Turbonomic Updates its AI-Powered App Resource Management for Kubernetes, CI/CD

Turbonomic has updated its AI-powered ARM platform and AIOps decision engine to improve the agility and elasticity of CI/CD pipelines and bring deeper support to Kubernetes It’s the latest update to ensure optimal performance of cloud apps.

Tags: AIOps, ARM, CI/CD, cloud, Kubernetes, Turbonomic,

Turbonomic is offering an update to its AI-powered Application Resource Management platform and AIOps decision engine to improve the agility and elasticity of CI/CD pipelines and bring deeper support to Kubernetes.  


With the latest updates, Turbonomic platform customers can now accelerate their adoption of cloud apps, and better ensure their optimal operations, according to Turbonomic CTO Charles Crouchman.


In general, when working on cloud-native apps, microservice architectures and the CI/CD pipeline can enable higher speed and agility. That said, ensuring continuous application performance often proves complex due to Kubernetes, which creates more components to manage and more frequent deployments, he noted.


“Achieving cloud economics requires simplifying the operation of cloud-native applications through a top-down, application-driven approach. . . Turbonomic Application Resource Management delivers customers with unified, simplified, and elastic operations to enable the delivery of true cloud economics,” Crouchman said. 


Among top challenges cited by developers and IT operations include application rehosting, re-platforming, and rewriting on hybrid and multi-cloud deployments, as well as increased use of PaaS and CaaS, he added. 


To address these growing Kubernetes-related issues, Turbonomic updated its platform to improve insights into these opaque resources and improve the agility and elasticity of CI/CD pipelines via AI and AI Ops. 



In specific, the latest Turbonomic’s update includes: 

Continuous Service Optimization in Kubernetes: This scale cloud-native applications, containers, pods, and nodes based on real-time resource needs. Also, actions can be executed in real-time, or as part of an existing deployment process.


Rapid and Accurate Container Planning: This enables users to rapidly expand Kubernetes platforms through simulation of the required capacity to onboard new services and accurately understand available headroom.

The latest features build on Turbonomic’s full-stack of visibility and control services. The company's platform lets customers better understand and manage relationships between apps and various cloud resources they need to perform, including in PaaS, CaaS and IaaS.


In detail, Turbonomic’s core platform offers: 

AI-Driven Automation to make application resource decisions automatically.

Deep Visibility to understand application dependencies at every layer of the stack and match application resource demands to the underlying available supply.


Assured Performance by managing the complete application stack and automatically take specific actions to ensure apps are getting the resources required to perform.

Turbonomic integrates with many popular platforms, including AWS, Microsoft Azure, IBM Cloud, OpenShift and AppDynamics.


Turbonomic’s partnership with AppDynamics, announced earlier this summer, illustrates the company’s focus on AI, and automation to deliver AIOps benefits. 


In a blog post describing the partnership, Turbonomics’ Chris Sullivan wrote: 

By using application, user and business insight from AppDynamics, Turbonomic makes decisions and automatically implements actions to:


Continuously assure application performance and eliminate application performance risk due to infrastructure.


Close the loop between application performance and application resourcing by showing the direct impact automated resource actions have on business application response time and service level objectives.


Bridge the application and infrastructure team gap with full-stack control that elevates teams & provides a common understanding of application dependencies.


Accelerate & de-risk application migration to cloud with a holistic understanding of application topology, resource utilization, and the data center stack.

An analyst from IDC noted the on-going trend to add more AI and AIOps capabilities for app management solutions, especially as apps move to hybrid, cloud-native and multi-cloud models. 


“Container-enabled microservices, CI/CD toolchains and highly dynamic multi-cloud architectures are causing disruption, creating demand for new types of management approaches that leverage intelligent analytics and automation,” said Mary Johnston.


Turner, IDC research vice president of cloud management. In citing the increased demand, she was referring to findings from the recently-released IDC Enterprise Plans for Container Management Survey.


Turbonomic is available in three editions, providing additional capabilities to meet your specific requirements and use cases. Each edition can be run on-premises, in a public cloud or across a hybrid environment.