Optimize cloud costs while delivering flawless digital experiences

October 17 2023

Learn how new modern application optimization modules built on the Cisco Observability Platform can help you solve cloud cost and resource optimization challenges for your Kubernetes workloads.

Controlling unpredictable cloud cost and resource utilization has become critical for organizations to ensure the profitability of modern workloads. Understanding and optimizing cloud spend continues to be the top initiative, but legacy reporting tools can’t predict dynamic utilization or provide the correlated context that FinOps, CloudOps and App teams require to solve ongoing cloud budget challenges.

Cisco is enhancing modern application monitoring practices by enabling organizations to address cloud cost and workload optimization use cases with the Kubernetes Cost and Workload Profiler, Cost Insights and Application Resource Optimizer modules. Built on the Cisco Observability Platform, they capture cloud cost, correlate utilization and efficiency data and business functions, and leverage AI/ML algorithms to deliver detailed cost analysis and optimization recommendations. Technology teams gain real-time visibility into cloud usage, insights to make data-driven decisions and optimization recommendations to reduce cloud spend while ensuring the performance and reliability of business-critical applications.

Quickly identify workloads that are at risk of jeopardizing customer digital experiences

The Kubernetes Cost and Workload Profiler module is a free enhancement for Cisco Cloud Observability that delivers the initial capabilities required to integrate application optimization within established modern application monitoring practices. Powered by an AI/ML engine, it continuously analyzes and dynamically baselines the average spend and resource efficiency of Kubernetes workloads to identify and flag excessive cost availability risks in real time.  Technology teams can use the visibility of the Kubernetes Cost and Workload Profiler to scale up resources proactively or to assist with troubleshooting when determining if workload resources are the cause of performance problems.

Fig. 1 shows the Kubernetes Cost and Workload Profiler identifying excessive cost, and workload risk due to under-provisioning.

Easily understand the full fiscal impact of current workloads and make data-driven decisions on future technology investments

The Cost Insights module seamlessly integrates detailed cost data of Kubernetes workloads into established modern application monitoring practices using Cisco Cloud Observability to enable organizations to gain deeper visibility and understanding of their cloud spend. It generates detailed cost data for the workloads running on cloud and cloud native infrastructures by continually analyzing a combination of cloud infrastructure utilization, application performance metrics and user trends. Technology teams and business leaders gain meaningful insights that include the costs of infrastructure, containers and pods, and even uplevel them to workload, namespaces, clusters and teams to see how a workload is using allocated resources and, more importantly, wasted resources and the financial impact of idle resources. These shared insights enable technology teams and business leaders to work together to reduce wasted spend, hold teams accountable for cloud budgets and make data-driven decisions for future workloads and cloud investments.

Fig. 2 shows a detailed cost analysis of Kubernetes workloads from the Cost Insights module.

Reduce excess cloud costs and optimize performance and reliability for best-in-class user experiences

The Application Resource Optimizer module uses machine learning algorithms with active learning models to provide recommendations that improve application performance and reduce infrastructure costs by eliminating waste. Technology teams can quickly optimize cloud spend and application performance without the guesswork and time required in manual resource tuning. Based on user-defined application performance objectives, it analyzes cloud infrastructure performance, health and metrics against variables beyond human ability and scale to make recommendations that maximize workload performance and mitigate potential service disruptions. The enhanced capability of the Application Resource Optimizer enables Cisco Cloud Observability users to swiftly and confidently take action to reduce workload costs and ensure digital experiences that drive business outcomes.

Fig. 3 shows the Application Resource Optimizer module analyzing cloud resource utilization to make optimization recommendations.

Optimize your applications like never before

The Kubernetes Cost and Workload Profiler, Cost Insights and Application Resource Optimizer modules are available through the Cisco Observability Platform Exchange. Cisco Cloud Observability users can access the Cisco Observability Platform Exchange directly within the tool for quick access to a diverse ecosystem of modular solutions that extend its capabilities.

Fig. 4 shows the modules for Cisco Cloud Observability within the Cisco Observability Platform Exchange.

Only Cisco has the breadth of coverage to meet customers wherever they are on their path to full-stack observability — whether it be for on-prem, hybrid or cloud environments for both traditional and cloud native workloads — and the scale, flexibility and extensibility to cover any custom and future use cases related to business needs.

Learn more: 

To learn more about how the new cloud cost and optimization modules can deliver the visibility and insights your business needs to optimize workload resources and reduce cloud costs, register for the Application cost & resource optimization using the Cisco Observability Platform webinar and check out the following links for additional information:

Application Optimization Module
Cisco Observability Platform

Bhuvnesh Kumar is a Product Manager at Cisco AppDynamics and has been working on various components of the Full-Stack Observability Platform. His current focus is leading the Cost Management and Resource Optimization charter. Prior to Product Management, Bhuvnesh was an engineer on the Extensions team at Cisco AppDynamics. Bhuvnesh has a deep interest in the observability industry, OpenTelemetry™, and open standards.

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