GKE Archives - aster.cloud

7 min

5 GKE Features To Help You Optimize Your Clusters

In this post, we’ll be discussing 5 features in GKE you can use to optimize your clusters today. To get started with testing these in GKE, check out our interactive tutorials for getting started with standard and autopilot clusters. If you find value from running workloads on Kubernetes clusters in your organization, chances are your footprint will grow – be it through larger clusters or more clusters. Whichever your approach, one thing is certain: you’ll have more resources that you pay for. And you know what they say – more resources, more problems. The more resources you have across clusters,…

4 min

Developer Research Deep Dive: Let’s Build Faster Together

We like hearing feedback, and you’re not shy about giving it to us. Excellent! Each day, you reach us through our Twitter account, Innovator’s Program forums, and even when we meet in person at industry events. Your feedback helps us better understand what you need, what’s not working right, and how we can make your cloud experience better. Another way we hear from our customers? Independent research. Third-party research allows us to get a better understanding of how our products stack up against the competition. We just finished some new research that I want to tell you about. What did…

9 min

Technology

Monitoring GPU Workloads On GKE With NVIDIA Data Center GPU Manager (DCGM)

Artificial intelligence (AI) and machine learning (ML) have become an increasingly important enterprise capability, including use cases such as product recommendations, autonomous vehicles, application personalization, and automated conversational platforms. Building and deploying ML models demand high-performance infrastructure. Using NVIDIA GPUs can greatly accelerate the training and inference system. Consequently, monitoring GPU performance metrics to understand workload behavior is critical for optimizing the ML development process. Many organizations use Google Kubernetes Engine (GKE) to manage NVIDIA GPUs to run production AI inference and training at scale. NVIDIA Data Center GPU Manager (DCGM) is a set of tools from NVIDIA to manage…

9 min

Engineering

How GKE & Anthos Container-Aware Load Balancing Increases Applications’ Reliability

Reliability of a system can be measured based on several factors, including, but not limited to, performance, resilience and security. Nevertheless, resiliency is one of the key factors. For more information on how to architect and operate reliable services on a cloud platform, refer to the reliability category of Google Cloud Architecture Framework. This blog focuses on the optimization of network connectivity performance to containers hosted on Google Kubernetes Engine (GKE), as well as optimized resiliency of containerized applications with the direct visibility of a container’s health from an external load balancer.In a previous blog, we discussed the architecture components…

7 min

Engineering

Traffic Director: TLS Routing Using Envoy Gateway Proxy On GKE

A common pattern for solving application networking challenges is to use a service mesh. Users familiar with such architectures face challenges related to network flow, security, and observability. Traffic Director is a managed Google service that helps solve these problems.In this blog, we are going to share a sample architecture, using Traffic Director to configure gateway proxies, running on a GKE cluster, with TLS routing rules to route traffic from clients outside of the cluster to workloads deployed on the cluster.Furthermore, we will demonstrate how north-south traffic could enter the service mesh using the Envoy proxy acting as an ingress…

3 min

Announcing New GKE Functionality For Streamlined Security Management

At Google Cloud, we’re driven by a vision of invisible security, where advanced security capabilities are engineered into our platforms, operations are simplified, and stronger security outcomes can be achieved. As we pursue this ideal, we want to help make security easier to use and manage. Our new built-in Google Kubernetes Engine (GKE) security posture dashboard (now available in Preview) does both, with opinionated guidance for customers that can help improve the security posture of your GKE clusters and containerized workloads. It also includes insights into vulnerabilities and workload configuration checks, and offers integrated event logging so you can subscribe…

4 min

Accelerating App Development Lifecycle With Managed Container Platforms, Firebase And CI/CD

We understand that for startups in the build phase, the highest priority task is to continuously ship features based on your users’ needs. There are three main focus areas when building applications: Development: When it comes to development, focus on tasks that make your app unique by offloading backend setup and processing to someone else. For example, instead of setting up your own API servers and managing backend services, Firebase offers a managed experience. Hosting: Once you’ve built your app, the next step is to host it. Containers have become the de facto way of packaging applications today. You can…

4 min

Engineering

Introducing Custom Organization Policy For GKE To Harden Security

Compliance officers and platform engineering teams often find it challenging to ensure security, manage consistency, and oversee governance across multiple products, environments, and teams. Google Cloud’s Organization Policy Service can help tackle this challenge with a policy-based approach that simplifies policy administration across Google Cloud resources and projects. We’re excited to announce the Preview release of Custom Organization Policy, and to showcase the integration with Google Kubernetes Engine (GKE). Custom organization policy for GKE can improve security and efficiency using guardrails you define tailored to your organization’s needs, and it’s offered to Google Cloud customers at no additional cost. A…

4 min

Introducing A Modern Cloud Native Approach For Running Moodle At Scale

Even before 2020, the education market was rapidly leaning into digitalization. That trend exploded when the pandemic forced education online, requiring every part of the education process to be digitized. Interaction between students and teachers shifted from physical classrooms to entirely digital ones. Institutions had to work quickly to support this shift. Most either expanded their e-learning platform’s computational capacity to support the influx of users or quickly created new platforms to adhere to “new” digital demand. These e-learning platforms, also known as Learning Management Systems (or LMS’s), already played an important role in educational institutions. However, the pandemic changed…

6 min

How Let’s Enhance Uses NVIDIA AI And GKE To Power AI-Based Photo Editing

There’s an explosion in the number of digital images generated and used for both personal and business needs. On e-commerce platforms and online marketplaces for example, product images and visuals heavily influence the consumer’s perception, decision making and ultimately conversion rates. In addition, there’s been a rapid shift towards user-generated visual content for ecommerce — think seller-generated product imagery, host-generated rental property photos and influencer-generated social media content. The challenge? These user-generated images are often captured using mobile cameras and vary greatly in terms of their size, quality, compression ratios and resolution, making it difficult for companies to provide consistent…

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