How to Automate Deployment Analysis and Release Verification for Argo
Both Argo CD and Argo Rollouts provide a robust set of capabilities to implement contemporary software delivery practices. However, delivering safe, secure apps into production without risk requires intelligent automation of the software delivery workflow. Continuous learning powered by AI and machine learning can ensure that Argo release workflows improve over time, resulting in continuous improvements in reliability, software quality, and risk reduction.
In this webinar, we will discuss the following:
- Applying machine-learning-based analysis without depending on ad hoc or primitive thresholds-based metrics analysis
- Integrating intelligent automation with the vast data sources of logs and metrics in the DevOps toolchain
- Automating decisions for faster rollback or roll-forward
- Leveraging advanced diagnostics and triage of issues for more immediate remediation
By the end of this webinar, you will understand how to automate deployment analysis and release verification, reduce the operational complexity of managing multiple Argo instances, and provide a fast and secure way to scale Argo and Kubernetes in the enterprise.
Gopinath Rebala, CTO of OpsMx
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures of OpsMx Enterprise for Spinnaker.
Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well known leader in continuous delivery and in the Spinnaker community.
Mark Levy, Sr. Director of Product Marketing, OpsMx
Mark loves to learn, practice, discuss agile, devops, devops culture, lean, software delivery, and continuous delivery. Mark has over 30+ years of experience in enterprise software focusing on application development, software delivery, and IT operations. Outside of work, Mark enjoys crossfit, martial arts, and playing his guitar.