Bakul Banthia, Tessell, Co-Founder Perren Walker, Tessell, VP, Distinguished Oracle & Business Value Cloud Architect
Leverage cloud-native NVMe-based high-performance compute shapes to get up to an unbeatable 2 million IOPS on a single database instance. Learn about the patented architecture that converts this ephemeral infrastructure into a durable, persistent cloud storage solution, ensuring zero data loss protection. Enjoy these features for your choice of database engine (Oracle, PostgreSQL, MySQL, SQL Server, etc.) on your choice of cloud (AWS, Azure, etc.). No lock-in.
With close to two decades of experience in the lifecycle management of business-critical applications and cloud services, and with multiple patents to his name - Bakul Banthia is a multi-cloud, hybrid-cloud expert and leader. Bakul is currently the Co-Founder and Head of GTM at Tessell... Read More →
We often hear stories from Kafka users about taking nine months to implement production-ready Kafka-based data pipelines. We see customers having 50 teams relying on a single Kafka cluster managed by one person. Data engineers cannot easily simulate a production environment without a complex initial setup. Or data scientists struggle with data integration, building an offline ML pipeline to experiment, reproduce models, and debug them locally. Let's explore how to skip the headache of creating computing clusters, managing partitions, shards, and workers' setup.
The talk demonstrates a different way of implementing a cost-efficient serverless streaming pipeline using pure Python. We will leverage technologies like KEDA (Kubernetes Event-Driven Autoscaling) with integrated NATS Jetstream for the distribution of real-time events and Fission serverless framework to run lambda-like functions on Kubernetes.
𝐖𝐡𝐨 𝐈 𝐚𝐦Bobur is a developer advocate and speaker specializing in software and data engineering. With over 10- years of experience in IT, he blogs about open-source technologies and the community around them.𝐖𝐡𝐚𝐭 𝐈 𝐝𝐨Bobur works with companies... Read More →
Mohammed Amine Garmes, Amadeus, Principal Data Engineer Liam Mulhall, Amadeus, Innovation Leader
Platform Overview: The Amadeus Hexadata Platform (AHP) is an advanced suite of capabilities for constructing and managing multiple End-to-End (E2E) big data pipelines. - Processes approximately 2 billion transactions daily. - Fully migrated from on-premise to Azure Cloud. - Data size 10PB. Data Integration: - Integrates data from around 6,000 servers across various Amadeus divisions and external clients. - 90% of data handled via Kafka, hosted on Azure or within a private data center. - Utilizes Mirror Maker to replicate data across four Kafka clusters. - Utilizes KafkaConnectors to stream files to Kafka Technologies Used: KStreams, Databricks, Kafka Connectors, Airflow, Internal Framework Additional Capabilities: Operational on OpenShift. (4000 Pods) ElasticSearch MLOPS pipeline : CICDCD for ML models on the platform in Azure. - on-going - Key Benefits: Provides scalable, reliable, and efficient big data processing and analytics solutions.
As a Principal Data Engineer with over nine years of experience at Amadeus, I specialize in designing and optimizing the company's Big Data platform. I lead complex data engineering projects, leveraging my expertise to ensure scalable, efficient, and high-performance data processing... Read More →
A highly motivated and results-oriented technical leader with over 25 years of experience in delivering complex software solutions. My expertise lies in building scalable, secure, and real-time systems across various industries - all with a centralized view around 'achieving the best... Read More →
Learn why GPU clusters need massive high performance networks. InfiniBand vs Ethernet. And anatomy of large scale network fabrics behind cloud providers.
There are too many possibilities for base images in cloud environments and not enough time to validate which ones fulfill all of my requirements. Worse yet, I know that I have policies set by my security team that my infrastructure will be beholden to. So now what? I built an open source policy engine and image generator to implement directly into my build pipelines. I can start with any base image, apply my security policies that are verified by my security team, and now have a baseline that I can rapidly scale my infrastructure from.
Dedicated to optimization and designing effective workflows for continuous integration and continuous delivery, Kendall understands the melding of operations and development to quickly deliver code to customers. Has experience with the Cloud and monitoring processes as well as DevOps... Read More →
Mike Simon, Splunk, Staff Developer Evangelist - Observability
In cloud-native environments, embedding observability as part of your infrastructure-as-code strategy is no longer optional—it’s essential. This session explores the value and necessity of adopting an observability-inclusive as-code approach, allowing teams to automate monitoring, reduce blind spots, and accelerate incident response. We’ll dive into the opportunities this brings for enhancing visibility, ensuring system reliability, and empowering teams to take proactive, data-driven actions without manual overhead.
Mike Simon is a Staff Developer Evangelist at Splunk, where he has been part of the team for two years. In his tenure at Splunk, Mike has held roles as an Observability Strategist and Technical Architect.Before joining Splunk, Mike built a distinguished 16-year career as an Observability... Read More →
In this talk, I focus on addressing the high latency issues associated with Cloud storage in data processing systems that employ a decoupled compute and storage architecture. We delve into the root causes of latency in this context and explore various techniques to minimize the impact of object storage latency on stream processing performance. Our proposed approach is to implement a tiered storage mechanism that leverages a blend of high-performance and low-cost storage tiers to reduce data movement between the compute and storage layers while maintaining efficient processing.
We will present experimental results that demonstrate the effectiveness of our approach in mitigating the impact of Cloud storage latency on data processing. By the end of the talk, attendees will have gained insights into how to optimize their data processing systems for reduced latency and improved cost-efficiency.
Rayees Pasha is the Head of Product at RisingWave Labs, a startup pioneering the development of Streaming Database. Rayees is responsible for all areas of Product management and Marketing. His expertise is in the areas of data management and big data analytics. He has held product... Read More →
Unlock the power of managing infrastructure through code in this dynamic session! You'll dive into the fundamentals of infrastructure as code (IaC) with a focus on AWS CloudFormation. Step-by-step, you'll learn how to write your first template to efficiently create, update, and delete cloud resources.
By the end of this hands-on workshop, you'll have added a valuable skill to your repertoire and be equipped with the knowledge to further explore the vast possibilities of infrastructure as code. Join to enhance your technical skillset and embark on a journey of continuous innovation in cloud infrastructure management.
Jagrut Sharma is a senior software engineer at Adobe, where he leads the architecture and development of services enabling innovative machine-learning solutions and use cases. With over 20 years of experience in technology, Jagrut has contributed to a wide variety of projects across... Read More →
Bakul Banthia, Tessell, Co-Founder Perren Walker, Tessell, VP, Distinguished Oracle & Business Value Cloud Architect
Leverage cloud-native NVMe-based high-performance compute shapes to get up to an unbeatable 2 million IOPS on a single database instance. Learn about the patented architecture that converts this ephemeral infrastructure into a durable, persistent cloud storage solution, ensuring zero data loss protection. Enjoy these features for your choice of database engine (Oracle, PostgreSQL, MySQL, SQL Server, etc.) on your choice of cloud (AWS, Azure, etc.). No lock-in.
With close to two decades of experience in the lifecycle management of business-critical applications and cloud services, and with multiple patents to his name - Bakul Banthia is a multi-cloud, hybrid-cloud expert and leader. Bakul is currently the Co-Founder and Head of GTM at Tessell... Read More →
We often hear stories from Kafka users about taking nine months to implement production-ready Kafka-based data pipelines. We see customers having 50 teams relying on a single Kafka cluster managed by one person. Data engineers cannot easily simulate a production environment without a complex initial setup. Or data scientists struggle with data integration, building an offline ML pipeline to experiment, reproduce models, and debug them locally. Let's explore how to skip the headache of creating computing clusters, managing partitions, shards, and workers' setup.
The talk demonstrates a different way of implementing a cost-efficient serverless streaming pipeline using pure Python. We will leverage technologies like KEDA (Kubernetes Event-Driven Autoscaling) with integrated NATS Jetstream for the distribution of real-time events and Fission serverless framework to run lambda-like functions on Kubernetes.
𝐖𝐡𝐨 𝐈 𝐚𝐦Bobur is a developer advocate and speaker specializing in software and data engineering. With over 10- years of experience in IT, he blogs about open-source technologies and the community around them.𝐖𝐡𝐚𝐭 𝐈 𝐝𝐨Bobur works with companies... Read More →
Mohammed Amine Garmes, Amadeus, Principal Data Engineer Liam Mulhall, Amadeus, Innovation Leader
The Amadeus Hexadata Platform (AHP) is an advanced suite of capabilities for constructing and managing multiple End-to-End (E2E) big data pipelines. - Processes approximately 2 billion transactions daily. - Fully migrated from on-premise to Azure Cloud. - Data size 10PB. Data Integration: - Integrates data from around 6,000 servers across various Amadeus divisions and external clients. - 90% of data handled via Kafka, hosted on Azure or within a private data center. - Utilizes Mirror Maker to replicate data across four Kafka clusters. - Utilizes KafkaConnectors to stream files to Kafka Technologies Used: KStreams, Databricks, Kafka Connectors, Airflow, Internal Framework Additional Capabilities: Operational on OpenShift. (4000 Pods) ElasticSearch MLOPS pipeline : CICDCD for ML models on the platform in Azure. - on-going - Key Benefits: Provides scalable, reliable, and efficient big data processing and analytics solutions.
As a Principal Data Engineer with over nine years of experience at Amadeus, I specialize in designing and optimizing the company's Big Data platform. I lead complex data engineering projects, leveraging my expertise to ensure scalable, efficient, and high-performance data processing... Read More →
A highly motivated and results-oriented technical leader with over 25 years of experience in delivering complex software solutions. My expertise lies in building scalable, secure, and real-time systems across various industries - all with a centralized view around 'achieving the best... Read More →
Learn why GPU clusters need massive high performance networks. InfiniBand vs Ethernet. And anatomy of large scale network fabrics behind cloud providers.
A story of how our infrastructure evolved over time to accommodate an increasing number of users - from on-premise to cloud and back down.
How does one make an infrastructure to handle more than a couple of users?
How do you go from 100 to 1000 to 100,000 to tens of millions?
What happens when due to popular demand hundreds of thousands of users hit your servers at the same time?
I'll tell you a story of how a small team of people managed to move software and services from one server to two, and then to dozens on cloud and then back to on-premise. What we encountered on the way, where we failed, and how we solved it.
Josip has been involved with computers for the better part of his life. Started with web development back in high school. Since then he's moved to backend and DevOps. Loves security stuff and is obsessed with optimising everything. Works in Zagreb as CTO @ Sofascore
There are too many possibilities for base images in cloud environments and not enough time to validate which ones fulfill all of my requirements. Worse yet, I know that I have policies set by my security team that my infrastructure will be beholden to. So now what? I built an open source policy engine and image generator to implement directly into my build pipelines. I can start with any base image, apply my security policies that are verified by my security team, and now have a baseline that I can rapidly scale my infrastructure from.
Dedicated to optimization and designing effective workflows for continuous integration and continuous delivery, Kendall understands the melding of operations and development to quickly deliver code to customers. Has experience with the Cloud and monitoring processes as well as DevOps... Read More →
Mike Simon, Splunk, Staff Developer Evangelist - Observability
In cloud-native environments, embedding observability as part of your infrastructure-as-code strategy is no longer optional—it’s essential. This session explores the value and necessity of adopting an observability-inclusive as-code approach, allowing teams to automate monitoring, reduce blind spots, and accelerate incident response. We’ll dive into the opportunities this brings for enhancing visibility, ensuring system reliability, and empowering teams to take proactive, data-driven actions without manual overhead.
Mike Simon is a Staff Developer Evangelist at Splunk, where he has been part of the team for two years. In his tenure at Splunk, Mike has held roles as an Observability Strategist and Technical Architect.Before joining Splunk, Mike built a distinguished 16-year career as an Observability... Read More →
In this talk, I focus on addressing the high latency issues associated with Cloud storage in data processing systems that employ a decoupled compute and storage architecture. We delve into the root causes of latency in this context and explore various techniques to minimize the impact of object storage latency on stream processing performance. Our proposed approach is to implement a tiered storage mechanism that leverages a blend of high-performance and low-cost storage tiers to reduce data movement between the compute and storage layers while maintaining efficient processing.
We will present experimental results that demonstrate the effectiveness of our approach in mitigating the impact of Cloud storage latency on data processing. By the end of the talk, attendees will have gained insights into how to optimize their data processing systems for reduced latency and improved cost-efficiency.
Rayees Pasha is the Head of Product at RisingWave Labs, a startup pioneering the development of Streaming Database. Rayees is responsible for all areas of Product management and Marketing. His expertise is in the areas of data management and big data analytics. He has held product... Read More →
Unlock the power of managing infrastructure through code in this dynamic session! You'll dive into the fundamentals of infrastructure as code (IaC) with a focus on AWS CloudFormation. Step-by-step, you'll learn how to write your first template to efficiently create, update, and delete cloud resources.
By the end of this hands-on workshop, you'll have added a valuable skill to your repertoire and be equipped with the knowledge to further explore the vast possibilities of infrastructure as code. Join to enhance your technical skillset and embark on a journey of continuous innovation in cloud infrastructure management.
Jagrut Sharma is a senior software engineer at Adobe, where he leads the architecture and development of services enabling innovative machine-learning solutions and use cases. With over 20 years of experience in technology, Jagrut has contributed to a wide variety of projects across... Read More →
