What are the optimal use cases that I can recommend to the client for OpenShift observability?

[tijust1]

Hi,

My client is interested in implementing the best use cases for OpenShift Observability to benefit their DevSecOps team and overall business.

As I am not a DevOps expert, I am unable to determine the optimal use cases or features that should be configured in Dynatrace. If anyone has successfully implemented effective use cases in Dynatrace for OpenShift, please share your insights

Thanks,

Tijust

[radek_jasinski · Accepted solution]

Hi,

Consider automated full stack monitoring to gain insight into all aspects of your OpenShift environment to ensure proactive detection and resolution of issues, reducing downtime and improving application performance. Dynatrace's advanced AIOps capabilities automatically detect and diagnose issues, anomalies and performance bottlenecks, accelerating troubleshooting and allowing the DevSecOps team to focus on more strategic tasks. Real-time application performance monitoring provides an understanding of user experience and application dependencies, leading to optimised application performance and user experience, increasing user satisfaction. Monitoring container health and performance is key to effective container orchestration and management, optimising resource utilisation and ensuring smooth operation of containerised applications. Integrating observability into the DevSecOps pipeline enables continuous monitoring throughout the development lifecycle, enabling early detection of security and performance issues, reducing the risks and costs associated with post-deployment patches. Customised dashboards and reporting in Dynatrace enable specific views to be created for different stakeholders, highlighting key metrics and conclusions to help make informed decisions and provide clear visibility of system health and performance. Monitoring microservices and cloud native applications allows you to understand their interactions and dependencies, ensuring the reliability and scalability of modern applications, which is crucial in a dynamic cloud environment. Automated root cause analysis quickly identifies the source of problems, which minimises mean time to resolution (MTTR), increasing overall system reliability.

Here you have more info:

https://www.dynatrace.com/news/blog/devsecops-automation-improves-application-security/

https://www.dynatrace.com/news/blog/what-is-devsecops/

https://www.dynatrace.com/news/blog/how-devops-monitoring-tools-drive-efficiency/

[tijust1]

@radek_jasinskiThank you for your message. I will review these links to better understand the recommended features, especially as they seem particularly interesting to me "Integrating observability into the DevSecOps pipeline enables continuous monitoring throughout the development lifecycle".

Thanks,

Tijust