Search a title or topic

Over 20 million podcasts, powered by 

Player FM logo
Artwork

Content provided by SMC Journal. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SMC Journal or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Player FM - Podcast App
Go offline with the Player FM app!

Scaling Kubernetes, Microservices, and Ephemeral Environments

19:32
 
Share
 

Manage episode 434405325 series 3521006
Content provided by SMC Journal. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SMC Journal or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Speedscale addresses the challenges of scaling Kubernetes in a microservices and containerized, ephemeral environment. This includes real-traffic replays and service mocking to find bottlenecks and tune production and development environments.

This episode sponsored by SpeedScale https://bit.ly/46KFWbY

Insights on Scaling Kubernetes

🔍 Speedcale helps developers figure out if their code is about to blow up before pushing it into production by creating production conditions in their staging environments and local development machines.
🌐 Kubernetes enables teams to build microservice architectures, breaking the monolith into pieces and allowing for individual scaling of each component.
🚀 The ability to make small code changes and quickly push them to production with Kubernetes provides a time to market advantage for companies.
🚀 Speed and scale are key capabilities for teams testing their code in Kubernetes environments, not just for simulating production.
📊 Monitoring data and load testing are crucial for defining the memory and CPU needs of workloads in Kubernetes environments.
🚀 Scaling Kubernetes clusters can be challenging, but innovations like Carpenter can help manage node sizing and resource allocation effectively.
🔍 Using production monitoring data from tools like New Relic and DataDog can help in tuning production and non-production environments for Kubernetes and microservices.
🔮 Mocking out dependencies with one command line tool can revolutionize the development process and improve developer satisfaction.

🔥 Like and Subscribe 🔥

Connect with me 👋
TWITTER ► https://bit.ly/3HmWF8d
LINKEDIN COMPANY ► https://bit.ly/3kICS9g
LINKEDIN PROFILE ► https://bit.ly/30Eshp7

Want to support the show? Buy Me A Coffee! https://bit.ly/3NadcPK

🔗 Links:

  continue reading

77 episodes

Artwork
iconShare
 
Manage episode 434405325 series 3521006
Content provided by SMC Journal. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SMC Journal or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Speedscale addresses the challenges of scaling Kubernetes in a microservices and containerized, ephemeral environment. This includes real-traffic replays and service mocking to find bottlenecks and tune production and development environments.

This episode sponsored by SpeedScale https://bit.ly/46KFWbY

Insights on Scaling Kubernetes

🔍 Speedcale helps developers figure out if their code is about to blow up before pushing it into production by creating production conditions in their staging environments and local development machines.
🌐 Kubernetes enables teams to build microservice architectures, breaking the monolith into pieces and allowing for individual scaling of each component.
🚀 The ability to make small code changes and quickly push them to production with Kubernetes provides a time to market advantage for companies.
🚀 Speed and scale are key capabilities for teams testing their code in Kubernetes environments, not just for simulating production.
📊 Monitoring data and load testing are crucial for defining the memory and CPU needs of workloads in Kubernetes environments.
🚀 Scaling Kubernetes clusters can be challenging, but innovations like Carpenter can help manage node sizing and resource allocation effectively.
🔍 Using production monitoring data from tools like New Relic and DataDog can help in tuning production and non-production environments for Kubernetes and microservices.
🔮 Mocking out dependencies with one command line tool can revolutionize the development process and improve developer satisfaction.

🔥 Like and Subscribe 🔥

Connect with me 👋
TWITTER ► https://bit.ly/3HmWF8d
LINKEDIN COMPANY ► https://bit.ly/3kICS9g
LINKEDIN PROFILE ► https://bit.ly/30Eshp7

Want to support the show? Buy Me A Coffee! https://bit.ly/3NadcPK

🔗 Links:

  continue reading

77 episodes

ทุกตอน

×
 
Loading …

Welcome to Player FM!

Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.

 

Copyright 2025 | Privacy Policy | Terms of Service | | Copyright
Listen to this show while you explore
Play