Google Certified Cloud Associate
Google Cloud Engineer Associate
GCP is Google cloud platform which provides cloud based solution to all company to shift their IT infrastructure from physical premises to cloud and it may be private or public cloud. GCP is an example of Public cloud. This Google Cloud Engineer Associate Training enables you to learn about most of the Google Cloud Platform services which it provides through its Service catalogue.
This is the Best GCP training and certification course helps you to prepare the Google Cloud Engineer Associate Exam not only from theory point of view but also practical point of view. This course provides Best GCP lab online that will teach you step by step configuration method to configure all services provided by GCP which are useful to qualify the Google Cloud Engineer Associate EXAM.
The Course Pedagogy will help you to learn the following concepts on GCP Section which has been rated as Best Google Cloud Engineer Associate course online material.
- Google Cloud Services Overview
- Google Cloud Projects Billing & Accounts
- Google Cloud Compute Services
- Google Cloud Virtual Machines & Management
- Google Cloud Kubernetes Services
- Google Cloud App Engine
- Google Cloud -Cloud Functions
- Google Cloud Storage Deep Dive
- Networking in Google Cloud
- Google Cloud - Cloud Launcher & Deployment Manager
- Configuring Access & Security
- Monitoring , Logging & Cost Estimating
There are various Cloud Service Providers like AWS, Azure, Google, Oracle, who offers wide range of services like Compute, Storage, Network, and Other related infrastructure for running wide ranges of business applications.
Public Cloud Providers offers services that fall into four broad categories.
- Compute Resources
- Specialized Services like ML, AI, API’s.
Google Compute Resources
In Public Cloud like GCP, Compute resources comes in various forms, lets discuss one by one.
Google cloud platform offers large number of preconfigured VMs with various numbers of VCPU’s and Memory. Customer can also create a custom configuration if preconfigured offering from google does not meet customer environment.
Once customer creates a VM, it can be fully managed by customer to configure functions like file systems, add persistence storage, patching operating systems, install additional packages.
Auto scaling feature is also enabled in VMs. in which Auto scalars can add or remove VMs from the cluster based on current workload. This helps in controlling cost and also ensure sufficient compute capacity is available when workload increases.
Managed Kubernetes Clusters
Google cloud platform provides tool to create and manage clusters of servers. These Manage Clusters uses containers – which is like a light weight VM that isolates processes running in one container from processing running in another container on same servers. In managed server’s customer specify the number of servers they want to run and the containers that should run on them.
In managed Cluster, health of containers can be monitored and if containers fail, the cluster management software detects it and start another container.
It is a method in which developers and application admin run their code in a computing environment that does not require setting up VMs or kubernetes clusters.
Google Cloud Platform provides two serverless computing options:
- App Engine: It is used for applications and containers that run for extended period of time, such as a website backend, point-to-scale system, or custom business application.
- Cloud Functions: This platform is used to run code in response to an event such as uploading a file, adding message to message queue.
Google cloud platform offers below storage services, which are useful for wide range of application requirements.
Object storage is used to manage objects in terms of files or blobs. Objects are grouped in to bucket and each objects are individually addressable by URL.
Objects are stored or can be uploaded to storage without fear of disk limits. Multiple copies of objects are stored to improve availability and durability and in certain cases, copies of objects are stored in different regions to ensure availability even if region becomes inaccessible.
Object storage is also based on serverless model. In this there is no need to create VMs and add storage to them. Google cloud platform object storage is also called as Cloud storage, is accessible from servers running in GCP as well as from other devices with internet access.
Google Cloud platform has a file storage called as Cloud File Storage, and provides network shared file systems and is based on Network File system (NFS) storage systems.
This offering is best suited for applications that require operating systems – like file access to file. This file storage system decouples the file system from specified VMs.
Block Storage is used in ephemeral and persistent disks attached to VM. With block storage system, you can install file system on top of block storage or customer can run applications that access blocks directly.
Block storage are available on disks that ae attached to VMs in Google Cloud Platform. A Persistent disk continues to exist and store data even if it is detached from virtual server or the virtual server to which it is attached shuts down.
Ephemeral disks exist and store data only as long as a VM is running. It stores operating system files and data that are deleted when VM is shut down.
Caches are in-memory data stores, that is used to fast access to data. When customer has requirement to keep the read latency minimum, Cache are used.
Below is some consideration, that can be referred, Inorder to use cache not always.
- Cache memory are more expensive then SSD or HDD.
- Cache are Volatile in nature, means customer can lose the data stored in the cache when power is off or lost, or of the OS is rebooted.
Networking in GCP is achieved by designing Virtual Private cloud (VPC). In VPC, All External IP address are accessible from Internet and these IP address are either Static or Ephemeral.
Static IP address are assigned to a device for extended period of time, whereas Ephemeral IP address are attached to VM and is released when the VM is stopped.
We can also define Firewall rule to control inbound and outbound connection to your VMs or applications in your VPC.
We will understand the Networking in more detail in coming sections.
There are certain Specialized services that each public Cloud Service Provider provides and these service are building blocks of any applications.
Some of the common characteristics of Specialized Service are as follows:
- Serverless Model, Application do not require to configure servers or clusters.
- Provides some specific function like translating text, analyzing images.
- Provides API to access the functionality of service
GCP provides some of the specialized service, which are as follows:
- Auto-ML – Machine Learning language
- Cloud Vision – Analyzing Images
- Cloud Inference API – compute Correlation over Time-Series data
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- We don't offer Any Hands-On labs for practice in this course.
- Lab discussed here contains different Scenarios, task & Its recorded Solutions.
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