Operations | Monitoring | ITSM | DevOps | Cloud

As customers scale to thousands of hosts and deploy increasingly complex applications, it can be difficult to ensure that every host is configured to give you the visibility you need to monitor your infrastructure and applications. To ensure visibility across a growing number of hosts, you need to know that your observability strategy is implemented uniformly across your entire fleet of Datadog Agents installed on these hosts.

Datadog customers have an abundance of observability data at their fingertips. Using this data effectively requires having the right visualizations and analysis tools. For some teams, the powerful functionality of spreadsheets is critical to their ability to make data-driven forecasting and business decisions. That’s why we are pleased to announce that Actiondesk—a spreadsheet-powered connection to your live data—is joining Datadog.

The Datadog Service Catalog is a centralized hub of information around the performance, reliability, security, efficiency, and ownership of your distributed services. By using the Service Catalog, teams can eliminate knowledge silos and realize seamless DevSecOps workflows.

Incidents put systems and organizations to the test. They pose particular challenges at scale: in complex distributed environments overseen by many different teams, managing incidents requires extensive structure and planning. But incidents, by definition, break structures and foil plans. As a result, they demand carefully orchestrated yet highly flexible forms of response. This post will provide a look into how we manage incidents at Datadog. We’ll cover our entire process.

In this year’s report, we see how organizations are using containers not just to solve their day-to-day infrastructure needs. Rather, customers are exploring the next technology frontier of containers by building next-generation applications, enhancing developer productivity, and optimizing costs.

In a rapidly expanding, highly distributed cloud infrastructure environment, it can be difficult to make decisions about the design and management of cloud architectures. That’s because it’s hard for a single observer to see the full scope when their organization owns thousands of cloud resources distributed across hundreds of accounts. You need broad, complete visibility in order to find underutilized resources and other forms of bloat.

Modern distributed applications are composed of potentially hundreds of disparate services, all containing code from different internal development teams as well as from third-party libraries and frameworks with limited external visibility. Instrumenting your code is essential for ensuring the operational excellence of all these different services. However, keeping your instrumentation up to date can be challenging when new issues arise outside the scope of your existing logs.

The Datadog Service Catalog consolidates knowledge of your organization’s services and shows you information about their performance, reliability, and ownership in a central location. The Service Catalog now includes Service Scorecards, which inform service owners, SREs, and other stakeholders throughout your organization of any gaps in observability or deviations from reliability best practices.

IT environments can produce billions of log events each day from a variety of hosts and applications. Collecting this data can be costly, often resulting in increased network overhead from processing inefficiencies and inconsistent ingestion during major system events. Google Cloud Dataflow is a serverless, fully managed framework that enables you to automate and autoscale data processing.

CloudNatix is an infrastructure monitoring and optimization platform for VMs, containers, and other cloud resources. Customers can use CloudNatix’s Autopilot feature to automatically configure and run infrastructure optimization workflows that allocate and run their resources more efficiently. CloudNatix can take action to auto-size Kubernetes and VM workloads, defragment Kubernetes clusters, and create harvest pods from unused VMs, among other key optimizations.