In today’s technology-dependent world, engineering teams are under extreme pressure to deploy faster and more frequently while achieving impeccable (or seemingly impossible) resilience standards. Yet, constantly evolving Microservices and API dependencies make that harder than ever.
While cloud-native adoption promises speed and agility, teams are drowning in data and struggling to keep up with daily or hourly changes in their highly dynamic environments - often stuck in a reactive loop applying fixes after breakages happen. Dashboard based tools lack the capabilities to help engineering teams adopt a more proactive approach when seeking answers to questions like: how to make their apps highly performant, resilient and secure in the face of constant change? How to implement actions within complex stacks like K8s to meet application goals? It is time to convert the deluge of cloud-native data into insights and action that help fast-paced engineering teams proactively command their cloud-native apps, without the toil.
Operant offers a single data-powered command layer at the application level. Serving as a bridge between applications and infra, Operant provides the information teams need to make informed decisions before, during, and after deployments, and provides powerful automated command functions that give teams the control they need to manage their whole environment securely and resiliently.
While the holy grail of a “single pane of glass” has been sought after (and sold) for many years already, we have found again and again that the concept lacks real-world viability. While teams need a comprehensible and accurate view into what is happening across their native and third party ecosystems (already a feat that most teams are still struggling to build in-house and that solutions in the market fail to provide without extensive instrumentation and cost), teams also need the ability to quickly act on that information to actually make meaningful improvements to their systems at scale.
That is why Operant’s command layer is dynamic and intelligent, automatically updating as your systems and data signals evolve, so that teams do not have to waste time instrumenting and re-instrumenting to keep up with a pace of change that is impossible for humans to match. Instead, we provide key insights and automation right out of the box (remember when software actually came in boxes?) that teams need to take control of their applications proactively, so that both Dev and Ops can focus on solving more interesting and innovative problems without being bogged down by toil and drift.
We believe it is time to re-think how technology can empower engineering teams to manage the risky and stressful environment of fast-paced cloud-native development. Our unique solution is rooted in our deep expertise in Kubernetes, building streaming events processing systems, and building pipelines and models for reinforcement learning systems.