Migration of the infrastructure to GCP
Several applications and databases were migrated completely to Google Cloud
Hermes Europe GmbH
Enhanced redundancy and high availability
Time to Market
Focus on cloud native services
In A Nutshell:
- SECTOR: LOGISTICS
- Task: In this customer project a major infrastructure migration to Google Cloud Platform was performed.
- Several application teams for databases, specialist applications, Cloud
- Core Infrastructure Team (Central infrastructure & DevOps for various departments)
- Application Development Team (New development of applications for the target infrastructure)
- Migrations Team (Databases, infrastructure, applications)
- Project duration: +12 months
- Several days of downtime with the old cloud provider with high losses, as central services were hosted there
- No Infrastructure as Code, which made recovery much more difficult
- Little to no support from the old cloud provider when restoring the infrastructure
- Limited functionality in the old cloud infrastructure
- Modernization objective: Set up cloud native infrastructure and eliminate legacy systems
- Building the target infrastructure, architecture & new cloud landscape in GCP
- Migration of the individual applications, databases and services to the new target infrastructure
- Introduction of Terraform for versioning and securing the infrastructure
- Landing zone deployment via Terraform to provide application teams with projects and folders
- Multi-level base setup that allows teams to assign their projects, roles and rights almost fully automatically (via Terraform)
- Teams deploy all their infrastructure independently using Terraform and Bitbucket pipelines, centralized provisioning of templates for different infrastructures
- Cost savings through the use of modern infrastructure
- Improved redundancy and high availability functionality in core applications and databases
- Enhanced security through modern authentication methods and network design in the cloud
- Democratization of cloud resources through landing zones: Enabling specialist departments to quickly set up cloud infrastructure while taking security and appropriate cloud policies into account. Autonomous project teams that can create new projects and manage them independently in a very short time (Users, Rights, Services, …)
- Focus on cloud native services: All services run completely in the cloud incl. cloud native customizations (PubSub, Cloud Functions, …)
- Robust infrastructure: Resilient and modularized cloud infrastructure through the use of Infrastructure as Code
- Data protection and encryption
- Time to Market: Market advantage through faster introduction of new features with the help of DevOps processes
Problem of the old IT infrastructure
The decisive point for reconsideration was a breakdown of the previous cloud provider that lasted several days. This was accompanied by high losses for the customer, as essential services for the company were also hosted there. In addition, they were very dissatisfied with the support received from the provider during the recovery phase, so they decided to carry out an extensive migration. Furthermore, the functions and possibilities were limited compared to the Google Cloud, which made it difficult to design elaborate technical solutions. There was also a general desire to move from legacy technologies to cloud-native technologies.
Migration to GCP
The first task was to provide a design for the infrastructure that could accommodate large volumes of requirements while remaining lean and transparent. The autonomy of the teams responsible for the individual services also had to be preserved. This allows teams to deploy their own infrastructure needed to run the applications, using centrally provided templates and modules for Terraform. Deploying Google Kubernetes clusters, scaling Cloud Run instances and Cloud SQL instances was thus not a big problem and was accomplished quickly. Some existing services written in Spring Boot could simply be migrated from the previous provider to Google Cloud. Other services were either refactored or databases were migrated to Cloud SQL.
- Bitbucket Pipelines
- Cloud SQL
- Cloud Run
- Google Kubernetes Engine
- Cloud Scheduler
- Cloud Functions
- VPC (Shared VPC)
- Cloud DNS
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