June 2018 Summaries

Microsoft's Azure Kubernetes Service (AKS) is a managed service that automates the deployment, maintenance, and scaling of Kubernetes clusters. Datadog offers comprehensive visibility into AKS infrastructure by integrating with both Kubernetes and Azure Monitor. The integration allows users to monitor metrics, distributed request traces, and logs from all services running in their container infrastructure without additional configuration. With features like Autodiscovery, automatic tagging, Live Container view, and Live Process Monitoring, Datadog provides real-time insights into the health, resource consumption, and status of containers within AKS clusters.

Datadog's integrations with Kubernetes and Azure Monitor provide comprehensive visibility into Microsoft's managed service, Azure Kubernetes Service (AKS), without additional configuration. AKS automates the provisioning, maintenance, and scaling of Kubernetes clusters, managing control plane and launching other Azure resources to support containerized applications. Datadog collects metrics, distributed request traces, and logs from Kubernetes, Azure, and services running in the container infrastructure, enabling real-time insights into cluster health, resource consumption, and status. With automatic tagging, Datadog pulls in tags from Azure, Docker, and Kubernetes, allowing for easy monitoring of AKS clusters alongside other technologies. The Live Container view provides real-time insights into container health and resource consumption, making it easier to identify operational data and optimize performance.

Datadog has announced enhancements to its Microsoft Azure integration, now supporting over 60 Azure services. The updated integration collects metrics and tags from all services supported by Azure Monitor for comprehensive monitoring through a single integration. Additionally, support for Azure Service Fabric has been officially released, allowing users to track the health and resource consumption of auto-scaling microservices and containers in real time. These enhancements build on existing support for Azure Classic and ARM Virtual Machines, Azure SQL Database, Azure App Services, Microsoft IIS, and Windows Management Instrumentation. The updated integration also provides better tagging for Azure monitoring by converting dimensions into key:value format and automatically collecting custom tags for filtering and grouping data.

Datadog has enhanced its Microsoft Azure integration to support over 60 Azure services, including Cosmos DB and Azure DB for MySQL and PostgreSQL. The new integration automatically collects metrics and tags from Azure Monitor, providing comprehensive monitoring of the entire Azure ecosystem. Additionally, Datadog now supports Azure Service Fabric, a distributed systems platform that makes it easy to package, deploy, and manage reliable microservices and containers. With this update, users can track the health and resource consumption of their auto-scaling nodes in real-time. The integration also provides better tagging for Azure monitoring, allowing users to slice, group, and filter their data as needed. Furthermore, Datadog's Azure Virtual Machine extension enables easy deployment of the Agent on Service Fabric clusters, making it simple to monitor these environments.

Oracle Database is widely used in businesses for managing complex data sets and supporting various applications. It offers scalability, advanced partitioning, and optimized data availability across large infrastructures. Datadog has introduced an integration to monitor Oracle databases, collecting key metrics and visualizing them in a customizable dashboard. Users can create custom alerts based on these metrics to identify performance or capacity issues. Key Oracle metrics to monitor include tablespace usage, caches and buffers within the system global area (SGA), and disk I/O. The integration also provides additional data for assessing session activity, database wait time, and Real Application Clusters' global cache.

Oracle Database is widely used in the business world for handling complex data sets across various applications. The database emphasizes scalability, partitioning, and availability, with features like real-time backup and recovery tools. Datadog's new integration allows users to monitor Oracle databases, collecting and visualizing key metrics in a customizable dashboard. This enables users to identify performance bottlenecks and set up alerts for capacity issues. Key metrics include tablespaces, caches, and buffers within the system global area, as well as disk I/O and resource utilization. By monitoring these metrics, users can optimize their database's performance and efficiency, ensuring reliability, scalability, and throughput. The integration provides additional insights into database usage and performance, including session activity, database wait time, and Real Application Clusters' global cache. Users can set up the integration to start graphing and alerting on Oracle metrics immediately, or sign up for a free trial to explore Datadog's capabilities.

Heroku, a platform-as-a-service, streamlines application deployment by abstracting complex infrastructure tasks, employing buildpacks to modify runtime environments. The introduction of a new Heroku buildpack allows for the installation of the latest Datadog Agent, supporting distributed tracing and application performance monitoring (APM). Initially developed by Mike Fiedler to facilitate custom metric transmission via a Python-based DogStatsD server, the buildpack had to be rewritten as the Datadog Agent transitioned to a Go binary. Heroku's security model restricts root access and standard directory writes, necessitating the buildpack's installation in non-standard directories. The buildpack automatically tags metrics for easier aggregation and monitoring, with configuration options available to stabilize hostnames and manage costs. By using the buildpack, users can collect comprehensive metrics, and those new to Datadog can explore its capabilities with a complimentary 14-day trial.

Amazon Elastic Container Service for Kubernetes (EKS) is a cloud-based Kubernetes service that provides features for automated cluster management and maintenance. Datadog can help monitor container infrastructure and applications in real time, integrating seamlessly with EKS and other AWS services. With Datadog running in an Amazon EKS environment, users can get full visibility into their containers, Kubernetes cluster, and EC2 nodes. The Live Container view provides real-time resource metrics for containers, making it easy to see if any need attention.

Amazon Elastic Container Service for Kubernetes (EKS) is a cloud-based Kubernetes service that provides automated cluster management and maintenance, ensuring the health and availability of your Kubernetes cluster. EKS integrates seamlessly with other AWS services, using worker nodes as EC2 instances operating over Amazon's Virtual Private Cloud architecture. Datadog can help monitor container infrastructure and applications in real-time, providing visibility into all AWS services, metrics, logs, and distributed request traces from all applications. With Datadog running in your EKS environment, you can get full visibility into your containers, Kubernetes cluster, and EC2 nodes, correlating metrics across different logical groupings such as pods, Docker images, and AWS CloudFormation stacks. The platform provides a single dashboard to monitor your Amazon EKS cluster, allowing you to filter by tags pulled from AWS or Kubernetes, or custom tags in your cluster, to determine the health of containers and resource usage distribution across nodes.

Dash, a new conference about building and scaling applications, infrastructure, and technical teams, will take place on July 11-12 at Spring Studios in New York City. The event will feature speakers from leading organizations such as Shopify, Flatiron Health, Optimizely, Google, Segment, Capital One, Stitch Fix, EA, Zendesk, and Airbnb discussing topics like application performance, scalability, and team collaboration. Workshops by Amazon Web Services and Datadog will cover Kubernetes best practices, metric visualization, and container monitoring. Registration is open for the event.

Dash is a new conference focused on building and scaling next-generation applications, infrastructure, and technical teams. The event will take place in New York City on July 11 and 12 at Tribeca's Spring Studios. It features a mix of speaking sessions and workshops covering topics such as application and system performance, scalability, and team collaboration. A diverse lineup of speakers from top organizations like Shopify, Flatiron Health, Optimizely, Google, Segment, DraftKings, Capital One, Stitch Fix, EA, Zendesk, and Airbnb will share their experiences on building scalable, resilient, high-performance applications and teams. The conference also includes workshops covering Kubernetes best practices, metric visualization, and container monitoring with speakers from Amazon Web Services and Datadog. Registration is now open to secure a spot for the event.

Supervisord is a widely used tool for managing long-running processes in applications, including starting, monitoring, and restarting them when necessary. However, with multiple supervisord instances running simultaneously, tracking all processes and identifying problematic ones can be challenging. Datadog's supervisord integration automatically sends information about managed process counts, uptimes, and states to the platform. Users can create custom dashboards and alerts for Supervisor across their infrastructure or focus on specific Supervisor servers based on their needs. Supervisor processes have various basic states such as stopped, starting, running, exited, fatal, and unknown. Customizable checks can be set up to alert users when certain processes enter a critical state by creating new monitors for the supervisord integration and using the Integration Status tab. The monitor message can provide context like the affected host name, which is helpful for the person receiving the alert. Users can also build screenboards that display the overall status of their Supervisor deployment, showing the number of processes by their status and uptime statistics. This helps identify problematic processes requiring attention. Additionally, Datadog's integration allows users to monitor Supervisor's availability, ensuring its reliability in restarting processes when needed. Overall, this integration simplifies monitoring Supervisor-managed processes and the tool itself, making it easier for users to manage their applications' performance.