Observability + DevOps: A smarter way to stay resilient

If nature abhors a vacuum, business abhors uncertainty. But with the right capabilities, organizations can build resilience through uncertainty and position themselves to take advantage of opportunity.   

In business terms, the antidote to uncertainty is the ability to make data-driven decisions. Access to real-time, context-driven analytics and insights is often the difference between making an informed choice or guessing wrong. 

Shifting business conditions require that organizations be able to connect the dots between DevOps practices and the metrics that drive the business. The throughline? Observability and AI-driven analytics that understand how delivering the services customers rely on affects the bottom line.   

These capabilities are essential to building trust and alignment among stakeholders and unlocking the innovation and flexibility organizations need to embrace change and adapt to pivoting strategies. The ability to proactively identify, assess, and mitigate risks helps organizations to keep customers close, foster trust, and remain responsive to change.   

By combining these strategies, businesses can navigate uncertainty with confidence and resilience.

How is your business building resilience through uncertainty? Leave us a comment! 

Critical business processes thrive with observability and AI-driven anomaly detection 

 What happens when a stalled service delays orders, or a failed API breaks a loan validation?  

Dynatrace Business Flow helps teams track anomalies tied to business KPIs like conversions, cycle times, and exceptions. AI-powered observability lets you detect issues early, connect service performance to revenue, and respond before customers are affected.  

Gary Kaiser describes how Dynatrace helps you stay aligned, resilient, and responsive in the face of change.  

Distributed tracing best practices for the software development lifecycle 

Distributed tracing helps analysts throughout the organization understand the relationships among services to troubleshoot problems. But distributed tracing is especially crucial at every stage of the software development lifecycle. 

Christoph Neumüller, Thomas Rothschädl, and Kayla Bondy lay out distributed tracing best practices to help troubleshoot, design, implement, and automate software delivery at every stage of the SDLC. These best practices help developers build more reliable services that support key business outcomes.

How developer efficiency delivers better payment reliability for FreedomPay 

When FreedomPay, a global leader in digital commerce, adopted a unified observability strategy to resolve problems faster and boost transaction speeds, the team recognized an opportunity to create a more collaborative culture with its customers.  

Rather than just providing a simple status page, the team created shared dashboards that give customers deeper insights into business analytics, response times, error rates, and more. Discover how this insight connects customers to technical metrics so they can easily troubleshoot their code.

At its annual Build conference for developers, Microsoft announced support for a wide range of AI models, including xAI, Meta, Mistral, and Black Forest Labs–along with its new GitHub Copilot coding agent.   

These announcements highlight the rise of agentic AI and growing demand for AI diversity and automation at scale.  

As organizations adopt more GenAI tools, AI observability becomes critical. Not just for performance monitoring, but for tracking compliance, cost, and trust.

Join us on Wednesday, 11 June 2025 at 10:30 am ET | 3:30 pm BST | 4:30 pm CET for an exclusive webinar with IDC that highlights insights from IDC's latest study on how Dynatrace transforms businesses: Unlocking the Business Value of Dynatrace. 

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