Cloud DevOps Roadmap - Phase 3

Author

Vishakha Sadhwani
April 14, 2025

Alright Tech Explorers,

Welcome to the final phase of our Cloud DevOps roadmap!

Phase 3 is where we move into more advanced territories and open up avenues for specialization.

This is where you can really start to carve out your niche in the Cloud DevOps landscape. Let's dive in!

Advanced IaC:

We're taking Infrastructure as Code to the next level. This involves a deep dive into:

  • Terraform modules (reusable infrastructure components),

  • sophisticated state management (handling the blueprint of your infrastructure effectively),

  • and advanced provisioning techniques (automating complex infrastructure setups).

For Ansible, you should explore:

  • advanced playbooks (more intricate automation workflows),

  • leveraging roles for better organization,

  • and developing comprehensive automation strategies for diverse cloud environments.

Resources:

Advanced Kubernetes:

We're going beyond the basics of Kubernetes here. This includes:

  • Understanding networking within Kubernetes (how pods communicate).

  • Implementing advanced deployment strategies (like blue/green and canary deployments for zero-downtime updates).

  • Security in Kubernetes (RBAC, Network Policies).

  • Multi-Cluster Ingress: Managing external access to applications deployed across multiple Kubernetes clusters. Understanding concepts like global load balancing and cross-cluster service discovery.

  • Gateways (API Gateways/Ingress Controllers): Deep dive into advanced Ingress controller configurations (e.g., Nginx Ingress, Traefik) and the role of API Gateways (e.g., Kong, Ambassador) for routing, authentication, rate limiting, and more.

  • Service Mesh: Introduction to Service Mesh technologies (e.g., Istio, Linkerd) for managing microservices communication, traffic management (routing, retries, timeouts), security (mutual TLS), and observability within a Kubernetes cluster.

Resources:

Cloud Security:

Security in the cloud is paramount. This section involves an in-depth understanding of cloud security best practices:

  • how to manage access with IAM (Identity and Access Management),

  • configuring security groups (virtual firewalls),

  • and implementing robust network security.

We'll also revisit the OWASP Top 10 vulnerabilities but specifically in the context of cloud applications, and touch upon basic understanding of relevant Compliance standards like GDPR and HIPAA as they apply to cloud environments.

Resources:

Advanced Monitoring & Observability:

We're moving beyond basic metrics to implementing comprehensive monitoring solutions that give you deep insights into your systems. This includes:

  • setting up effective log aggregation and analysis (centralizing and understanding logs),

  • implementing tracing (following requests across services),

  • and configuring intelligent alerting systems.

The focus is on understanding key observability concepts (going beyond just monitoring to understand why things are happening) and the advanced usage of relevant tools.

Resources:

Performance Optimization:

Keeping your cloud applications and infrastructure running smoothly requires understanding how to identify and address performance bottlenecks. This involves techniques:

  • like load testing (simulating user traffic),

  • implementing effective scaling strategies (automatically adjusting resources),

  • and performing resource optimization (making the most of your cloud spend).

Resources:

Disaster Recovery (DR) & Business Continuity (BC):

Ensuring your systems can recover from major incidents is crucial for business continuity. Time to delve deeper into implementing various DR strategies in the cloud, including:

  • Backup and Restore,

  • Pilot Light,

  • Warm Standby, and Multi-site deployments.

A thorough understanding of RTO (Recovery Time Objective) and RPO (Recovery Point Objective) is essential for designing effective DR plans.

Resources:

Caching Strategies in the Cloud:

We'll explore advanced caching techniques specifically within a cloud context. This includes in-depth usage of in-memory caches like:

  • Redis and Memcached in distributed cloud environments,

  • implementing and managing Content Delivery Networks (CDNs) for global performance,

  • and understanding sophisticated cache invalidation techniques to ensure data freshness.

Resources:

Database Management in the Cloud:

Managing databases at scale in the cloud requires understanding advanced concepts for both SQL and NoSQL databases. This includes strategies for achieving high availability and scalability, and specific data modeling considerations that are optimized for cloud environments.

Resources:

MLOps (Machine Learning Operations) & AI Infrastructure: 

  • Deep dive into the principles and practices of MLOps in the cloud.

  • Introduction to Kubeflow: Understanding its components for managing the ML lifecycle on Kubernetes.

  • Exploring other MLOps tools and platforms (e.g., MLflow for tracking, Seldon Core for model serving, cloud-specific ML platforms like SageMaker, Vertex AI).

  • Considerations for AI infrastructure: GPU management, specialized storage for ML datasets.

Resources:

This final phase is about deepening your expertise and potentially specializing in an area that truly interests you within the vast landscape of Cloud DevOps. The resources provided are starting points – the key is to explore, experiment, and continuously learn.

Sample Role Descriptions (Relevant as you progress through Phase 3):

At this stage, with deeper knowledge and potential specializations, you might be targeting roles like these:

Senior DevOps Engineer:

We are looking for a seasoned Senior DevOps Engineer with extensive experience in building and managing highly scalable and resilient cloud infrastructure. You will be responsible for leading the implementation of advanced IaC practices (Terraform, Ansible), designing and managing Kubernetes clusters, implementing robust security and monitoring solutions, and driving performance optimization efforts. Expertise in CI/CD pipelines and a strong understanding of cloud best practices (AWS/Azure) are essential. You will also mentor junior team members and contribute to the overall DevOps strategy.

Here are a couple of sample role descriptions that now incorporate MLOps and AI infrastructure aspects:

Senior DevOps/MLOps Engineer:

We are seeking a highly skilled Senior DevOps/MLOps Engineer to build and manage the infrastructure and automation for our machine learning workflows in the cloud. You will be responsible for implementing and managing MLOps tools like Kubeflow, MLflow, and Seldon Core on Kubernetes. This role involves expertise in containerization (Docker, Kubernetes), IaC (Terraform, Ansible), cloud platforms (AWS/Azure/GCP), and a strong understanding of the machine learning lifecycle. Experience with GPU-based infrastructure and optimizing ML pipelines for performance and scalability is highly valued.

AI Infrastructure Engineer:

We are looking for an experienced AI Infrastructure Engineer to design, build, and maintain the underlying infrastructure required for our machine learning and AI initiatives in the cloud. This includes managing Kubernetes clusters optimized for AI workloads, deploying and managing MLOps platforms like Kubeflow, and working with specialized hardware like GPUs. A strong understanding of cloud networking, storage solutions for large datasets, and automation of AI/ML pipelines is essential. You will work closely with data scientists and machine learning engineers to provide a robust and scalable AI infrastructure.

Platform Engineer:

We are looking for a skilled Platform Engineer to build and maintain our internal developer platform on the cloud. This role involves deep expertise in Kubernetes, advanced IaC (Terraform, Ansible), and building self-service tools and automation to empower development teams. Strong knowledge of monitoring and observability practices, as well as experience with CI/CD and cloud networking, is crucial. You will be responsible for the reliability, scalability, and usability of our platform.

Remember that this roadmap is a guide, and your journey will be unique. The key is continuous learning and hands-on experience. Good luck with your ongoing exploration of the exciting world of Cloud DevOps!