Say hi to the new GKE: A better default compute for every workload // TRAIN BRAIN

Say hi to the new GKE: A better default compute for every workload

Learn more → https://goo.gle/3InVpHa
GKE Standard mode clusters now support running Google Kubernetes Engine (GKE) Autopilot workloads through the use of ComputeClasses.
Autopilot is a GKE operational mode where Google manages the node infrastructure, scaling, security, and pre-configured features. It is designed to optimize most production workloads by applying recommended settings for security, reliability, performance, and scalability.
This integration means developers no longer need to decide between Autopilot and Standard mode at cluster creation but instead developers can choose the appropriate mode for each individual workload.
? Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech
#GoogleKubernetesEngine #Autopilot
Speakers: Mofi Rahman
Products Mentioned: Google Kubernetes Engine

Google Cloud Tech

Helping you build what's next with secure infrastructure, developer tools, APIs, data analytics and machine learning....

My AI agent crashed and how to save its memory

Gemini vs. the clock: 5 hours to build a FinTech agent

This month in GKE: September edition

Giving your AI agent a "scratchpad" memory

Secure ADK elements with Secret Manager

Validate your Looker workflow from data to dashboard

AI Agent Dance Off: Comparing Design Approaches

The Agent Factory - Episode 10: Agent Security

Why do AI agents forget everything?

Workflow agents and communication in ADK

Build serverless applications in the Cloud Run hackathon

Common Cloud Run errors and how to fix them with Cloud Logging

Deploying A GPU-Powered LLM on Cloud Run

Build an AI app that watches videos using Gemini

Large scale data ingestion for MongoDB using Application Integration

Salesforce bulk data ingestion using Application Integration

How to enable app management for Google Cloud folder

The Agent Factory - Episode 9: Agent evaluation with ADK & Vertex AI

Protect your LookML: Continuous Integration for reliable data

Secure AI: De-identifying data with SDP

Gemini in Google Threat Intelligence

Foundations of multi-agent systems with ADK

What is Looker CI?

Programmable data quality with Dataplex and generative AI

The Looker MCP server: Your data's universal translator for AI

Observability in action: A Google Cloud Next demo

This month in GKE: August edition

Effortless data prep in BigQuery: A low coder's guide

Brunch, Automated: How to Architect AI Agents for Everyday Tasks

Say hi to the new GKE: A better default compute for every workload

The Agent Factory - Episode 8: Agent payments, can you do my shopping?

How to connect Cloud Run to NoSQL Firestore

They built an AI agent in 3 hours: Virtual try on with skin tone detection

The Agent Factory - Episode 7: Gemini CLI with Taylor Mullen

Configure a Java Producer for Google Cloud’s managed Apache Kafka service (step-by-step)

How memory makes AI agents more effective

Build AI Agents on GKE in the GKE Turns 10 Hackathon

Visualizing BigQuery geospatial data in Colab

How to deploy a container image to Cloud Run

The Agent Factory - Episode 4: Remember me: Memory in Agents

Container-Optimized Compute Platform for GKE Autopilot

The Future of Automation: How AI Agents are Revolutionizing Data and Robotics

Enable Looker Studio report generation with one click!

GKE Inference Reference Architecture, Your Blueprint for Production-Ready Inference

This Month in GKE: July Edition

The Agent Factory - Episode 3: Building Custom Tools for Agents

The future of AI architecture: Using agents to supervise other agents

What is Private Google Access?

Defining AI agents: From definitions to stopping conditions

The AI Agent Bake-Off Ep.1 Trailer / Can They Build an AI Agent in 3 Hours?

The AI Agent Bake-Off Ep.1 | Can they build an AI Agent in 3 hours?

Roll & Score: Evolve arcade with AI

How to use Agentspace search on Google Distributed Cloud

AI Agents: From concept to code

Let’s build a GenAI app on Cloud Run

Save time and follow data best practices with Looker Blocks!

Unlock AI Potential: Introducing the Google Cloud & NVIDIA Community

Self Serving Allowlisting of Privileged Apps on GKE Autopilot

The Agent Factory - Episode 2: Multi-Agent Systems, Concepts & Patterns

Develop with Looker and Looker Studio

Is your Infrastructure Ready for GPUs and AI Agents?

Build AI agents with Cloud Run and Firebase Genkit

The Agent Factory - Episode 1: Agents, their frameworks and when to use them

Agentic Business Intelligence done right

Ways to enhance your developers’ productivity with Gemini

Platform engineering: building a developer platform

Develop with Looker Studio Community Connectors and Visualizations

How to Turn Images Into Animated Stories Using Gemini and Veo 2

Secure Your AI Lifecycle with AI Protection in Security Command Center

Build AI Agents in the Agent Development Kit Hackathon

This Month in GKE: April Edition

Ground Gemini with Google Search with the Gen AI SDK

Effortless Image Editing + Animation with Gemini 2.0 Flash and Veo 2

Scaling your tuned models with Cloud Run

Optimizing AI infrastructure for modern retail

Watch devs analyze Formula E races with Google Cloud

Sentiment analysis with LLMs/BQML over your data

How to optimize costs and fuel innovation by moving VMware to Google Cloud

How Google Cloud makes AI scale at unbelievable speed!

AI Crash Course: From Still to Motion: Create Visuals & Videos with Imagen 3 and Veo 2