Indonesia – 28 October 2026

• Understanding architectural shifts needed for next-generation applications
• Adopting cloud-native DevOps practices (microservices, containerization, serverless)
• Identifying cloud-native capabilities teams must build by 2026

• From copilots to agents: AI across the full software delivery lifecycle.
• Context is everything: code, issues, pipelines, security, and policies working together.
• Speed with guardrails: automate more without sacrificing security, compliance, or human control.

Hardy Chou, Senior Solutions Architect, GitLab

• Using machine learning to monitor, predict anomalies, automate incident responses
• Understanding practical AIOps tools and use cases relevant to Indonesia’s industries

Raditya Gumay, Distinguished Engineer, GoTo Group

• AI, Cloud and Digital Infrastructure
• Addressing infrastructure gaps and talent constraints

Moderator:

Edy Salim, Chief Technology Officer, Akulaku Finance Indonesia

• Creating workflows where automation accelerates both delivery and security
• Integrating security tools without disrupting developer experience
• Using AI to enhance code quality, detect vulnerabilities, and streamline compliance
• Real-world examples of teams shifting to a security-first culture

Khang Toh, Head of Engineering: Digital Operations, SRE and Cloud Infrastructure, DKatalis / Bank Jago

• Understanding how platform engineering complements DevOps, SRE, and security teams
• Creating platform teams that build internal self-service developer platforms
• Reducing friction and allowing developers to ship faster while ensuring guardrails

Cayadi Sutanto, Head of Product Engineering, SawitPRO

Simplifying and Automating Kubernetes cluster management by integrating Model Context Protocol (MCP) with platforms like Azure Kubernetes Service (AKS). MCP acts as a bridge between AI assistants (e.g., GitHub Copilot, Cursor) and Kubernetes clusters, enabling natural language interactions for operational tasks.

Siva Yakkanti, Senior Member of Technical Staff, AMD

• What does an effective cross-functional DevOps product team actually look like in practice – and how do you structure responsibilities across development, operations, QA, and security?
• How do you choose between the different AI and DevOps tools amongst the many that are out there?
• If you had to invest in one capability today to future-proof your DevOps organization for the next few years, what would it be — and why?