NewRelic
Datadog
Zabbix
Dynatrace
AppDynamics
Prometheus
Sentry.io
Splunk
AWS Deep Learning AMIs
AWS Auto Scaling
IBM Cloud Bare Metal Servers
Amazon Elastic Inference
Amazon Simple Workflow Service (SWF)
MxToolBox
Faronics Deep Freeze
Zing
NewRelic AWS Deep Learning AMIsBased on our record, NewRelic seems to be a lot more popular than AWS Deep Learning AMIs. While we know about 81 links to NewRelic, we've tracked only 3 mentions of AWS Deep Learning AMIs. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
*1. New Relic *— it’s a tool to check on the slow performance of your app. If any action of the user takes longer than usual, NewRelic will inform you about that. - Source: dev.to / 20 days ago
Tip: You can use tools like DataDog, perf (Linux), New Relic etc. To monitor cache performance. - Source: dev.to / about 2 months ago
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 / 2 months ago
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 / 3 months ago
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 / 3 months ago
AWS Deep Learning AMIs can be used to accelerate deep learning by quickly launching Amazon EC2 instances. - Source: dev.to / over 2 years ago
Ok a bit more on topic of your question. Set up a docker locally on your computer, pick a relevant image with all the python stuff and then do pip install -r requirements -t ./dependencies zip it up, upload to S3 and then get it from there and use on the EC2 instance. Or look into using Deep Learning AMIs they should have pytorch installed: https://aws.amazon.com/machine-learning/amis/. Source: about 3 years ago
Literally nothing stops you from running EC2 instance with GPU and configuring it yourself. There are even AMIs specialized for ML workloads with everything preconfigured and ready to use - https://aws.amazon.com/machine-learning/amis/. Source: about 3 years ago
Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.
AWS Auto Scaling - Learn how AWS Auto Scaling monitors your applications and automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost.
Zabbix - Track, record, alert and visualize performance and availability of IT resources
IBM Cloud Bare Metal Servers - IBM Cloud Bare Metal Servers is a single-tenant server management service that provides dedicated servers with maximum performance.
Dynatrace - Cloud-based quality testing, performance monitoring and analytics for mobile apps and websites. Get started with Keynote today!
Amazon Elastic Inference - Utilities, Application Utilities, and Machine Learning as a Service