Operations | Monitoring | ITSM | DevOps | Cloud

Datadog on Building Reliable Distributed Applications Using Temporal

Temporal is an open source platform to build resilient and reliable distributed systems. Datadog started using Temporal in 2020 as the foundation for our internal software delivery platform. Since then, its usage has been widely adopted as a platform that any engineering team can use to build their systems. In this Datadog on episode, Ara Pulido chats with Loïc Minaudier, Senior Software Engineer in the Atlas team, responsible for providing a developer platform on top of Temporal, and Allen George, Engineering Manager in the Datadog Workflows team.

Introducing the Datadog Architecture Center

To prevent visibility gaps in your cloud environment, you need to efficiently deploy observability solutions that integrate easily with key technologies in your stack and scale reliably with new applications and migrated workloads. But observability deployments can be complex, often requiring deep and specific knowledge that may not be available within your teams.

Track and troubleshoot MongoDB performance with Datadog Database Monitoring

Many modern applications rely on MongoDB and MongoDB Atlas to manage growing data volumes and to provide flexible schema and data structures. As organizations adopt these and other NoSQL databases, effective monitoring and optimization become critical, especially in distributed environments.

Ensure high service availability with Datadog Service Management

Adopting a cloud-based, distributed architecture may help your organization scale quickly, but it can also add complexity. Correlating telemetry, security signals, and alerts across services often proves difficult, resulting in slower issue remediation. Additionally, when something goes wrong, figuring out who to contact—for example, the on-call responder or the service owner— may become needlessly time-consuming.

Best practices for monitoring cloud costs with Datadog Scorecards

To ensure that your organization’s cloud spend is efficient, you need detailed and granular visibility to understand what comprises your costs, what causes them to change, and how the cloud services and resources you use are enabling your business goals. Extending your visibility and more closely monitoring your cloud costs can position you to successfully adopt FinOps, which provides a framework that can help you maximize the value you get from your cloud spend.

Detect issues, manage incidents, and streamline workflows with Datadog's Microsoft Teams integration

Microsoft Teams is deeply embedded in many organizations’ workflows, acting as a hub to both communicate and collect information about issues and ongoing projects. However, as with most communication platforms, it can be challenging to context-switch between conversations, tickets, and monitoring data when troubleshooting collaboratively.

This Month in Datadog: Google Gemini integration, Unified Error Tracking, and more

Datadog is constantly elevating the approach to cloud monitoring and security. This Month in Datadog updates you on our newest product features, announcements, resources, and events. To learn more about Datadog and start a free 14-day trial, visit Cloud Monitoring as a Service | Datadog. This month, we put the Spotlight on Datadog LLM Observability’s native integration with Google Gemini.

How Appfolio uses Datadog LLM Observability to deliver exceptional GenAI experiences

Learn how Appfolio is delivering positive customer experiences in real estate with generative AI — supported and safeguarded by Datadog’s LLM Observability. See how you can use Datadog LLM Observability to monitor, troubleshoot, improve, and secure your LLM applications.