Manoj Sardana
Director Of Information System and Operations - HCL Software
Delhi, India
Actions
With over 20 years of IT experience, I am Director of operations and information Systems at HCLSoftware, where I lead a team to manage the availability, reliability, and performance of SaaS-based solutions on AWS, GCP, and IBM Cloud. I have extensive experience on cloud native tools like Kubernetes, Docker, Istio, OpenTelemetry and observability tools like Dynatrace, new relic and Grafana. I am a firm believer of automating most operational tasks by defining standard processes and practices.
Badges
Area of Expertise
Topics
Building an effective observability pipelines for application deployed on Kubernetes
Modern cloud-native applications generate massive amounts of telemetry data, and managing this data efficiently is critical for reliable operations. This hands-on workshop is designed to help participants set up the OpenTelemetry Collector and learn how to build optimized telemetry pipelines that are scalable, cost-efficient, and ready for production use.
This session is ideal for SREs, DevOps engineers, and platform teams looking to strengthen their Observability foundations.
outcomes :
Deploy and configure an OpenTelemetry Collector
Build and customize telemetry pipelines
Apply effective filtering and processing strategies
Optimize data flow to reduce noise and improve Observability quality
AIOps - Role of AI in Observability
As modern applications evolve into complex, distributed ecosystems, traditional observability approaches struggle to keep pace with the scale, speed, and dynamic nature of microservices. AI-powered observability offers a transformative approach, enabling organizations to move beyond manual monitoring and reactive troubleshooting. By leveraging machine learning models, anomaly detection, and intelligent correlation, AI enhances observability pipelines—automating root cause analysis, predicting incidents before they escalate, and optimizing system performance in real-time.
This session explores how AI augments observability by integrating with OpenTelemetry and other telemetry data sources to provide deeper insights, proactive alerts, and automated remediation.
Join us to discover how AI is reshaping observability, making modern systems more resilient, efficient, and intelligent.
Bridging K8s Observability and Intelligence with AIOps and OpenTelemetry
OpenTelemetry provides a unified framework for collecting, processing, and exporting telemetry data, enabling visibility across diverse systems and environments including K8s based microservices.
AIOps (Artificial Intelligence for IT Operations) leverages AI and machine learning to automate and enhance IT operations, improving incident management, performance monitoring, and decision-making at scale.
When paired together , OpenTelemetry’s rich data becomes a powerful foundation for advanced analytics, anomaly detection, and automated incident response through AIOps techniques. Training the right model on the existing Observability data and various other data sets like past incidents, user interaction & feedback, action taken etc. can help the operation reach a level of fully autonomous with close to zero human interaction.
The session will cover the high level overview of high standardization of OpenTelemetry and help in realizing the dream of AIOps, a fully autonomous operations world.
Building Effective Observability Pipelines for Applications on Kubernetes
Modern cloud-native systems generate tons of telemetry data, and understanding how to manage, process, and optimize this data is essential for any SRE, DevOps, or platform engineer.
In this workshop, you’ll learn how to:
✅ Deploy & configure the OpenTelemetry Collector
✅ Build and customize telemetry pipelines
✅ Apply filtering & processing strategies
✅ Optimize signal flow to reduce noise and improve observability quality
This session is packed with practical knowledge to help you strengthen your observability foundations and apply industry best practices.
Please note that Sessionize is not responsible for the accuracy or validity of the data provided by speakers. If you suspect this profile to be fake or spam, please let us know.
Jump to top