Making the Enterprise Multi-Cloud Decision: A 2023 Comparison of Amazon Web Services (AWS) vs Google Cloud Platform (GCP)

Dear reader, as your organization moves vital operations to the cloud, choosing the right provider is a complex yet critical decision. In this technology brief, I compare the two dominant infrastructure-as-a-service platforms—AWS and GCP—across 12 assessment criteria relevant to large enterprises. My goal is to provide unbiased evidence on their technical capabilities, business models, roadmaps and ideal use cases so you can craft an efficient multi-cloud strategy leveraging strengths of both.

I. Cloud Market Overview – Staggered Launches Result in Divergent Platforms

Let‘s recap key milestones in the dynamic public cloud industry…

AWS Origin Story

  • Launched simple S3 storage + EC2 compute in 2006
  • First mover status enabled years of uncontested growth
  • By 2015, AWS neared $10B revenue with 30%+ cloud market share

GCP Playing Catch-up

  • Late entry to market in 2008 initially slowed adoption
  • Priority on big data, machine learning and APIs
  • Revenue topped $10B in 2020; now firmly second behind AWS

Despite staggered timelines, both evolved into full-fledged platforms covering hundreds of enterprise IT needs:

CategoryAWS CapabilitiesGCP Capabilities
Infrastructure170+ compute, storage and network services80+ core infrastructure services
DatabasesManaged relational, key-value, graph, time-seriesCloud SQL, Firebase/Firestore, Spanner
Big DataRedshift, EMR, Kinesis, Lake FormationBigQuery, Dataflow, Dataproc, DataFusion
Machine LearningSageMaker, Forecast, Personalize, Fraud DetectorVertex AI, AutoML Tabular/Text/Video, TPUs
ManagementConsole, Config, CloudWatch, CloudTrail, Control TowerConsole, Config Manager, Monitoring, Logging, Access Transparency
DevOpsCodeCommit, CodeBuild, CodeDeploy, CodePipelineCloud Build, Source Repos, Cloud CDN, Argo Workflows

Let‘s dig deeper into the technical and business differentiators…

II. Comparing Core Infrastructure – Global Scale vs Advanced Services

While similarities exist across basic functionality, architectural philosophies diverge noticeably…

AWS – Unmatched Scale and Reliability

  • 84 Availability Zones (AZs) within 26 Regions
  • The broadest and deepest cloud infrastructure globally
  • Extensive compliance certification coverage

GCP – Strategic Technology Focus Areas

  • 73 Zones within 24 Regions – trailing but catching up
  • Specialized differentiation across ML, analytics, APIs
  • Very competitive on security, privacy and sustainability

Drilling down, we see alternative approaches play out in the IaaS foundation:

Virtual MachinesEC2 (Elastic Compute)Compute Engine
Object StorageS3 (Simple Storage)Cloud Storage
Block StorageEBS (Elastic Block Store)Persistent Disk
File StorageEFS (Elastic File System)Filestore
Load BalancingELB (Elastic Load Balancing)Cloud Load Balancing
DNS ServiceRoute 53Cloud DNS

While meeting 80%+ of typical IaaS needs, AWS out-invests GCP in niche services like batch computing, workflow orchestration and media processing. GCP counters with deeper open source leveraging Kubernetes, Istio service mesh and high-throughput data ingestion.

Both secure infrastructure through granular IAM policies, VPC service segregation and ISO/SOC-certified hardware. GCP recently introduced Confidential VMs leveraging AMD processors to encrypt in-memory data.

For core networking, storage and databases, performance prevails on either option:

Max SQL IOPS320,000 (RDS on EC2)450,000 (N2 High Memory)
Max NoSQL IOPS1.5M (DynamoDB)2.8M (Datastore)
Max Filesystem IOPS100,000 (GP3 Storage)1M (Zonal SSD Persistent Disk)
Load Balancer Latency30ms (NLB)35ms (Network TCP)

On regional availability, AWS maintains leadership reaching 87 metro areas globally – ideal for applications requiring local data residency. GCP trails at 34 metros but actively expands across Europe, Asia and Latin America.

III. Specialized Strengths – ML/AI Supremacy vs Unmatched Integrations

Delving beyond infrastructure, vast platform ecosystems have emerged…

GCP – ML/AI Supremacy

With TensorFlow, Kubeflow and AutoML originations, GCP dominates machine learning:

  • Vertex AI – Unified MLOps environment
  • BigQuery ML – SQL interface for creating models
  • Cloud TPUs – Hardware acceleration for model training
  • Exclusive access to latest Google ML research

AWS – Unmatched Integrations

AWS cultivated a partner ecosystem unrivaled in breadth and depth:

  • Security – CloudWatch, GuardDuty, Macie
  • Migration – DMS, Application Discovery Service
  • Containers – ECS, EKS integrates major tools like Datadog
  • Industry Solutions – Amazon Retail, Amazon Health, Amazon FinSpace

RICH: No public cloud can match the vertical expertise encoded into these industry platforms.

For startups and mid-market firms, AWS third-party maturity lowers risks of adopting cloud infrastructure. With GCP, you gain groundbreaking ML but sacrifice some configurability.

IV. Comparing Business Factors – Pricing, Support and Strategic Vision

Beyond technical specifics, commercial influences matter greatly…

Pricing – Devil in the Details

Abstracting complex rate cards, a typical multi-Region 100 VM production footprint would cost:

| Service | AWS | GCP | Effort to Optimize |
| EC2 m5.2xlarge VMs | ~$95K/month | ~$77K/month | High |
| GCP n2-standard-8 VMs | | | Low |

Apply reservations, sustained use discounts and specialized instances to trim ~30% expenses on either. Cost efficiency favors time investment – complex on AWS but rewarded, straightforward on GCP.

Support – Open Source vs Premium Models

AWS offers business, enterprise and professional tiers with escalated response times and designated account managers costing 10-15% extra.

GCP includes email and chat with standard contracts – no upcharges – but lacks account management. However, GCP contributes extensively to communities around solutions like Kubernetes and Istio. AWS cultivates more proprietary capabilities around SageMaker, Alexa and Kindle.

Strategic Vison – Ever-Expanding Breadth vs Technical Innovations

AWS seems destined to offer every infrastructure service imaginable; GCP strategically funds paradigm shifts in data analytics, ML and Web 3.0.

Google Cloud also presses the industry toward carbon neutrality and ethical AI advancements. In contrast, Amazon and AWS face external criticism around sustainability and workplace culture.

V. Recommendations – Crafting an Intelligent Multi-Cloud Strategy

Synthesizing insights from this evaluation, I suggest a multi-cloud approach maximizing strengths of both platforms:

Eight Best Practices for Multi-Cloud Excellence

  1. Standardize environments & tools for consistency across clouds
  2. Encapsulate services in containers & API layers for portability
  3. Classify workloads by infrastructure sensitivity, data regulations
  4. Analyze cost, capacity and feature trade-offs continuously
  5. Automate deployments, scalability and failover recovery
  6. Govern through role segregation, tagging conventions and change controls
  7. Orchestrate unified visibility via management tools across clouds
  8. Skill for cloud platforms generally – avoid custom integration logic

Strategic Workload Placement Guide

Application TypeTarget Cloud VendorRationale
Mobile apps, gamingGCPCloud Firestore, Cloud CDN, Apigee
Big data pipelinesGCPBigQuery, Dataflow stream processing
General business systemsAWSBroader ecosystem, enterprise support
ML model developmentGCPVertex AI, Cloud TPU pods
Global digital presenceAWSWider region footprint
Digital marketing analyticsGCPLooker BI, Data Studio
Security operations, fraud detectionAWSGuardDuty threat detection

This blueprint aligns your portfolio to cloud provider strengths today while keeping future migration options open.

VI. Closing Thoughts

Neither AWS nor GCP can fulfill 100% of enterprise cloud infrastructure needs exclusively.

AWS leads in services count, partner integrations and global reach – fuelling startups and established IT organizations equally with robust foundational technologies. GCP counterpunches with concentrated investments in ML, analytics and market-disruptive capabilities.

Approaching your cloud program as collaborators rather than competitors extracts the most business value short-term while retaining flexibility long-term. A multi-cloud management platform like Morpheus or VMware CloudHealth simplifies day-to-day operations by centralizing visibility, security policies and workload orchestration.

I hope illuminating key technical and business differences between AWS and GCP – plus recommendations on intelligently leveraging both platforms – proves useful navigating your own cloud transformations in 2023 and beyond!

This independent cloud infrastructure briefing brought to you by Rich Bowen – 25 year technology executive and cloud architect.

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