Operations | Monitoring | ITSM | DevOps | Cloud

Every software organization has its own unique architecture and workflows. Beyond services and APIs, teams rely on internal libraries, CI/CD jobs, data pipelines, AI agents, and more to keep systems running smoothly. But as architectures grow more complex and interconnected, it can become difficult to keep track of all the structural dependencies and interactions in one place.

In complex data pipelines with dozens of jobs and intermediary datasets, it can be difficult to effectively monitor how data travels and changes through various steps. When tracking issues in these pipelines, you need visibility into upstream components where the root cause may originate from, as well as downstream datasets and consumers of data that may be experiencing further impacts.

When employee authentication fails or becomes unreliable, users can lose access to the critical systems they need. Authentication enables access to internal tools like HR applications, finance portals, and internal dashboards, so even short outages can interrupt day-to-day work, while persistent issues increase the risk of broader operational disruption.

AWS Parallel Computing Service (AWS PCS) is a managed service that helps users run and scale their high performance computing (HPC) workloads. AWS PCS uses Slurm, an open source workload manager, for scheduling and orchestrating simulations, which enables users to build their scientific and engineering models in a familiar HPC environment.

The Windows Certificate Store is a critical component of any modern Windows environment. Certificates enable TLS encryption for Internet Information Services (IIS)-hosted applications, support certificate-based authentication in Active Directory, and help validate the identity of trusted Windows services. But if a certificate in your store expires, is revoked, or is part of a broken certificate chain, you risk instability and security gaps in your Windows environment.

Modern cloud environments are highly complex and dynamic, with critical services relying on large numbers of ephemeral resources. Ensuring observability coverage across this landscape is essential for troubleshooting, maintaining reliability, optimizing performance, and enforcing security standards. But as environments grow more elaborate and their ownership more dispersed, tracking observability coverage becomes increasingly challenging.

When you first start coding in Go, you quickly learn how error handling in the language differs from error handling in languages such as Java, Python, JavaScript, or Ruby. In those languages, throwing an exception automatically generates a stack trace. Go, by contrast, provides no built-in error tracing to reveal an error’s origin.

Data Build Tool (dbt) is an open source analytics engineering framework that enables teams to transform raw data that has been loaded into a warehouse like Snowflake, BigQuery, Redshift, or Databricks using SQL-based workflows. dbt is available in two main forms: dbt Core, the free and open source CLI tool, and dbt Cloud, a managed platform that adds scheduling, UI support, collaboration tools, and native integrations.

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.

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.