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Containers

48 posts
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  • 3 min
  • Engineering
  • Tools

Monitor Kubernetes Cloud Costs With Open Source Tools

OpenCost is a cloud cost monitoring tool that integrates seamlessly with Kubernetes, allowing you to track your cloud spend in real-time so you can optimize your resources accordingly. Kubernetes is a powerful platform for managing dynamic containerized applications in the cloud, but it may be difficult to understand where costs are incurred. Managing the cost efficiency of Kubernetes resources can be a challenge. That’s where OpenCost comes in. OpenCost is a cloud cost monitoring tool that integrates seamlessly with Kubernetes, allowing you to track your cloud spend in real-time so you can optimize your resources accordingly. OpenCost is an open source CNCF Sandbox project and specification for…
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  • 7 min
  • Cloud-Native
  • Design
  • Engineering
  • Technology

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,…
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  • 5 min
  • Engineering
  • Software Engineering

How To Reduce Costs Via Dense Google Kubernetes Engine (GKE) Cluster Packing

Greetings everyone! Today we would like to share our experience using Google Kubernetes Engine to manage our Kubernetes clusters. We’ve been using it for the latest three years in production and are pleased that we no longer have to worry about managing these clusters ourselves. Currently, we have all our test environments and unique infrastructure clusters under the control of Kubernetes. Today, we want to talk about how we encountered an issue on our test cluster and how we hope this article will save others time and effort. We must provide information about our test infrastructure to understand our problem…
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  • 8 min
  • Computing
  • Design
  • Engineering

You Get What You Pay For: Principles For Designing A Chargeback Process

Principles for designing a chargeback process As large organizations increase their cloud footprint, it becomes critical to ensure costs are being managed effectively. A good understanding of the cost of running each workload, and the value that workload brings to your business, allows organizations to have confidence in the efficiency of their cloud consumption — which is why we see many customers who are successful in driving financial accountability and cost efficiency embrace the Cloud FinOps framework. One crucial capability of Cloud FinOps is chargeback, which is the process of mapping cloud consumption to internal consumers within your organization and…
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  • 5 min
  • Platforms

Improved gVisor File System Performance For GKE, Cloud Run, App Engine And Cloud Functions

Flexible application architectures, CI/CD pipelines, and container workloads often run untrusted code and hence should be isolated from sensitive infrastructure. One common solution has been to deploy defense-in-depth products (like GKE Sandbox which uses gVisor) to isolate workloads with an extra layer of protection. Google Cloud’s serverless products (App Engine, Cloud Run, Cloud Functions) also use gVisor to sandbox application workloads. However, adding layers of defense can also introduce new performance challenges. We discovered one such challenge when gVisor’s user space kernel required several operations to walk file system paths. To address this and significantly increase gVisor performance, we wrote…
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  • 3 min
  • Engineering
  • Solutions
  • Technology

These Retailers Have One Thing In Common

They run containers on Google Cloud. Why is that important and why should you care? Containers are at the heart of modern applications. According to the 2022 State of DevOps report, containers have been the number one deployment target for primary services and applications for the past two years, and adoption continues to accelerate rapidly. Nowhere is this more evident than in the retail industry. In a world where improving inventory margins and operational efficiency is a top priority, containers allow retail organizations’ IT teams to do just that. Google pioneered container technologies and Google Cloud is optimized for containers.…
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  • 5 min
  • Automation

Building An Automated Serverless Deployment Pipeline With Cloud Build

You’ve got a shiny new application ready to deploy to the cloud. After researching your options, you land on using Cloud Run with Cloud Build to build and push your containerized application code to an Artifact Registry repository. In three steps, using a Dockerfile and a Cloud Build configuration you build your container, push it to Artifact Registry, and deploy it to Cloud Run: The example above combines the build, push and deployment steps into one Cloud Build job. This blog will show you what this could look like as a series of manual deployment steps, and how it can…
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  • 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…
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  • 3 min
  • Engineering
  • Software

Skaffold V2 GA: Further Enhancing Developer Productivity

For years, Google has been committed to maximizing developer productivity. In 2019, we announced the general availability of Skaffold, a command-line tool that facilitates continuous development and delivery for containerized applications. Today, we’re excited to announce that Skaffold V2 is now generally available. Skaffold V2 expands Skaffold’s supported platforms and architectures with the introduction of Cloud Run as a supported deployer, and now supports building from and deploying to both ARM and x86 architectures. Skaffold V2 also offers enhanced support for CI/CD and GitOps workflows, with the introduction of the skaffold render phase, verify phase, and kpt integration. Best of…
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  • 3 min
  • Engineering
  • Technology

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…
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