March 2015 Summaries

ServiceNow is an IT service management platform that helps manage and track enterprise-level IT processes in one place. A new Datadog integration for ServiceNow's support ticketing component has been introduced, allowing users to create tickets from triggered alarms in Datadog. This integration also enables the addition of Datadog-generated graphs and comments to ServiceNow tickets, as well as managing the resolution workflow within Datadog. Users can now auto-generate ServiceNow tickets from Datadog alerts by mentioning @servicenow in the alert message or adding it to the notification list for that monitor. Once the monitor state returns to normal, the associated support ticket is automatically marked as "resolved." Additionally, users can send Datadog graphs to ServiceNow on an ad hoc basis by clicking the camera icon and sharing a snapshot of any Timeboard graph with context in the comment box, then @mentioning ServiceNow. To integrate Datadog's alerting capabilities with ServiceNow, sign up for a 14-day free trial or get started as a Datadog customer.

Datadog integrates with ServiceNow to help manage IT service management processes in a single location, enabling automatic creation of ServiceNow tickets and incident resolution. The integration allows for bidirectional syncing between Datadog cases and ServiceNow tickets, streamlining incident response and reducing alert fatigue. By configuring the integration, users can automatically create ServiceNow tickets when alerts are triggered, resolve tickets faster with bidirectional syncing and event correlation, and streamline their incident response using Datadog Incident Management. The integration is available for a 14-day free trial, and users can learn more about it in the documentation and blog post.

ServiceNow, a widely-used IT service management platform, can be integrated with Datadog to enhance IT Operations Management (ITOM) and IT Service Management (ITSM) by automatically generating incidents and events. This integration allows users to manage ServiceNow tickets and resolution workflows directly from the Datadog platform, thus minimizing the time between issue occurrence and ticket resolution. By configuring Datadog applications, organizations can automatically create ServiceNow tickets in response to Datadog monitor alerts, prioritize responses through instance priority mapping, and maintain a system of record with bidirectional syncing. This setup helps teams operating primarily in ServiceNow efficiently handle IT issues, reduce alert fatigue, and respond swiftly to incidents. Additionally, Datadog's Event Management correlates multiple alerts to a single ServiceNow incident, minimizing noise and ensuring that incidents in Datadog are synchronized with ServiceNow. The integration supports both platforms' use cases, allowing developers and support teams to operate within their preferred environments while maintaining visibility and accountability.

At GopherCon India, Jason Moiron, Software Engineer and Gopher at Datadog, presented "Go Faster: Optimizing Go Programs." The talk covered various optimization techniques explored by Datadog in the past year of using Go in production. Topics included the use of the Go profiler, test benchmarks, runtime behavior, cgo, compiler optimization/inlining, ASM support, and implementation details for maps, channels, the runtime, and select statement. The presentation was part of a great show by the Go Language Community in India and Innovation and Technology Trust. For more information on Datadog's performance metrics, sign up for a free trial.

Jason Moiron, a Software Engineer at Datadog, presented "Go Faster: Optimizing Go Programs" at GopherCon India last month. The presentation covered various optimization techniques explored by Datadog in the past year, including using the Go profiler, benchmarking with test runs, examining runtime behavior, utilizing cgo and compiler optimizations, leveraging Go's Assembly Support, and delving into implementation details of maps, channels, the runtime, and the select statement. These techniques aim to improve performance metrics visibility for Go programs, and viewers can learn more by signing up for a free trial of Datadog.

You can access the host map from the Infrastructure link in the navigation bar in your Datadog account. The host map represents each host as a hexagon, with colors showing the percentage of CPU utilization on the host. You can easily change the host map to represent different metrics and choose a different color palette. The size of each hexagon represents the relative value of a metric, such as uptime or disk free space. You can filter and group your hosts using tags, allowing you to visualize a subset of your infrastructure based on shared attributes. Once you've filtered and visualized your host data, you can easily save the host map to use again later.

Datadog has introduced Host Maps, a new feature designed to provide a comprehensive view of all hosts in a user's infrastructure on a single screen, allowing for customizable grouping and filtering with visual metrics. This tool aids in spotting outliers, detecting usage patterns, and optimizing resources across various scales, from small setups to extensive infrastructures with thousands of hosts. Host Maps offer flexibility for users to ask infrastructure-level questions and obtain instant, visual answers, particularly useful for tasks like resource optimization where users can analyze AWS instance types and their utilization. Additionally, Host Maps facilitate understanding availability zone placements and assist in problem investigations by allowing users to group hosts by different dimensions to identify issues quickly. This feature enhances operational efficiency and understanding of infrastructure, making routine operations more intuitive and engaging for teams.

We're happy to announce the release of new muting features for Datadog monitors, allowing teams to filter out expected events and quickly pinpoint critical issues in their infrastructure. With this release, you can mute specific scopes of a monitor on an ad hoc basis using tagging, schedule global downtime during a specific time window to suppress all alerting related to a tag, and automatically mute monitors in response to planned downtime in certain situations such as manual instance shutdowns or autoscaling features. This feature is available for both Datadog customers and non-customers who can sign up for a 14-day free trial and check out the new feature for themselves.

Konotor, a mobile-first user engagement platform, faced challenges in scaling their PostgreSQL database due to slow writes on AWS Elastic Block Store (EBS). They discovered that EBS was throttling their writes as they had failed to correctly calibrate how many IOPS the disks would consume. Using Datadog, Konotor investigated and identified the issue, leading them to explore various solutions such as striping multiple disks, using Provisioned IOPS (SSD), ephemeral storage, moving frequently used tables/indexes to another disk, and reducing I/O writes. They also emphasized the importance of monitoring and alerting for I/O transactions, CPU time spent on I/O waits, and disk latencies. Datadog's ability to correlate data, gather metrics from various sources, and its lightweight nature made it an invaluable tool for Konotor during this process.

Datadog has helped Konotor, a mobile-first user-engagement platform, solve its problem of scaling its PostgreSQL database by detecting issues before they affect users and correlating different events and metrics to make sense of what's happening. The company discovered that it had exceeded the IOPS (input/output operations per second) limit on its SSD-backed AWS Elastic Block Store, causing slow writes. After investigation, they found that the issue was due to incorrect calibration of IOPS allocated to the disks. Datadog provided valuable insights and tools, such as monitoring CPU time spent on I/O waits, disk latencies, and correlating data, which helped Konotor implement solutions like striping multiple disks, using Provisioned IOPS (SSD), ephemeral storage, moving frequently used tables/indexes to another disk, reducing I/O writes, detection and prevention measures. Datadog's lightweight agents and plugins also made it easy for Konotor to monitor its infrastructure and identify potential problems before they affect users.

Datadog has added Windows Service checks to its latest version (5.2) of the Datadog Agent. This feature allows users to monitor the availability status of their Windows Services and receive notifications when a service stops running. The integration supports native services like Windows Remote Management and Windows Task Scheduler, as well as applications such as MS Exchange, MS SQL, or third-party services. Users can create monitors based on failed service checks, specific service states, or simple up/down checks. Alerts generated by these checks can be sent via email, integrated with various third-party platforms like PagerDuty and Slack, or used to build a holistic view of all critical Windows components in Datadog's monitoring platform.

Datadog has introduced Windows Service checks in its Datadog Agent version 5.2, allowing users to monitor the availability status of services such as Windows Remote Management and Task Scheduler, as well as third-party applications like MS Exchange and MS SQL. This integration provides full visibility into service availability and notification capabilities when a service stops running, enabling users to create custom Monitors for notification purposes and avoid noisy alerts. The feature can also be used to notify teams via email or integrations with services like PagerDuty and Slack. With this addition, Datadog customers gain a unified view of their servers and applications, including critical Windows components.