We primarily use Datadog for logs, APM, infrastructure monitoring, and lambda visibility.

We have built a number of critical dashboards that we display within our office for engineers to have a good understanding of the application performance, as well as business partners to understand at a high level the traffic flowing through the app.

We started with logging, as our primary monitor, and have shifted to APM to get a deeper understanding of what our system is doing, and how the changes we are making impact the apps.

We deploy agents on-premise to collect data on on-premise VM instances. We don't use Datadog in our cloud network. We do have some Cloud apps that we have it on and we also have Containers. We have it on their headquarters, the main software for them is on their own Cloud.

Eventually, we're building out the process now and using it better. We plan to use Datadog for root cause analysis relating to any kinds of issues we have with software, with applications going down, latency issues, connection issues, etc. Eventually, we're going to use Datadog for application performance, monitoring, and management. To be proactive around thresholds, alerts, bottlenecks, etc. 

Our developers and QA teams use this solution. They use it to analyze network traffic, load, CPU load, CPU usage, and then Tracey NPM, API calls for their application. There are roughly 100 users right now. Maybe there's 200 total, but on a given day, maybe 13 people using this solution.

We primarily use Datadog for the monitoring of EC2 and ECS containers running mostly Rails applications that host a SaaS product. We also monitor ElasticSearch and RDS, and we are working on adding their Application Performance Monitoring solution to monitor our applications directly.

We use DataDog to create dashboards, graphs, and alerts based on interesting metrics. DataDog is our first place to look to find the performance of our system.

We also use their logging platform and it works well. Especially useful is that the logs and metrics are tightly integrated so you can jump between them easily.

We were in need of a cloud monitoring tool that was operationally focused on the AWS Platform. We wanted to be able to responsibly and effectively monitor, troubleshoot, and operate the AWS platform, including Server, Network, and key AWS Services.

Tooling that highlighted and detected problems, anomalies, and provided best practice recommendations. Tooling that expedites root-cause analysis and performance troubleshooting.

Datadog provided us the ability to monitor our cloud infrastructure (network, servers, storage), platform/middleware (database, web/applications servers, business process automation), and business applications across our cloud providers.

Our primary use of Datadog includes: 

• Keeping a close look into our AWS resources. Monitoring our multiple RDS and ElastiCache instances play a big role in our indicators.
• Kubernetes. We aren't using all of the available Kubernetes integrations but the few of them that work out of the box adds great value to our metrics.
• Monitoring and alerting. We wired our most relevant monitoring and alerts to services like PagerDuty, and for the rest of them, we keep our engineers up to date with constant Slack updates. 
  

We primarily use DataDog for performance and log monitoring of cloud environments, which include VMs and Azure Services like Azure compute, storage, network, firewall, and app services via event hubs.  

Alerting based on monitors via teams and PagerDuty. 

Logs collection for Azure services like Azure database, Azure Application Gateway, Azure AKS, and other Azure services.

Custom metrics using a Python script to collect metrics for components not natively supported by Datadog.

Synthetic testing to ensure uptime and browser tests via CI/CD pipeline.

We use it for monitoring and instrumentation of security. We secure our databases and servers. It is typically for the security of apps, services, and systems. We are using its latest version.

Our clients use it for monitoring applications. Its deployment depends on our customer's use case. 

It is 100% cloud. We have got a multi-tenant environment, so we segment it out.

We used Datadog to capture the salvatory of our AWS fleet of around 1,200 servers.

My customers were using Datadog for monitoring purposes. They were using it only because the solution is running on AWS and it's a microservices-based solution. They were using an application called Dynatrace for their log.

We use Datadog as a monitoring platform to achieve visibility into our container environments.

Almost all of our workloads are containerized and with DataDog, we are able to get metrics, logs, alerts, and events about all the containers that we are running. Our developers also extensively use APM to find and diagnose performance issues that might appear.

We use Terraform to automatically create all of the necessary monitors and dashboards that our developers need to make sure that our level of service is sufficient.

I'm a senior cloud security engineer and we are customers of Datadog. 

We're in the process of doing a Proof of Concept with the solution right now.

We are evaluating Datadog for observability and monitoring requirements that we have in our company. In our use case, our intention is to provide some kind of framework for multiple app teams to use the tool for our cyber ability and engineering practices.

We use it for our infrastructure network and servers.

I'm not sure which version we're using, although I believe it to be the latest. 

We essentially use the solution in advance of performance testing, performance monitoring, and troubleshooting.

We implement these solutions for our clients. We have implemented Datadog as an SIEM solution.

Our primary use case is log management and we also use the solution for monitoring the application and underlying infrastructure. I'm an IT test manager. 

We use Datadog for application monitor, to help identify errors. It is also used to monitor application performance.

We are currently testing it. If the testing goes well, we'll purchase the full version, and it will probably be our main monitoring tool. We plan to use it for monitoring our activities and the attacks on our systems or network.

We use Datadog to monitor our product on the cloud.

We primarily use this product for availability and performance monitoring, log aggregation.

We have a web infrastructure that uses Amazon Web Services containers with everything included, and we use Datadog to monitor them all.

I am using Datadog for error reporting.

I used Datadog typically for monitoring website statistics and some of the cloud networking equipment.

I implement this solution for clients.

We have used this solution primarily for application performance monitoring. To do this, we needed to make sure we had the right data in the system so that people could be able to monitor their applications end-to-end.