Decoding Kubernetes: Is Robin the industry’s answer to enterprise demands?
If the last few years have taught us anything, it is that digital transformation is an inevitable reality for all industries, across the globe. Enterprises are running thousands of applications to deliver to growing customer needs. Data centers are continuously evolving to cater to these applications, with yesterday’s siloed, on-premises versions eventually making way to the hybrid cloud models that we see today.
Hybrid cloud models bring together the robustness of on-premises data centers and the agility and elasticity of the public cloud. Thanks to the latest advancements in public cloud infrastructure, we are seeing more enterprises choosing to run their workloads on it. This in turn has led to three dominant technology trends, each bringing along their own set of challenges.
1. The rise of cloud-native
Developers today have embraced the agility of DevOps and CI/CD, leaving behind traditional models where the demarcation between the operations and software development teams used to be clear and the release cycles, longer. Veterans may recall how, previously, development teams were incentivized for the speedy delivery of software and operations teams for the stability of operations. Of course, in the aggressive marketplace of today, this strategy is no longer viable. Today dev and ops teams are co-responsible for successful deployments – the focus being solely on accelerated, high-quality delivery.
Applications too have evolved. What used to be monolithic yesterday are all cloud-native today.
Why the growing preference for cloud-native? There are many reasons. For instance, cloud native as an approach does away with the rigidity of monolithic applications, relying on the fluidity of microservices instead. Each micro-service can be dedicated to a specific business functionality, and they communicate with each other using well-defined APIs. This roughly translates to easier iterations and faster rollouts.
Another fact: Application scaling after deployment is inherent in a cloud-native app. Overallocation of resources is simply out of the question. Cloud-native applications also abstract the underlying OS and infrastructure. Each micro-service can have different development teams working on it in parallel. Within their individual containers, they can be independently deployed, upgraded, scaled, restarted and so on.
2. Kubernetes is hot!
With every passing day, more data is being generated by users and IoT devices. With 5G, this will increase even further, as faster speeds and better connectivity enable high-quality output. The magnitude of this is something we have not seen before.
Big tech companies are already dealing with large-scale data, and they are building their own platforms, storage and automation systems to deal with it. In the future, these tools and technologies will be available to small and medium companies as well. Kubernetes is a very good example of that.
Kubernetes is the de facto container orchestration platform for running cloud-native applications today. It is one of the fastest grown open-source projects. Industry leaders are offering managed Kubernetes services where the applications are run directly on the Kubernetes clusters managed by the cloud provider. Without doubt, Kubernetes is the most viable orchestration option available in the market today, but it poses a few challenges.
For starters, applications come with varying requirements. Let’s take MySQL as an example. The MySQL application needs compute, storage, and network connectivity for clients to connect to it. Let’s look at the storage part. To avoid loss of data due to disk failure, volume replication is essential. Similarly, there should also be provisions in place to withstand rack, node, or data center failures. Essentially, the fault domain ranges anywhere from a disk to a rack, node, or data center. Most of the compute, storage, network specifications can be expressed in a YAML spec file and scheduled using a Kubernetes scheduler. But for distributed or data-heavy applications, like Mongo DB, Apache Cassandra, or Hadoop, you need a different kind of scheduler on top of the Kubernetes scheduler to address all the storage requirements and placement policies.
3. Multi-cloud portability is a reality
Every cloud is unique. Each has its own method of automation, deployment, storage, and performance characteristics. Hence there are obvious challenges in moving databases and data-heavy applications from one cloud to the other. For portability to be a seamless exercise, it should be possible with a single click or API call – even when it comes to moving complex or distributed applications. With enterprises that run thousands of applications, this can be a substantial challenge.
When deciding whether and how to migrate, enterprises need to evaluate things from multiple angles. They need to see if moving to a different cloud poses value in terms of performance impact, security, and market differentiation. For instance, it may make sense for some applications to remain on-premises or on particular clouds due to various factors.
Robin: One platform for multiple challenges
The Robin Cloud Native Platform uses a container-based set-up. It is a pure software solution that works between application and infrastructure layers. It is run on top of any existing Kubernetes cluster, and ships with upstream Kubernetes.
Robin enables enterprises to deploy and manage their complex data- and network-intensive applications with as-a-service experience on any public or private cloud. What is unique about Robin is that it uses an app-centric approach, whether you are provisioning compute, storage, or network. Every I/O that starts from the app is tracked all the way to the drive and carries the application ID with it, so that you can tune all parameters as per that specific app requirement.
To know more about Robin, click here.
The road ahead
The future is exciting. Enterprises are beginning to focus on apps that enable their teams to look beyond the underlying infrastructure and differentiate themselves based on business logic. Public cloud adoption is increasing, and new workloads are now cloud-first, written as cloud-native.
Irrespective of the nature of workloads, there is an overwhelming need for the deployment, monitoring and lifecycle management of operations and services to have a unified interface. Simplifying data protection and management through a single pane of glass has become the need of the hour. That need led to the origins of Robin.io. Inherently cloud-native, Robin’s Kubernetes framework has all the essential features, like auto scheduling, self-healing, auto rollout or rollbacks, load balancer and so on. It can also run anywhere – on-premises, or on clouds supporting both stateful and stateless applications. As enterprises roll out business-critical applications at a rapid pace, Robin answers their need to ensure they are automated, managed and monetized easily.
To know more about Robin, click here.