Test Data Manager - customer insights & AI features demo
Catch up on our Test Data Manager livestream from PASS 2025 where we speak to Ben Wiggin from DataPaws, and demo the latest AI custom dataset functionality.
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The latest News and Information on APIs, Mobile, AI, Machine Learning, IoT, Open Source and more!
Gisual Enters the Stack: Power, AI, and the Next Phase of Observability
ScienceLogic recently partnered with Gisual—a leader in AI power intelligence—to bring real-time power insight directly into the ScienceLogic AI Platform. On the surface, that might sound like a straightforward integration story. In reality, it signals something much bigger: observability continues to expand well beyond the digital stack, and operators now treat power as a first-class operational signal.
Mobile App Synthetic Monitoring enables proactive testing across devices and networks
In the mobile-first digital economy, your application’s performance is your brand’s frontline. Your backend is fast. Your APIs respond in milliseconds. Yet, somewhere on a slow network in a bustling city center, a user is staring at a frozen login screen. This scenario highlights a critical truth. App synthetic monitoring is the proactive discipline of simulating real user interactions—like app launches, logins, searches, and checkouts—from real devices and networks worldwide.
SIGNL4 December 2025 Release - Smarter Workflows, Smoother Shifts
SIGNL4 December 2025 Release – Smarter Workflows, Smoother Shifts.
Knowledge Graph + RAG: A Unified Approach to DevOps Intelligence
Knowledge graphs and RAG (Retrieval-Augmented Generation) are complementary techniques for enhancing large language models with external knowledge, and each brings unique strengths for DevOps use cases. While they are often mentioned together, they are fundamentally different systems, and combining them delivers far better outcomes than relying on either approach alone.
A framework for measuring effective AI adoption in engineering
These days, engineering leaders find themselves caught between a rock and a hard place. On paper, AI adoption looks like an unqualified success. Developers are shipping more code faster than ever, pull request volumes are up, and teams report feeling more productive. Their leaders rush to LinkedIn to share their plans to scale adoption because their teams are just so much more efficient. But then, the incidents and bug reports start piling up.
Monitor and reduce your mobile app size with Size Analysis (beta)
Note: This blog post was originally published for the Early Access of Size Analysis. if you're already familiar with Size Analysis in Sentry, go to the section titled What's new in the beta. If you're not familiar with Size Analysis, start at the section titled The curious case of man.jpg.
No-Code AI Tools That Are Changing Digital Marketing Forever
Artificial intelligence is no longer limited to data scientists or enterprise teams with large development budgets. Over the past few years, a new wave of no-code AI tools has emerged, allowing marketers to automate tasks, generate insights, and optimize campaigns-without writing a single line of code. For digital marketers, this shift is transformational. No-code AI tools reduce execution time, lower costs, and empower teams to focus on strategy rather than manual work. More importantly, they level the playing field, allowing small and mid-sized businesses to compete with larger brands.
Serhii Tokarev: What Central and Eastern European start-ups are missing
The past ten years have seen rapid growth in the number of start-ups within Central and Eastern Europe (CEE). Yet, CEE faces various barriers, some of which are not related to funding or access to capital, to fully realise its potential as a global hub for innovation. Despite widespread assumptions that founders are held back by small markets, political risks or limited funding, the real obstacles lie elsewhere. IT entrepreneur Serhii Tokarev explains what is slowing down the region's growth.
Streamlining Lab Data Workflows for Next-Gen Operational Excellence
Modern laboratories operate in an environment shaped by speed, precision, and accountability. As expectations grow, so does the pressure to deliver reliable outcomes without slowing operations. Data sits at the center of this challenge. How it is captured, managed, and shared directly affects productivity and trust. Streamlining lab data workflows is no longer a technical upgrade; it is a strategic move toward operational excellence.