AWS vs GCP Which is Better in 2021 | Networking Funda
Only a few years in the past, enterprises have been reluctant to migrate to the cloud. Now, the cloud is a mainstream era, multi-cloud is the wave of the future, and hybrid environments are gaining in popularity. Flexera’s state of the Cloud 2019 survey4 observed that.
‐ 94% of enterprises use the cloud, and 31% say that
public cloud is their #1 priority.
‐ Multi-cloud is by far the preferred strategy; 84% of
enterprises run multiple clouds.
‐ 58% of enterprises run hybrid environments, up from
51% the year prior.
Organizations now find themselves tasked with evaluating and selecting not just one but multiple public cloud providers, then integrating and maintaining them, along with on-prem infrastructure.
AWS vs GCP Overview:
Launched in 2006, AWS was one of the first pay-as-you-go cloud computing models to be offered to the general public. Google launched GCP in 2008. Comparisons of AWS and GCP frequently claim that the public cloud is a “new” venture for Google.
While it’s true that AWS has been selling cloud services to the general public for a long, Google is not “new” to the cloud. In fact, Google’s cloud infrastructure predates Amazon’s.
Google developed Borg, the predecessor to Kubernetes, in about 2003 or 2004, and used it to manage production containers internally before introducing the open-source Kubernetes in 2014 and officially releasing it in 2015.
The company needed a highly secure and massively scalable platform for its ambitious
internal projects, including Google Search, Maps, AdSense, and Gmail.
At the time, no other company was doing what Google was doing — and certainly not on the same scale — so Google had to build its own solution! GCP simply allows other enterprises to take advantage of the same secure, time-tested, and highly optimized cloud infrastructure that Google has relied upon for years.
AWS vs GCP Service Comparison:
Both GCP and AWS offer a core set of services for compute, storage, networking, and databases. Higher-level services, such as machine learning and application services are built atop these core features:
Compute: Google Compute Engine and Google App Engine | Amazon Elastic Compute Cloud (EC2)
Storage: Google Cloud Storage | Amazon Simple Storage Service (S3) and Amazon Elastic Block Store (EBS)
Networking: Google Virtual Private Cloud | Amazon Virtual Private Cloud (VPC)
Databases: Google Cloud SQL, Google Cloud Firestore, and Google Cloud Bigtable | Amazon Relational Database Service (RDS) and Amazon DynamoDB.
This table provides side-by-side comparison with more detail:
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