Five key trends that will determine the next chapter of observability

Observability is becoming increasingly vital as Australian businesses grapple with the growing complexity of diverse IT infrastructures and software. However, gone are the days when observability merely meant monitoring system metrics and logs. This year, it will become the cornerstone of intelligent, autonomous, and sustainable IT operations.

This shift comes at a critical time as businesses face exceptional challenges in managing hybrid cloud environments, AI-driven services, and evolving compliance requirements. The traditional reactive approach to system monitoring and maintenance is giving way to a more sophisticated, predictive modus operandi that will transform how organisations ensure reliability, security, and performance. 

Several key trends are emerging that will define the next chapter of observability, fundamentally changing how businesses operate and innovate in the digital age.

Observability to become preventive
Firstly, preventive observability will move beyond siloed systems into interconnected, autonomous ecosystems, redefining how organisations ensure reliability and resilience. These ecosystems will function seamlessly across distributed environments, leveraging AI to understand the real-time context of digital services. This capability enables automation to predict and prevent issues before they occur, leading to an era of foresight and collaboration.

Unlike earlier AI for IT operations (AIOps) approaches that struggled to deliver due to limited contextual understanding, this new generation of AI-powered observability integrates insights from across systems to identify root causes, predict cascading failures, and act autonomously in real time.

In these autonomous ecosystems - built on hybrid and multicloud environments - preventive observability automates the complex task of orchestrating distributed systems. By predicting and resolving issues before they impact operations, organisations can ensure service availability, minimize downtime, and reduce operational overhead. This proactive, context-aware approach will create a level of interconnectedness that will drive operational excellence and soon become the industry standard.

Observability and security converge around continuous compliance
In 2025, compliance is no longer a static exercise. Continuous compliance will evolve into a real-time dynamic system driven by the 2023-2030 Australian Cyber Security Strategy and APRA regulatory frameworks.  This shift adds to the growing need for observability and security to converge, providing organisations with unified insights to address compliance, reduce redundant data collection, and strengthen threat detection and incident response.

For example, AI systems will continuously monitor threat exposure to assess risks and prepare configuration adjustments. These adjustments can be reviewed and approved by humans or applied automatically, ensuring organisations maintain compliance without disrupting operations. This human-in-the-loop approach is essential for maintaining accountability, particularly when regulatory violations must be reported to governing institutions or national regulators.

The convergence of observability and security offers more than just regulatory benefits - it equips organisations to combat increasingly sophisticated cyber threats. Observability widens the lens through which security professionals view and analyse data, delivering the context necessary to enhance resilience and reduce costs. By integrating observability into security strategies, organisations can foster the trust needed to operate confidently in an era of heightened risk.

Observability is mandatory for any serious IT sustainability strategy
Increasingly, as organisations face growing energy demands from cloud environments and AI-driven operations, sustainability will take centre stage in 2025.

Observability platforms will become essential for monitoring and optimising the energy consumption of AI workloads, identifying inefficiencies, and enabling intelligent workload distribution. As an added benefit, optimising energy efficiency through observability not only lowers operational costs but also aligns with sustainability commitments set by cloud providers. This approach ensures businesses stay competitive as energy costs rise and sustainability regulations tighten.

As energy-intensive AI workloads become the norm and new sustainability quotas gain traction through regional mandates and the requirement as from 1 January 2025 for Australian businesses with consolidated revenue of more than $500 million to prepare annual sustainability reports, it's clear that sustainability is no longer optional.  Organisations that fail to integrate sustainability into their IT strategies risk non-compliance, reputational harm, and rising costs. Observability plays a leading role in this transformation by delivering the detailed insights necessary to optimise operations—not just report on sustainability. This shift helps businesses strike a balance between innovation and environmental efforts.

AI observability becomes indispensable for AI-driven services
In the evolution of digital transformation, the rise of AI-based services introduces new complexities that make observability more critical than ever. With observability, teams will be able to build and operate new AI-powered digital services for performance and reliability, keeping cost, AI drift, user experience, and transparency in mind. These capabilities will give organisations the confidence to deploy AI technologies at scale.

As businesses deploy AI-driven services for predictive maintenance, financial forecasting, or cybersecurity, observability platforms will go beyond monitoring system performance to include visibility into AI queries. With this clarity, organisations can identify potential errors, correct biases, and ensure decisions align with both business goals and ethical standards.
In 2025, observability will play an even larger role as organisations increasingly rely on AI to power critical services. By providing end-to-end visibility and actionable insights, observability will empower businesses to confidently scale AI systems, maintaining accountability, reducing risks, and building trust. Therefore, observability will no longer be an optional enhancement, but a mandatory component for delivering safe and effective AI-driven services.

The resurgence of AIOps
AIOps has promised to transform operations for some time, but its fragmented technologies and limited context have prevented it from achieving its full potential. In 2025, AIOps will finally deliver on its promise, fuelled by advances that enable AI systems to effectively communicate and collaborate. This evolution will redefine how organisations manage IT and business operations, setting a new standard for preventive operations.

The breakthrough comes from composing diverse AI techniques to work together toward common goals. Through interconnected AI systems - some specialised in prediction, others in precision processing of context, and others in suggesting remediations - AIOps will deliver intelligent automation and real-time root-cause analysis. These systems will predict disruptions, resolve issues before they escalate, and ensure business continuity. By integrating these capabilities, AI can provide deeper insights and take more precise actions by analysing data in context and learning continuously from operational feedback.

The resurgence of AIOps will redefine industry benchmarks for efficiency and resilience. By automating tasks, reducing operational overhead, and enabling faster time-to-market, organisations will achieve unprecedented agility. To succeed, businesses must invest in advanced observability solutions and ensure teams are equipped to unlock the full potential of AI-driven operations.

Looking further ahead 
As organisations confront a rapidly evolving digital landscape, observability will play an indispensable role in shaping the future of IT operations. Those that embrace these emerging trends will transform technological challenges into opportunities, building more resilient, efficient, and innovative digital systems. Advanced observability isn't just an advantage; it's critical for success in forging tomorrow's digital world.