Operations | Monitoring | ITSM | DevOps | Cloud

Visually identify and prioritize security risks using Cloudcraft

As cloud infrastructure becomes more dynamic and distributed, DevOps and security teams need to quickly detect risks and understand their context: where those risks live, how critical they are, and how to respond effectively. By surfacing misconfigurations, vulnerabilities, sensitive data risks, and identity threats directly on a real-time diagram of your infrastructure, Cloudcraft helps teams identify, prioritize, and remediate security issues at scale.

This Month in Datadog - August 2025

In the August episode of This Month in Datadog, Jeremy shares how you can make more informed cloud cost decisions, gain insights into your LiteLLM-powered applications, and secure Kubernetes infrastructure with Datadog Workload Protection. Later in the episode, Danny puts the spotlight on Datadog Kubernetes Autoscaling, which helps you deliver cost savings without sacrificing performance.

Eliminate cloud waste across AWS, Azure, and Google Cloud with Cloud Cost Recommendations

As organizations increasingly adopt multi-cloud strategies, identifying areas to reduce cloud spend has become highly complex and time consuming. While there are many reasons that organizations choose to run their infrastructure in a multi-cloud environment, many do so to comply with regional data requirements, take advantage of best-of-breed offerings, or avoid vendor lock-in.

We vibe coded a path tracer: Here's how we used static and dynamic analysis to fix it

When developing software, the longer you intend to keep a system around, the more important it becomes to prioritize its code quality. But as more organizations move toward microservice architectures and adopt agentic AI and LLMs into their development workflows, many engineering teams have increased their emphasis on accelerating developer velocity, often at the expense of code quality. This can often result in code that fails to meet standards for performance, reliability, and security.

What's new for scheduling and resource management in Kubernetes v1.34?

Kubernetes v1.34, which is scheduled for release August 27, 2025, focuses on improved scheduler visibility, deeper life cycle observability, and enhanced resource management. As always, the list of changes and improvements in the official changelog is extensive, and cluster operators may be wondering which changes are most important. If you're operating a monitoring platform or depend on deep Kubernetes observability, here's how a number of new features will affect your workflows.

Manage your dashboards and monitors at scale

In the early stages of building a system, a few well-placed dashboards and monitors can provide sufficient visibility into service health and performance. However, as infrastructure scales and teams grow, so does the complexity of the monitoring landscape. In organizations where individual teams manage their own services but rely on a central platform or observability team for tooling and guidance, this complexity can quickly multiply.

Instrument your Azure Container Apps workloads with the new Datadog Agent sidecar

Modern application development is evolving rapidly, with serverless containers and microservices becoming the standard for scalable, resilient architectures. Azure Container Apps is at the forefront of this movement, enabling developers to deploy containerized applications without having to manage infrastructure.

Identify slowdowns across your entire network with Datadog Network Path

As modern infrastructure becomes increasingly distributed across on-premises data centers, multi-cloud environments, ISPs, and remote offices, understanding how traffic flows across your network is critical to delivering reliable performance and great user experiences. But pinpointing the source of network slowdowns remains one of the most persistent challenges for operations, network, and IT teams.

Datadog governance 101: From chaos to consistency

As your organization scales, managing observability resources and usage becomes increasingly important. More users and teams mean more dashboards, tags, API keys, and costs to manage. The job of keeping track of these resources and ensuring that they’re compliant can quickly grow in complexity.

How we saved $1.5 million per year with Cloud Cost Management

In collecting and analyzing trillions of events each day, Datadog ingests a massive amount of data. We spend substantially to process and store this data in the cloud, and teams across the organization are committed to optimizing the return on this investment. To this end, our FinOps analysts have always tracked the costs of delivering our services and identified opportunities for savings.