Logs provide a wealth of information that is invaluable for use cases like root cause analysis and audits. However, you typically don’t need to view the granular details of every log, particularly in dynamic environments that generate large volumes of them. Instead, it’s generally more useful to perform analytics on your logs in aggregate.
RethinkDB is a document-oriented database that enables clients to listen for updates in real time using streams called changefeeds. RethinkDB was built for easy sharding and replication, and its query language integrates with popular programming languages, with no need for clients to parse commands from strings. The open source project began in 2012, and joined the Linux Foundation in 2017.
Understanding how your users experience your application is critical—downtime, broken features, and slow page loads can lead to customer churn and lost revenue. Last year, we introduced Datadog Browser Tests, which enable you to simulate key user journeys and validate that users are able to complete business-critical transactions.
Creating security policies for the devices connected to your network is critical to ensuring that company data is safe. This is especially true as companies adopt a bring-your-own-device model and allow more personal phones, tablets, and laptops to connect to internal services. These devices, or endpoints, introduce unique vulnerabilities that can expose sensitive data if they are not monitored.
Datadog’s AWS integration brings you deep visibility into key AWS services like EC2 and Lambda. We’re excited to announce that we’ve simplified the process for installing the AWS integration. If you’re not already monitoring AWS with Datadog, or if you need to monitor additional AWS accounts, our 1-click integration lets you get started in minutes.
Google Cloud Platform (GCP) is a suite of cloud computing services for deploying, managing, and monitoring applications. A critical part of deploying reliable applications is securing your infrastructure. Google Cloud Audit Logs record the who, where, and when for activity within your environment, providing a breadcrumb trail that administrators can use to monitor access and detect potential threats across your resources (e.g., storage buckets, databases, service accounts, virtual machines).
Microsoft Azure is a cloud computing platform for building, deploying, and managing global-scale applications. With a wide range of offerings, including dozens of different services, Azure provides tools for users to create large and sophisticated systems for hosting any type of workload. But with the huge number of configuration options and resource types, understanding the health and performance of your applications in Azure can be challenging.
Datadog dashboards provide immediate visibility and insight into your environments. Setting template variables enables you to filter your dashboard graphs on the fly to visualize specific sets of tagged objects. Now, with saved views, you can save sets of frequently used template variables in order to easily find the data you most care about with just a few clicks.
Logs are an invaluable source of information, as they provide insights into the severity and possible root causes of problems in your system. But it can be hard to get the right level of visibility from your logs while keeping costs to a minimum. Systems that process large volumes of logs consume more resources and therefore make up a higher percentage of your overall monitoring budget. Further, log throughput can be highly variable, creating unexpected resource usage and financial costs.
As more environments run on Kubernetes—including our own— Datadog has been making it easier to get visibility into clusters of any scale. To minimize load on the Kubernetes API server, the Datadog Agent runs in two different modes. The node-based Agent queries local containers or external endpoints for data, while the Cluster Agent fetches cluster-level metadata from the API server.
