The Remaking of Enterprise Infrastructure – The Sequel

“We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten. Don’t let yourself be lulled into inaction.” – Bill Gates, The Road Ahead

Just over a year ago, we wrote about how enterprise infrastructure was being reimagined and remade, driven by the rapid adoption of cloud computing and rise of ML-driven applications. We had postulated that the biggest trends driving the next generation of enterprise software infrastructure would be (a) cloud-native applications across hybrid clouds, (b) abstraction/automation of infrastructure, (c) specialized hardware and hardware-optimized software, and (d) open source software.

Since then, we have witnessed several of those trends accelerating while others are taking longer to gain adoption. The COVID-19 pandemic over recent months, in particular, has arguably accelerated enterprises multiple years down evolutionary paths they were already on – digital transformation, move to the cloud for business agility, and a perimeter-less enterprise. Work and investments in these areas have moved from initiatives to imperatives, balanced with macroeconomic realities and the headwind of widespread spending cuts. Against that backdrop, today we again take stock of where next-generation infrastructure is headed, recapping which trends we feel are accelerating, which are emerging, and which are stalling – all through the lens of customer problems that create opportunities for entrepreneurs.

Next-generation enterprise infrastructure, as we show in the figure above, will be driven by major business needs including usability, control, simplification, and efficiency across increasingly diverse, hybrid environments and evolve along the four dimensions of (1) cloud native software services, (2) developer experiences, (3) AI/ML infrastructure, and (4) vertical specific infrastructure. We dive into these four areas, and their respective components, in the rather lengthy post below. We hope some of you will read the whole thing, and others can jump to their area of interest!

As we have noted in the past, below are a few “blueprints” as we look for the next billion-dollar company in enterprise infrastructure. As we continue to meet with amazing founders who surprise and challenge us with their unique insights and bold visions, we continue to refine and recalibrate our thinking. What are we overlooking? What do you disagree with? Where are we early? Where are we late? We’d love to hear your thoughts. Let’s keep the dialogue going!

Cloud Native Software and Services

Cloud native technologies and applications continue to be the biggest innovation wave in enterprise infrastructure and will remain so for the foreseeable future. As 451 Research and others point out, “… the journey to cloud-native has been embraced widely as a strategic imperative. The C-suite points to cloud-native as a weapon it will bring to the fight against variables such as uncertainty and rapidly changing market conditions. This viewpoint was born prior to COVID-19 – which brings all those variables in spades. As this crisis passes, and those who survive plan for the next global pandemic, there are many important reasons to include cloud-native at the core of IT readiness.”[1]

However, enterprises that have begun to adopt technologies such as containers, Kubernetes, and microservices are quickly confronted with a new wave of complexity that few engineers in their organization are equipped to tackle. This is producing a second wave of opportunity to ease this adoption path.

Hybrid and Multi-cloud Management

We highlighted last year that we are now in a “hybrid cloud forever” world. Whether workloads run in a hyperscale public cloud region or on-premises, enterprises will adopt a “cloud model” for how they manage these applications and infrastructure. We are seeing the forces driving such multi-site and multi-cloud operations continuing to accelerate. While AWS remains the leader, both Azure and Google are adding new data centers around the world and expanding support for on-premises applications. Azure has gained significant ground with a growing number of services that are production-ready, and Google has invested heavily in expanding their enterprise sales and service capabilities while continuing to offer best-in-class ML services for areas such as vision, speech, and Tensorflow. Azure and Google continue to close the gaps and are often preferable to AWS in situations where enterprises must comply with regulatory and compliance directives for data residency and need to account for possible changes in strategic direction that may require migrating their applications to different cloud providers.

These compliance and data residency considerations are leading organizations to invest in skills and tools for building applications that are easily portable, which improves deployment agility and reduces the risk of vendor lock-in. This creates new sets of challenges in operating applications reliably across varying cloud environments and in ensuring security, governance, and compliance with internal and external policies. In 2019, we invested in MontyCloud which helps companies address the Day 2 operational complexities of multi-cloud environments. We continue to see more opportunities in hybrid and multi-cloud management as regulatory guidelines continue to evolve and organizations emerge from the early stages of executing the shift.

Automated Infrastructure

Automated infrastructure management has been a key enabler for organizations that need to operate in varying cloud and on-premises environments. As containers have grown mainstream, container orchestration with Kubernetes is becoming the most common enterprise choice for operating complex applications. Combining version-controlled configuration and deployment files with operational stability based on control loops has enabled teams to effectively and simultaneously embrace devops and automation while building applications that are portable across on-premises and multi-cloud environments. We invested in Pulumi, which allows organizations to use their programming language of choice in place of Kubernetes YAML files or other domain specific languages, further enabling a unified programming interface with the same development workflows and automated pipelines that development teams are already familiar with.

Machine Learning continues to promise automation of capacity management, failover and resiliency, security, and cost optimization. We see further innovation in ML-powered automation services that will allow developers to focus on applications rather than infrastructure monitoring while enabling IT organizations to identify vulnerabilities, isolate insecure resources, improve SLAs, and optimize costs. While we are already seeing technologies such as autonomous databases offer the promise of automating index maintenance, performance, and cost tuning, we have yet to see wider innovation in this space. We expect some of these capabilities to be natively offered by the public cloud providers. The opportunity for startups will be to offer a solution that leverages unique data from varying sources, delivering effective controls and mitigation, and supporting multi-cloud and on-premises environments.


Serverless remains at the leading edge of automated infrastructure, where developers can focus on business logic without having to automate, update, or monitor infrastructure. This is creating opportunities across multiple application segments, from front end applications gaining richer functionality through APIs to backend systems expanding integrations with event sources and gaining richer built-in business logic to transform data. AWS Lambda continues to lead the charge, lending some of its core concepts and patterns to a range of fast-growing applications. However, migrating traditional enterprise applications to an event-driven serverless design can require enterprises to take a larger than anticipated leap. While several pockets of an organization could be experimenting with serverless applications, we continue to look for signs of broader adoption across the enterprise. New approaches that help serverless more effectively address internal policy and compliance requirements would help grease the skids and increase the adoption for many of these serverless applications. Opportunities exist for new programming languages to make it easier to write more powerful functions along with new approaches for managing persistence and ensuring policy compliance. As applications begin to operate across increasingly diverse locations, distributed databases such as FaunaDB will help address the need to persist state in addition to elastically scaling stateless compute resources in transient serverless environments. We are more convinced than ever that serverless will grow to be a dominant application architecture over time, but it will not happen overnight and thus far has been developing more slowly than we forecasted.


With the growth of applications across public cloud regions, remote locations, and individual devices, enterprises are already learning new approaches to secure data at rest, define data perimeters, establish secure network paths. The move to working-from-home has accelerated this evolution, not only from a network perspective but also with a proliferation of bring-your-own-devices (BYOD). We are seeing continued and often increasing activity on several fronts:

  • Securing hardware and devices. Our portfolio company Eclypsium protects against firmware and hardware exploits, helping enterprises deal with the new normal of a distributed workforce and an increasingly risky environment of sophisticated attackers. We expect to see more companies realizing the need for firmware and hardware protection as well as broader opportunities around next generation endpoint protection solutions to support work-from-home, BYOD, and the now perimeter-less enterprise.
  • Secure computing environments. New virtualization technologies such as Firecracker using languages such as Rust are already delivering security and performance in constrained capacity environments. This is particularly valuable for the next generation of applications designed for low latency interactions with end users around the world. With Web Assembly (WASM), code written in almost any popular language can be compiled into a binary format and executed in a secure sandboxed environment within any modern browser. This can be valuable when optimizing for resource hungry tasks such as processing image or audio streams where Javascript isn’t the right tool for the required performance.
  • Securing data in use. While cryptographic methods can secure data at rest and in motion, these methods alone may be inadequate to protect data in use when it sits unencrypted in system memory. Secure enclaves provide an isolated execution environment that ensures that data is encrypted in memory and decrypted only when being used inside the CPU. This enables scenarios such as processing sensitive data on edge devices and aggregating insights securely back to the cloud.
  • Data privacy. Automated data privacy remains a challenge for companies of all sizes. GDPR and CCPA has resulted in unicorns such as OneTrust (who just acquired portfolio company Integris) as more countries adopt and implement similar regulations. Organizations around the world across industry verticals will require new workflows and services to store and access critical data as well as address an enduring business priority of understanding various data attributes – where it lives, what it contains, and what policies must apply to various usage patterns.
  • Securing distributed applications. Traditional approaches to securing applications that were designed for monolithic applications continue to be upended by distributed, microservices-based applications where security vulnerabilities may sit at varying points in the network or component services. Our portfolio company Extrahop’s Reveal(x) product exemplifies the value of deeply analyzing network traffic in order to secure applications. We expect to see this market continuing to expand in the future. We believe that companies can turn managing security from a business risk into a competitive advantage by embracing “SecOps.” SecOps includes building secure applications from the ground up, using secure protocols with end to end encryption by default, building tools to quickly identify and isolate vulnerabilities when they arise, and modernizing the way teams work together integrating security planning and operations directly into development teams. We are interested in new companies that further enable this SecOps approach for customers.

Developer Experiences

Rapid Application Development

Where front end and back end components were historically packaged together, we are seeing these components increasingly decoupled to speed up application development and raise productivity of relatively non-technical users.

For example, developers working on simple web applications, such as corporate websites, marketing campaigns, and small private publications that don’t require complex backend infrastructure, are already realizing the advantages of automated build and deployment pipelines integrated with hosting services. These automated workflows enable developers to see their updates published immediately and delivered blazingly fast through CDNs in SEO friendly ways. Open source Javascript-based frameworks such as GatsbyJS and Next.js can improve application performance by an order of magnitude by simply generating static HTML/CSS at build time or pre-rendering pages at the server instead of client devices. These improvements in application performance combined with ease of deploying to hosting platforms is empowering millions of front-end developers in building new applications.

Content Management Systems (CMS) that store and present the data for these simple web applications have turned ‘headless,’ storing and serving data through APIs that can be plugged into different applications across varying channels. This has enabled non-technical users to simply update their corporate website or product and documentation pages without depending on engineers to deploy updates. This points to a related trend of a rapidly growing API ecosystem that can enrich these ‘simple’ applications with functionality delivered by third party providers.

In fact, workflows (business activities such as processing customer orders, handling payments, adding loyalty points once a purchase is complete, etc.) in modern enterprises are increasingly implemented by calling a set of different (often 3rd-party) services that could be implemented as serverless functions or in other forms. While each service is independent and does not have any context of any other service, business logic dictates the order, timing, data, etc. with which each service should be called. That business logic needs to be implemented somewhere – using code – and the scheduling of each constituent service needs to be done by an orchestration engine. A workflow engine is exactly that – it stores and runs the business logic when triggered by an event and orchestrates the underlying services to fulfill that workflow. Such an engine is essential to build a complex, stateful, distributed application out of a collection of stateless services. The rapidly growing popularity of open source workflow engines such as Cadence (from Uber) is a good testament of this trend and we expect to see much more activity in this space going forward.

Everything as an API

Whether it’s a single page application with a mobile front end or a microservice that’s part of a complex system, APIs are enabling developers to reuse existing building blocks in different contexts rather than build the same functionality from scratch. “Twilio for X” has become shorthand for businesses that turn a frequently needed service into an easy to use, reliable, and affordable API that can be plugged into any distributed application. While Twilio (SMS), Stripe (payments), Auth0 (authentication), Plaid (fintech) and Sendgrid (emails) are already examples of successful API-focused companies, we continue to see more interesting companies in this area such as (adds 1-click video chat to any app/site), Sila (Madrona portfolio company providing ACH and other fintech back-end services as an API), and many more. As the API economy grows, so does the need for developers to easily create, query, optimize, meter, and secure these APIs. We are already seeing technologies such as GraphQL driving significant innovation in the API infrastructure and expect to see many more opportunities in this space.

AI/ML Infrastructure

Data Preparation

Data preparation remains the largest drain on productivity in data science today. Merging data from multiple sources, cleansing and normalizing training data, labeling and classifying this data, and compensating for sparse training data are common pain points that we hear from customers and our portfolio companies. Vertical applications that mine unstructured data is a large investment theme and reflected in Madrona investments such as intelligent contract management solution, Lexion, as well as in significant social challenges such as identifying and moderating misleading or toxic online content. Technologies such as Snorkel that help engineers quickly label, augment and structure training datasets hold a lot of promise. Similarly, tools such as Ludwig make it easier to train and test deep learning models for citizen data scientists and developers. These are examples of tools beginning to address the broader need for better and more efficient means of preparing data for effective ML models.

Data Access & Sharing

Another key challenge relates to developing and publishing data catalogs with the parallel challenge of accessing critical data in secure ways. Often superficial policies and access controls limit the extent to which scientists are able to use sensitive data to train their models. At times, the same scientist is unable to reuse the data that they used for a previous model experiment. We see data access patterns differing across different steps in the model development workflow, indicating the need for data catalog solutions that provide built-in access controls as enterprises begin to consolidate data from a rapidly growing set of sources. This challenge of federating and securing data across organizations while ensuring privacy – whether partners, vendors, industry consortia, or regulatory bodies – is an increasingly important problem that we are observing in industries such as healthcare, financial services, and government. We see opportunities for new techniques and companies that will arise to enable this new “data economy.”

Observability & Explainability

As the use of machine learning models explodes across all facets of our lives, there’s an emerging need to monitor and deliver real-time analytics and insights around how a model is performing. Just as a whole industry has grown around APM (application performance management) and observability, we see an analogous need for model observability across the ML pipeline. This will enable companies to increase the speed at which they can tune and troubleshoot their models and diagnose anomalies as they arise without relying on their chief data scientists to root cause issues and explain model behavior. Explaining model behavior may sometimes be straightforward, such as in some medical diagnostic scenarios. In other cases, the need for underlying reasoning could be driven by regulation/compliance, customer requirements, or simply a business need to better understand the results and accuracy of model predictions. So far, explaining model predictions has largely been an academic exercise, though interesting new companies are emerging to operationalize this functionality in production for their customers.

Computer Vision and Video Analytics

The use cases for better, faster, and more accurate computer vision and analysis of video continue to proliferate. The COVID pandemic has highlighted more remote sensing scenarios and the use of robotics in scenarios ranging from cleaning to patient monitoring. Analyzing existing video streams for deep fakes is front and center in consumer consciousness while business scenarios for video analytics in media and manufacturing efficiency are promising new areas. Converting video streams to a visual object database could soon enable ‘querying’ a video stream for, say, the number of cars that crossed a given intersection between 10:00 to 10:15am. While entrepreneurs need to ethically navigate the privacy concerns around video analysis, we feel there will be numerous new company opportunities in this area.

Model Optimization for Diverse Hardware

The hyperscale cloud providers continue to release new compute instances and chips optimized for specific workloads, particularly for machine learning. Aiming to realize the desired performance on these specialized instances in any cloud environment or edge location as well as a range of hardware devices, businesses need a path to optimize their models to run efficiently on diverse hardware platforms. We recently invested in an exciting new company, OctoML, that builds on Apache TVM (an open source project created by OctoML’s founders), offering an end to end compiler stack for models written in Keras, MXNet, PyTorch, TensorFlow, and other popular machine learning frameworks. We continue to believe that hardware advances in this space will create new investment opportunities for applications across domains such as medical imaging, genomics, video analytics, and rich edge applications.

Vertical-specific Infrastructure

The Impact of 5G

Major wireless providers have begun rolling out 5G services while cloud providers such as AWS (with Wavelength) and Azure ($1B+ acquisitions of Affirmed Networks and Metaswitch) have been investing in supporting software services. Investments in next generation telecom infrastructure could provide significant opportunities for operators to move to virtual network appliances that previously required specialized hardware devices as well as expensive operations and support systems to provision these services. Further, the greater bandwidth and software-defined network infrastructure being built for 5G should create a variety of new opportunities for startups such as (a) network management for enterprises including converged WiFi/5G networks, (b) the harnessing and orchestration of new data (what will be connected and measured that never has before?), (c) new vertical applications and/or new business models for existing apps, and (d) addressing global issues of compatibility, coordination, and regulation. Like previous wireless network standard upgrades, the full move to 5G and its impacts will undoubtedly take a number of years to be fully realized. That being said, given current rollouts in key geographies, we expect the software ecosystem around 5G to coalesce fairly rapidly, creating new company opportunities in both the near and medium term.

Continued Proliferation of IoT

Relatedly, we expect 5G to push the wave of digitization beyond the inherently data-rich industries such as financial services and into more industrialized sectors such as manufacturing and agriculture. The Internet of Things (IoT) will capture the data in these sectors and is likely to result in billions of sensors being attached to a variety of machines. Earlier this year we invested in that helps developers manage intelligent IoT devices, extending the type of DevOps functionality that exists in the cloud to any edge device with a UI, which are increasingly Android-based. Industrial IoT also continues to emerge into the mainstream with manufacturing companies investing in ML and other analytics solutions after years of discussion. We think companies taking a vertical approach and providing applications tailored to the specific need of a certain industry will grow most quickly.

Vertical-Specific Hardware+Software

We are also seeing several verticals requiring specialized hardware for key business functions. For example, electronic trade execution services must provide deterministic responses to orders placed within a small window of time. In addition to requiring hardware-based time sync across the network, participants often use specialized hardware including FPGAs to execute their algorithms. FPGAs are also common in high speed digital telecom systems for packet processing and switching functions. Similarly, FPGA-based solutions are being adopted across healthcare research disciplines. FPGA’s can accelerate identifying matches between experimental data and possible peptides or modified peptides that can be evaluated in near real time, enabling deeper investigation, faster discovery, and more effective diagnostics to improve healthcare outcomes. We are realizing that a long tail of such applications across verticals would benefit from a cloud-based “hardware-as-a-service” that offers a path for almost every application to run in the cloud.

Business Model Innovation

While this post has been largely organized around business needs that are being met by technology innovations and new product opportunities, we are also interested in investing in companies that take advantage of related business model innovations that these technological advances in enterprise infrastructure have enabled. For instance, the move to the cloud allows companies to provide consumption-based pricing, self-service models, “as-a-service” versions of products, freemium SKUs, rapid POCs and product trials, and direct reach to end-user developers or operations team members. We are equally interested in founders and companies that have found new ways to go-to-market and efficiently identify and reach customers.

Relatedly, the continued adoption of open source as the predominant software licensing approach for enterprise infrastructure has created new opportunities for business model innovation, significantly evolving the traditional “paid support” model for open source to open core and “run it for you” approaches. Enterprises are increasingly demanding an open source option because of the typical benefits of lower TCO and control. Developers (and vendors) love open source because of the bottoms-up adoption that creates validation and virality. At the same time, the bigger platforms (cloud providers) are embracing open source technologies on their platform often in a manner that provides an inherent tension with commercial companies built around those same open source technologies. We continue to strongly believe that having a differentiated, unique value proposition on top of an open source project is critical for a commercial company to be built. It is that differentiated value proposition that ultimately creates a strong moat and defensibility from the platform companies supporting open source technologies on their stack. We anticipate that all these factors, plus this intrigue of heightened tensions between hyperscale clouds and open source vendors, will add up to continued opportunity in the dynamic world of open source in the years to come.

[1] 451 Research, April 9, 2020, “COVID-19: Cloud-native impacts.” Brian Partridge, William Fellows, et. al.

Investing in VNDLY and the Future of Enterprise Applications – Intelligent Apps

Over the past few years and the next few years, we will see the formation of the next generation of enterprise application companies, companies applying intelligence to their applications. Over the subsequent decade those companies will replace legacy companies such as SAP, Oracle, NetSuite [part of Oracle] and Salesforce.

This will happen for a simple reason. It will happen because applications will become, well, intelligent. As ML/AI becomes integrated into every element of the application stack, applications will learn on a real-time basis and they will start to take actions on our behalf. Intelligent applications will deliver a far better customer experience, solve more of the customer problem set, and do so at far better economics than traditional or even SaaS applications.

That thesis on intelligent applications is why I am so excited about many of the companies we are working with including, Clari [Revenue Operations], a stealth corporate travel startup, a stealth financial application startup, and our most recent investment, VNDLY.

VNDLY, is a talent management solution founded by Shashank Saxena and Narayan Surabhi. Based in Cincinnati, OH, VNDLY’s clould-native vendor management solution gives employers and contractors an AI-based platform that adapts to the changing needs of both groups.

Over the past few decades, the contract and contingent portion of the corporate workforce has grown from less than 20% to more than 40%. My experience leading the Fieldglass team at SAP helped me to see the scale of the challenge businesses face in effectively recruiting, paying, managing and engaging with this critical part of a company.

Like every other component of the enterprise application stack, there is an opportunity to materially improve the completeness, the economic value and the ease of use, of solutions focused on the vendor and contract workforce.

There is an opportunity to serve this part of the workforce with the same fullness of solutions that companies like WorkDay, provide for full-time employees.

Shashank, who was previously an executive at Kroger, and I met a few years ago. I knew at that time that I would enjoy working with him. Shashank and his team are customer centric, insatiably curious, intellectually honest and continually raise the bar on themselves.

I am thrilled to have led Madrona’s investment in VNDLY and excited to work alongside Shashank and team as VNDLY’s newest board member.

Our investment in VNDLY is an Acceleration Fund investment, which is focused on companies that have found product and market fit and are scaling their businesses.


The Remaking of Enterprise Infrastructure – Investment Themes For Next Generation Cloud

Enterprise infrastructure has been one of the foundational investment themes here at Madrona since the inception of the firm. From the likes of Isilon to Qumulo, Igneous, Tier 3, and to Heptio, Snowflake and Datacoral more recently, we have been fortunate to partner with world-class founders who have reinvented and redefined enterprise infrastructure.

For the past several years, with enterprises rapidly adopting cloud and open source software, we have primarily focused on cloud-native technologies and developer-focused services that have enabled the move to cloud. We invested in categories like containerization, orchestration, and CI/CD that have now considerably matured. Looking ahead, with cloud adoption entering the middle innings but with technologies such as Machine Learning truly coming into play and cloud native innovation continuing at a dizzying pace, we believe that enterprise infrastructure is going to get reinvented yet again. Infrastructure, as we know it today, will look very different in the next decade. It will become much more application-centric, abstracted – maybe even fully automated – with specialized hardware often available to address the needs of next-generation applications.

As we wrote in our recent post describing Madrona’s overall investment themes for 2019, this continued evolution of next-generation cloud infrastructure remains the foundational layer of the innovation stack against which we primarily invest. In this piece, we go deeper into the categories that we see ourselves spending the most time, energy and dollars over the next several years. While these categories are arranged primarily from a technology trend standpoint (as illustrated in the graphic above), they also align with where we anticipate the greatest customer needs for cost, performance, agility, simplification, usability, and enterprise-ready features.

Management of cloud-native applications across hybrid infrastructure

2018 was undeniably the year of “hybrid cloud.” AWS announced Outposts, Google released GKE On-Prem and Microsoft beefed up Azure Stack (first announced in late 2017). The top cloud providers officially recognized that not every workload will move to the cloud and that the cloud will need to go to those workloads. However, while not all computing will move to public clouds, we firmly believe that all computing will eventually follow a cloud model, offering automation, portability and reliability at scale across public clouds, on-prem and every hybrid variation in between.

In this “hybrid cloud forever” world businesses want more than just the ability to move workloads between environments. They want consistent experiences so that they can develop their applications once and run anywhere with complete visibility, security and reliability — and have a single playbook for all environments.

This leads to opportunities in the following areas:

  • Monitoring and observability: As more and more cloud-native applications are deployed in hybrid environments, enterprises will demand complete monitoring and observability to know exactly how their applications are running. The key will be to offer a “single pane of glass” (complete with management) across multiple clouds and hybrid environments, thereby building a moat against the “consoles” offered by each public cloud provider. More importantly, the next-generation monitoring tools will need to be intelligent in applying Machine Learning to monitor and detect – potentially even remediate – error conditions for applications running across complex, distributed and diverse infrastructures.
  • SRE for the masses: According to Joe Beda, the co-founder of Heptio, “DevOps is a cultural shift whereby developers are aware of how their applications are run in a production environment and the operations folks are aware and empowered to know how the application works so that they can actively play a part in making the application more reliable.” The “operations” side of the equation is best exemplified by Google’s highly trained (and compensated) Site Reliability Engineers (SRE’s). As cloud adoption further matures, we believe that other enterprises will begin to embrace the SRE model but will be unable to attract or retain Google SRE level talent. Thus, there will be a need for tools that simplify and automate this role and help enterprise IT teams become Google-like operators with the performance, scalability and availability demanded by enterprise applications.
  • Security, compliance and policy management: Cloud, where enterprises lose total control over the underlying infrastructure, places unique security demands on cloud-native applications. Security ceases to be an afterthought – it now must be designed into applications from the beginning, and applications must be operated with the security posture front and center. This has created a new category of cloud native security companies that are continuing to grow. Current examples include portfolio company, Tigera, which has become the leader in network security for Kubernetes environments, and container security companies like Aqua, StackRox and Twistlock. In addition, data management and compliance – not just for data at rest but also for data in motion between distributed services and infrastructures – create a major pain point for CIOs and CSOs. Integris addresses the significant associated privacy considerations, partly fueled by GDPR and its clones. The holy grail is to analyze data without compromising privacy. Technologies such as security enclaves and blockchains are also enabling interesting opportunities in this space and we expect to see more.
  • Microservices management and service mesh: With applications increasingly becoming distributed, open source projects such as Istio (Google) and Envoy (Lyft) have emerged to help address the great need to efficiently connect and discover microservices. While Envoy has seen relatively wide adoption, it has acted predominantly as an enabler for other services and businesses such as monitoring and security. With next-generation applications expected to leverage the best-in-class services, regardless of which cloud/on-prem/hybrid infrastructure they are run on, we see an opportunity to provide a uniform way to connect, secure, manage and discover microservices (run in a hybrid environment).
  • Streams processing: Customers are awash in data and events from across these hybrid environments including data from server logs, network wire data, sensors and IoT devices. Modern applications need to be able to handle the breadth and volume of data efficiently while delivering new real time capabilities. The area of streams processing is one of the most important areas of the application stack enabling developers to unlock the value in these sources of data in real time. We see fragmentation in the market across various approaches (Flink, Spark, Storm, Heron, etc.) and an opportunity for convergence. We will continue to watch this area to understand whether a differentiated company could be created.

Abstraction and automation of infrastructure

While containerization and all of the other CNCF projects promised simplification of dev and ops, the reality has turned out to be quite different. In order to develop, deploy and manage a distributed application today, both dev and ops teams need to be experts in a myriad of different tools, all the way from version control, orchestration systems, CI/CD tools, databases, to monitoring, security, etc. The increasingly crowded CNCF roadmap is a good reflection of that growing complexity. CNCF’s flagship conference, Kubecon, was hosted in Seattle in December and illustrated both the interest in cloud native technologies (attendees grew 8x since 2016 to over 8,000) as well as the need for increased usability, scalability, and help moving from experimentation to production. As a result, in the next few years, we anticipate that an opposite trend will take effect. We expect infrastructure to become far more “abstracted,” allowing developers to focus on code and letting the “machine” take care of all the nitty gritty of running infrastructure at scale. Specifically, we think opportunities are becoming available in the following areas:

  • Serverless becomes mainstream: For way too long, applications (and thereby developers) have remained captive of the legacy infrastructure stack in which applications were designed to conform to the infrastructure and not the other way around. Serverless, first introduced by AWS Lambda, broke that mold. It allowed developers to run applications without having to worry about infrastructure and to combine their own code with best-in-class services from others. While this has created a different concern for enterprises – applications architected to use Lambda can be difficult to port elsewhere – the benefits of serverless, in particular rapid product experimentation and cost, will compel a significant portion of the cloud workloads to adopt it. We firmly believe that we are at the very beginning of serverless adoption and we expect to see a lot more opportunities in this space to further facilitate serverless apps across infrastructure, similar to (toolkit for building serverless apps on any platform) and IOpipe (monitoring for serverless apps).
  • Infrastructure backend as code: The complexity of building distributed applications often far exceeds the complexity of the app’s core design and wastes valuable development time and budget. For every app, a developer wants to build, s/he ends up writing the same low-level distributed systems code again and again. We believe that will change and that the distributed systems backend will be automatically created and optimized for each app. Companies like Pulumi and projects like Dark are already great examples of this need.
  • Fully autonomous infrastructure: Automating management of systems has been the holy grail since the advent of enterprise computing. However, with the availability of “infinite” compute (in the cloud), telemetry data, and mature ML/AI technology, we anticipate significant progress towards the vision of fully autonomous infrastructure. Even in the case of cloud services, many complex configuration and management choices need be made to optimize the performance and costs of several infrastructure categories. These choices range from capacity management in a broad range of workloads to more complex decisions in specific workloads such as databases. In databases, for example, there has been some very promising research done on applying machine learning to basic configuration all the way to index maintenance. We believe there are exciting capabilities to be built and potentially new companies to be grown in this area.

Specialized infrastructure

Finally, we believe that specialized infrastructure will make a comeback to keep up with the demands of next-general application workloads. We expect to see that in both hardware and software.

  • Specialized hardware: While ML workloads continue to proliferate and general-purpose CPUs (and even GPUs) struggle to keep up, new specialized hardware has arrived from Google’s TPUs to Amazon’s new Inferentia chips in the cloud. Microsoft Azure also now offers FPGA-based acceleration for ML workloads while AWS offers FPGA accelerators that other companies can build upon – a notable example being the FPGA-based genomics acceleration built by Edico Genome. While we are unlikely to invest in a pure hardware company, we do believe that the availability of specialized hardware in the cloud will enable a variety of new investable applications involving rich media, medical imaging, genomic information, etc. that were not possible until recently.
  • Hardware-optimized software: With ML coming to every edge device – sensors, cameras, cars, robots, etc. – we believe that there is an enormous opportunity to optimize and run models on hardware endpoints with constrained compute, power and/or bandwidth., for example, optimizes ML models to run on resource-constrained edge devices. More broadly, we envision opportunities for software-defined hardware and open source hardware designs (such as RISC-V) that enable hardware to be rapidly configured specifically for various applications.

Open Source Everywhere

For every trend in enterprise infrastructure, we believe that open source will continue to be the predominant delivery and license mechanism. The associated business model will most likely include a proprietary enterprise product built around an open core, or a hosted service where the provider runs the open source as a service and charges for usage.

Our own yardstick for investing in open source-based companies remains the same. We look for companies based around projects that can make a single developer look like a “hero” by making her/him successful at some important task. We expect the developer mindshare for a given open source project to be reflected in metrics such as Github stars, growth in monthly downloads, etc. A successful business then can be created around that open source project to provide the capabilities that a team of developers and eventually an enterprise would need and pay for.


These categories are the “blueprints” we have in our minds as we look for the next billion-dollar business in the enterprise infrastructure category. Those blueprints, however, are by no means exhaustive. The best founders always surprise us by their ability to look ahead and predict where the world is going, before anyone else does. So, while this post describes some of the infrastructure themes we are interested in at Madrona, we are not exclusively thesis-driven. We are primarily founder driven; but we also believe that having a thoughtful point of view about the trends driving the industry – while being humble, curious and open-minded about opportunities we have not thought as deeply about – will enable us to partner with and help the next generation of successful entrepreneurs. So, if you have further thoughts on these themes, or especially are thinking about building a new company in any of these areas, please reach out to us!

Current or previous Madrona Venture Group portfolio companies mentioned in this blog post: Datacoral, Heptio, Igneous, Integris, IOpipe, Isilon, Pulumi, Qumulo, Snowflake, Tier 3, Tigera and

Investment Themes for 2019

2018 was a busy year for Madrona and our portfolio companies. We raised our latest $300 million Fund VII, and we made 45 investments totaling ~$130 million. We also had several successful up-rounds and company exits with a combined increase of over $800 million in fund value and over $600 million in investor realized returns. We don’t see 2019 letting up, despite the somewhat volatile public markets. Over the past year we have continued to develop our investment themes as the technology and business markets developed and we lay out our key themes here.

For the past several years, Madrona has primarily been investing against a 3-layer innovation stack that includes cloud-native infrastructure at the bottom, intelligent applications (powered by data and data science) in the middle, and multi-sense user interfaces between humans and content/computing at the top. As 2019 kicks off, we thought it would be helpful to outline our updated, 4-layer model and highlight some key questions we are asking within these categories to facilitate ongoing conversations with entrepreneurs and others in the innovation economy.

For reference, we published our investment themes in previous years and our thinking since then has both expanded and become more focused as the market has matured and innovation has continued. A quick scan of this prior post illustrates our on-going focus on cloud infrastructure, intelligent applications, ML, edge computing, and security, as well as how our thinking has evolved.

Opportunities abound within AND across these four layers. Infinitely scalable and flexible cloud infrastructure is essential to train data models and build intelligent applications. Intelligent applications including natural language processing models or image recognition models power the multi-sense user interfaces like voice activation and image search that we increasingly experience on smartphones and home devices (Amazon Echo Show, Google Home). Further, when those services are leveraged to help solve a physical world problem, we end up with compelling end-user services like Booster Fuels in the USA or Luckin Coffee in China.

The new layer that we are spending considerable time on is the intersection between digital and physical experiences (DiPhy for short), particularly as it relates to consumer experiences and health care. For consumers, DiPhy experiences address a consumer need and resolve an end-user problem better than a solely digital or solely physical experience could. Madrona companies like Indochino, and provide solutions in these areas. In a different way, DiPhy is strongly represented in Seattle at the intersection of machine learning and health care with the incredible research and innovations coming out of the University of Washington Institute for Protein Design, the Allen Institute and the Fred Hutch Cancer Research Center. We are exploring the ways that Madrona can bring our “full stack” expertise to these health care related areas as well.

While continuing to push our curiosity and learning around these themes, they are guides not guardrails. We are finding some of the most compelling ideas and company founders where these layers intersect. Current company examples include voice and ML applied to the problem of physician documentation into electronic medical records (Saykara), integrating customer data across disparate infrastructure to build intelligent customer profiles and applications (Amperity), or cutting edge AI able to run efficiently in resource constrained edge devices (

Madrona remains deeply committed to backing the best entrepreneurs, in the Pacific NW, who are tackling the biggest markets in the world with differentiated technology and business models. Frequently, we find these opportunities adjacent to our specific themes where customer-obsessed founders have a fresh way to solve a pressing problem. This is why we are always excited to meet great founding teams looking to build bold companies.

Here are more thoughts and questions on our 4 core focus areas and where we feel the greatest opportunities currently lie. In subsequent posts, we will drill down in more detail into each thematic area.

Cloud Native Infrastructure

For the past several years, the primary theme we have been investing against in infrastructure is the developer and the enterprise move to the cloud, and specifically the adoption of cloud native technologies. We think about “cloud native” as being composed of several interrelated technologies and business practices: containerization, automation and orchestration, microservices, serverless or event-driven computing, and devops. We feel we are still in the early-middle innings of enterprise adoption of cloud computing broadly, but we are in the very early innings of the adoption of cloud native.

2018 was arguably the “year of Kubernetes” based on enterprise adoption, overall buzz and even the acquisition of Heptio by VMware. We continue to feel cloud native services, such as those represented by the CNCF Trail Map, will produce new companies supporting the enterprise shift to cloud native. Other areas of interest (that we will detail in a subsequent post) include technologies/services to support hybrid enterprise environments, infrastructure backend as code, serverless adoption enablers, SRE tools for devops, open source models for the enterprise, autonomous cloud systems, specialized infrastructure for machine learning, and security. Questions we are asking here include how the relationship between the open source community and the large cloud service providers will evolve going forward and how a broad-based embrace of “hybrid computing” will impact enterprise customer product/service needs, sales channels and post-sales services.

For a deeper dive click here.

Intelligent Applications with ML & AI

The utilization of data and machine learning in production has probably been the single biggest theme we have invested against over the past five years. We have moved from “big data” to machine learning platform technologies such as Turi, Algorithmia and Lattice Data to intelligent applications such as Amperity, Suplari and AnswerIQ. In the years ahead, “every application is intelligent” will likely be the single biggest investment theme, as machine learning continues to be applied to new and existing data sets, business processes, and vertical markets. We also expect to find interesting opportunities in services that enable edge devices to operate with intelligence, industry-specific applications where large amounts of data are being created like life sciences, services to make ML more accessible to the average customer, as well as emerging machine learning methodologies such as transfer learning and explainable AI. Key questions here include (a) how data rights and strategies will evolve as the power of data models becomes more apparent and (b) how to automate intelligent applications to be fully managed, closed loop systems that continually improve their recommendations and inferences.

For a deeper dive click here.

Next Generation User Interfaces

Just as the mouse and touch screen ushered in new applications for computing and mobility, new modes of computer interaction like voice and gestures are catalyzing compelling new applications for consumers and businesses. The advent of Alexa Echo and Show, Google Home, and a more intelligent Siri service have dramatically changed how we interact with technology in our personal lives. Limited now to short simple actions, voice is becoming a common approach for classic use cases like search, music discovery, food/ride ordering and other activities. Madrona’s investment in Pulse Labs gives us unique visibility into next generation voice applications in areas like home control, ecommerce and ‘smart kitchen’ services. We are also enthused about new mobile voice/AR business applications for field service technicians, assisted retail shopping (E.g., Ikea’s ARKit furniture app) and many others including medical imaging/training.

Vision and image recognition are also rapidly becoming ways for people and machines to interact with one another as facial recognition security on iPhones or intelligent image recognition systems highlight. Augmented and virtual reality are growing much more slowly than initially expected, but mobile phone-enabled AR will become an increasingly important tool for immersive experiences, particularly visually-focused vocations such as architecture, marketing, and real estate. “Mobile-first” has become table stakes for new applications, but we expect to see more “do less, but much better” opportunities both in consumer and enterprise with elegantly designed UIs. Questions central to this theme include (a) what ‘high-value’ new experiences are truly best or only possible when voice, gesture and the overlay of AR/VR/MR are leveraged? (b) what will be the limits of image (especially facial recognition) in certain application areas, (c) how effective can image-driven systems like digital pathology be at augmenting human expertise, and (d) how will multi-sense point solutions in the home, car and store evolve into platforms?

For a deeper dive click here.

DiPhy (digital-physical converged customer experiences)

The first twenty years of the internet age were principally focused on moving experiences from the physical world to the digital world. Amazon enabled us to find, discover and buy just about anything from our laptops or mobile devices in the comfort of our home. The next twenty years will be principally focused on leveraging the technologies the internet age has produced to improve our experiences in the physical world. Just as the shift from physical to digital has massively impacted our daily lives (mostly for the better), the application of technology to improve the physical will have a similar if not greater impact.

We have seen examples of this trend through consumer applications like Uber and Lyft as well as digital marketplaces that connect dog owners to people who will take care of their dogs (Rover). Mobile devices (principally smartphones today) are the connection point between these two worlds and as voice and vision capabilities become more powerful so will the apps that reduce friction in our lives. As we look at other DiPhy sectors and opportunities, one where the landscape will change drastically over the coming decades is physical retail. Specifically, we are excited about digital native retailers and brands adding compelling physical experiences, increasing digitization of legacy retail space, and improving supply chain and logistics down to where the consumer receives their goods/services. Important questions here include (a) how traditional retailers and consumer services will evolve to embrace these opportunities and (b) how the deployment of edge AI will reduce friction and accelerate the adoption of new experiences.

For a deeper dive click here.

We look forward to hearing from many of you who are working on companies in these areas and, most importantly, to continuing the conversation with all of you in the community and pushing each other’s thinking around these trends. To that end, over the coming weeks we will post a series of additional blogs that go into more depth in each of our four thematic areas.

Matt, Tim, Soma, Len, Scott, Hope, Paul, Tom, Sudip, Maria, Dan, Chris and Elisa

(to get in touch just go to the team page – our contact info is in our profiles)

The Difficult Decision For Heptio To Sell to VMware

We are thrilled for Heptio’s acquisition by VMware! This transaction is another resounding reinforcement that Kubernetes has become the de facto standard for infrastructure across clouds. It is also a tremendous validation of Heptio’s team, vision and execution.

Deciding “when to sell” is one of the toughest decisions faced by founders, boards and investors in growing companies. When presented with an attractive alternative to continuing to build the company independently, boards have a “high class problem” — but one they must consider with utmost thoughtfulness. Heptio was presented a very difficult challenge in this regard.

Heptio was founded by Kubernetes co-creators, Joe Beda and Craig McLuckie, less than two years ago. Madrona had the privilege of investing with Accel in the $8.5M Series A round at the company’s formation, and I joined the board as an Observer. Since this Day One, I’ve never been associated with a company that has accomplished more in as short a period of time. Craig and Joe had an original vision that the Kubernetes’ community would continue to strengthen and its rapid adoption would continue to increase; however, it needed to become easier and enterprises needed help with adoption. From this starting point, they saw an opportunity to lead a cloud native transformation in the enterprise and redefine the deployment and operations of modern applications across clouds.

This vision has exactly played out, and Heptio backed it up with great execution landing a blue-chip array of Fortune 500 customers for their Heptio Kubernetes Service (HKS) including 3 of the 4 largest retailers in the world, 4 of the 5 largest telcos in the US, and 2 of the 6 largest financial services companies in the US. They also made significant impact on the Kubernetes community by contributing 5 OSS projects (ksonnet, sonobuoy, contour, gimbal, ark) and collecting over 5000 Github stars. With this great execution, more funding followed. Nine months in, Madrona led the $25M Series B and the company invited me to join the Board and my colleague Maria Karaivanova joined as an Observer.

Through it all, Craig and Joe were the consummate founders. They approached building their business with laser-focus and a driving ambition to genuinely help customers and create a large, lasting business in the process. They were rock stars in the Kubernetes community, but approached all interactions with humility and pragmatism. They were extremely strategic in thinking through potential moves on the industry chessboard in what is a very dynamic market; but they always realized that none of it would matter if not paired with week-in-week-out blocking and tackling. Perhaps most importantly, they were relentless recruiters and built a world-class team of over 100 employees in less than 2 years, attracting other great leaders like Shanis Windland, Marcus Holm and Scott Buchanan. In doing so, they walked the talk that culture and diversity matter deeply in building a successful business, often passing on a good hire in favor of the right hire who was an even stronger fit for the business.

So, why in the world did we decide to sell? In short, sometimes you receive an offer too good to refuse. Heptio had the team, momentum and plenty of funding to continue; but in VMware, they saw a partner who not only recognized Heptio’s unique insights, assets and market position, but also had the resources and reach to execute more quickly on their vision and deliver an enterprise Kubernetes service to any cloud. The excitement over this potential – and a great financial offer – drove this deal. Market consolidation was always anticipated, and this decision was certainly not a reaction to IBM acquiring Red Hat or other market externalities.

In this decision process, the role of the investor is to ensure the founders and management team have the broad perspective of “what might be possible,” provide an objective view on the market (both opportunities and risks), and ensure the company has the necessary resources. At the end of the day, we support the founders and management team. In this case, while this acquisition came sooner than anyone anticipated, we all agreed that the strategic fit and economics made joining forces the right decision. Through it all, Craig and Joe balanced the interests of shareholders and employees along with other strategic considerations in exactly the way you hope any founders would. Ping Li from Accel was also an incredible thought partner from before company formation through this decision, and overall was one of the best board directors I’ve ever had a chance to work with.

Congratulations again to the Heptio team! We wish you all the best in furthering your mission and vision via the leadership roles you are taking inside VMware. We are excited the whole team is staying intact in Seattle and will continue to grow here. This acquisition is also a great validation of our broader investment theme around the enterprise move to cloud native and open source, and we continue to be very excited about our related investments in companies like Tigera, Shippable, and Pulumi.

Now my and Madrona’s fortunate job is to go find the next great Day One company … but I know it will be difficult to find another quite like Heptio.

Why Madrona Invested in Pulumi

Today I am very excited to announce our investment in Pulumi.

Pulumi aims to fundamentally improve the way people build, manage, and interact with cloud-native applications, services, and infrastructure.

There is a massive movement to the cloud among enterprise customers around the world. As that trend continues to gather and gain momentum, new and transformative techniques are required as customers truly begin to take advantage of cloud-native capabilities. This transformation grows leaps and bounds with serverless computing starting to emerge as the next frontier to enable truly distributed applications and services that are powered by microservices and event-driven functions.

Recent cloud infrastructure breakthroughs include serverless, containers and hosted cloud infrastructure. Containers are great for complex stateful systems, often taking existing codebases and moving them to the cloud. Serverless functions are perfect for ultra-low-cost event- and API-oriented systems. Hosted infrastructure lets you focus on your application-specific requirements, instead of reinventing the wheel by manually hosting something that your cloud provider can do better and cheaper. Arguably, each is “serverless” in its own way because infrastructure and servers fade into the background.

“This disruptive sea change is enabling Pulumi to deliver a single platform and tools suite that allow developers to build and ship code to the cloud in the easiest and fastest way.”


Eric Rudder, Joe Duffy and Luke Hoban are a world-class team to deliver such transformative experiences in a cloud-native world. They have decades of experience in platforms, tools, and programming models. Eric Rudder was one of the most senior executives at Microsoft, including running the $10B+ Server and Tools business, serving as a Technical Advisor to Bill Gates, and most recently as the EVP for Advanced Technology before leaving Microsoft. Joe Duffy was a senior technical engineering leader at Microsoft and was a critical part of the early team that built .NET and C#. Most recently, he was Director of Engineering and Developer Tools Strategy and, in that role, was instrumental in open sourcing .NET and taking it cross-platform to Linux and Mac. Luke has held a variety of product and engineering roles at Amazon and Microsoft. While at Microsoft, Luke co-founded TypeScript and developed Go support for Visual Studio Code.

I have had the privilege and the fortune to have worked with Eric, Joe and Luke closely over the years, and their passion to solve hard problems for developers and enterprise customers is unparalleled. I am personally very excited for the opportunity to work with this very talented group of people. We are confident that this kind of a world-class team is what is going to help drive a breakthrough as cloud-native becomes fundamental to enterprise software today and in the future.

We are doubly excited to partner with Pulumi given it is a Seattle-based early-stage start-up focused on native-cloud environment with a world-class founding team.

Please join me in welcoming Eric, Joe, Luke and the Pulumi team to the Madrona family!

Welcome Unearth to Madrona!

Pictured in photo: From left to right, Nate Miller, S. Somasegar, Brian Saab & Amy Hutchins.

Welcome Unearth to Madrona!

It is always a happy occasion to welcome a family member back into the household.

With Madrona’s investment in Unearth Technologies, we are excited to be working again with Brian Saab (CEO/Co-Founder) who we had previously worked with as the co-founder of buuteeq (a former Madrona portfolio company that was acquired by Booking Holdings, formerly Priceline). Brian co-founded Unearth with two other buuteeq & Booking Holdings employees, Amy Hutchins, Chief Product Officer and Nate Miller, Chief Design Officer. buuteeq spurred a lot of entrepreneurial spirit as we have also backed Pixvana – started by another co-founder of buuteeq, Forest Key.

Brian went back to his family roots as he began thinking of his next company. Brian grew up in a multigenerational construction company – a business he, as a technology executive, noticed hadn’t really changed that much despite cloud technologies, aerial imagery, and the plethora of tablets and laptops. He and his co-founders did some field testing and realized they could change that with their skills.

The construction industry has long been plagued by both low digitization and low productivity from its workforce. A $1.5T annual industry in the US alone and a $10T opportunity globally, the construction industry is projected to keep growing as new infrastructure is required to keep up with the global economy.

Because of the low productivity, the construction industry suffers from large amounts of waste and lost opportunity. For example, 98% of construction projects face cost overruns or delays with the average project delayed by 20 months and 80% more expensive than planned. In the US, this waste equates to approximately $500B lost per year. This is especially evident in large commercial and civic projects that require large teams and extensive communication between the field and office. This is the problem that Unearth is tackling.

Unearth has built a cloud-native collaboration and communication platform, called OnePlace, for construction and architecture teams to track the progress of their projects in real time. By giving all parties (including project owners and project managers) access to the Unearth platform, everyone is informed every step of the way of the progress of the construction. OnePlace is specifically built to seamlessly handle different data types aerial imagery, 360 images, traditional pictures, plans, and surveys.These are all integrated into the software platform which creates one view available to both office and field teams. After a year in beta and in use on major civic construction projects, OnePlace is open today for sign up at

The construction industry is at an inflection point of digitization and software adoption and Unearth is well-positioned to provide a compelling solution for its customers.

Please join me in welcoming Brian, Amy, Nate and the Unearth team to the Madrona family.

Tigera Joins the Madrona Family

Ever since the advent of virtualization technology in the early 2000s, software has become increasingly abstracted from its underlying hardware. The ability to “write once, run anywhere” has led to the runaway success of technologies like containers, which package software in a format that can run in isolation on a shared operating system. This allows developers to more easily collaborate on code across environments, get better utilization from their hardware, and build agile, secure software delivery pipelines.

The concept of the “software-defined datacenter” extends this analogy beyond compute into networking, storage, and security as well. With the advent of hybrid and multi-cloud, the underlying infrastructure is only getting more complex. The ability to manage infrastructure that cuts across private and public cloud leads to cost-effective solutions; better ability to simplify, automate, and scale; and the agility to move quickly in today’s IT landscape.

While containers have been the rage for the last 18-24 months, the complexity that grows from this technology quickly escalates to an unmanageable level from an application connectivity and security perspective. In fact, this has often been the talking point of those who are hesitant to adopt them too deeply. This conundrum has been an issue for large enterprises as they look to benefit from these new methods of software architecture and management.

This is the context in which we are very excited to invest in Tigera and the team.

Tigera provides secure application connectivity solutions built for modern cloud native applications. It addresses the application networking connectivity challenges that come with cloud native architectures, especially those that must connect to on-premises, legacy environments. Tigera does this by extending leading open source projects, Calico and Istio into commercial enterprise software that enables policy-based security, enterprise controls and compliance that works across on-premises data centers and all public clouds. Tigera offers large enterprise companies a solution for deploying containers within the Zero Trust security framework that they require and opens up this Fortune 500 market to innovations that increase agility and cost effectiveness.

The leadership team behind Tigera including the CEO, Ratan Tipirneni; co-founders Andy Randall, Alex Pollitt, Christopher Liljenstolpe, VP of Engineering, Doug Collier; and the most recent additions including Andy Wright, VP of Marketing and Amit Gupta, VP of Product Management make a world-class team that knows networking and cloud deeply. They have demonstrated strong leadership in the open source community and the ability to build a commercial offering that solves real pain points for enterprise customers moving to the cloud.

We, at Madrona, are looking forward to this exciting journey with Ratan and team at Tigera.

Heptio – a Day One Cloud Native Company Raises Series B

Today, Madrona is very pleased to announce that we are leading the new $25M Series B round in Heptio, partnering with existing investor Accel Partners and new investor Lightspeed Venture Partners. Heptio is another example of a “Day One” investment for Madrona. In November of 2016, we participated in the Heptio Series A led by Accel. In doing so, we partnered with Heptio founders and Kubernetes co-creators Craig McLuckie and Joe Beda at the very formation of their company whose mission is to (initially) make Kubernetes more accessible for all enterprises and (longer term) provide the standard framework for delivering enterprise apps in a multi-cloud world.

Our thesis with the Series A was pretty simple: (1) one of the largest trends in enterprise computing was the move to cloud native technology (container-based distributed microservices) and operations, (2) Kubernetes had become the leading way to orchestrate and manage container-based applications, (3) customers were beginning to demand better ease of use, accessibility, and an independent provider of support, services and training, and (4) the best team in the world to build this company began with Craig and Joe, two of the Kubernetes co-creators.

Since that time, the team has executed extremely well and, if anything, the market for Kubernetes has continued to explode even beyond expectations. Today, 50 of the Fortune 100 are using Kubernetes across industry verticals from retail to banking to manufacturing. Kubernetes continues to be the most active open source project in the world, and all the major cloud platforms are adopting it. Craig and Joe have begun to build a world class team at Heptio, launched three initial products, landed a number of high-profile (although still confidential) customers, and laid the groundwork for key partnerships.

Given all this progress, and our conviction that Heptio can be one of the next billion-dollar cloud companies in Seattle, we were honored to partner with great open source and infrastructure investors like Ping Li from Accel and John Vrionis from Lightspeed to lead the Series B. We are looking forward to continuing to partner closely with the Craig, Joe, and team to build Heptio through this next phase and beyond.

IOpipe – A Cloud Native Company

As the cloud increases its footprint in the enterprise, and ‘cloud native’ (aka serverless) development scales up, Madrona is continuing to uncover opportunities that make it easier to innovate and work in this new environment. Today we are proud to announce our seed investment in IOpipe. We co- led this round and teamed up with our colleagues at NEA and Underscore VC to fund the growth of this innovative company. IOpipe has moved its headquarters to Seattle to be near the center of gravity of the public cloud and the company will add team members in the area to support the company’s growth.

We first met Adam Johnson, the founder and CEO of IOpipe, at AWS re:Invent last fall– at TWO different events. After a quick follow-up pitch at the airport, we were hooked. IOpipe is providing important insight into how serverless applications run – and uses that info to diagnose what isn’t going right. AWS Lambda is a strategically important cloud service focused on this market and it has grown substantially into a major piece of how these applications area created. Developers embed IOpipe into their application and can see how functions are performing in realtime via the IOpipe dashboard.

For both developers and operations engineers, this is crucial information that will enable more organizations to develop cloud native serverless applications. IOpipe has already helped analyze and monitor over a billion events from users to date.

IOpipe is also an example of how accelerators are helping drive technology innovation and business. The company was a graduate of NYC Techstars – the founders moved to NYC for the program – which helped them flesh out their ideas, build a product and secure customers. We are supporter of Techstars through the Seattle chapter and love the chance to work with companies early on as they build and find their product market fit.