Enterprise networks have unknowingly become the most complex that they have ever been, while the solutions designed to manage them have been scaled up to keep pace. The worldwide network observability market, expected to be worth $2.9 billion in 2024, is poised to grow at a compound annual growth rate of 11.2% until 2033 to reach around $7.6 billion in revenue by the end of the forecast period, as per a recent report by DataIntelo. This amounts to an additional $4.7 billion in value generated over nine years a more than two-and-a-half times increase on today’s base indicating a fundamental shift in the way visibility into mission-critical systems is seen, thanks to AI loads, multi-cloud infrastructure, and an environment that no longer accepts vulnerabilities.
The above chart shows part of the larger observability boom. A smaller sub-category labeled “Core Network Observability,” which focuses on telecommunication infrastructure observability, is worth $1.45 billion in 2025 and expected to grow to $6.79 billion in 2035 for a CAGR of 16.7%, whereas the AI-observability subcategory, currently nascent at $1.4 billion in 2023, is expected to grow to $10.7 billion by 2033 at 22.5% annually. The observability tools and platforms market category, covering the observability of networks, applications, infrastructure, and data, is worth $11.91 billion in 2026 and will be worth $22.99 billion in 2031 for a CAGR of 14.1%. Network observability’s growth of 11.2% may be slower than its neighbors, but that is because the category is maturing.
From Network Monitoring to Network Observability
Traditional network monitoring, which relied on dashboards and notifications for detecting failed devices and exceeded thresholds, was sufficient when networks were centralized and could be reasonably predicted. However, it is no longer applicable in modern IT environments, which are composed of microservices, containers, and distributed applications across various cloud providers and edge nodes.
Observability is not focused on reporting failures, but, rather, on correlating telemetry – logs, metrics, traces, flows – in order to help engineers figure out what is happening and, usually, before any issues affect end-users. It is the change in paradigm from reactive to proactive and context-oriented that makes CIOs view observability solutions as core infrastructure instead of tools.
AI workloads added more pressure to this trend. Pipelines of training and inference of ML models produce east-west traffic patterns, which were never covered by perimeter-centric network monitoring solutions. Failure modes of AI networks, such as latency spikes and packet loss, require detailed telemetry in order to identify and resolve them. The enterprises that deploy generative AI applications understand that the performance of their models is typically constrained by the performance of the network, not compute resources.
Segment-Level Growth Signals
By segment, the Solutions – the software platforms per se – account for the lion’s share of revenues with real-time visibility tools, AI-driven anomaly detection, and dashboards for multi-cloud environments included. The related market of observability tools is composed primarily of the Solutions with their 68.6% share of revenues, compared to 71.3% of the observability platform market overall. Meanwhile, the portion of the Services grows more quickly, showing the 17-18% CAGR in similar markets, or 1.5x the speed of software licensing, as companies lacking such skills resort to experts.
By deployment type, cloud observability is increasingly accounting for larger shares of spending. In the larger observability platform market, the cloud/SaaS delivery model currently represents 68.4% of the segment, with the hybrid model representing a smaller share, which will increase by more than 20% CAGR – almost doubling the growth rate of the entire market. On-premises deployments remain prevalent in regulated industries such as banking, health care, and government because of data localization rules, but their share of new implementations continues to fall.
Application-wise, performance monitoring and security monitoring constitute the top two use cases. Security monitoring is witnessing major changes as a result of the rise of AI technology: the 22.5% CAGR of the AI-in-observability segment against a 2023 base of $1.4 billion indicates that machine learning-based anomaly detection is rapidly turning into a must-have function rather than an expensive extra option. Fault management and network optimization complete the list, along with the fast-growing “other” category which includes compliance monitoring, capacity planning, SLA management.
Vertical-wise, IT and telecommunications stands first, accounting for nearly 30% of total spend (29.5%-30.2% depending on the report). BFSI comes second – in the data observability market, the BFSI vertical takes up over 21% of the market share. The healthcare vertical shows the highest growth rate among adjacent verticals in several research reports, amounting to nearly 22% CAGR. Despite the fact that large enterprises remain the largest buyers (comprising 62%-65% of the spend), SMEs are growing at about 17% CAGR owing to cheaper and cloud-native solutions.
Regional Outlook, in Figures
| Region | 2024 Market Size | Global Share | Forecast CAGR |
| North America | ~$1.19 billion | ~41% | Mature, steady |
| Europe | ~$870 million | ~30% | 10.6% |
| Asia Pacific | ~$630 million | ~22% | 13.4% (fastest) |
| Latin America | ~$150 million | ~5% | Below-average |
| Middle East & Africa | ~$60 million | ~2% | Below-average |
North America is still the largest regional market with early adoption of cloud computing, density of major vendors, and regulatory pressures in finance, healthcare, and government sectors. The European region follows as the second-largest market with a 10.6% CAGR driven by compliance and infrastructure investment in Germany, the UK, and France, only slightly lower than the global average of 11.2%.
The Asia-Pacific region leads in relative terms with 13.4% CAGR and a growth rate of about 20% higher than the global average due to increasing cloud adoption in China, India, Japan, and Australia. Latin America and the Middle East & Africa regions continue to be the smallest markets, making up less than 8% of global revenue.
What is fueling the curve
The combination of factors that fuels adoption includes but is not limited to architectural complexity – as more companies embrace microservices, containers, and other distribution architectures, the number of components producing telemetry is increasing at a rate faster than human troubleshooting efforts can handle. The second reason is cybersecurity – network-based threats became too complex for traditional solutions, which is why observability serves the purpose of a warning system.
The third driving factor is regulation – frameworks such as GDPR in Europe, along with industry-specific requirements in healthcare and finance, make companies turn to tools that allow monitoring and fast responses. The fourth reason is the proliferation of IoT devices and remote work – decentralization of network activity requires end-to-end visibility. Lastly, AI is a two-edged force here – it adds to the complexity of networks and, at the same time, becomes an integrated part of observability solutions through root cause analysis automation.
Competitive Landscape
The vendor space includes both legacy network and IT vendors along with pure-play observability vendors. While Cisco, IBM, Broadcom, and Juniper Networks can offer deep integration with existing technology stacks, Datadog, Dynatrace, Splunk, New Relic, and Kentik are all companies that have built platforms that rely heavily on unified telemetry correlation and artificial intelligence analytics. The purchase of ThousandEyes by Cisco and AppNeta by Broadcom is an example of a bigger trend where larger players are acquiring specialized capabilities.
Key areas of differentiation include visibility across on-premise, cloud, and edge environments; use of AI for diagnostic purposes as opposed to just telemetry correlation; and speed of getting the benefit out of the solution. Vendors are also bundling software with managed services for mid-sized organizations that want the outcome of observability without staffing a dedicated team.
Headwinds Worth Watching
Growth is never frictionless. Incorporating observability into existing legacy IT ecosystems is not easy, and interoperability within multi-vendor, multi-cloud stacks still eludes many organizations. Regulatory challenges related to data privacy and data sovereignty impede cloud growth in some industries, while the skills shortage of people who can understand the volume of telemetry that these systems produce still persists despite advancements in AI automation.
The Takeaway for Decision-Makers
There is no doubt where this path needs to lead for senior information technology and security professionals even if the exact route differs between companies. Network observability is evolving from being a niche monitoring tool into a base level requirement that helps enable digital resilience, security positioning, and artificial intelligence readiness. Companies considering making an investment into this space should be just as focused on flexibility of deployment, AI native analysis capability, and vendor success within their regulatory environment as they are on pricing considerations. This will only become more true as networks incorporate increasing AI loads and IoT capabilities.
Reference: https://dataintelo.com/report/network-observability-market