Google Cloud BootCamp

I'm attending a Google Cloud BootCamp, a great opportunity to expand my knowledge in cloud computing and related technologies.

Here's a brief overview of the topics that will be covered:

1. General Cloud Knowledge

Cloud computing refers to the delivery of various services over the Internet. These services include storage, databases, servers, networking, software, analytics, and more. Key characteristics of cloud computing include:

• On-Demand Self-Service: Users can access services as needed without human interaction with the service provider.

• Broad Network Access: Services are available over the internet and accessible through standard mechanisms and platforms (e.g., mobile phones, laptops, workstations).

• Resource Pooling: The provider's computing resources are pooled to serve multiple consumers, with different physical and virtual resources dynamically assigned and reassigned according to demand.

• Rapid Elasticity: Resources can be elastically provisioned and released to scale rapidly outward and inward, commensurate with demand.

• Measured Service: Cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts).

2. General Google Cloud Knowledge

Google Cloud Platform (GCP) is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, like Google Search, Gmail, file storage, and YouTube. Key components include:

• Compute Engine: Infrastructure as a Service (IaaS) that provides users with virtual machine instances for workload hosting.

• App Engine: Platform as a Service (PaaS) for app development and hosting in the cloud.

• Google Kubernetes Engine: Manages and orchestrates Docker containers on Google Cloud.

3. Google Cloud Products and Services

GCP offers a wide range of products and services, including:

• Computing and Hosting Services: Like Compute Engine, App Engine, and Kubernetes Engine.

• Storage: Such as Cloud Storage, persistent disks, and file storage.

• Databases: Like Cloud SQL, Cloud Bigtable, and Firestore.

• Big Data and Analytics: Tools like BigQuery, Dataflow, Dataproc, and Data Studio.

• AI and Machine Learning: Services like AI Platform, Vision AI, and Video AI.

4. Digital Transformation, Data, and AI/ML

Digital transformation involves using digital technologies to create or modify existing business processes, culture, and customer experiences. In the context of cloud computing, it often includes:

• Data Analytics: Using tools like BigQuery and Dataflow to analyze and gain insights from data.

• AI and Machine Learning: Leveraging cloud-based AI and ML services to automate processes and glean insights from large data sets.

• Cloud Integration: Migrating and integrating existing systems and applications to the cloud.

5. Modernizing Company IT Infrastructure and Applications

This involves updating and optimizing the IT infrastructure and applications to be more efficient, scalable, and cost-effective. Key aspects include:

• Migration to the Cloud: Shifting physical servers and data centers to cloud-based solutions.

• Application Modernization: Refactoring or re-architecting legacy applications to be more cloud-native.

• Adopting DevOps Practices: Implementing tools and methodologies for faster and more efficient application development, deployment, and maintenance.