google cloud platform (gcp)
Google Cloud Platform
Compute Engine - Scalable, high-performance virtual machines.
Migrate for Compute Engine - Fast, flexible, and safe migration to Google Cloud with Migrate for Compute Engine (formerly Velostrata)
App Engine - Build and deploy applications on a fully managed platform.
Kubernetes Engine (GKE) - managed, production-ready environment for deploying containerized applications.
Container Registry - Store, manage, and secure your Docker container images.
Migrate for Anthos - Migrate VMs from on-premises or other clouds directly into containers in GKE.
Knative - Kubernetes-based platform to build, deploy, and manage modern serverless workloads
Cloud Functions - Event-driven serverless compute platform
Cloud Run on GKE
Storage & Databases
Cloud Storage - Unified object storage for developers and enterprises
Filestore - High-performance, fully managed file storage
Cloud SQL - fully managed database service - easy to set up, maintain, manage, and administer your relational PostgreSQL, MySQL, and SQL Server databases
Cloud Spanner - Fully managed, scalable, relational database service for regional and global application data
Cloud Bigtable - petabyte-scale, fully managed NoSQL database service for large analytical and operational workloads.
Cloud Firestore - NoSQL document database for mobile and web app data
Cloud Memorystore - Fully managed in-memory data store service for Redis
Cloud Dataprep - intelligent cloud data service to visually explore, clean, and prepare data for analysis and machine learning
Cloud Data Fusion - fully managed, cloud-native data integration service that helps users efficiently build and manage ETL/ELT data pipelines
Data Catalog - fully managed and highly scalable data discovery and metadata management service
AI / ML
AI Platform - Create your AI applications once, then run them easily on both GCP and on-premises.
AI Hub - Hosted AI repository with one-click deployment for machine learning teams
AI Platform Notebooks - managed service that offers an integrated JupyterLab environment
Cloud AutoML - Train high-quality custom machine learning models with minimal effort and machine learning expertise
AutoML Tables - Automatically build and deploy state-of-the-art machine learning models on structured data
Document Understanding AI
Natural Language API - Derive insights from unstructured text using Google machine learning
Vision API - Derive insights from your images in the cloud or at the edge with AutoML Vision or use pre-trained Vision API models to detect emotion, understand text, and more.
Translation API - Dynamically translate between languages using Google machine learning
Cloud Video Intelligence API - Video AI - Enable powerful content discovery and engaging video experiences
Dialogflow - end-to-end, build-once deploy-everywhere development suite for creating conversational interfaces for websites, mobile applications, popular messaging platforms, and IoT devices
Site Reliability Engineering (SRE)
Google Events - I/O, NEXT
Google Research / Experiments
Careers @ Google Cloud
Data Analytics / Smart Analytics
Hybrid Cloud Specialist
VM Migration / Migration Specialist
Technical Foundation / Solution Architecture
Technical Account Manager (TAM)
Strategic Cloud Engineer (SCE)
Practice Lead - Digital Transformation
Cloud Data Engineer Specialist
Big Data and Analytics Cloud Consultant
Enterprise Cloud Architect
Cloud Infrastructure Engineer
Partner Practice Manager
Customer Success Manager (CSM)
Become GCP Partner
First, please apply to be a GCP partner.
Build Engagement Model
In the event that you do not yet have certified resources on staff, here are some helpful tips to get your team started:
Practice exams for the 2 different certifications can be found here:
Contact Partner Concierge team