For the first time in human history, in Q2, more than 50% of the traffic flowing across Cloudflare’s network was not human. The number of requests on our network from AI agents continues to grow unabated.
Matthew Prince, Cloudflare, Q2 ‘26 Earnings Call
Product-led Growth (PLG) to Agent-led Growth (ALG).
Developer Experience (DX) to Agent Experience (AX).
These shifts have been under way for some time, but we’re clearly accelerating.
Proxies of agent traffic across infrastructure and security software earnings calls underlines just how much.
Infrastructure Software
DigitalOcean
AI customer ARR reached $234 million, growing over 200% year-over-year… 85% of AI customer ARR… came from inference services and core cloud, not from bare metal. Inference services… now represent over 70% of our total AI customer ARR.
…over 6,000 customers have leveraged the inference engine, while customer count grew an average of close to 60% month-over-month, and the token volume increased 30x over the last 60 days.
This token growth is driven by strong demand from AI natives… As workloads shifted from human prompted to agent-driven, token consumption and cost exploded.
Datadog
As of Q2, over 750 AI customers use Datadog… all 10 of the top 10 AI leaders are Datadog customers… We are also seeing signs of rapid growth in agentic activity with a number of MCP tool calls quadrupling again quarter-over-quarter and growing more than 22x when compared to Q4 2025.
The second thing we see is a very rapid increase in the usage of all of our AI-first surfaces. So that would be the products that measure agents and LLMs, we see an explosion of traffic in terms of the LLM and tool calls we’re getting.
That would be the amount of calls we’re getting to our MCP endpoints. So we see that explode completely over the past 2 quarters.
Dynatrace
Our unified architecture becomes more valuable as AI increases complexity, and that growing value is reflected in higher consumption, broader platform adoption and the following 3 new monetization opportunities. First, AI workloads are similar to core observability workloads in that they leverage the same types of data such as logs, traces and metrics. But AI workloads generate dramatically more telemetry than the systems that came before them.
This is one of the reasons why log management remains our fastest-growing product category, with consumption nearly doubling since surpassing the $100 million milestone just 2 quarters ago
Every time a customer uses Dynatrace Intelligence to get answers through AI function calls or MCP integrations or when one of our agents like the SRE or Assist agent takes autonomous action to resolve an issue, it drives DPS usage. As agents increasingly become consumers of observability, this represents a growing opportunity that didn’t exist 2 years ago.
Atlassian
MCP calls were up 400% in the quarter with barely a blip in people actually using the applications through the web or through a mobile client.
The Teamwork Graph, importantly, we opened up at Team ‘26 US, which is a really important step with our MCP server, with our command-line interface, or CLI, the ability to put the Teamwork Graph to access its information in any Agentic harness that you’re using either chat applications, agents running on other platforms is really important. This is about being an interconnected part of a customer’s technology estate. It’s about the Atlassian platform being a strategic piece in the puzzle of how it is that they run their business. And I think that integration is a really important point. We’re seeing that the reason we talk about the MCP server, MCP and CLI users in the quarter, passing 1 million MAU. We don’t know where that puts us in a world scale, but I think it’s 1 of the biggest MCP servers that exist, more than doubling in the quarter is because of people getting to the Teamwork Graph getting to that context from their agents wherever they’re deployed.
GitLab
For more than a decade, GitLab has brought together the context of how software is built, secured and shipped across source code, issues, merge requests, pipelines, vulnerabilities, policies, approvals and deployments.
As AI becomes more capable, we believe that connected context becomes even more valuable, and we’re seeing early evidence of that with GitLab Orbit, our context graph for the software life cycle. Since opening the beta in June, more than 2,200 organizations have enabled orbit indexing, an increase of 70% in 4 weeks. Customers have generated more than 170,000 queries and roughly 80% of customer query volume comes from customers connecting Orbit to external agents such as Claude Code and Codex.
Year-over-year, secure repositories grew 60%, code pushes grew 50%, CI/CD pipelines grew 40%. Among some customers moving aggressively into AI-assisted development, we’ve seen code bases grow as much as 500%.
Security Software
Palo Alto Networks
The impact on our SASE platform is already evident, where agentic traffic has surged 9x over the last 9 months. Defending at this scale requires machine speed inspection or competence, a core competence we have refined for 2 decades, enabling us to block more than 30 billion attacks in a single day.
Prisma AIRS achieved a significant milestone, surpassing $100 million in ARR within 4 quarters of general availability. This represents the fastest scaling product in the history of Palo Alto Networks.
Fastly
We shared in Q2 that AI-generated traffic is growing at roughly 6.5x the rate of human traffic. Machines don’t browse the way people do. They query, scrape or act on someone else’s behalf, and that makes every request more complicated. This means every request requires an immediate decision. Is this an authorized agent, should it be cached, throttled, monetized and/or blocked? That’s why we see our security and compute products accelerating right alongside this machine traffic.
Akamai
Yes. And we have seen real tailwinds from AI and sort of the post-Mythos world for our more longer-term security products. I think roughly because of AI, the attackers have assembled much larger bot armies to launch attacks. And we’ve seen the scale of the attacks grow by maybe a factor of 10 over the last year.
CrowdStrike
In Q2, our endpoint business accelerated for the fourth consecutive quarter as customers look to secure their growing AI attack surface. We’re seeing dramatic expansion in agentic work on the endpoint, both through fast-growing tools such as Codex and Claude as well as custom agentic applications.
In sampling our customer base, we’ve seen more than 400% growth in Claude usage and more than 100% growth in custom agent usage on endpoints in recent months.
Okta
In terms of like where the products stack up in the quarter, we had, as I mentioned, the quarter was strong across almost every dimension, particularly strong was the 30% of the new bookings were from new products. Okta for AI agents inside of that bucket, there were dozens of deals in the quarter, including several million dollar-plus deals, which is super exciting. But the reality is it’s still very early. We do thousands of transactions every quarter.
And as exciting as that is, Okta for AI agents, it’s still -- it’s too small to show up in the numbers right now. But going forward, especially over the next couple of years, we’re super optimistic. We think this being the system of record for Agentic for agents in the enterprise and being the system of record for agent identity, in the fullness of time, it could be the biggest category of cyber.