Cloud GPU VS NewRelic

Cloud GPU Reviews

NewRelic Reviews

Cloud GPU mentions (7)

• Does Google Cloud GPU use physical GPUS or are they emulated

  Per https://cloud.google.com/gpu, they use NVIDIA L4, P100, P4, T4, V100, and A100 GPUs. These are physical units loaded into servers and then shared to the OS by the hypervisor. Source: about 1 year ago

• Fine-tuning?

  You probably can't do it through onedrive, though I'm not sure if MS has something like that that carries over into other services. The thing you need is GPU power, not storage. Most people use something like google cloud https://cloud.google.com/gpu but there are a lot of other options. Source: about 1 year ago

• Home Server - Student

  Uh, you ask these questions before you buy the hardware. There are various tools you could have used for free, or for cheap instead of spending $2500 on equipment, and not even seemingly the right equipment. You would know more than me, but you mentioned AI/Machine learning, but I do not see any graphics cards mentioned in your build, and a lot of that work is enhanced with graphic cards. (3 of these or just this... Source: over 1 year ago

• The machine learning models I am running requires GPU. Is there a way to SSH into another computer and use another computer's GPU?

  Why are you not running in google colab? Https://cloud.google.com/gpu. Source: over 1 year ago

• Reasons to be cheerful: 'GPU mining is dead less than 24 hours after the merge'

  Unless you are spinning up GPUs in the cloud with stolen credentials/credit cards. https://cloud.google.com/gpu. Source: over 1 year ago

NewRelic mentions (80)

• Caching in depth

  Tip: You can use tools like DataDog, perf (Linux), New Relic etc. To monitor cache performance. - Source: dev.to / 22 days ago

• How to Handle N+1 Queries for Optimal Database Performance in Django?

  Using APM tools like NewRelic, Sentry, Datadog, etc to monitor the performance of your application and while you're on it, they can help you identify N+1 queries. - Source: dev.to / about 1 month ago

• How to improve page load speed and response times: A comprehensive guide

  These tools track server and underlying infrastructure and backend performance. They monitor several metrics, like disk I/O, CPU and memory usage, network traffic, and more. Some examples of these tools include New Relic, Datadog, and AppDynamics. Web administrators can use them to see what's causing slow SRT, like high CPU usage or network traffic. Server-side monitoring tools also provide real-time alerts to... - Source: dev.to / 2 months ago

• Experience Continuous Integration with Jenkins | Ansible | Artifactory | SonarQube | PHP

  11 Application performance: Before we even perform a deployment, we should configure monitoring tools like Retrace, DataDog, New Relic, or AppDynamics to look for performance problems, hidden errors, and other issues. During and after the deployment, we should also look for any changes in overall application performance and establish some benchmarks to know when things deviate from the norm. - Source: dev.to / 2 months ago

• Breaking the 300 barrier

  Recently, we have been experiencing some Latency issues. The reason being the increase in our userbase as more companies are adopting our platform to do their procurement efficiently. Our core product is a monolith rails application served on AWS servers. We use AWS ELB's Application load balancer to swiftly balance the load on multiple servers and increase them when needed. So, these sudden latency issues caused... - Source: dev.to / 2 months ago