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.
Google Cloud Monitoring might be a bit more popular than Datadog. We know about 7 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 / about 2 years ago
Currently supported : Datadog, Jenkins, DNS, HTTP. Source: almost 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 / about 4 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: over 4 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 4 years ago
Monitoring: Use Cloud Monitoring and Cloud Logging to track the performance of both Gemma and your LangChain application. Look for error rates, latency, and resource utilization. - Source: dev.to / 8 months ago
Autoscaling based on container CPU usage, allowing for efficient resource allocation and improved integration with Cloud Monitoring for better performance insights. - Source: dev.to / over 1 year ago
In this article, weโll look at one of the ways to monitor the InterSystems IRIS data platform (IRIS) deployed in the Google Kubernetes Engine (GKE). The GKE integrates easily with Cloud Monitoring, simplifying our task. As a bonus, the article shows how to display metrics from Cloud Monitoring in Grafana. - Source: dev.to / over 1 year ago
Cloud Run emits some metrics by default, like CPU usage, memory usage, number of instances. You can build dashboards based on those metrics in Cloud Monitoring. Source: over 2 years ago
Monitoring and Logging: Utilize tools like Cloud Monitoring and Cloud Logging to keep a close eye on the performance and progress of your scheduled tasks. - Source: dev.to / over 2 years ago
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