VMblog: Can you give us the high-level rundown of your company's technology offerings? Explain to readers who you are, what you do, what problems you solve, etc.
Ajay Gandhi: Dynatrace provides software intelligence to simplify cloud complexity and accelerate digital transformation for the world's largest organizations. With automatic and intelligent observability, the all-in-one Dynatrace Software Intelligence Platform delivers precise answers about the performance of applications, microservices, the underlying infrastructure, and the experience of all users to enable organizations to innovate faster, collaborate more efficiently, and deliver more value with dramatically less effort.
Our customers say Dynatrace is a key strategic platform they can't operate without. They are under pressure as digital transformation continues to accelerate - digital services are crucial for new revenue streams, managing customer relationships, keeping employees productive, and safeguarding organizations. This transformation is happening in dynamic, multicloud environments, with microservices, containers, and Kubernetes helping them achieve the agility they need to accelerate innovation and more successful business outcomes. However, these environments are incredibly complex - we recently commissioned a study of 700 CIOs which found that 63% say the complexity of their cloud environment has surpassed human ability to manage, as the scale and frequency of change is exponentially greater than that of the old data-center world. Many technologies collect data from these environments, but while important, collecting data is not enough.
To maintain productivity, meet customer demands, and keep up with the competition, teams need to transform how they work - innovating faster, collaborating more efficiently, and delivering greater business value. They need precise answers - not statistical guesses - detailing the current state of their multicloud environments. There's no time to manually configure and instrument these environments, as 70% of CIOs say their team is already forced to spend too much time doing manual tasks that could be automated. That's where Dynatrace comes in. We enable the world's largest organizations to keep their clouds moving smoothly, ensure all digital services run flawlessly, and identify and resolve issues or bottlenecks before they impact end users.
VMblog: How does your company or product fit within the container, cloud, Kubernetes ecosystem?
Gandhi: As organizations pursue digital transformation efforts, they're increasingly investing in cloud-native applications that run on containerized, microservices-based architectures. But the dynamic nature of multiclouds, containers, and Kubernetes has created extremely complex IT environments that are beyond human capacity to manage - there is no time to keep up with and manually configure and instrument apps, or script and source data. No matter your cloud platform, container runtime or service mesh layer, or if you are running thousands of nodes, monitoring your Kubernetes infrastructure and workloads should be simple.
With AI-powered automatic, intelligent observability, our customers dramatically reduce manual or redundant work and multiply teams' productivity. Dynatrace's AI engine, DavisTM, assists digital teams by reducing wasted motions and accelerating outcomes, whether that's speed and quality of innovation for development, automation and efficacy for operations, or optimization and consistency of user experiences and business outcomes. It's like having an entire new team working for you 24/7, allowing you to focus your resources on what really matters.
Davis multiplies the power and effectiveness of an organization's entire team several fold - and it's automatic. As a result, teams shift from reactive to proactive, from guessing to knowing, from sifting through logs or becoming tied up in war rooms to driving innovation, acceleration, and business value.
Earlier this year, we also announced enhancements to the Dynatrace Software Intelligence Platform, providing AI-powered observability into the infrastructure layer of Kubernetes environments, including every container, pod, node, and cluster. In doing this, we are helping our customers instantly understand the availability, health, and resource utilization of Kubernetes infrastructure. And because Kubernetes is so dynamic, Dynatrace continuously discovers all infrastructure components, microservices, and interdependencies between entities to create and maintain a precise, real-time topology map. Davis then uses this map to automatically identify and prioritize anomalies and, as needed, enable automatic remediation.
We have always provided deep observability across applications and microservices running in Kubernetes, so with these updates, we were excited to bring that same AI-powered advanced observability to all layers of Kubernetes infrastructure. From running a managed Kubernetes service such as EKS, AKS or GKE, to deploying Kubernetes on-premise with OpenShift or any combination in between, with Dynatrace, users will gain that deeper level insight into their Kubernetes environment.
VMblog: And while talking about your products, can you give readers a few examples of how your offerings are unique? What are your differentiators?
Gandhi: Dynatarace is the only Kubernetes monitoring solution that provides full stack observability without changing code, container images, or deployments. Unlike our competitors, the Dynatrace platform is purpose-built for operations, application, and business/digital experience use cases, leveraging a unified data model with automation and AI built into the core. Our unified platform-approach to observability means data from metrics, logs, traces, user behavior, APIs, OpenTelemetry, and other open source frameworks are unified in a common data model, with the full context of dependencies and relationships. What's more, we do all of this automatically, and massively at scale. And through advanced analytics collected via the Davis AI engine, we are able to add predictability and actionability, giving our customers back their time so that they can leap ahead of the competition in efficiency, speed, innovation, and cost.
Our competitors go to market with a suite of tools, but without purpose-built use cases. We believe the volume, velocity, and variety of data in modern multiclouds is already too great for humans to deal with simply using dashboards. Dynamic, multicloud observability needs to be combined with continuous automation and AI-assistance to tame complexity and make sense of the mountains of data gathered and analyzed.
We purpose-built the Dynatrace Software Intelligence Platform on a unified data model with automation and AI at the core. Modules for APM, Infrastructure Monitoring, AIOps, Digital Experience Monitoring, and Analytics easily extend the platform to help digital teams manage BizDevOps use cases. This provides a time-to-market, efficiency, and cost of ownership advantage over our competitors' solutions.
VMblog: Normally at the KubeCon event, sponsors are showcasing new products or new product updates and features for the first time. Do you have anything new that you've either recently announced or plan to discuss in more detail at the event? Can we get a sneak peek?
Gandhi: Digital transformation is accelerating, with projections that by 2022, 90% of new enterprise applications will be developed as cloud-native, using agile methodologies and API-driven architectures that leverage microservices, containers, and serverless functions. In fact, the push for faster software innovation has increased investments in not only cloud native development, but also new open standards such as OpenTelemetry, which companies are using to build observability telemetry and instrumentation into their Kubernetes environments
As a company, we are always innovating. We do about 25 major releases a year, including earlier this year when we announced our collaboration with Google and Microsoft on the OpenTelemetry project to help shape the future of open standards-based observability. OpenTelemetry is focused on providing standardized transaction-level observability through the generation, collection, and description of telemetry data for distributed cloud-native systems. As OpenTelemetry becomes more widely adopted, it will serve as an additional data source that further extends the breadth of cloud observability.
At Dynatrace, we're excited about the opportunity for OpenTelemetry to increase the breadth of data and scope of the cloud ecosystem that organizations can observe. We are already working with companies like Microsoft, Google, and others to provide our technical expertise, manpower, and code to equip the project with enterprise-grade capabilities such as higher-level instrumentation APIs, integration of universal trace context, and runtime management.
At KubeCon, we'll be making an announcement that expands on our work in this space, increasing the breadth of data and the scope of the cloud ecosystem, providing DevOps, CloudOps, and cloud application teams deep, automatic, and intelligent observability at scale for the most advanced cloud environments. As a key contributor to OpenTelemetry and a founding member and co-chair of the W3C Trace Context, Dynatrace is a big supporter of the open standards movement around the traceability of modern environments.
This year at KubeCon, we have some exciting news that will further our support of this movement and extend the reach of our observability as we look to bring even more value to our many multicloud customers.
VMblog: At what stage do you feel we are at with regard to containers? Is there anything still holding it back? Or keeping it from a wider distribution?
Gandhi: We've seen a real embrace of the use of containers. We recently commissioned a study of 700 CIOs which found that 86% of respondents said they are using modern architectures, which includes cloud-native technologies and platforms such as Kubernetes, microservices, and containers. I expect that this number will continue to climb. As organizations look to accelerate their digital transformation and innovate faster, they will increase their use of microservices, containers, and Kubernetes. As a result, we'll see even more complexity from the increasing scale of more dynamic multiclouds, causing an even greater need to gain automatic and intelligent observability into these environments as they grow in scale and volume.
VMblog: Finally, without a crystal ball, what do you think trade shows look like in 2021? Do we go back to thousands of people in person at an event? Or do things stay virtual for the near term? Is your company prepared to sponsor a physical event next year should they return?
Gandhi: At Dynatrace, we have been really focused on helping our customers and partners navigate the pandemic. As a part of this, we have transitioned all our events to virtual settings, so I think that for the near-term, we will definitely stay virtual. We just wrapped our regional Dynatrace Go conferences which were very successful and included keynotes from Steve Wozniak and Netflix's Marc Randolph. Looking ahead to 2021, we are ramping up efforts around our annual Perform conference taking place virtually February 8-11 - expect to see some great talent and exciting announcements there, as well.
When it comes to events in general, I think that there are a lot of benefits to virtual events in terms of audience reach and connecting with customers, partners, and other key stakeholders who otherwise may not have been able to attend an in-person event. That said, Dynatrace is committed to prioritizing the safety and well-being of our employees, customers and partners. As a global company, the majority of our employees are still working from home, this is certainly true in the US. As an organization, we will continue to look to local health authorities for guidance, but look forward to attending and hosting in-person events once deemed safe for all.
