Why I Became a Google Cloud Certified Fellow in Hybrid Multi-Cloud
Robin Percy, CTO of OpsGuru, is now a Google Cloud Certified Fellow in Hybrid Multi-Cloud. He shares why Hybrid Multi-Cloud is so critical to your Cloud Adoption journey. ...
At OpsGuru, we support a diverse set of workloads across different cloud providers. While it may seem eclectic, our driver is cloud-native adoption. However, given the definition of cloud-native seems to be evolving, sometimes it is worthwhile to revisit: What exactly do we mean by “cloud-native”?
From the Charter of Cloud Native Computing Foundation “CNCF”:
“Cloud-native technologies empower organizations to build and run scalable applications in modern, dynamic environments such as public, private, and hybrid clouds. Containers, service meshes, microservices, immutable infrastructure, and declarative APIs exemplify this approach. These techniques enable loosely coupled systems that are resilient, manageable, and observable. Combined with robust automation, they allow engineers to make high-impact changes frequently and predictably with minimal toil.”
The OpsGuru follows this definition too. Cloud-native doesn't mean only public cloud, but design and implementations that give you flexibility such that you can run workloads wherever it makes sense.
But how do we implement that? Here are some highlights:
Lightweight and portable, containers are the preferred mechanism for modern application deployment because it is fast, predictable and easy to scale. It is cost-effective because of higher server density and better resource utilization. The speed and scalability of containers, however, require a more sophisticated scheduling/orchestration mechanism - that’s why we heavily recommend Kubernetes, whose rich features and extensive support across all vendors mean that it can be used to manage workloads on all major clouds and on-premise.
As data workloads get more sophisticated, it is impossible to find one single technology that will service all workloads. For a complex workload, relational databases, key-value data stores, document data storage, data lake/warehouse/lakehouse and many more all have their roles to play. The goal is to avoid single points of failure, ensuring predictable performance by preventing noisy neighbours, and abstracting service interfaces such that users can enjoy the reliable data access without needing to know about the underlying storage complexity.
Infrastructure as code is often precursors to infrastructure automation. However, more importantly, it enforces engineering discipline by enabling code reviews and methodical testing on infrastructure provisioning. At OpsGuru we are strong advocates of Terraform because it is easy to learn, widely supported and powerful as it covers many vendors and platforms.
The infrastructure may scale quickly, but if the application cannot be delivered with the same velocity, the value of fast infrastructure provisioning is severely diminished. At OpsGuru we implement CI/CD for both application and infrastructure, such that the full-stack - infrastructure resources and applications - can be automatically provisioned and scale in and out according to the evolving demand.
Every solution needs to identify and track key performance metrics, collect application logs and provide tracing capabilities to maintain system health. Being able to keep the system running is only half of the solution though; at OpsGuru, we believe in data-driven enhancement. By leveraging the operational data collected, we help clients identify performance bottlenecks, security loopholes and engineer solutions to improve the overall health of systems.
As cloud-native becomes more popular, the definition keeps evolving. However, agility, operability, resiliency and scalability are some timeless goals that all solutions should adhere to. The values of the cloud are only achievable when the tech stack can grow with the features offered by the cloud. To that end, OpsGuru aims to help our clients to get the value of their adoption and investment into the cloud.