
Sentry announced new capabilities that significantly reduce management overhead and accelerate issue response times for enterprise development teams.
With percent-based alerts, Code Owners for GitHub and GitLab, team and personal notifications in Slack, and SCIM support for Okta, teams can find the right people at the right time to fix the right issues, streamline workflows, and improve developer efficiency.
Sentry’s new capabilities help scale code observability to all app development teams so that enterprises can move faster with less risk and reduce operational overhead.
“Successful teams innovate rapidly to deliver a standout product experience, resulting in more and frequent code changes. Getting to the bottom of issues requires figuring out the who behind the code, which is core to our focus on accelerating actionable resolution,” said Milin Desai, CEO, Sentry. “Building deeper workflows into GitHub, Slack, and Okta allows for developers to quickly see the issues that matter and solve them faster so they can get back to writing code that delivers business value.”
Sentry’s new capabilities enable enterprise teams to:
- See the issues that matter with percent-based alerting: Teams can identify and prioritize issues based on user impact by setting alerts when an issue exceeds a certain percentage of user sessions within a time period. For companies with variable or seasonal usage, count-based alerts can lead to noisier environments. Percent-based alerts reduce the noise by adjusting to changes in app usage so teams can quickly identify the right problem at the right time.
- Solve issues faster with Code Owners and Slack notifications: Managers and product owners can save time assigning issues by integrating directly with the CODEOWNERS file in GitHub or GitLab. Teams can automatically route error notifications to the right person or team with no additional configuration. Once set up, alerts go directly to the corresponding individual or team who owns the code with Personal and Team notifications in Slack, reducing notification fatigue, accelerating response time, and preventing missed issues.
- Automate Sentry access with SCIM support for Okta: Managers and IT departments can automatically provision and deprovision users and teams directly through Okta. SCIM streamlines user provisioning tasks while reducing security risks so engineers can get up and running quickly with the tools they need.
These new capabilities build on Sentry’s ecosystem support and analytics features that development teams need to scale their code observability practices and efficiently manage application code health from the frontend to the backend. Other recently released enterprise features include customizable dashboards and updates to its Jira and Azure DevOps integrations.
The Latest
In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...