Datadog announced Datadog On-Call, an on-call experience with observability-enriched paging and seamless incident management workflows.
Datadog On-Call instantly coordinates teams with relevant context for faster issue resolution, better incident control and improved collaboration.
By unifying observability and paging into one seamless platform, Datadog On-Call solves these issues and eliminates the inefficiencies of multiple disjointed tools, allowing engineers to focus on resolving incidents quickly and effectively without the added stress of switching contexts or missing critical information.
“Being on-call is one of the most challenging aspects of an engineer’s job, where redundant service configurations between various tools can lead to brittle, error-prone setups. The general overhead of maintaining on-call schedules and the ambiguity around service and team ownership make it a grueling ordeal, especially during critical times,” said Michael Whetten, VP of Product at Datadog. “Datadog On-Call addresses these pain points with a team-centric design that clarifies ownership, reduces redundancy and minimizes errors. This approach ensures that every team member knows their role and responsibilities, leading to quicker and more effective incident response.”
Datadog On-Call helps DevOps, SRE, Security and IT Operations teams:
- Act Quickly and Stay Informed: Paging with integrated observability and seamless incident management ensures critical insights and data are readily available within a single platform, eliminating the need for context switching.
- Connect with the Tools They Use Every Day: On-Call integrates with a rich ecosystem of third-party monitoring, alerting and service management tools so teams don’t have to learn new workflows or spend resources on training.
- Ensure Clear Service and Team Ownership: Break down knowledge silos and avoid confusion by associating teams with their respective services to simplify configuration, address ownership gaps and ensure the right responders are paged during an alert. Instantly trace upstream and downstream services affected by an outage or issue.
- Implement Intuitive Scheduling and Notifications: Automate scheduling and escalation policies to ensure continuous coverage and timely responses, reducing the burden on individual team members and enhancing overall team coordination.
- Measure On-Call Performance: Rich and customizable analytics measure on-call performance to help ensure system reliability, improve mean-time-to-resolution and optimize the well-being of on-call teams.
Datadog On-Call is in beta now.
The Latest
Broad proliferation of cloud infrastructure combined with continued support for remote workers is driving increased complexity and visibility challenges for network operations teams, according to new research conducted by Dimensional Research and sponsored by Broadcom ...
New research from ServiceNow and ThoughtLab reveals that less than 30% of banks feel their transformation efforts are meeting evolving customer digital needs. Additionally, 52% say they must revamp their strategy to counter competition from outside the sector. Adapting to these challenges isn't just about staying competitive — it's about staying in business ...
Leaders in the financial services sector are bullish on AI, with 95% of business and IT decision makers saying that AI is a top C-Suite priority, and 96% of respondents believing it provides their business a competitive advantage, according to Riverbed's Global AI and Digital Experience Survey ...
SLOs have long been a staple for DevOps teams to monitor the health of their applications and infrastructure ... Now, as digital trends have shifted, more and more teams are looking to adapt this model for the mobile environment. This, however, is not without its challenges ...
Modernizing IT infrastructure has become essential for organizations striving to remain competitive. This modernization extends beyond merely upgrading hardware or software; it involves strategically leveraging new technologies like AI and cloud computing to enhance operational efficiency, increase data accessibility, and improve the end-user experience ...
AI sure grew fast in popularity, but are AI apps any good? ... If companies are going to keep integrating AI applications into their tech stack at the rate they are, then they need to be aware of AI's limitations. More importantly, they need to evolve their testing regiment ...
If you were lucky, you found out about the massive CrowdStrike/Microsoft outage last July by reading about it over coffee. Those less fortunate were awoken hours earlier by frantic calls from work ... Whether you were directly affected or not, there's an important lesson: all organizations should be conducting in-depth reviews of testing and change management ...
In MEAN TIME TO INSIGHT Episode 11, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Secure Access Service Edge (SASE) ...
On average, only 48% of digital initiatives enterprise-wide meet or exceed their business outcome targets according to Gartner's annual global survey of CIOs and technology executives ...
Artificial intelligence (AI) is rapidly reshaping industries around the world. From optimizing business processes to unlocking new levels of innovation, AI is a critical driver of success for modern enterprises. As a result, business leaders — from DevOps engineers to CTOs — are under pressure to incorporate AI into their workflows to stay competitive. But the question isn't whether AI should be adopted — it's how ...