Datadog vs GitLab
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Summary
Datadog is a SaaS-bases data analytics platform monitoring service for cloud-scale applications that provides monitoring of servers, databases, tools, and services. Datadog uses a Go based agent and supports cloud service providers Amazon Web Services, Microsoft Azure, Google Cloud and RedHat OpenShift.
GitLab has a powerful monitoring capability with Prometheus, a time-series monitoring service, providing a flexible platform for monitoring GitLab and other software products. GitLab provides out of the box monitoring with Prometheus, providing easy access to high quality time-series monitoring of GitLab services. GitLab has built-in monitoring that can automatically monitor your deployed applications, with extensive support for native cloud, container and microservices technology. Additionally, Gitlab uses Jaeger, an open source end-to-end distributed tracing system used for monitoring and troubleshooting microservices-based distributed systems.
Resources
| FEATURES |  |  |
|---|---|---|
| Synthetic Transaction Monitoring
The ability to monitor websites using Web browser emulation or scripted recordings of Web transactions. Creating behavioral scripts to simulate an action or path performed by a customer/end-user that would be taken on an application | ||
| Cloud Native Monitoring
The monitoring of cloud native applications including micorservices that are built to run in the cloud so that bottlenecks and issues can be addressed via insights into collected metrics. | ||
| Server Monitoring
Reviewing and analyzing a server for availability, operations, performance, security and other operations-related processes. Monitor servers system resources like CPU Usage, Memory Consumption, I/O, Network, Disk Usage, Process, etc. GitLab uses the Node Exporter (via Prometheus) to expose an extensive set of machine-level metrics on Linux and other Unix systems such as CPU usage, memory, disk utilization, filesystem fullness, and network bandwidth. | ||
| Log Correlation
The monitoring of servers, application, network and security devices via generated log files to identify errors and problems for analysis. GitLab makes it easy to view the logs of running pods in connected Kubernetes clusters. By displaying the logs directly in GitLab, developers can avoid having to manage console tools or jump to a different interface. | ||
| Baselining
Measures an application’s performance and tells whether it meets the service level agreements before it goes live to customers. Used for a product’s or platform’s continuous performance analysis and monitorin | ||
| Real User Monitoring (RUM)
Records user interaction with a client interacting with a server or cloud-based application. Determines if users are being served quickly and without errors and, if not, which part of a business process is failing | ||
| Topology
Network mapping that provides real-time views and performance monitoring of network devices, services, applications, connections and traffic patterns on one or more networks | ||
| Tracing
Tracing provides insight into the performance and health of a deployed application, tracking each function or microservice which handles a given request. This makes it easy to understand the end-to-end flow of a request, regardless of whether you are using a monolithic or distributed system. |
If you feel there are inaccurate statements in this comparison or a tool missing, please edit this page or propose edits by opening an issue. You can also send an email to devopstools@gitlab.com with your suggested edits if you're unable to open an issue or edit this page.
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