Software failures are inevitable. But they should never turn into disasters that wreak havoc throughout the country.
Whether an outage develops into a major outage or is immediately identified, diagnosed and resolved depends on how well the organization prepared and responded.
Vice President of Portfolio and Strategy at Dynatrace.
Building and delivering reliable, resilient software requires deep, AI-driven, end-to-end visibility that provides a consistent, single source of truth about how well the software environment is performing and the source of any problem that compromises that performance. performance.
Today's enterprise software environments are complex and include cloud-native applications, multi-cloud deployments, third-party services, APIs, and the growing influence of artificial intelligence.
These multi-tiered environments introduce significant opacity into the software supply chain, making it difficult to manage risk, performance, and sustainability at scale.
Risk of modern technology stacks
Research shows that 42% of organizations expect an incident caused by one of their suppliers. Too often, teams are caught off guard when things go wrong, which can be frustrating and costly.
To operate with confidence, businesses need visibility into their entire digital supply chain, which is not possible with core technologies. monitoring.
Unlike traditional monitoring, which often focuses on disparate metrics or alerts, observability provides a single, real-time view of the entire technology stack, enabling faster, data-driven decisions at scale.
Real-time AI surveillance implementation covers every component from infrastructure and services for applications and user experience.
Observability is a strategic necessity
End-to-end observability goes beyond its current role in IT and DevOps become a fundamental element of modern business strategy. At the same time, observability plays a critical role in managing risk, ensuring business continuity and protecting digital trust.
Observability also allows organizations to proactively identify anomalies before they become failures, quickly identify root causes in complex distributed systems, and automate response activities to reduce mean time to resolution (MTTR).
The result is operations that are faster, smarter, and more resilient, giving teams the confidence to innovate without compromising system stability—a critical advantage in a world where digital resilience and speed must go hand in hand.
Resilient systems must absorb shocks without collapsing. This requires both cultural and technical investments, from implementing shared responsibility across teams to adopting modern deployment strategies such as canary releases, blue-green deployments, and feature flagging.
Modern strategies only work if teams have real-time feedback and clarity, allowing organizations to understand what is happening, why and what to do about it before customers notice failures.
Agentic AI: a new level of risk
We have entered the era of artificial intelligence as organizations adopt generative and agent-based AI to accelerate innovation, improve productivity, and reduce costs. They are also exposing themselves to new types of risks.
Agent-based AI can be configured to act independently, making changes, running workflows, or even deploying code without direct human intervention. This level of autonomy poses significant challenges that accompany the potential benefits of AI.
For example, a misconfigured agent or malicious prompt can have far-reaching consequences down the line on machine speed, be it cost overruns, anomalous behavior, or full-fledged outages.
A small ripple can become a wave that is faster, wider and more difficult to contain. Real-time surveillance platforms driven by artificial intelligence are needed not only to monitor what agents are doing, but also to understand how they act, how they interact with other systems, and when intervention is required.
Observability helps harness the potential of agent-based AI safely and paves the way for autonomous operations.
Failure Protection
Industry leaders must adopt new technologies, including agent-based artificial intelligence, to keep pace with their competition. At the same time, they also need to adapt to the new security and compliance requirements of operating in increasingly complex technology stacks.
The best way for organizations to cope with this growing complexity and pressure is to view observability as a strategic business driver rather than just an IT capability. This ensures that each layer of the technology stack is transparent, accountable and sustainable by design.
By prioritizing real-time visibility through artificial intelligence, organizations can build strong trust, adapt quickly, and drive business growth, while avoiding wasting time and money dealing with devastating business failures.
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