Job Summary
The SRE will be responsible for the reliability, availability, and performance of Azure/AWS PaaS and IaaS workloads. They bridge the gap between development and operations, focusing on building automated systems that prevent failures, managing incident responses, and optimizing cloud costs.
Key Responsibilities
System Reliability & Monitoring: Design, implement, and maintain comprehensive monitoring and alerting systems such as Azure Monitor, AWS CloudWatch, Application Insights, and Log Analytics. • Automation & Toil Reduction: Automate repetitive manual operations (toil) such as environment provisioning, system patching, and scaling. Use IaC tools like Terraform and Ansible to manage infrastructure. • Incident Response & Management: Actively manage incident responses, root cause analysis (RCA), and post-mortem investigations to improve system reliability and minimize mean time to resolution (MTTR). • Cloud SRE Agent Integration: Deploy and configure Cloud SRE Agent to automate incident investigation, execute remediation steps (restart, scale, rollback), and manage routine tasks. • Capacity Planning & Scalability: Analyze usage patterns to optimize cloud resources, ensuring high availability and performance while managing costs via Azure Cost Management. • CI/CD & DevOps Collaboration: Integrate automation workflows into CI/CD pipelines (e.g., GitHub Actions or Azure Pipelines) to ensure reliable deployments.
Skill Requirements
Cloud Platforms: Expert knowledge of Microsoft Azure infrastructure services (Compute, Storage, Networking, AKS). • Scripting & Programming: Proficiency in Python, Bash, or PowerShell for building automation tools. • Infrastructure as Code (IaC): Extensive experience with Terraform and ARM templates/Bicep. • Observability Tools: Experience with Azure Monitor, Grafana, Prometheus, or Datadog. • Containers & Orchestration: Solid understanding of Kubernetes/AKS (Azure Kubernetes Service). • Operating Systems: Proficient in Windows/Linux environments. • Azure Certification is a + • Exposure to multi Cloud environment is must.
Other Requirements
Reviewing Service Level Objectives (SLOs) and error budgets. 2. Refining auto-scaling rules for Kubernetes clusters based on traffic trends. 3. Working with developers to review service architecture and ensure fault tolerance. 4. Configuring AI-driven alert suppression to reduce alert fatigue. 5. Creating Azure Dashboards to visualize key performance indicators (KPIs).