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Week of October 23rd

Mark Shay

Part III of a Cloud☁️ Journey

“I’m learning to fly ✈️, around the clouds ☁️”

Hi All –

Happy National Mole Day! 👨‍🔬👩🏾‍🔬

“Open your eyes 👀, look up to the skies🌤 and see 👓”

As we have all learned, Cloud computing ☁️ empowers us all to focus our time 🕰 on dreaming 😴 up and creating the next great scalable ⚖️ applications. In addition, Cloud computing☁️ enables us less worry😨 time 🕰 about infrastructure, managing and maintaining deployment environments or agonizing😰 over security🔒. Google evangelizes these principals stronger💪 than any other company in the world 🌎.

Google’s strategy for cloud computing☁️ is differentiated by providing open source runtime systems and a high-quality developer experience where organizations could easily move workloads from one cloud☁️ provider to another.

Once again, this past week we continued our exploration with GCP by finishing the last two courses as part of Google Cloud Certified Associate Cloud Engineer Path on Pluralsight. Our ultimate goal was to have a better understanding of the various GCP services and features and be able to apply this knowledge, to better analyze requirements and evaluate numerous options available in GCP. Fortunately, we gained this knowledge and a whole lot more! 😊

Guiding us through another great introduction on Elastic Google Cloud Infrastructure: Scaling and Automation were well-known friends Phillip Maier and Mylene Biddle. Then taking us through the rest of the way through this amazing course was the always passionate Priyanka Vergadia.

Then finally taking us down the home stretch 🏇 with Architecting with Google Kubernetes Engine – Foundations (which was last of this amazing series of Google Goodness 😊) were famous Googlers Evan Jones and Brice Rice.  …And Just to put the finishing touches 👐 on this magical 🎩💫 mystery tour was Eoin Carrol who gave us in depth look at Google’s game changer in Modernizing existing applications and building cloud-native☁️ apps anywhere with Anthos.

After a familiar introduction by Philip and Mylene we began delving into the comprehensive and flexible 🧘‍♀️ infrastructure and platform services provided by GCP.

“Across the clouds☁️ I see my shadow fly✈️… Out of the corner of my watering💦 eye👁”

Interconnecting Networks – There are 5 ways of connecting your infrastructure to GCP:

  1. Cloud VPN
  2. Dedicated interconnect
  3. Partner interconnect
  4. Direct peering
  5. Carrier peering

Cloud VPN – securely connects your on-premises network to your GCP VPC network. In order to connect to your on-premise network via Cloud VPN configure cloud VPN, VPN Gateway, and to repeat in tunnels.

Please note: The maximum transmission unit or MTU for your on-premises VPN gateway cannot be greater than 1460 bytes.

$gcloud compute --project "qwiklabs-GCP -02-9474b560327d" target-vpn-gateways create "vpn-1" --region "us-central1" --network "vpn-network-1"

$gcloud compute --project "qwiklabs-GCP -02-9474b560327d" target-vpn-gateways create "vpn-1" --region "us-central1" --network "vpn-network-1"
$gcloud compute --project "qwiklabs-GCP -02-9474b560327d" forwarding-rules create "vpn-1-rule-esp" --region "us-central1" --address "35.192.18.39" --IP -protocol "ESP" --target-vpn-gateway "vpn-1"

$gcloud compute --project "qwiklabs-GCP -02-9474b560327d" forwarding-rules create "vpn-1-rule-udp500" --region "us-central1" --address "35.192.18.39" --IP -protocol "UDP" --ports "500" --target-vpn-gateway "vpn-1"

$gcloud compute --project "qwiklabs-GCP -02-9474b560327d" forwarding-rules create "vpn-1-rule-udp4500" --region "us-central1" --address "35.192.18.39" --IP -protocol "UDP" --ports "4500" --target-vpn-gateway "vpn-1"

$gcloud compute --project "qwiklabs-GCP -02-9474b560327d" vpn-tunnels create "tunnel1to2" --region "us-central1" --ike-version "2" --target-vpn-gateway "vpn-1"

$gcloud compute --project "qwiklabs-GCP -02-9474b560327d" vpn-tunnels create "vpn-1-tunnel-2" --region "us-central1" --peer-address "34.78.144.99" --shared-secret "GCP  rocks" --ike-version "2" --local-traffic-selector "0.0.0.0/0" --target-vpn-gateway "vpn-1"

Cloud Interconnect and Peering

Dedicated connections provide a direct connection to Google’s network while shared connections provide a connection to Google’s network through a partner

Comparison of Interconnect Options

Peering

Direct Peering provides a direct connection between your business network and Google.

Carrier Peering provides connectivity through a supported partner

Choosing the right connection – Decision Tree 🌳

Shared VPC and VPC Peering

Shared VPC allows an organization to connect Resource is from multiple projects to a common VPC network.

VPC Peering is a decentralized or distributed approach to multi project networking because each VPC network may remain under the control of separate administrator groups and maintains its own global firewall and routing tables.

Load Balancing 🏋️‍♂️ and Autoscaling

Cloud Load Balancing 🏋️‍♂️ – distributes user traffic 🚦across multiple instances of your applications. By spreading the load, load balancing 🏋️‍♂️ reduces the risk that your applications experience performance issues. There are 2 basic categories of Load balancers:  Global load balancing 🏋️‍♂️ and Regional load balancing 🏋️‍♂️.

Global load balancers – when workloads are distributed across the world 🌎 Global load balancers route traffic🚦 to a backend service in the region closest to the user, to reduce latency.

They are software defined distributed systems using Google Front End (GFE) reside in Google’s PoPs are distributed globally

Types of Global Load Balancers

Regional load balancers – when all workloads are in the same region

Internal load balancers are software defined distributed systems (using Andromeda) and network load balancers which use  Maglev distributed system.

Types of Global Load Balancers

Managed instance groups – is a collection off identical virtual machine instances that you control as a single entity. (Same as creating a VM but applying specific rules to an Instance group)

Regional managed instance groups are usually recommended over zonal managed instance groups because this allow you to spread the application’s load across multiple zones through replication and protect against zonal failures.

         Steps to create a Managed Instance Group:

  1. Need to decide the location and whether instance group will be Single or multi-zones
  2. Choose ports that are going allow load balancing🏋️‍♂️ across.
  3. Select Instance template
  4. Decide Autoscaling ⚖️ and criteria for use
  5. Creatine a health ⛑ check to determine instance health and how traffic🚦should route

Autoscaling and health checks

Managed instance groups offer autoscaling ⚖️ capabilities

HTTP/HTTPs load balancing

Backend Services

SSL certificates

SSL proxy load balancing – global 🌎 load balancing service for encrypted non-http traffic.

TCP proxy load balancing – a global load balancing service for unencrypted non http traffic.

Network load balancing – is a regional non-proxy load balancing service.

Internal load balancing – is a regional private load balancing service for TCP and UDP based traffic🚦

“..clouds☁️ roll by reeling is what they say … or is it just my way?”

Infrastructure Automation – Infrastructure as code (IaC)

Automate repeatable tasks like provisioning, configuration, and deployments for one machine or millions.

Deployment Manager -is an infrastructure deployment service that automates the creation and management of GCP. By defining templates, you only have to specify the resources once and then you can reuse them whenever you want.

Deployment manager creates all the resources in parallel.

Additional infrastructure as code tools🛠 for GCP

It’s recommended that you provisioned and managed resource is on GCP with the tools🛠 you are already familiar with

GCP Marketplace 🛒 – lets you quickly deploy functional software packages that run 🏃‍♂️ on GCP.

“… Must be the clouds☁️☁️ in my eyes 👀”

Managed Services – automates common activities, such as change requests, monitoring 🎛, patch management, security🔒, and backup services, and provides full lifecycle 🔄 services to provision, run🏃‍♂️, and support your infrastructure.

BigQuery is GCP serverless, highly scalable⚖️, and cost-effective cloud Data warehouse

Cloud Dataflow🚰 executes a wide variety of data processing patterns

Cloud Dataprep – visually explore, clean, and prepare data for analysis and machine learning

Cloud Dataproc – is a service for running Apache Spark 💥 and Apache Hadoop 🐘 clusters

“Captain Jack will get you by tonight 🌃… Just a little push, and you’ll be smilin’😊 “

Architecting with Google Kubernetes Engine – Foundations

After Steller🌟 job by was Priyanka taking us through the load balancing 🏋️‍♂️ options, infrastructure as code and some of the managed service options in GCP it was time to take the helm⛵️ and get our K8s ☸️ hat 🧢 on.

Cloud Computing and Google Cloud

Just to wet our appetite 😋 for Cloud Computing ☁️and Evan takes through 5 fundamental attributes:

  1. On-demand self-services (No🚫 human intervention needed to get resources)
  2. Broad network access (Access from anywhere)
  3. Resource Pooling🏊‍♂️ (Provider shares resources to customers)
  4. Rapid Elasticity 🧘‍♀️ (Get more resources quickly as needed)
  5. Measured 📏Service (Pay only for what you consume)

Next, Evan introduced some of GCP Services under Compute like Compute Engine, Google Kubernetes Engine (GKE), App Engine, Cloud Functions. He then discussed some Google’s managed services with Storage, Big Data, Machine Learning Services.

Resource Management

Network

The network interconnect with the public internet at more than 90 internet exchanges and more than 100 points of presence worldwide🌎 (and growing)

Billing

How to keep billing under control

  1. Budgets and alerts 🔔
  2. Billing export 🧾
  3. Reports 📊
    • Quotas are helpful limits
      • Quotas apply at the level of GCP Project
      • There two types of quotas
        • Rate quotas reset after a specific time 🕰
        • Allocation quotas govern the number of resources in projects

GCP implements quotas which limit unforeseen extra billing charges. Quotas error designed to prevent the over consumption of resources because of an error or a malicious attack 👿.

Interacting with GCP -There are 4 ways to interact with GCP:

  1. Cloud Console

2. SDK

3. Cloud Shell

4. Console mobile App

“Cloud☁️ hands🤲 reaching from a rainbow🌈 tapping at the window, touch your hair”

Introduction to Containers

Next Evan took us through a history of computing. First starting with deploying applications on its physical servers. This solution wasted resources and took a lot of time to deploy maintaining scale. It also wasn’t very portable. It all applications were built for a specific operating system, and sometimes even for specific hardware as well.

Next transitioning to Virtualization. Virtualization made it possible to run multiple virtual servers and operating systems on the same physical computer. A hypervisor is the software layer that removes the dependencies of an operating system with its underlying hardware. It allows several virtual machines to share that same hardware.

Finally, Evan introduced us to containers as they solve a lot of the short comings of Virtualization like:

Containers are isolated user spaces for running application code. Containers are lightweight as they don’t carry a full operating system. They could be scheduled or packed 📦tightly onto the underlying system, which makes them very efficient.

Containerization is the next step in the evolution of managing code.

Benefits of Containers:

Containers and Container Images

An Image is an application and its dependencies

A container is simply a running 🏃‍♂️ instance image.

Docker 🐳 is an open source technology that allows you to create and run 🏃‍♂️ applications and containers, but it doesn’t offer away to orchestrate those applications at scale ⚖️

How to get containers?

Introduction to Kubernetes ☸️

Kubernetes ☸️ is an open source platform that helps you orchestrate and manage your container infrastructure on premises or in the cloud☁️.

It’s a container centric management environment. Google originated it and then donated it to the open source community.

K8s ☸️ automates the deployment, scaling ⚖️, load balancing🏋️‍♂️, logging, monitoring 🎛 and other management features of containerized applications.

K8s ☸️ features:

Kubernetes also supports workload portability across on premises or multiple cloud service providers. This allows Kubernetes to be deployed anywhere. You could move Kubernetes ☸️ workloads freely without vendor lock🔒 in

Google Kubernetes Engine (GKE)

GKE easily deploys, manages and scales⚖️ Kubernetes environments for your containerized applications on GCP.

GKE Features:

Compute Options Detail

 Computer Engine

                  Use Cases

  App Engine

Use Cases

Google Kubernetes Engine

Use Cases

Cloud Run

Use Cases

Cloud Functions

Use Cases

Kubernetes ☸️ Architecture

There are two related concepts in understanding K8s ☸️ works object model and principle of declarative management

Pods – the basic building block of K8s ☸️

Principle of declarative management – Declare some objects to represent those in generic containers.

The Kubernetes ☸️Control Plane ✈️ – continuously monitor the state of the cluster, endlessly comparing reality to what has been declared and remedying the state has needed.

K8s ☸️ Cluster consists of a Master and Nodes

Master is to coordinate the entire cluster.

Nodes runs run pods.

Google Kubernetes ☸️ Engine Concepts

GKE makes administration of K8s ☸️ much simpler

Zonal Cluster – has a single control plane in a single zone.

Regional Cluster – has multiple replicas of the control plane, running in multiple zones within a given region.

Private Cluster – provides the ability to isolate nodes from having inbound and outbound connectivity to the public internet.

Kubernetes ☸️ Object Management – identified by a unique name and a unique identifier.

Pods and Controller Objects

Pods have a life cycle🔄

There are 3 initializer spaces in the cluster.

  1. Default name space for objects with no other name space defined.
  2. Kube-system named Space for objects created by the Kubernetes system itself.
  3. Kube-Public name space for objects that are publicly readable to all users.

Best practice tip: namespace neutral YAML

Advanced K8s ☸️ Objects

Services

Volume

Controller Objects

“Can I get an encore; do you want more?”

Migrate for Anthos – tool🛠 for getting workloads into containerized deployments on GCP

Migrate for Anthos moves VMs to containers

Migrate for Anthos Architecture

Migrate for Anthos Installation -requires a processing cluster

         Installing Migrate for Anthos uses migctl

$migctl setup install

         Adding a source enables migration from a specific environment

$migctl source create cd my-ce-src –project my-project –zone zone

         Creating a migration generates a migration plan

$migctl migration create test-migration –source my-ce-src –vm- id my-id –intent image

         Executing a migration generates resource and artifacts

$migctl migration generate-artifacts my-migration

         Deployment files typically need modification

$migctl migration get-artifacts test-migration

Apply the configuration to deploy the workload

$Kubectl apply -f deployment_sepc.yaml

“And we’ll bask 🌞 in the shadow of yesterday’s triumph🏆… And sail⛵️ on the steel breeze🌬”

Below are some of the destinations I am considering for my travels for next week:

Thanks –

–MCS

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