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1 Inside Deloitte Ventures: Strategic Corporate VC Insights on Scaling Startups and Vertical AI Trends 34:07
Scaling Developer Productivity with Apache Kafka ft. Mohinish Shaikh
Manage episode 424666829 series 2510642
Confluent Cloud and Confluent Platform run efficiently largely because of the dedication of the Developer Productivity (DevProd) team, formerly known as the Tools team. Mohinish Shaikh (Software Engineer, Confluent) talks to Tim Berglund about how his team builds the software tooling and automation for the entire event streaming platform and ensures seamless delivery of several engineering processes across engineering and the rest of the org. With the right tools and the right data, developer productivity can understand the overall effectiveness of a development team and their ability to produce results.
The DevProd team helps engineering teams at Confluent ship code from commit to end customers actively using Apache Kafka®. This team proficiently understands a wide scope of polyglot applications and also the complexities of using a diverse technology stack on a regular basis to help solve business-critical problems for the engineering org.
The team actively measures how each system interacts with one another and what programs are needed to properly run the code in various environments to help with the release of reliable artifacts for Confluent Cloud and Confluent Platform. An in-depth understanding of the entire framework and development workflow is essential for organizations to deliver software reliably, on time, and within their cost budget.
The DevProd team provides that second line of defense and reliability before the code is released to end customers. As the need for compliance increases and the event streaming platform continues to evolve, the DevProd team is in place to make sure that all of the final touches are completed.
EPISODE LINKS
- Leveraging Microservices and Apache Kafka to Scale Developer Productivity
- Join the Confluent Community Slack
- Learn more with Kafka tutorials, resources, and guides at Confluent Developer
- Live demo: Kafka streaming in 10 minutes on Confluent Cloud
- Use 60PDCAST to get an additional $60 of free Confluent Cloud usage (details)
265 פרקים
Manage episode 424666829 series 2510642
Confluent Cloud and Confluent Platform run efficiently largely because of the dedication of the Developer Productivity (DevProd) team, formerly known as the Tools team. Mohinish Shaikh (Software Engineer, Confluent) talks to Tim Berglund about how his team builds the software tooling and automation for the entire event streaming platform and ensures seamless delivery of several engineering processes across engineering and the rest of the org. With the right tools and the right data, developer productivity can understand the overall effectiveness of a development team and their ability to produce results.
The DevProd team helps engineering teams at Confluent ship code from commit to end customers actively using Apache Kafka®. This team proficiently understands a wide scope of polyglot applications and also the complexities of using a diverse technology stack on a regular basis to help solve business-critical problems for the engineering org.
The team actively measures how each system interacts with one another and what programs are needed to properly run the code in various environments to help with the release of reliable artifacts for Confluent Cloud and Confluent Platform. An in-depth understanding of the entire framework and development workflow is essential for organizations to deliver software reliably, on time, and within their cost budget.
The DevProd team provides that second line of defense and reliability before the code is released to end customers. As the need for compliance increases and the event streaming platform continues to evolve, the DevProd team is in place to make sure that all of the final touches are completed.
EPISODE LINKS
- Leveraging Microservices and Apache Kafka to Scale Developer Productivity
- Join the Confluent Community Slack
- Learn more with Kafka tutorials, resources, and guides at Confluent Developer
- Live demo: Kafka streaming in 10 minutes on Confluent Cloud
- Use 60PDCAST to get an additional $60 of free Confluent Cloud usage (details)
265 פרקים
כל הפרקים
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1 Apache Kafka 3.5 - Kafka Core, Connect, Streams, & Client Updates 11:25

1 How to use Data Contracts for Long-Term Schema Management 57:28

1 How to use Python with Apache Kafka 31:57

1 Next-Gen Data Modeling, Integrity, and Governance with YODA 55:55

1 Migrate Your Kafka Cluster with Minimal Downtime 1:01:30

1 Real-Time Data Transformation and Analytics with dbt Labs 43:41

1 What is the Future of Streaming Data? 41:29

1 What can Apache Kafka Developers learn from Online Gaming? 55:32

1 How to use OpenTelemetry to Trace and Monitor Apache Kafka Systems 50:01

1 What is Data Democratization and Why is it Important? 47:27

1 Git for Data: Managing Data like Code with lakeFS 30:42

1 Using Kafka-Leader-Election to Improve Scalability and Performance 51:06

1 Real-Time Machine Learning and Smarter AI with Data Streaming 38:56

1 The Present and Future of Stream Processing 31:19

1 Top 6 Worst Apache Kafka JIRA Bugs 1:10:58

1 Learn How Stream-Processing Works The Simplest Way Possible 31:29

1 Building and Designing Events and Event Streams with Apache Kafka 53:06

1 Rethinking Apache Kafka Security and Account Management 41:23

1 Real-time Threat Detection Using Machine Learning and Apache Kafka 29:18

1 Improving Apache Kafka Scalability and Elasticity with Tiered Storage 29:32

1 Decoupling with Event-Driven Architecture 38:38

1 If Streaming Is the Answer, Why Are We Still Doing Batch? 43:58

1 Security for Real-Time Data Stream Processing with Confluent Cloud 48:33

1 Running Apache Kafka in Production 58:44

1 Build a Real Time AI Data Platform with Apache Kafka 37:18

1 Optimizing Apache JVMs for Apache Kafka 1:11:42


1 Application Data Streaming with Apache Kafka and Swim 39:10

1 International Podcast Day - Apache Kafka Edition | Streaming Audio Special 1:02:22


1 Real-Time Stream Processing, Monitoring, and Analytics With Apache Kafka 34:07

1 Reddit Sentiment Analysis with Apache Kafka-Based Microservices 35:23

1 Capacity Planning Your Apache Kafka Cluster 1:01:54

1 Streaming Real-Time Sporting Analytics for World Table Tennis 34:29

1 Real-Time Event Distribution with Data Mesh 48:59

1 Apache Kafka Security Best Practices 39:10

1 What Could Go Wrong with a Kafka JDBC Connector? 41:10

1 Apache Kafka Networking with Confluent Cloud 37:22

1 Event-Driven Systems and Agile Operations 53:22

1 Streaming Analytics and Real-Time Signal Processing with Apache Kafka 1:06:33

1 Blockchain Data Integration with Apache Kafka 50:59

1 Automating Multi-Cloud Apache Kafka Cluster Rollouts 48:29

1 Common Apache Kafka Mistakes to Avoid 1:09:43

1 Tips For Writing Abstracts and Speaking at Conferences 48:56

1 How I Became a Developer Advocate 29:48

1 Data Mesh Architecture: A Modern Distributed Data Model 48:42

1 Flink vs Kafka Streams/ksqlDB: Comparing Stream Processing Tools 55:55

1 Practical Data Pipeline: Build a Plant Monitoring System with ksqlDB 33:56


1 Scaling Apache Kafka Clusters on Confluent Cloud ft. Ajit Yagaty and Aashish Kohli 49:07

1 Streaming Analytics on 50M Events Per Day with Confluent Cloud at Picnic 34:41


1 Optimizing Apache Kafka's Internals with Its Co-Creator Jun Rao 48:54

1 Using Event-Driven Design with Apache Kafka Streaming Applications ft. Bobby Calderwood 51:09

1 Monitoring Extreme-Scale Apache Kafka Using eBPF at New Relic 38:25

1 Confluent Platform 7.1: New Features + Updates 10:01

1 Scaling an Apache Kafka Based Architecture at Therapie Clinic 1:10:56

1 Bridging Frontend and Backend with GraphQL and Apache Kafka ft. Gerard Klijs 23:13
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