What is Microservices Architecture?
Microservices architecture (often shortened to microservices) refers to an architectural style for developing applications. Microservices allow a large application to be separated into smaller independent parts, with each part having its own realm of responsibility. To serve a single user request, a microservices-based application can…
Architecture: Scalable commerce workloads using microservices
Retail commerce requirements and microservices Retail commerce workloads require a number of cloud-native features in order to meet demand from an ever-growing number of consumer devices and platforms: Typically, these deployments must be multi-region to serve a global customer base. They must support some degree…
Using GPUs for Training Models in the Cloud
Graphics Processing Units (GPUs) can significantly accelerate the training process for many deep learning models. Training models for tasks like image classification, video analysis, and natural language processing involves compute-intensive matrix multiplication and other operations that can take advantage of a GPU’s massively parallel architecture….
Tokopedia’s journey to creating a Customer Data Platform (CDP) on Google Cloud Platform
Founded in 2009, Tokopedia is an ecommerce platform that enables millions of Indonesian to transact online. As the company grows, there is an urgent need to better understand customer’s behavior in order to improve the customer’s experience across the platform. Now, Tokopedia has more than…
Managing ML data sets with Vertex AI
Many enterprises want to use data to make meaningful predictions that can bolster their business or help them venture into new markets. This often requires using custom machine learning models—something not every business knows how to create or use. This is where Vertex AI can…
Use Deep Learning VM Images and Deep Learning Containers with Vertex AI
Deep Learning VM Overview Deep Learning VM Images is a set of virtual machine images optimized for data science and machine learning tasks. All images come with key ML frameworks and tools pre-installed. You can use them out of the box on instances with GPUs…
Introduction to Vertex AI
Vertex AI is Google Cloud’s end-to-end ML platform for data scientists and ML engineers to accelerate ML experimentation and deployment. The platform unifies Google Cloud’s existing ML offerings into a single environment for efficiently building and managing the lifecycle of ML projects. Vertex AI brings…
M&S: Calling on Google Cloud for personalized customer service that’s both digital and human
Marks & Spencer implements Google Cloud speech recognition to automate calls to stores, increase personalization, and better serve its customers through digitally enabled contact centers. Google Cloud results Improves efficiency by automating 13 in-store switchboards in the UK and Ireland and migrating stock availability calls…
Getting Started with GKE Image Streaming
Google Cloud excited to announce the general availability of a new feature in Google Kubernetes Engine (GKE): image streaming. This revolutionary GKE feature has the potential to drastically improve your application scale-up time, allowing you to respond to increased user demand more rapidly, and save money by…
Tokopedia: Scaling to accommodate major shopping events with Google Kubernetes Engine
Google Cloud results Enables Tokopedia Play to handle a 20x increase in traffic thanks to Google Cloud Supports growth by optimally scaling up to 30x with automated provisioning Reduces operating costs by 90% by migrating to Google Cloud How do you prepare for an epic…
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Recent Posts
- Dataproc Serverless: Now faster, easier and smarter
- Tips and tricks for project management with Google Workspace
- Doubling calculation speed and other new innovations in Google Sheets
- Continued growth and success in the competitive logistics market
- How to get started with new Gemini model capabilities for Places API
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