To optimize its cloud investments, your organization needs internal stakeholders to act on shared knowledge about its cloud costs and cloud usage. But in practice, it’s difficult for organizations to gain a high degree of clarity about their cloud spending. The factors contributing to cost data are not normally visible to all stakeholders, and it’s often impossible to attribute costs to the teams, services, and applications that incurred them.

Today at Dash 2022, we announced new products and features that enable your teams to break down information silos, shift testing to the left, monitor cloud and application security, and more. Now, you can analyze cloud cost data alongside other telemetry, create synthetic tests for your mobile applications, and prevent malicious activity in your environment by blocking IPs directly from Datadog. We expanded Sensitive Data Scanner to include APM, RUM, and Events stream data.

For most organizations, GitHub is mission critical. Your GitHub repositories likely also contain some of your organization’s most sensitive data. GitHub provides tools to help you protect and govern this data, with tools such as audit logs, code scanning alerts, and secret scanning alerts. However, analyzing these logs and alerts through GitHub’s UI can be challenging. For example, looking for trends in your code scanning alerts over time through GitHub’s UI is just not possible.

Large organizations often rely on multiple monitoring tools, security platforms, and auditing systems to meet the diverse needs of their observability, security, engineering, and compliance teams. Because these teams may use the same logs for many different use cases—including detecting potential threats or breaches, troubleshooting errors, and gauging the effectiveness of new features—it can be difficult to effectively standardize and route data.

Whether you’re rushing to troubleshoot an incident or proactively performing a security audit, the trial-and-error process of searching through millions of logs for key information can be time-consuming and cumbersome. To help you quickly surface important details from large swaths of log data, Datadog’s Log Explorer allows you to search and filter your logs, create visualizations, as well as group your logs by fields, patterns, or transactions.

Azure Cosmos DB for PostgreSQL is a fully managed relational database service for PostgreSQL that is powered by the open source Citus extension. With remote query execution and support for JSON-B, geospatial data, rich indexing, and high-performance scale-out, Cosmos DB for PostgreSQL enables users to build applications on single- or multi-node clusters.

OpenTelemetry is an open source, vendor-neutral observability framework that provides tools, APIs, and SDKs to collect and standardize telemetry data from cloud-native applications and services. One of OpenTelemetry’s key components is the OpenTelemetry Collector, which receives and processes data before using exporters to route it to the destinations of your choice.

OpenTelemetry is an open source set of tools and standards that provide visibility into cloud-native applications. OpenTelemetry allows you to collect metrics, traces, and logs from applications written in many languages and export them to a backend of your choice.

Google Cloud Run is a managed platform for the deployment, management, and scaling of workloads using serverless containers. You can deploy workloads in the cloud or, using Cloud Run for Anthos, on your on-prem infrastructure.