We use cookies to ensure that we give you the best experience on our website. By continuing your visit on the website, you consent to the use of the cookies. If you want to find out more about the cookies we use, you can access our Privacy Policy.
A service mesh is a configurable, low‑latency infrastructure layer designed to handle a high volume of network‑based interprocess communication among application infrastructure services using application programming interfaces (APIs).
About this event
Let's Get Started with Service Meshes!
We are having Shivay Lamba with us, giving a talk on Getting Started with Service Meshes, Shivay is a Google Summer of Mentor, MLH Fellow. He is an active community member and former messmate of Layer5 which is a service mesh community and has projects like Meshery incubated in the CNCF Landscape.
Key takeaway's from the event:
1. What are Service Meshes?
2. Why do we need Service Meshes?
3. Different categories of Service Meshes.
Speaker
Shivay Lamba
Google Summer Of Code Mentor Dev Advocate at Fabric Contributor at Layer5
Shivay is a Google Summer of Mentor, MLH Fellow, Dev Advocate at Fabric. He is an active community member and former meshmate of Layer5 which is a service mesh community and has projects like Meshery incubated in the CNCF Landscape.
Shivay is a Google Summer of Mentor, MLH Fellow, Dev Advocate at Fabric. He is an active community member and former meshmate of Layer5 which is a service mesh community and has projects like Meshery incubated in the CNCF Landscape.
Ritesh Yadav is a Jr. Data Scientist at Ineuron.ai.He is a core contributor to the CNCF Porter Project, a tool to package your application artifact, client tools, configuration, and deployment logic together as a versioned bundle. He is also a Kaggle Notebook Master, NLP Researcher, and loves to work with DevOps tools. Ritesh has been actively involved in the open-source community for over a year, helping many open-source DevOps tools and CNCF Projects like Meshery, Keptn, TensorFlow, Ansible, and Thanos through his contributions, apart from this he has also worked in building end to end scalable Machine Learning Pipelines. He is motivated to contribute to the development of emerging technologies including Cloud Computing, Natural Language Processing, and Conversational AI.