Navigating the SecOps Cloud Platform Revolution for Product Builders

The build-versus-buy posture for security infrastructure has a default answer that almost nobody questions out loud. If you want to ship a security product, you build the plumbing yourself: stand up storage, wire connectors, normalize feeds, then build your actual idea on top. Christopher Luft, LimaCharlie's co-founder, hosted this session, and his lead sales engineer Matt Bromiley spent it making a sharper claim than the usual platform pitch. The plumbing is not where your product lives. It is where your product dies, slowly, over the several months you spend on data wrangling instead of on the one thing customers will actually pay you for.

The undifferentiated middle eats the product

Bromiley's strongest material is his portrait of building without a platform underneath you, because it is specific about where the time goes. A builder with an idea, say something that uses behavioral telemetry and machine learning to catch unauthorized users, does not start on the model. They start on the database. They stand up a SIEM, an aggregation tool, or, increasingly, a search-engine-style store, because the first instinct is "I need a giant thing to hold all my data." Then comes the normalization, the parsing, the connectors for dozens of sources spanning security tools, SaaS, and cloud platforms. Bromiley puts a number on it: unifying data can be 80 percent of the work while delivering maybe 10 percent of what you need before detection and response even begins.

The deeper cost is not time, it is ambition. Build on someone else's platform and you inherit its limits, and those limits usually surface in telemetry. It ingests four of the six sources you wanted. It takes the data but hands you the parsing. Bromiley's most pointed example is the category of AI and ML security products that, once you drill in, are running their analytics on four or five Windows event log IDs. A model is only as good as the data feeding it, so a builder who set out to do something ambitious with machine learning and then starves it of telemetry has not built their vision. They have settled for a second-best version because it was what the infrastructure allowed. The platform's argument here is that it removes the constraint entirely: you bring in live, parsed, normalized telemetry streams and can action against them immediately, so the time to the part you are actually good at collapses from months of plumbing toward a single day.

Pricing the agent as a vehicle, not a toll booth

The same logic runs through how Bromiley talks about cost, and it is where the cloud analogy does real work rather than decorative work. The industry convention is to peg the endpoint agent to whatever competitors charge, X plus one or X minus one, and treat that agent as the product. Everything else gets stacked on top of a per-endpoint floor. Bromiley rejects the framing outright. A cloud provider charges you in proportion to the storage you use; LimaCharlie takes the same posture, and efficiencies the engineering team finds get passed down rather than pocketed. He cites a recent internal case where someone made a data lookup faster and that translated directly into a cost reduction for the customers using it. The point is structural: a platform whose business is enabling builders cannot also be the thing that prices them out at the floor.

That reframing is what makes "endpoint bus-as-a-service" more than a slogan. If the LimaCharlie sensor is already deployed, deploying five, six, or seven additional agents to get EDR, AV, asset management, and network monitoring is waste you have learned to tolerate. The same installer, Bromiley notes, has served as a detection and response engine, a threat hunting tool, a digital forensics and IR tool, a security control testing tool, and an asset management and visibility layer. The agent is a vehicle for capability, not a SKU. For a provider trying to thin a crowded stack across every client, consolidating onto one sensor is both an operational simplification and a margin decision.

Bi-directionality is the bet on where response is going

The newest capability Bromiley discusses, bi-directionality, released by founder Maxime Lamothe-Brassard on stage at Google Next, is interesting less as a feature than as a statement about scope. Reaching back into a source to act on it has always existed for the endpoint: an EDR sensor kills a process, collects a file, answers a question about a host. What LimaCharlie is extending is that same actionability to nearly any telemetry source, using the native tools each source already exposes. Cloud platforms, email, identity providers, SaaS applications, the systems that have traditionally been treated as secondary or tertiary, become primary drivers of response. A suspicious login in a cloud platform that only a handful of your customers use is now something you can detect and act on without stitching together a third automation product and praying the API chain between three systems holds. That last point is the one that matters for anyone operating at scale. The fragility of build-it-yourself security is rarely the individual tools; it is the brittle web of integrations between them.

The proof point Bromiley offers is Blumira, a Series B managed security provider of roughly 70 employees that wanted to build out XDR. On the platform, they went from concept to a full, customer-facing, revenue-generating XDR offering in about four months. The number is the argument compressed: when the infrastructure, scaling, and normalization are already solved, the timeline is set by your team's expertise rather than by how long it takes to reinvent the foundation.

For an MSSP or MDR with more than a handful of staff, the framing is not abstract, because you are already a product builder whether you call yourself one or not. Every client environment you operate is a tenant you are running detection and response across, and the question of whether you spend your engineers' hours on plumbing or on the work clients actually pay for is the question that decides your margin. Bromiley's case is that the parts everyone treats as table stakes, ingestion, normalization, the agent, multi-tenancy, API-first access, should in fact be table stakes, owned by infrastructure rather than rebuilt by you, so that what you ship is the part only you can build.