Operations | Monitoring | ITSM | DevOps | Cloud

Monitor Slurm with Datadog

Slurm (Simple Linux Utility for Resource Management) is an open source workload management system used to schedule jobs and manage resources for high-performance computing (HPC) Linux clusters. It ensures that jobs and resources are scheduled fairly and efficiently and is scalable across large clusters, an issue that native Linux process management tools struggle with.

Ship features faster and safer with Datadog Feature Flags

Releasing new features is one of the highest-stakes moments in the software delivery life cycle. Even with CI/CD pipelines in place, plenty of things can still go wrong when a feature goes live for actual users. Most feature flagging tools operate in isolation from important observability tooling, forcing engineers to monitor changes across multiple disconnected systems to fully understand their impact. This slows down development and increases the chance of missing critical issues.

Model your architecture with custom entities in the Datadog Software Catalog

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.

Monitor your data pipelines with Airflow lineage

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.

Proactively monitor Kerberos-authenticated web apps and APIs with Datadog Synthetics

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.

Track the performance of your HPC workloads with Datadog's AWS PCS integration

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.

Monitor Windows Certificate Store with Datadog

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.

Visually identify observability gaps with Cloudcraft in Datadog

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.

A practical guide to error handling in Go

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.

Understanding dbt: basics and best practices

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.