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Datadog is a monitoring and analytics platform for cloud-scale application infrastructure. Combining metrics from servers, databases, and applications, Datadog delivers sophisticated, actionable alerts, and provides real-time visibility of your entire infrastructure. Datadog includes 100+ vendor-supported, prebuilt integrations and monitors hundreds of thousands of hosts.
Datadog
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Machine Box might be a bit more popular than Datadog. We know about 5 links to it since March 2021 and only 5 links to Datadog. 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.
Ideally, if we had access to the underlying infrastructure, we could probably install the Datadog Agent and configure it to send our logs directly to Datadog, or even use AWS Lambda functions or Azure Event Hub + Azure Functions in case we were facing some specific cloud scenarios. - Source: dev.to / almost 3 years ago
Currently supported : Datadog, Jenkins, DNS, HTTP. Source: over 3 years ago
Datadog is a powerful monitoring and security platform that gives you visibility into end-to-end traces, application metrics, logs, and infrastructure. While Datadog has great documentation on their Kubernetes integration, we've observed that there's some missed nuance that leads to common pitfalls. - Source: dev.to / almost 5 years ago
.. Is to see you email address being silently distributed to every single company that I've watched a talk from. And now suddenly get several promotional spam emails per day from some 4-5 different domains like instana.com, datadoghq.com, snyk.io, cockroachlabs.com (some of them send even multiple emails per day!). Source: about 5 years ago
We're commonly doing this with logging, using services such as Loggly or DataDog. We're using managed databases, be it on AWS, Heroku or database-vendor-specific solutions. We're storing binaries on S3. Externalising user authentication and authorization might be a good candidate as well. - Source: dev.to / over 5 years ago
Reminds me of Machine Box (http://machinebox.io). Source: over 3 years ago
Thank you :) I did that to teach dogโs breed to an AI. If you donโt know machine box yet : Https://machinebox.io It seems really cool and easy to use. Source: almost 4 years ago
I think you should go 5 Pi X 5 Jetson Nanoโs I havenโt seen many people offloading the Nanoโs GPU functionality for ML similar to this Serverless style of product. https://machinebox.io/. Source: almost 5 years ago
For face recognition - CompreFace. Disclaimer - I created it, as an alternative you can use MachineBox, but it's not open source and has limits. Also, I think, you will use some software to control the system, e.g. Frigate or Home Assistant, I think this repository can be useful for you. Source: almost 5 years ago
If you have a really simple application, you can just save the encodings into the files. If not - it's better to use a database. SQL is ok. But for the best results, I would suggest using milvus.io, as it was created for saving vectors and finding the distances (I haven't tried it, though). If your final goal is not to learn face recognition basics, you can just use free ready to use solutions like CompreFace... Source: almost 5 years ago
Zabbix - Track, record, alert and visualize performance and availability of IT resources
Medallia - Medallia enables companies to capture customer feedback, understand it in real-time, and take action to improve the customer experience (CX).
NewRelic - New Relic is a Software Analytics company that makes sense of billions of metrics across millions of apps. We help the people who build modern software understand the stories their data is trying to tell them.
DeepAI - Easily build the power of AI into your applications
Dynatrace - Cloud-based quality testing, performance monitoring and analytics for mobile apps and websites. Get started with Keynote today!
Model Zoo - Deploy your machine learning model in a single line of code.