Expert
Enrolling
👋 Manoj Savukar
Agentic AI for DevOps - Sep Cohort
Design, harden and ship agentic AI for real DevOps: production pipelines, AI incident response and multi-agent architectures. An advanced program with production-grade tracks across ops, platform and security.
📅Class scheduleMon, Tue, Wed, Thu, Fri
Mon, Tue, Wed, Thu, FriMeets
2026-09-01Starts
∞Seats
12Modules
2Projects
₹23,600Incl. GST
What you will learn and build
The full curriculum, module by module, with hands-on project steps along the way.
1
Production-grade CI/CD pipelines
You will learn and practice production-grade CI/CD pipelines.
2
AI incident response
You will learn and practice aI incident response.
3
Hardened, secure AI agents
You will learn and practice hardened, secure AI agents.
4
Multi-agent architecture
You will learn and practice multi-agent architecture.
5
Ops, platform and security tracks
You will learn and practice ops, platform and security tracks.
Project
Design, harden and ship in production
You will learn and practice design, harden and ship in production.
6
Module 1: Agentic Foundations
What makes a system agentic: Autonomy, tool use, memory and planning; LLM capabilities and limits in DevOps contexts; Agent architectures: ReAct, Plan-and-Execute, multi-agent; The DevOps and AI feedback loop, from toil to autonomous ops; Landscape: Copilot, Claude Code, GitHub Models, open-source agents; LangChain and LangGraph
7
Module 2: Connecting Agents to Infrastructure
Wire agents into your stack: Prompt patterns: chain-of-thought, structured output, tool calls; Model selection for latency vs capability in production; Context-window management for logs, runbooks and traces; Function and tool calling: AWS CLI, kubectl, Terraform, PagerDuty; Streaming, async patterns and cost budgeting in agentic loops
8
Module 3: AI Inside Your Pipelines
Agents in CI/CD: AI-assisted code review in PR workflows with GitHub Actions; Automated test generation and coverage-gap analysis; Intelligent build-failure triage and root-cause explanation; Deployment risk scoring and intelligent rollback triggers; Claude Code and Copilot inside CI, benefits and blast radius
9
Module 4: From Signals to Summaries
AI for observability: RAG over logs: embedding and querying Datadog, Loki, Splunk; Anomaly detection: where LLMs add value vs classical methods; Incident summarization, timeline reconstruction and RCA drafting; On-call copilot: runbook retrieval, alert correlation, escalation; Multi-signal agents correlating metrics, traces, logs and deploys
10
Module 5: Generate, Review & Reconcile IaC
Agentic infrastructure as code: Terraform and Pulumi generation, review and refactoring via LLMs; Drift detection and agentic reconciliation loops; Policy-as-code generation: Rego, Sentinel, Open Policy Agent; Natural language to IaC translation and failure modes; Human-in-the-loop gates for destructive changes
11
Module 6: Harden Your Agents
Security and guardrails: Threat modeling: prompt injection, privilege escalation, exfiltration; Minimal-permission design: scoped credentials, role boundaries; Input and output guardrails: filters, schema validation, rate limiting; Audit logging and SIEM integration for agent actions; AI-assisted vulnerability scanning, SBOM analysis and compliance
12
Module 7: Orchestration That Doesn't Fall Over
Multi-agent systems: Orchestrator and subagent patterns: delegation, handoff, aggregation; Model Context Protocol (MCP): servers, clients, tool discovery; Agent memory: short-term context, long-term vector stores; Multi-agent failure modes: hallucination, deadlock, cascades; Operational concerns: latency budgets, retries, graceful degradation
Project
Capstone: Autonomous Ops Platform
Design, integrate, harden and demo a working autonomous ops platform - CI/CD hooks, observability feeds, IaC tooling and Slack/PagerDuty, tested under chaos and adversarial prompts.
Common questions
Is this live or recorded?Live, scheduled sessions with your trainer and cohort. Every session is recorded, so you can catch up if you miss one.
What do I get at the end?Finish the cohort to unlock a verifiable CareerByteCode certificate, 5 exam passes and 5 ByteLabs projects, plus your shipped project work in a public portfolio.
How is the price shown?The price is the base plus 18 percent GST, shown all-in (₹23,600). You pay securely via Razorpay.
Do I need experience?Pick a cohort at your level (Expert here). Your trainer supports you through every module and project.
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