GCP - Compute migrate
Compute migrate
modern Hybrid on Multi-Cloud Computing
Traditional: on-premises distributed systems architecture
how business is traditionally made the enterprise computing needs before cloud computing.
- most enterprise scale applications are designed as distributed systems.
- Spreading the computing workload required to provide services over two or more network servers.
- containers can break these workloads down into microservices,
- more easily maintained and expanded.
- on-premises systems
- Enterprise systems and workloads, containerized or not, have been housed on-premises,
- a set of high-capacity servers running in the company’s network or data center.
- When an application’s computing needs begin to outstrip its available computing resources
- need to procure more powerful servers.
- Install them on the company network after any necessary network changes or expansions.
- Configure the new servers
- and finally load the application and it’s dependencies onto the new servers before resource bottlenecks could be resolved.
- shortcut
- The time required to complete an on-premises upgrade could be from months to years.
- also costly, the useful lifespan of the average server is only three to five years.
what if you need more computing power now, not months from now?
What if the company wants to begin to relocate some workloads away from on-premises to the Cloud to take advantage of lower cost and higher availability, but is unwilling or unable to move the enterprise application from the on-premises network?
What if you want to use specialized products and services that only available in the Cloud?
This is where a modern hybrid or multi-cloud architecture can help.
Modern: hybrid on multi-cloud architecture
- creating an environment uniquely suited to the company’s needs.
- keep parts of the systems infrastructure on-premises
- Move only specific workloads to the Cloud at the own pace
- because a full scale migration is not required for it to work.
- benefits:
- Take advantage of the cloud services for running the workloads you decide to migrate.
- flexibility, scalability, and lower computing costs
- Add specialized services to the computing resources tool kit.
- such as machine learning, content caching, data analysis, long-term storage, and IoT
- Take advantage of the cloud services for running the workloads you decide to migrate.
- the adoption of hybrid architecture for powering distributed systems and services.
Migration
Migrate for VM
Migrate for Compute Engine
Anthos (Migrate for Container / from VM to Container)
- modern solution for hybrid and multi-cloud distributed systems and service management
- powered by the latest innovations in distributed systems, and service management software from Google.
- On-permises and Cloud environments stay in sync
- The Anthos framework rests on Kubernetes and GKE on-prem.
- provides
- the foundation for an architecture
- the foundation that is fully integrated with centralized management through a central control plane that supports policy based application lifecycle delivery across hybrid and multi-cloud environments
- a rich set of tools
- Manage sevices on-permises and in the cloud
- monitor systems and services
- for monitoring and maintaining the consistency of the applications across all network (on-premises, Cloud, multiple clouds)
- migrate application from VMs into the clusters
- maintain consistent policies across across all network (on-premises, Cloud, multiple clouds)
- the foundation for an architecture
build modern hybrid infrastructure stack
- Google Kubernetes Engine on the Cloud site
of the hybrid network.
- a managed production-ready environment for deploying containerized applications
- Operates seamlessly with high availability and an SLA.
- Runs certified Kubernetes ensuring portability across clouds and on-premises.
- Includes auto-node repair, and auto-upgrade, and auto-scaling.
- Uses regional clusters for high availability with multiple masters.
- Node storage replication across multiple zones.
- Google Kubernetes Engine deployed ON-PREM
- a turn-key production-grade conformed version of Kubernetes
- with the best practice configuration already pre-loaded.
- Provides
- easy upgrade path to the latest validated Kubernetes releases
by Google.
- Provides access to container services
on Google Cloud platform,
- such as Cloud build, container registry, audit logging, and more.
- integrates with Istio, Knative and Marketplace Solutions
- easy upgrade path to the latest validated Kubernetes releases
- Ensures a consistent Kubernetes version and experience across Cloud and on-premises environments.
- Marketplace
- both Google Kubernetes Engine in the Cloud and Google Kubernetes Engine deployed on-premises integrate with Marketplace
- so all of the clusters in network (on-premises or in the Cloud), have access to the same repository of containerized applications.
- benefits:
- use the same configurations on both the sides of the network,
- reducing the time spent developing applications.
- use ones replicate anywhere
- maintaining conformity between the clusters.
Enterprise applications may use hundreds of microservices to handle computing workloads. Keeping track of all of these services and monitoring their health can quickly become a challenge.
- Anthos
- an Istio Open Source service mesh
- take these guesswork out of managing and securing the microservices.
- Cloud interconnect
- These service mesh layers communicate across the hybrid network by Cloud interconnect
- to sync and pass their data.
- Stackdriver
- the built-in logging and monitoring solution for Google Cloud.
- offers a fully managed logging, metrics collection, monitoring dashboarding, and alerting solution that watches all sides of the hybrid on multi-cloud network.
- the ideal solution for single easy configure powerful cloud-based observability solution
- a single pane of class dashboard to monitor all of the environments.
- the built-in logging and monitoring solution for Google Cloud.
- Anthos Configuration Management
- provides
- a single source of truth for the clusters configuration.
- source of truth is kept in the policy repository, a git repository.
- this repository can be located on-premises or in the Cloud.
- deploy code changes with a single repository commit.
- implement configuration inheritance, by using namespaces.
- a single source of truth for the clusters configuration.
- provides
- Anthos Configuration Management agents
- use the policy repository to enforce configurations locally in each environment,
- managing the complexity of owning clusters across environments.
Transfer Appliance (Migrate for big data)
Migrate for IAM
Deployment methods
Blue green deployments
- 2 environments, arbitrarily called blue, and green
- toggle between the two of them.
- Imagine
- green environment is currently serving traffic,
- use the blue environment to test out the latest version,
- and once you’re happy with the results, just switch the traffic over to blue,
- and you just repeat this process.
Rolling deployments
- Rolling deployments progressively replace a resource with another version until everything has been updated.
- Imagine
- have five resources all on version 100, and you wanna roll out version 101, without impacting users,
- so you update the resources one at a time, making sure there are no failures until everything is up to date.
canary deployments
- Canary deployments get their name from a mining practice, which involved bringing canaries into coalmines, because their death was an indicator of lethal gases.
- The process is similar in software though, without the potential ethical debates.
- Imagine
- A new version is introduced into the current group of resources and it’s monitored.
- If there are problems, then only a small portion of the total user base are going to experience those problems.
- Once everything’s working as it should, that version can be fully deployed.
Traffic splitting deployments
- Traffic splitting diverts traffic to a different version of a resource
- use cases for this.
- the classic A/B testing use case.
- You have two versions that you want to see how users respond to,
- and so you split the traffic between those two versions,
- you monitor for whatever it is you’re looking to see,
- once you know which one is more successful, that is the one that you can actually deploy.
- the classic A/B testing use case.
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