AWS

AWS CloudWatch

Master AWS CloudWatch for robust applications! Elevate your skills in monitoring & optimizing AWS ecosystems with our comprehensive course for cloud engineers, developers, and architects

Raghunandana Sanur

Staff Data Engineer & MLOps Engineer at Talabat

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Description

Explore the depths of AWS CloudWatch in this comprehensive course designed to elevate your understanding of observability and monitoring within the AWS ecosystem. From foundational concepts to advanced techniques, immerse yourself in a journey through CloudWatch's powerful suite of tools.

• Introduction to Observability in AWS

Understanding the significance of monitoring and tracing
Exploring the basics of logging within cloud environments

• Anatomy of Alarms

Setting up, configuring, and managing proactive alerts
Responding to system deviations and anomalies effectively

• CloudWatch Dashboards

Crafting intuitive and informative visualizations
Efficiently comprehending complex data sets for actionable insights

• CloudWatch Logs

Aggregating, analyzing, and extracting valuable insights
Troubleshooting and optimizing system performance

• CloudWatch Events, EventBridge, and Event Buses

Facilitating seamless event-driven architectures
Streamlining communication between AWS services

• CloudWatch Insights, X-Ray, and Service Map

Gaining unparalleled visibility into application performance
Understanding dependencies and behavior for optimization

• Advanced Observability with CloudWatch

Exploring sophisticated methodologies and best practices
Leveraging cutting-edge techniques for maximum value extraction
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Who Should Attend:

Aspiring cloud engineers
Seasoned developers
Systems architects seeking advanced AWS proficiency

Unlock the power of AWS CloudWatch, build resilient applications, and master observability within AWS!

About the instructor

Raghunandana Krishnamurthy, currently serving as a Staff Data Engineer and MLOps Engineer at Talabat, is renowned for his expertise in the fields of data engineering and machine learning operations. He has a strong background in both GCP and AWS platforms, utilizing tools like SageMaker and VertexAI to accelerate model development and deployment.

His experience at HelloFresh as a Senior Data Engineer involved migrating legacy ETL to AWS EMR and managing hybrid data infrastructure, showcasing his proficiency in big data cloud stacks. He was also responsible for creating visibility on ETL's through monitoring and alerting with Prometheus, Grafana, and other tools.

At Careem, Raghunandana was a Data Engineering Technical Lead, focusing on big data platform development and ensuring the health and alignment of the growing team. His responsibilities included maintaining big data platforms and ensuring data quality for analytics, machine learning, and AI applications.

His tenure at Cerner Corporation as a Big Data Engineer further highlights his deep understanding of Hadoop systems and DevOps culture. He was involved in the development, maintenance, and upgrading of Hadoop clusters, as well as in building scalable distributed systems.

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