and encourages collaboration.
Recognition and Rewards: Recognize and reward the collaborative behavior and achievements that perfectly match the principles of DevOps.
2. Legacy Systems Integration: Nowadays many companies have legacy systems that are not designed to work with the latest DevOps tools and practices. Integration of these systems can be complex and time-consuming as it can delay the adoption of DevOps. To overcome this challenge organizations should apply these points:
Assessment and Planning: You should conduct a thorough assessment of existing systems to understand the integration requirements and potential obstacles. Develop a detailed integration plan that includes phased implementation to minimize delays.
Incremental Approach: Implement the modern DevOps practices incrementally and start with the areas that are easier to modernize. This approach allows for slow integration of legacy systems while showing early successes.
Modernization and Refactoring: Easily modernize and refactor legacy applications to make them more compatible with DevOps standards. This might include breaking monolithic applications into microservices or adopting APIs for better integration.
3. Security Concerns: Integrating security into the DevOps pipeline is often known as DevSecOps and it can be challenging. Traditional security standards may not match with the fast-paced and iterative nature of DevOps which can lead to vulnerabilities. Overcome this challenge by integrating these security points given below:
Shift Left Security: Integrate security standards early in the development process (shifting left) to identify and address vulnerabilities before they reach production.
Automation of Security Testing: Use different types of automated security testing tools to continuously scan code and applications for vulnerabilities. Integrate these tools into the CI/CD pipeline to ensure that security checks are part of the development workflow.
Security Training: You should provide training about secure coding practices and emerging security threats to your developers and operations teams. This knowledge allows the teams to build security into their processes.
4. Managing Complex Environments: DevOps environments can become highly complex, especially in large organizations with different types of applications and infrastructure. Managing this complexity while maintaining consistency and control is considered a big challenge. You can overcome this challenge by following these points.
Infrastructure as Code (IaC): Include the Infrastructure as Code (IaC) to manage and provision environments consistently. Different types of tools like Terraform, Ansible, and Kubernetes can help automate the configuration and scaling of complex environments.
Monitoring and Logging: Implement thorough monitoring and logging to gain visibility into your systems and quickly identify issues.
Configuration Management: Start using configuration management tools because it ensures that all environments are consistent and reproducible while reducing the risk of configuration drift.
What is the future of DevOps?
Explore this section to determine the future of DevOps.
1. Emerging Trends and Technologies:
GitOps: GitOps is an approach that uses Git repositories as the single source to manage infrastructure and application configurations. This trend indicates declarative configurations and automating updates through Git workflows.
DevSecOps: Integrating the latest security standards into the DevOps process is known as DevSecOps and it ensures that security is a shared responsibility from the start. This trend is getting popular as organizations are prioritizing security in their software development lifecycle.
AI and Machine Learning in DevOps: The use of AI and ML helps optimize DevOps processes like predictive analytics to identify potential issues before they occur through automated code reviews and intelligent incident management.
Serverless Computing: Serverless architecture allows the developers to build and run different types of applications without managing infrastructure. This trend is affecting how applications are deployed and scaled in a DevOps environment.
2. Predictions for the Evolution of DevOps Processes:
Greater focus on Collaborative Tools: As remote and hybrid work models become more usual the usage of various tools ensures flawless collaboration so that it can become an integral part of DevOps practices.
Expansion of DevOps: The principles of DevOps will continue to be adopted in other areas of organizations like HR, finance, and marketing which promotes the culture of continuous improvement and agility.
Evolution of DevOps: As DevOps grows, the metrics used to measure its success will evolve and it includes more detailed indicators of performance like business value metrics and customer satisfaction scores.
Conclusion
DevOps is one of the evolving technologies, and it has strengthened the software development process. Further, with the implementation of DevOps, the applications become more reliable, robust, focused, and result-driven.
At Linearloop, we aim to work with the leading technologies, and DevOps is one of them. We have delivered countless projects in DevOps across the globe.
Added, we offer end-to-end support for DevOps and Cloud Computing Services. We are a leading cloud service provider in India & USA and if you have any doubt, feel free to connect.
We hope now you have an idea about DevOps and how DevOps work? Also, we will be looking into your queries.
Let's work together to build a more efficient and high-performing software development pipeline!