Datadog vs GitLab

GitLab compared to other DevOps tools

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.

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.