Operations | Monitoring | ITSM | DevOps | Cloud

Tracing has become essential for monitoring today’s increasingly distributed architectures. But complex production applications produce an extremely high volume of traces, which are prohibitively expensive to store and nearly impossible to sift through in time-sensitive situations. Most traditional tracing solutions address these operational challenges by making sampling decisions before a request even begins its path through your system (i.e., head-based sampling).

Datadog Synthetic Monitoring allows you to proactively monitor your applications so that you can detect, troubleshoot, and resolve any availability or performance issues before they impact your end users. With our API test suite, you can send simulated HTTP requests to your API endpoints, check the validity of SSL certificates, verify the performance and correctness of DNS resolutions, test TCP connections, and ping endpoints to detect server connectivity issues.

Azure Government is a dedicated cloud for public sector organizations that want to leverage Azure’s suite of services in their highly regulated environments. As these organizations migrate their applications to Azure Government, they need to ensure that they can maintain visibility into the status and health of their entire infrastructure.

At Datadog, we believe that having visibility into production is crucial to building better software, especially as modern environments become more and more complex. Bugs that occur in production are often difficult to reproduce locally, which leaves developers guessing about what went wrong. To solve this problem, teams need the same depth of visibility into their production environments as they do into their local environments.

Within distributed applications, data moves across many loosely connected endpoints, microservices, and teams, making it difficult to know when services are storing—or inadvertently leaking—sensitive data. This is especially true for governance, risk management, and compliance (GRC) or other security teams working for enterprises in highly regulated industries, such as healthcare, banking, insurance, and financial services.

Sending custom metrics to Datadog allows you to monitor important data specific to your business and applications, such as latency, dollars per customer, items bought, or trips taken. And tags are key to being able to slice and dice these custom metrics to quickly find the information you need. But collecting enough custom metrics to have complete visibility can be cost prohibitive. For example, you might run microservices instrumented across thousands of containers.

NS1 is an intelligent DNS and traffic management platform that helps optimize the performance of your network infrastructure and speed application delivery to your end users. Since even a small increase in service latency can lead to churn and revenue loss, it’s critical to remove any inefficiencies embedded in basic network functions. NS1 helps ensure high performance for name resolution and routing through support for the edns0-client-subnet (ECS) DNS extension and for Filter Chain technology.

Monitoring frontend performance and user behavior is essential to ensure that your application is functioning optimally. Datadog RUM enables you to collect key user data and correlate all of it with frontend performance metrics to track how your pages’ performance affects user behavior.

Life happens—even when you’re on-call. You can’t take your laptop everywhere, but whether you’re on the train, at dinner, or at the gym, you can count on the Datadog mobile app for access to key data about the status and performance of your applications. Now, you can use Datadog mobile widgets to build an on-call mobile dashboard directly on your phone’s home screen, so it’s even easier to track the data you care about from anywhere.

To have full visibility into modern cloud environments, businesses need to collect an ever-growing avalanche of log data from a range of highly complex data sources. Indexing logs is key for real-time monitoring and troubleshooting, but it can quickly become expensive at high volumes, meaning that organizations often must choose which logs to index and which to archive.