In one day, 2021 will officially be a wrap. Before we all checkout for some champagne and fireworks, let’s take a look at a few of our highlights from the last year and how Superwise is enabling customers to observe models at high scale.
Connect anything, anywhere, by yourself
MLOps is a stack. It’s about best-in-breed solutions that streamline your entire model lifecycle and beyond. That’s why we went API-first this year, made integrating with the Superwise model observability fully flexible and model and platform agnostic, launched extensive documentation, and are continuously adding ecosystem integrations like the one we launched with New Relic, and there are many more coming next year.
We didn’t just double down on making Superwise an open platform – we also made any integration a matter of minutes and 100% self-service from the platform UI, Superwise SDK, and our APIs.
Comprehensive metric discovery
Our metrics were already great, and now they’re even better. All our metrics are automatically discovered and configured whenever you add a model or version. This leverages all of the best practices we’ve baked in to shorten your time to value by delivering out-of-the-box metrics for integrity, activity, distribution, and drift tailored to your models and data. We’ve also just released custom performance metrics, so you can express any business KPI you need to analyze and monitor.
Self-service monitoring policy builder
No one wants to configure policies metric by metric. It’s slow, tedious, and not scalable given how each model is unique and monitoring use cases vary. That’s why we rolled out Superwise’s monitoring policy builder:
- It lets you build and deploy policies within minutes
- Has flexible logic to support any unique use case
- Automatically configures thresholds
- Lets you control sensitivity based on business impact.
Now you can logically express what events you need to be alerted about, and Superwise will continuously scan your models for you and ensure that the right team gets the right alert at the right time.
We tripled our user base over the last 2 quarters alone. With more data science and ML engineering teams using the platform to observe their models in production, we added a host of authentication, security, and user management capabilities to the platform.
User management, Multi-Factor Authentication, SAML, token management, and audit logs are all available for our customers on the platform.
2021 has been a year marked with achievements across the board and not just in terms of customers onboarded, feature releases, and engineering accomplishments. We opened our first U.S. office in New York, doubled the team (and still are – check out our open positions here), and even had our first all-hands event since coming back from working remotely!
We’re proud of everything that our team across the globe has achieved over the last year, and given that we know what’s coming up next, 2022 is going to take model observability to a whole new level.