Today Turbonomic announces its support for Kubernetes-as-a-Service offerings from Amazon, Azure, Google, and Pivotal. Now workloads in your KaaS deployments can self-manage—continuously navigating the tradeoffs between performance, compliance and cost. More specifically, the actions that can be automated in these Kubernetes distributions:
- Ensure optimal container redistribution through automated pod rescheduling. When rescheduling pods, Turbonomic also considers container platform compliance policies, including node labels, affinity and anti-affinity;
- Optimize container-resource reservation, requests, and limits in KaaS deployments, ensuring containers have the exact resources needed to perform, while eliminating over-provisioning so that customers never overspend in the cloud
- Intelligently scale Kubernetes clusters in and out based on real-time demand, assuring application performance while minimizing cost, which allows customers to fully realize the Kubernetes promise of elasticity.
These capabilities are an extension of what Turbonomic has been doing since its founding in 2009: software makes the right resource decisions at the right time—not people. We’re thrilled to be working with several key customers as part of our Early Access program as they advance their container use cases and modernize their infrastructure for cloud native architectures.
GA support for EKS, AKS, GKE and PKS will be available this Fall. For more information, watch the on-demand webinar, Self-Managing KaaS: Workload Automation for EKS, AKS, GKE, and PKS. Here’s a little preview:
Why Does It Matter
Kubernetes has become the infrastructure standard for today’s modern applications (dynamic, distributed, and microservice) and organizations are eager to adopt the platform. It offers portability (run anywhere) and elasticity (quickly spin up resources up when you need them, back when you don’t). Ultimately this is a story about speed—how quickly can ideas become real products or services that differentiate a business?
Enter Kubernetes-as-a-Service. With KaaS you can build and deploy your Kubernetes clusters more quickly. It installs and configures the Kubernetes platform for you. It provides the scripts that make it easier to configure and create infrastructure—virtual machines or cloud instances, storage, network (VPN, subnet, access/security, etc.). It makes it easier to interact with the platform through a high-level dashboard or portal. It makes upgrading and security patching easier. So now that you have your Kubernetes infrastructure fully locked and loaded, you’re all set, right? Not so fast.
While Kubernetes is the modern infrastructure standard, even with Kubernetes-as-a-Service it’s still on you to manage performance, compliance and cost. Or, given that it’s 2018 and you’re reading this Turbonomic blog, let software do it for you. Enter workload automation. Because, while this is a story about developer speed, it’s the “choose your own adventure” kind. You, the protagonist, will get your Kubernetes clusters up and running much more quickly thanks to EKS, AKS, GKE, or PKS. But, will you do so with workloads that self-manage, anywhere, in real time? (The perfect sidekick, no?) Or, will you stick with traditional approaches that rely on you to make resource decisions 24/7?
Here are some of the plot twists you can avoid with SMART workloads:
- You overprovisioned nodes and clusters to avoid risks to performance, but quickly realized that gets expensive at scale—it really hurt the IT wallet and your reputation because you’re in the cloud and paying by the minute.
- You spent most of your story configuring containers and nodes, defining your autoscaling policies and setting thresholds to manage your clusters. It was time consuming… now do it again at scale.
- Somewhere along the line, because you’re human—and would really prefer to be doing other things by this point—you make a mistake. That one container misconfiguration cost you some absurd amount of money in the cloud. Or, maybe that CPU-based autoscaling policy didn’t capture the fact that your application really needed more Memory… and never got it. Oops.
This story has all the wrong kinds of drama.
What Would Your Story Be with Self-Managing KaaS?
What would your story be if your Kubernetes-as-a-Service of choice was self-managing and you and your team were focused on more impactful work? Maybe you’d improve internal processes or launch new ones. Maybe you’d be having a conversation with the Developer team about the machine learning services they want to leverage from Google Cloud and how that’s going to talk with the 10-years of data you’ve got on-prem, soon to be in Azure. Maybe you ride off into the sunset with DevOps….
If you’re a Turbonomic customer and would like to participate in our Early Access program, contact: email@example.com. We look forward to working with you!