Boston-based Sea Street Technologies has managed to hit a significant deployment milestone and push its own model of IT system management into a more visible position. Founded in 2012, and having raised $41m in funding to spur launch, Sea Street has made a target of very large enterprise organizations, notably telecom service providers. With its Human Capital Transformation program, it says it has productized a way to effect the cultural change necessary for large enterprises to take advantage of modern IT operations and service-delivery capabilities (notably its own). It has also partnered with global IT services and technology provider Amdocs.
The 451 Take
What would you say if a tiny band of elite technicians wanted to tear up your entire IT services delivery model and replace it with what they call ‘models’ of their own that look nothing like what you know works already? Reluctance and discomfort would be in the package, to say the least. Sea Street appears to have found a workaround in its education and outreach efforts that don’t target decision-makers, but rather engineers and operators. That learning curve has been a two-way street, but if Sea Street can package its cultural and organizational transformation efforts into its overall product, it may have found a way to broaden its appeal. IT modernization and industrialization efforts are at least as much about helping organizations take a different view of IT as they are about investment or core technology. Sea Street needs to move fast on its methods and models – machine learning and IT ops are the next big thing.
Sea Street sells a core platform called StratOS, of which the most important components are what it calls ‘models’ – stateful (retaining data rather than passing it on), mostly autonomous, policy-driven software robots that operate in a continuous feedback-and-improvement loop and are designed, along with other components of the platform, to ingest data and operate controls on a wide range of systems to deliver a service. This means not just computer and application data, but also physical hardware like wireless broadcast towers, datacenter equipment, and ticketing and dispatch systems; in theory, anything that can send out operations data and receive remote instruction could be operated by StratOS. It supports a range of enterprise IT products and services, but more can be added opportunistically.
The firm says that one of the major challenges it faced in a years-long deployment scenario at a very large customer was barriers – intentional and otherwise – thrown up by having to explain the subtleties. Partnering with Amdocs was a necessary move to gain leverage and effect change, and Sea Street says it will look at other partnerships opportunistically. In response to the lessons learned, Sea Street has formalized its approach to systematic change with what it calls Human Capital Transformation. It is a counterpoint to the StratOS platform.
During the process, Sea Street realized that the technology platform was just one – and perhaps not the most significant – piece of the puzzle. Demonstrating the capabilities and functions of its StratOS platform and getting it stood up inside its customer was a challenge, but the larger challenge was interfacing and communicating with (often very diplomatically) the key constituents within the enterprise, and slowly wrangling them into putting it into practice and reshaping the IT organization to be able to understand and take advantage of StratOS’ service-modeling capabilities. Sea Street says it had to create not only a services deployment factory, but also an educational mission to ensure that its technology, which, by necessity, overlays almost everything else, wasn’t shunned or sidestepped by engineers that maintained and developed services on their own. That meant showing off ways in which automation wouldn’t displace workforce, for instance, or coaching on how to integrate the functions of venerable institutions and sacred cows without touching off resistance.
Human Capital Transformation represents Sea Street’s recognition of the more-or-less catholic set of issues facing enterprise IT transformation – 451 Research Voice of the Enterprise (VotE) buy-side research indicates that technical compatibility with existing systems and resistance to change are now the biggest barriers to IT transformation, leapfrogging cost and security concerns. Human Capital Transformation involves a series of certifications for architects, developers and resource drivers that are taught how use the StratOS process in a specific design methodology.
The path toward success for Sea Street was to set up a ‘service factory’ that could be applied to a wide range of services that needed updating. Once engineers and operators went through the education process, they could be plugged into this process and redesign and implement their products and services using StratOS (in addition to a radically streamlined workflow using the governance and machine learning properties of StratOS’s ‘models’). Boiled down, it’s templating and orchestration on a grand scale, combined with a robust semi-autonomous operations capability.
Sea Street claims that it was able to achieve an 80% reduction in transmission costs per KB for its customer (Deployment, above), and that now that its ‘service factory’ is in place, product and service updates are taking place at a record pace. If all of that has actually occurred, and Sea Street has found a way to make cranky engineers able to rejigger their own projects in this fashion, it could be a viable way for enterprises to escape the technical hell basement and speed up IT transformation.
There are a handful of competitors actively seeking to inject machine learning into IT operations today, and a whole lot more on the immediate horizon. C3 Automation, Yotascale, ScienceLogic and others are competitors on the smaller side, but IBM and CA have strong initiatives here, and Amazon Web Services and Microsoft Azure have machine learning that is being applied to cloud-based operations. Venerable data-driven toolsets like Moog and Splunk also stake claims to machine learning in the guts of IT ops.
Sea Street’s model-based approach to service composition is unique in the market for large-scale service delivery, and has open-ended potential for semi-autonomous operations in almost any kind of technology.
Sea Street is a very small organization fighting for visibility and access to very large organizations with established partners and vendors.
The opportunity here is to change the industry perception of how IT operations should be veiwed, conducted and constructed into a radically more efficient state.
Threats include getting lost in a crowd of similar- sounding machine learning products and not being able to push customers into material improvements fast enough to avoid getting bogged down.