Digital.ai released Ascension, its new AI-Powered DevOps Platform.
The new release—dubbed Ascension—empowers both private and public sector organizations to unify, secure and generate predictive insights across the software lifecycle, increasing business value with integrated software delivery, and driving down technical debt through enterprise connections.
The Ascension release further enables technology leaders to scale their distributed workforce and connect agile development at the portfolio, team and individual levels. The new features help ensure their business strategy is aligned to team-level execution while gaining increased visibility of the entire toolchain. Digital.ai is trusted by more than 1,500 organizations worldwide and across industries, including over 50% of the Fortune 500, to meet the challenges and opportunities of digital transformation.
“The last decade’s worth of well-funded, VC-backed software vendors has forever fragmented the way software is developed and delivered,” said Stephen Elop, CEO at Digital.ai. “Technology leaders today need a platform that offers the connective tissue to plan, measure and accelerate business value from software investments, while reducing costs, maintaining security, and managing compliance. With our latest release, Digital.ai’s platform solves problems organizations encounter by delivering connected tools that offer a wealth of insight across the full development and delivery lifecycle.”
The AI-Powered DevOps Platform provides innovative solutions that support the software development and delivery lifecycle, enabling technology teams to use individual solutions or the entire platform. Digital.ai solutions can be easily integrated into existing processes, applications, and infrastructure to propel innovation and bring greater visibility and insight across the entire software architecture and ecosystem.
Key new enhancements include:
■ Integrated DevOps Platform
- Embedded Mobile Application Security - Mobile app owners and developers can rapidly build and secure engaging mobile apps for iOS, Android, and other mobile operating systems with a single solution, offering organizations the assurance that all applications are protected from bad actors and threats.
- Scale and Integrate Application Testing - Autonomous testing focuses on low-code test automation with self-learning capabilities that navigate mobile applications and auto-generate sanity tests. Mobile Studio provides a new user experience in the cloud for better device interactions while testing, and Test Editor allows non-technical users to create, validate and manage test scripts.
■ Intelligent Software Delivery
- Increased Pipeline Visibility - Test and Deploy Analytic Lenses complete the 360° view for software delivery analysis. Test Lens brings pre-built metrics and best practice dashboards to mitigate software delivery bottlenecks and understand test volume coverage across devices and browsers. Deploy Lens provides telemetry and improves deployment efficiency by providing end-to-end visibility of deployments across apps and environments.
- Predictive Insights - The democratization of artificial intelligence (AI) across the Digital.ai platform continues with this release, including further enhancements to Change Risk Prediction to provide greater visibility, and better use of historic data to apply machine learning and make predictions.
■ Expanding DevOps Ecosystem
- App Store Experience - Integrations Marketplace offers customers one location to gain easier access to Digital.ai’s 100s of integrations for Agility, Release and Deploy products, as well as official partner and community plug-ins.
- Cloud-native Connectors - In addition to supporting traditional environments, as customers shift workflows to the cloud, release teams can now quickly set up, continuously deliver and promote code using Argo CD to orchestrate releases for Kubernetes. Customers using GitOps can leverage their infrastructure best practices.
- Enhanced End-to-End Integrations - Agility Sync offers customers a simple way to create their own integrations and/or extend existing integrations helping to reduce technical debt.
The Latest
Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...
Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...
For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...
New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...
Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...
In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ...
In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...
When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...
Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...
Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...