filmov
tv
Scaling Kubernetes, Microservices, and Ephemeral Environments

Показать описание
Scaling Kubernetes, Microservices, and Ephemeral Environments. Speedscale founder Ken Ahrens discusses the challenges of scaling Kubernetes in a microservices and containerized environment and their approach to address these issues by providing a solution for efficient development and ephemeral environments. It includes using real-traffic replays and service mocking to help find bottlenecks and figure out where to tune development environments.
Video 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 👋
🔗 Links:
#scaling #Kubernetes #Microservices #Ephemeral #Environments #k8s #kubernetesarchitecture #scalability #microservice
Chapters
00:00 - Intro
01:00 - Ken Ahrens of Speedscale
02:12 - Different approach to load testing
04:44 - how does Speedscale help scale k8s?
07:40 - service mocking
09:00 - it's for development, not just production
10:30 - how to scale the components of kubernetes
12:20 - Example of tuning making a big difference
16:55 - how to find out more about this solution?
18:30 - Outro
Video 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 👋
🔗 Links:
#scaling #Kubernetes #Microservices #Ephemeral #Environments #k8s #kubernetesarchitecture #scalability #microservice
Chapters
00:00 - Intro
01:00 - Ken Ahrens of Speedscale
02:12 - Different approach to load testing
04:44 - how does Speedscale help scale k8s?
07:40 - service mocking
09:00 - it's for development, not just production
10:30 - how to scale the components of kubernetes
12:20 - Example of tuning making a big difference
16:55 - how to find out more about this solution?
18:30 - Outro