Moving to the cloud from a traditional method of on-premise data storage increases agility, cuts costs, and makes innovations possible for all different businesses. The COVID-19 pandemic and remote work have accelerated digital transformation. Cloud computing has become the de facto choice for IT management. Cloud computing platforms accelerate digital transformation projects compared to outdated information technology go-to models.
Choosing the best cloud platform for your business isn’t easy. It would be best if you considered several factors like your business functions and budget. If you hastily or improperly alter your digital business environment, it can end up being very expensive. This blog will help you avoid common pitfalls while choosing cloud services.
Amazon Web Services Overview
The most popular cloud platform providers include Microsoft Azure, Google Cloud, and Amazon Web Service (AWS). Minimizing costs while still receiving excellent support and service is the ultimate end goal.
Amazon Web Services is a robust cloud computing platform for various enterprises. Amazon, managed by Amazon, whose services are divided between edge locations, geographical areas (regions), and availability zones (data centers). In order to ensure that there aren’t any breaks in service due to unforeseen circumstances like disasters, the AWS availability zones are geographically separated for faster response and delivery times. Edge locations cache web content closer to the user’s location. The AWS infrastructure allows data delivery deployment to be faster without conceding service and performance availability. AWS ranks as the top infrastructure-as-a-service (IaaS) platform and supports all operating systems in terms of performance, the sheer number of applications, and availability.
Google Cloud Overview
Although relatively new, Google Cloud has been able to create its mark in the IaaS field. This cloud platform supports different generations of Windows and Linux server versions. It has over 22 regions globally, with each region divided into more than three zones. Because of Google’s substantial investment in expanding cloud services, it’s projected to massively expand its cloud platform services in the future . It has a unique cabling undersea server deployment system that effectively connects the servers in Japan, Asia, the US mainland, Australia, and South Pacific.
Microsoft Azure Overview
Does your business rely on Windows-based standardization? Microsoft Azure’s integrated platform is one of the best cloud platforms you can use. Azure is Linux friendly because it’s compatible with Linux container platforms and virtual guest operating systems. Azure comes with built-in server apps that can accommodate numerous programming languages, including .NET, PHP, Python, Node.js, Java, etc. It is available in over 60 regions across the globe and has both convenient operation and configuration. It utilizes has the latest technology to boost cost-savings and productivity.
Cloud platforms offer wide-ranging storage capabilities. Azure, for example, comes with specialized solutions like Data Lake for data-rich, large applications. Google Cloud offers fewer storage options than AWS and Azure, while AWS comes with more.
- Storage Services: Azure offers Queue storage for workloads with high volume and Blob storage for REST-based object storage of unstructured data. Furthermore, Azure also has Data Lake Store to manage bulky data applications in addition to File and Disk Storage.
- Extensive Database: Azure’s database includes Data Warehouse service, Redis Cache, Cosmos DB, and Table Storage for NoSQL, three SQL-based options, and the enterprises that use Microsoft SQL Server in their own data centers have Server Stretch Database. Microsoft Azure also offers Site Recovery Service and Archive Storage as well as backup service
- SSS to EFS: The services offered by AWS include Elastic Block Storage (EBS) for persistent blocks, Simple Storage Service (S3) for objects, and Elastic File System (EFS) for files. To enable a hybrid storage environment, AWS also offers a Storage Gateway. It has Snowball – a physical storage device that transfers petabytes of data in scenarios of no network connectivity.
- Database and archiving: AWS storage includes Getaway archives that manage backup easily. Glacier is designed for long-term archival storage.
Google Cloud Storage
- SQL and NoSQL: Google Cloud has a relational database called Cloud Spanner and its SQL-based Cloud SQL for essential core workloads. Furthermore, it has two NoSQL options: Cloud Datastore and Cloud Bigtable. Unfortunately, it does not have archive and backup services.
Each of these different platforms has different benefits and drawbacks according to your respective needs. Whereas Azure offers built-in compatibility benefits, AWS offers a wider reach and availability of services. On the other hand, Google supports almost any OS with a wide range of products and platforms.
AWS Compute Features
AWS offers E2C (Amazon Elastic Compute Cloud) with a high degree of database cost optimization and compatibility. As it is a scalable platform, you can scale up or down automatically. This means that it can deploy several instances in seconds. The auto-scaling monitor allows you to monitor your apps without padding the price according to your requirements and capacity. Its availability is 99.99 percent.
Amazon Elastic Container (Amazon ECS) also supports Docker through a series of API calls. You can manage website API calls, query your application’s state, access security groups, and start or end Docker-enabled apps.
Here are some additional AWS compute features:
Google Cloud Compute Features
- Amazon Lightsail
- AWS Lambda
- AWS Fargate
- AWS Beanstalk
- AWS Batch
- AWS Outposts
- AWS Serverless Application Repository
- VMware Cloud for AWS
Google Cloud supports Docker containers and further specializes in Kubernetes. Its services allow you to deploy code from Firebase, Google Cloud, or Assistant with real-time scaling up or down as you deploy apps and manage your resources.
Other GCP compute features include:
- Instant groups
- Compute Engine
- Docker Container registry
- Google App Engine
- The graphic processing unit (GPU)
Azure Compute Features:
To enable computing solutions for testing application deployment, development testing, and datacenter extensions, Azure relies on a network of virtual machines. It is based on an open-source model that is compatible with Windows and Linux servers, Oracle, SQL servers, and SAP. It further offers a hybrid cloud model, which is a combination of public clouds and on-premise storage. Load balancing can be integrated with it.
Other Azure features include:https://mdsitservices.com/2021/02/the-best-cloud-platforms/?preview=true
- Service Fabric
- Azure Batch
All three cloud platforms are committed to machine learning technology and AI advances. Here is a comparison of how the three are efficient in serverless platforms, IoT networking, and AI:
Azure Key Tools
Microsoft software and business apps are integrated with on-premises-supported tools (API) and AI tools (enhanced along with Cognitive Services). The serverless platform orchestrates and manages complex workloads.
Google Key Tools
Google’s cloud-based enterprise key tools include translation, natural language, and global enterprise coordination to ML app development transitioning speech. Google Cloud also has TensorFlow – a large open-source library. Its serverless platforms and IoT are in the beta stage.
AWS Key Tools
AWS supports deploying machine learning and staff training through its utilization of SageMaker. You’ll experience increased flexibility with the option to deploy apps from the serverless repository. AWS also offers a serverless computing environment through Lambda. For better customizations, you can integrate IoT enterprise solutions.
Security in cloud platforms is based on authorization and authentication. Security defenses are never adequate, and the possibility of breaching always exists. Data is stored in on-premise networks and data centers with third-party vendors, and in these environments, you are never aware of the persons who have access to the data. Therefore, organizations should fashion their own data protection strategies to ensure anyone who has access to the data is authenticated – “Zero Trust.” Let’s look at how these three cloud platforms approach cloud security.
AWS Cloud Security
Building a cloud platform from the ground up offers greater flexibility in design rather than building on an existing base. To make sure its security is superior, AWS adds functionality to their identity controls. They pin identity as their prime control mechanism. Organizations can add granularity by linking an identity through the added tags. Commands through the policies allowed by AWS can be restricted to regions within the cloud. This gives an organization leverage to manage an identity-based security environment. AWS’s security tools include CloudWatch, Security Hub, AWS Config, Macie, GuardDuty, and CloudTrail. AWS limits any data breach’s blast radius by allowing users to put workloads and projects in separate accounts. AWS assigns roles to entities. This allows access policy and strong identity to be imposed on workloads, containers, or serverless functions. Developers can therefore avoid corrupt practices like embedding credentials where they shouldn’t be embedded. AWS also exhibits consistency and rock-solid performance.
Azure Cloud Security
Microsoft Azure has an extensive threat intelligence operation with the ability to analyze nearly half a billion emails, a billion Windows device updates, 18 billion Bing web pages, and 450 billion authentications monthly. They also have 3,500 experts in cybersecurity on hand to ensure Azure’s security. It is vital to note that Azure is based on Microsoft’s Active Directory product, which is very popular with many IT professionals, making it simple to work with. Syncing Azure to an active enterprise Active Directory is easy due to the strong connection between them. Therefore, memberships and identity groups from the enterprise float into the cloud, where preservations on controls are done.
Google Cloud Security
Google had to embrace its competitors’ features to be relevant. Its security uses Active Directory and identity security, and its design of bucket policies resembles AWS. Google’s Kubernetes support has the best secure implementation, and its machine learning services are excellent. The main shortcoming of this platform is that anyone can get invited to a project, especially if they have a Gmail address.. Boundaries in Google cloud are constructed around projects. Since identities are also constructed around projects, they have access to what they need related to the workload. However, the overall security on Google cloud is a work in progress.
Comparison of Strengths
- Extensive and mature offerings
- Dominant market position
- Global reach
- Support for large organizations
- Flexibility and a wider range of services
- Hybrid cloud
- Ideal for startups and developers
- Support for open source
- Broad feature set
- Second-largest provider
- Integration with Microsoft software and tools
- Most cost efficient
- Flexibility contracts
- DevOps expertise
- Complete container-based model
- Commitment to open source and portability
- Designed for cloud-native business
Compatible businesses/applications comparison
Being the oldest in the cloud computing field, AWS has a bigger user base and community support. The businesses/applications it supports include:
Its infrastructure is the same as Google Search and YouTube. Clients include:
- 20th Century Fox
Microsoft Azure has high-profile customers such as:
- Johnson Controls
Although it is difficult to parse pricing between the three, here are some basic figures:
The basic instance includes 2 Virtual CPUs and 8GB RAM and costs around US$69 per month.
The basic instance includes 2 Virtual CPUs as well as 8GB RAM and costs around US$70 per month.
Compared to AWS, the basic instance includes 2 Virtual CPUs and 8GB RAM. It offers a 25% cheaper rate, which will cost around US$52 per month.
The largest instance includes 3.84 TB of RAM and 128 vCPUs, costing around US $3.97 per hour.
Its largest instance includes 3.89 TB of RAM and 128 vCPUs, and it costs around US $6.79 per hour.
For GCP, the largest instance includes 3.75 TB of RAM and 160 vCPUs. It costs roughly US $5.32 per hour.
Pros and Cons Comparison
- Enterprises can deploy Windows and other Microsoft software
- Integrated with other applications
- Supports on-premise software like Office, Windows Server, Dynamic Active Directory, .Net SQL, Sharepoint, among others.
- High overhead
- More popular with its massive scope
- Carries a huge (and growing) array of services
- Has a comprehensive network of data centers
- Expensive cost structure compared to other cloud platforms
- Offers solutions such as big data, machine learning, and analytics
- Offers load balancing and scaling
- Global data center network
- Considered a secondary provider
- It is not open-source-centric
Looking from this angle now, deciding on the best cloud platform between Google vs. Azure vs. AWS is no longer a hard task. Based on the aforementioned information, AWS is the superior overall cloud platform option. However, your specific business needs should always come first in identifying the right cloud platform for you.