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Examining Technical Processes for GCP

Examining Technical Processes for GCP

In your role as an architect, you'll be involved in numerous technical procedures, some of which were covered in earlier chapters, like continuous integration/continuous delivery (CI/CD) and post-mortem analysis. This chapter will delve deeper into these and other processes like software development lifecycle management, testing and validation, and business continuity and disaster recovery planning. Our aim is to present a comprehensive understanding of these technical processes, with an emphasis on their connection to business goals. For a more technical exploration, including the use of tools like Jenkins in CI/CD, please refer to the subsequent discussions.

Christopher GodwinAbout 25 minGoogle CloudTechnologystudy guideGoogle cloudgcpGCCPCA
Analyzing Technical Processes for GCP

Analyzing Technical Processes for GCP

Architects are involved in many different types of technical processes:

  • Continuos Deployment
  • Continuous Delivery
  • Post-mortem Analysis
  • Development Lifecycle Planning
  • Testing
  • Validation
  • Business continuity
  • Disaster Recovery(DR)

Christopher GodwinAbout 8 minGoogle CloudTechnologystudy guideGoogle cloudgcpGCCPCA
Architecting for Reliability

Architecting for Reliability

A reliable system is one people can get to now. Reliability is the probability a system can be reached and used without failure and Availability is a measure of how available a system is to be used within a given period of time.

Cloud Operations Suite

Christopher GodwinAbout 18 minGoogle CloudTechnologystudy guideGoogle cloudgcpGCCPCA
Architecting GCP Solutions for Security and Legal Compliance

Architecting GCP Solutions for Security and Legal Compliance

Identity and Access Management

Identity and Access Management or IAM is a service which lets you specify which users can perform which actions in the cloud. IAM includes the following objects:

  • Identities and Groups
  • Resources
  • Permissions
  • Roles
  • Policies

Christopher GodwinAbout 16 minGoogle CloudTechnologystudy guideGoogle cloudgcpGCCPCA
Architecting GCP Network Solutions

Architecting GCP Network Solutions

OSI Model Layers

  1. Physical, the actual metal, wires, electrons and plastic ethernet plugs. You'll find wifi's radio frequency here because radio is physical phenomenon. In Quantum networking this layer are the entangled particles and the equipment uses to read and write to them plus the equipment used to connect to that. Voltage is sometimes the physical layer in Ethernet Over Power. With tin cans on a string, this layer is the cans, string and the vocal vibrations traveling through them.
  2. Data Link, ARP, Mac Addresses, Collision avoidance. This is broken into two mini-layers, the first is media access control(MAC) and the second is Logical Link Control(LLC). The second acts as a negotiator between the MAC layer and the third 'Network' layer.
  3. Network, this is where IP Addresses live. Keep in mind these network layers are the layers of a packet sent over the network. This is the base layer for packets. A packet is data encapsulated in a route with source and destination addresses.
  4. Transport. The protocol that makes this process work known by all networking devices speak is Transmission Control Protocol(TCP) or User Datagram Protocol(UDP). The Protocol identifier stored in a packet lives in this layer.
  5. Session, this layer manages handshakes. An SMTP connection timeout would exist on this layer. TLS handshakes happen here. An https packet is fully encrypted, so a request to a server asking for a url cannot be understood unless it is decrypted, then it can be seen. Inside layer 4 lives an encrypted layer 5 envelope in the case oF HTTPS connections. Layer 5 is the encrypted data, while layer 6 is the decrypted data.
  6. Presentation, A GET / request is in this layer. Mappings of network resources to application resources in the OS kernel happen at layer 6.
  7. Application, This is the later applications connect to in order to do networking. A webbrowser fetches web pages from this layer. This layer one might consider a data format. A TXT file vs a Json file. Mime types exist at this Layer. Layer 7 in the packet is the raw data unenveloped by network dressing that tells the network about it.

Christopher GodwinAbout 12 minGoogle CloudTechnologystudy guideGoogle cloudgcpGCCPCA
Architecting Storage Solutions in Google Cloud Storage

Architecting Storage Solutions in Google Cloud Storage

Object Storage

Object Storage is common to all cloud systems and has its roots way back in 2006 with Amazon S3 and Rackspace Files/OpenStack Swift and Google Cloud Storage in 2010. These systems are for storing files or documents as objects as opposed to a directory filesystem. Instead of hierarchical the particulate nature of object storage treats everything atomically. You can't seek and read parts of the file, you can't tail off of object storage. You can get, put, delete objects. Their organization depends on the system.

Christopher GodwinAbout 15 minGoogle CloudTechnologystudy guideGoogle cloudgcpGCCPCA
Architecting Compute Engine Solutions in GCP

Architecting Compute Engine Solutions in GCP

Compute Engine Services

Each of these services have different use cases. You'll have to know how to select the right one for your requirements.

Service Use Case Fancy Buzzword
Compute Engine If you need root access and are running multiple processes in the same operating system instance. Infrastructure as a Service (IaaS)
App Engine You need to run a nodeJS, Java, Ruby, C#, Go, Python or PHP application quickly with no configuration or management. Platform as a service (PaaS)
Cloud Functions You need to run a serverless routine. Executions as a Service (EaaS)
Cloud Run Run individual containers. PaaS
Kubernetes Engine Run several docker containers in group. Containers as a Service (CaaS)
Anthos Run containers in a hybrid or multi-cloud environment. Hybrid CaaS

Christopher GodwinAbout 24 minGoogle CloudTechnologystudy guideGoogle cloudgcpGCCPCA
Desiging Solutions for Technical Requirements

Desiging Solutions for Technical Requirements

High Availability

High availability is a key characteristic of any reliable system, and is typically measured by what is known as the "99999" rule. This rule states that a system must be operational 99.9999% of the time in order to be considered highly available. This equates to a maximum downtime of just over 5 minutes per year. In order to achieve such a high level of availability, a system must be designed and implemented with care, and must be constantly monitored and maintained. Additionally, a high availability system must have a robust service-level agreement (SLA) in place in order to ensure that the system meets the required availability levels.

Christopher GodwinAbout 13 minGoogle CloudTechnologystudy guideGoogle cloudgcpGCCPCA
List of All Managed Google Cloud Platform(GCP) Services

List of All Managed Google Cloud Platform(GCP) Services

Service Type Description
AutoML Tables AI and Machine Learning Machine learning models for structured data
Recommendations AI AI and Machine Learning Personalized recommendations
Natural Language AI AI and Machine Learning Entity recognition, sentiment analysis, language identification
Cloud Translation AI and Machine Learning Translate between two languages
Cloud Vision AI and Machine Learning Understand contents of images
Dialogflow Essentials AI and Machine Learning Development suite for voice to text
BigQuery Analytics Data warehousing and analytics
Batch Compute fully managed batch jobs at scale
VMware Engine(GCVE) Compute running VMware workloads on GCP
Cloud Datalab Analytics Interactive data analysis tool based on Jupyter Notebooks
Data Catalog Analytics Managed and scalable metadata management service
Dataproc Analytics Managed hadoop and Spark service
Dataproc Metastore Analytics Managed Apache Hive
Cloud Composer Analytics Data workflow orchestration service
Cloud Data Fusion Analytics Data integration and ETL tool
Data Catalog Analytics Metadata management service
Dataflow Analytics Steam and Batch processing
Cloud Spanner Database Global relational database
Cloud SQl Database Regional relational database
Cloud Deployment Manager Development Infrastructure-as-code service
Cloud Pub/Sub Messaging Messaging service
Bigtable Storage Wide column, NoSQL databases
Cloud Data Transfer Storage Bulk data transfer service
Cloud Memorystore Storage Managed chage service using Redis or memcached
Cloud Storage Storage Managed object storage
Cloud Filestore Storage Managed shared files via NFS or mount
Cloud DNS Networking Managed DNS with API for publishing changes
Cloud IDS Networking Intrusion Detection Systems
Cloud Armor Managed Protection Plus Networking DDos Protection with Cloud Armor's AI adaptive protection
Service Directory Networking Managed Service registry
Cloud Logging Operations Fully managed log aggregator
AI Platform Neural Architecture Search (NAS) AI Platform AI Search
AI Platform Training and Prediction AI Platform NAS training
Notebooks AI Platform JupyterLab environment
Apigee API Management API Gateway security and analysis
API Gateway API Management API Gateways
Payment Gateway API Management integration with real-time payment systems like UPI
Issuer Switch API Management user transactor deployment
Anthos Service Mesh Hybrid/Multi-Cloud devide up gke traffic into workloads and secure them with istio
BigQuery Omni Analysis Use BigQuery to query other clouds
BigQuery Data Transfer Service Analysis Migrate data to BigQuery
Database Migration Service Storage fully-managed migration service
Migrate to Virtual MachManaged Service for Microsoft Active Directory (AD) ines Migration migrate workloads at scale into Google Cloud Compute Engine
Cloud Data Loss Prevention Security and Identity discover, classify, and protect your most sensitive data
Cloud HSM Security and Identity Fully managed hardware security module
Managed Service for Microsoft Active Directory (AD) Identity & Access Managed Service for Microsoft Active Directory
Cloud Run Serverless Computing Run serverless containers
Cloud Scheduler Serverless Computing cron job scheduler
Cloud Tasks Serverless Computing distributed task orchestration
Eventarc Serverless Computing Event rules between gcp services
Workflows Serverless Computing reliably execute sequences of operations across APIs or services
IoT Core Internet of Things Collect, process, analyze and visualize data from Iot devices in real time
Cloud Healthcare Healthcare and Life Sciences send, receive, store, query, transform, and analyze healthcare and life sciences data
Game Servers Media and Gaming deploy and manage dedicated game servers across multiple Agones clusters

Christopher GodwinAbout 2 minGoogle CloudTechnologystudy guideGoogle cloudgcpGCCPCA