AWS/Cloud DevOps Roadmap (2025–2027)
Team Overview
Our DevOps team consists of two senior engineers and one trainee. We focus on enabling cloud infrastructure reliability, observability, security, and operational agility. This two-year roadmap balances strategic innovation with realistic execution timelines and includes clearly stated Risks, Challenges & Assumptions (RCA) to keep expectations aligned with operational realities, team capacity, and evolving priorities.
Strategic Objectives (FY 2025–2027)
| Objective |
Expected Outcomes |
| Observability & Tooling | Unified monitoring and faster incident resolution |
| High Availability & DR | Reliable systems with validated disaster recovery |
| Security & Compliance | Stronger security posture and compliance readiness |
| AI-Powered Automation | Faster incident resolution through smart automation |
| Multi-Cloud & Cost Saving | Flexibility with cloud providers and 25–30% savings |
Why This Roadmap?
- Legacy tools are outdated or not integrated
- No centralized logging or visibility
- Not all services are highly available
- Cloud spend is rising, vendor lock-in risks
- Shortage of staff for 24×7 operations
This roadmap addresses these challenges through phased modernization, automation, and strategic use of multi-cloud and AI.
DevOps Roadmap: Yearly Highlights
Year 1 (July 2025 – June 2026)
| Quarter |
Theme |
Key Deliverables |
| Q1: Jul – Sep 2025 | Observability & Internal Tools | New monitoring tools (ELK, Prometheus, Grafana) |
| Q2: Oct – Dec 2025 | High Availability & Backups | Multi-AZ setup, automated backups, DR playbooks |
| Q3: Jan – Mar 2026 | Security & Secrets Management | IAM improvements, WAF setup, Secrets Management |
| Q4: Apr – Jun 2026 | AI-Driven Operational Intelligence | AWS DevOps Guru, CloudWatch AD, auto-remediation |
Year 2 (July 2026 – June 2027)
| Quarter |
Theme |
Key Deliverables |
| Q1: Jul – Sep 2026 | Kubernetes Adoption | 80% workloads containerized & on EKS |
| Q2: Oct – Dec 2026 | Compliance & Reporting Automation | ISO/GDPR/HIPAA compliance, automated reporting |
| Q3: Jan – Mar 2027 | Advanced AI Monitoring | AI monitoring of infra & client apps |
| Q4: Apr – Jun 2027 | Multi-Cloud & Cost Optimization | Migrate 50% workloads to Azure/GCP, cost savings |
Roadmap Progress Overview
Q1 2025
Observability & Internal Tools
Q2 2025
High Availability & DR
Q3 2026
Security & Secrets Mgmt
Q4 2026
AI-Driven Ops Intelligence
Q1 2026
Kubernetes Adoption
Q2 2026
Compliance Automation
Q3 2027
Advanced AI Monitoring
Q4 2027
Multi-Cloud & Cost Efficiency
Q1 2025: Observability & Internal Tools
| Focus Area | Details |
|---|
| Monitoring Tools | Build at least 1 custom Python-based tool and enhance 5+ existing scripts to extend monitoring coverage and reliability. |
| Centralized Logging & Dashboards | Deploy ELK/OpenSearch, Prometheus, and Grafana to centralize logs and metrics for real-time insights and diagnostics. |
- Current Challenges: 5+ tools outdated; no centralized logging system.
- Why Needed: To keep tools updated and provide valuable metrics, and to centralize log visibility for engineers.
- Expected Outcomes: Enhanced observability, faster detection of issues, and improved operational efficiency.
- KPIs: ≥90% log coverage; incident detection time ↓ ≥30%.
- RCA: Monitoring work may be delayed by emergent priorities or infra noise; staff availability may fluctuate.
Q2 2025: High Availability & DR
| Focus Area | Details |
|---|
| High Availability | Re-architect production workloads using Multi-AZ EC2, Auto Scaling, and Route 53 failover policies to ensure service continuity. |
| Disaster Recovery | Automate snapshot backups for EC2, EBS, and S3; perform a controlled DR drill for validation. |
- Current Challenges: Only some applications are running on partial high availability (not on multi AZ); few applications are not highly available.
- Why Needed: To achieve ≥99.98% infra uptime with robust DR.
- Expected Outcomes: ≥99.9% uptime; robust DR preparedness.
- KPIs: 100% backup automation; DR drill executed successfully.
- RCA: AWS capacity quotas, infra cost spikes, incident escalations may impact schedule or scope.
Q3 2026: Security & Secrets Management
| Focus Area | Details |
|---|
| Cloud Infrastructure Security | Implement IAM hardening (least privilege), WAF on public-facing workloads, and AWS Inspector scans to reduce exposure. |
| Application Security | Integrate AWS Secrets Manager, Parameter Store, and CI-based vulnerability scanning for improved data protection. |
- Current Challenges: AWS default security implemented; many applications run with outdated security practices.
- Why Needed: Necessary to fix cloud infra and app-level security challenges to protect data and credentials.
- Expected Outcomes: Improved security compliance; zero high-risk findings.
- KPIs: IAM audit 100%; all production secrets centrally managed; zero open CVEs.
- RCA: Security work requires developer effort; infra cost/resource availability may impact schedule or scope.
Q4 2026: AI-Driven Ops Intelligence
| Focus Area | Details |
|---|
| AI-Driven Monitoring | Deploy AI tools like AWS DevOps Guru and CloudWatch Anomaly Detection to identify trends and early failures. |
| Auto-remediation & ChatOps | Use Lambda, SageMaker (if applicable), and AWS Chatbot for automated recovery and alert delivery to ops teams. |
- Current Challenges: Too many servers for human monitoring; small team size makes 24×7 monitoring hard.
- Why Needed: AI tools help a small team operate and monitor 24×7, reducing staff burden.
- Expected Outcomes: MTTR ↓ 25%; improved ops predictability.
- KPIs: ≥1 auto-remediation routine live; positive team feedback.
- RCA: AI implementation may need tuning; costs/business priorities may affect scope.
Q1 2026: Kubernetes Adoption
| Focus Area | Details |
|---|
| Containerization & EKS | Dockerize remaining services and move to Amazon EKS to standardize deployments and improve autoscaling. |
| Traffic Optimization | Use ALB/NLB and Route 53 latency/geolocation routing to optimize performance under load. |
- Current Challenges: No containerization; infra auto scaling is a bottleneck.
- Why Needed: Crucial for auto scaling infra and handling heavy operations/traffic.
- Expected Outcomes: 80% workloads on K8s; 50% improvement in traffic handling.
- KPIs: 80% workloads on K8s; 50% improvement.
- RCA: Migration complexity and skill ramp-up may delay rollouts; developer effort needed for infra readiness.
Q2 2026: Compliance & Reporting Automation
| Focus Area | Details |
|---|
| Compliance Documentation | Develop ISO 27001, GDPR, HIPAA documentation using AWS Artifact and others. |
| Compliance Automation | Automate 50% of reporting using Audit Manager, GitLab/Jira workflows to simplify and accelerate evidence gathering. |
- Current Challenges: Very limited compliance documentation.
- Why Needed: Crucial for client onboarding and trust; showcases compliance maturity.
- Expected Outcomes: 100% documentation readiness; ≥50% reporting automated.
- KPIs: 100% docs, ≥50% automation.
- RCA: Compliance timelines may be affected by production escalations or audit rescheduling; subject to resource bandwidth.
Q3 2027: Advanced AI Monitoring
| Focus Area | Details |
|---|
| AI-Based Advanced Infra Monitoring | Deploy LLMs or DevOps Guru/SageMaker to perform real-time incident detection and predictive alerts. |
| Client Website Observability | Implement always-on monitoring agents for client applications to detect downtime, slowness, and anomalies. |
- Current Challenges: Infra growth makes operations management with limited staff challenging.
- Why Needed: 24×7 monitoring and automated incident prediction will be more efficient and effective, reducing need for extra staff.
- Expected Outcomes: 30% fewer critical incidents; MTTD ↓ 40%; AI adoption ≥ 90%.
- KPIs: Critical incidents ↓ 30%; MTTD ↓ 40%.
- RCA: Complexity of ML/LLM models and limited AI expertise may slow adoption; optionality to phase out non-critical use cases.
Q4 2027: Multi-Cloud & Cost Efficiency
| Focus Area | Details |
|---|
| Multi-Cloud Infrastructure | Migrate 50% of critical workloads to Azure/GCP using Terraform IaC with active-active or failover designs. |
| Cloud Cost Optimisation | Implement tools like CloudHealth or Cloudability for spend analysis, optimize workloads, enforce right-sizing strategies, and achieve 20% cost savings without SLA impact. |
- Current Challenges: Single cloud dependency; AWS resource limitations; not always cost-efficient.
- Why Needed: Reduce dependency, leverage best-of-breed cloud tools, optimize cost.
- Expected Outcomes: 50% workloads multi-cloud; cloud spend ↓ 20%; SLA adherence.
- KPIs: 50% workloads multi-cloud; spend ↓ 20%.
- RCA: Multi-cloud governance and compatibility adds complexity; rollout needs to be controlled.
Contingency Planning
- Monthly RCA and velocity reviews; delays >2 weeks flagged to leadership
- Priority adjustments: Defer non-critical deliverables or break into MVP + stretch goals
- Capacity augmentation: Engage external consultants if team saturation occurs
- Cost governance: Exec oversight if cloud/infrastructure forecast exceeds planned budget by >15%
Document Owners: Devesh Yadav / Anand Mohan
Last Updated: 21 May 2025
Team Overview
Current Team Composition
| Team Member |
Role/Designation |
| Anand Mohan |
Lead DevOps Resource |
| Devesh Yadav |
Senior DevOps Resource |
Prashant |
Junior-Level DevOps Resource |
| Ashutosh Kushwaha |
Trainee - DevOps Resource |
Resource Gap and Requirements
To ensure timely and effective execution of the roadmap initiatives, the following additional
resource is required:
- 1 Junior-Level DevOps Engineer (with 3–5 years of experience)
- Expected to contribute across automation, monitoring, CI/CD, and operations
Team Scalability Needs
To fully meet the scope and complexity of the roadmap (FY 2025–2027), we recommend:
- Minimum of 2 Senior DevOps Engineers
- At least 1 Mid-Level DevOps Engineer