According to CRN, Dynatrace has launched a new AI-powered observability platform called Dynatrace Intelligence at its Perform conference in Las Vegas. The platform fuses deterministic intelligence with agentic AI that can reason and act within guardrails. The company also introduced Dynatrace Intelligence Agents, expanded cloud-native integrations with AWS, Azure, and Google Cloud, and next-gen Real User Monitoring. Alongside the tech, the company highlighted a massive channel pivot, revealing it now works with about 700 partners and that a staggering 80% of new sales bookings last year came “through and with” its partner ecosystem. Channel chief Jay Snyder emphasized a move from transactional deals to a lifecycle-based approach with partners.
The real story is the channel pivot
Look, the AI stuff is cool and expected. Every observability vendor is bolting on “agentic” capabilities. But here’s the thing: the more interesting strategic move is Dynatrace locking itself into a channel-centric future. An 80% partner-influenced new sales rate is a huge number for a company that, let’s be honest, used to be pretty direct-sales heavy. This isn’t just about reselling licenses anymore. Snyder’s mantra about moving “from the transaction to the lifecycle” is key. They want partners to build full-blown observability practices and manage customer outcomes over time. That’s a much stickier, more valuable relationship. And it directly counters the fear that SaaS platforms make partners obsolete. Dynatrace is basically saying, “We need you more than ever to make this complex AI-driven data useful.”
The AI-in-observability arms race heats up
So what about Dynatrace Intelligence? It’s the latest salvo in an increasingly crowded and noisy market. The promise of moving from reactive to proactive to “autonomous” operations is the holy grail everyone’s selling. Dynatrace’s angle seems to be this combo of deterministic (rules-based, causal) AI and the newer, flashier agentic AI that can take actions. That’s smart. Pure agentic AI can be a black box and a liability—nobody wants a rogue AI agent rebooting production servers on a hunch. By grounding it in their existing causal-DAG model (Smartscape), they’re trying to offer power with safety. But let’s be real, every competitor from Datadog to New Relic to the cloud-native guys is making similar promises. The differentiator might not be the AI itself, but who can best integrate it into a customer’s actual workflow. Which, hey, brings us right back to those 700 partners.
It’s all about integration and the ecosystem
The expanded cloud integrations and the bidirectional links to tools from ServiceNow, GitHub, Atlassian, and others are arguably as important as the core AI. In modern, fragmented tech stacks, an observability platform is only as good as its connections. You can have the world’s smartest AI, but if it only sees data from your platform, it’s got blinders on. Dynatrace is trying to position Grail, its data lakehouse, as the unifying layer. Snyder said they’re bringing “everything… into one single platform” to see how it’s all connected from cloud to user experience to business outcomes. That’s the real value proposition now. It’s not just monitoring, it’s being the central nervous system for digital operations. For partners, especially system integrators, this is gold. It gives them a single pane of glass to build managed services and automation around. This is where the channel strategy and the product strategy completely align.
What this means going forward
Basically, Dynatrace is executing a classic two-pronged strategy: deepen the product moat with AI and cloud integrations, while simultaneously widening its reach and implementation muscle through the channel. The “teaming agreements” Snyder mentions are telling—they’re formalizing co-delivery and shared accountability. That’s a mature partnership model. The big question is whether partners can scale with the platform’s complexity. Selling and managing a basic APM tool is one thing; selling an AI-agentic, multi-cloud “autonomous operations” platform is another. It requires serious skills. Dynatrace is betting that by feeding partners its own service frameworks, they can bridge that gap. If it works, they build a formidable delivery network that’s hard to replicate. If it doesn’t, they risk having a powerful platform that’s underutilized by customers. The next year will show if this partner-led, AI-powered bet pays off.
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