Introducing Decisions: smart correlation for busy ops teams

As an SRE or DevOps engineer, a huge percentage of your day is composed of micro-decisions. You’re constantly context-switching, silencing noisy pages, creating mental notes and links between incoming issues, investigating root causes, and developing solutions for more sustainable infrastructure — and, too frequently, fire-fighting.

Imagine if you could take all the nuggets of knowledge you pick up throughout this journey — about service dependencies, application performance trends, quirks in your production system, etc — and combine them with the power of a machine learning engine that continuously improves from your monitoring data and feedback. Now imagine if this process was light-touch, intuitive, and even fun.

Introducing SignifAI Decisions: an incredibly flexible, machine-learning powered correlation engine, combined with a beautiful and intuitive logic builder, all designed with SRE and DevOps teams in mind.

Automatically generated logic

As soon as you integrate your monitoring tools, SignifAI starts learning from all incoming data and suggests Decision logic based on historical trends. Like a well-trained data scientist that understands SRE and DevOps-specific use cases, SignifAI automatically proposes new correlation rules that can help give context and reduce noise for commonly occurring problems.

Capture user input in natural language

With the most comprehensive engine available, Decisions allows you to replicate any kind of logic with unlimited flexibility. Each Decision you create runs over all of your incoming monitoring data to correlate related events and reduce your alert noise. The minutes invested in creating new Decisions can pay off in hours of reduced time context switching or investigating issues, and since the logic is natural language-based, it’s practically self-documenting (you’re welcome, future you!).

Intuitive and beautiful

The SignifAI Decision builder is designed with busy users in mind. Smart auto-complete and easy-to-understand operators guide you through creating logic — on average, it takes less than a minute to create new Decisions. Instead of starting with a gigantic dashboard of knobs and gizmos, the Decision builder keeps it simple, and allows you to quickly add layers of complexity as you need them.

Continuously improving

A default set of Decisions provides, on average, over 80% noise reduction out of the box and over 95% over time. As you add your own logic, activate Suggested Decisions, and provide feedback to the system about the accuracy of your correlated issues, SignifAI will learn and get smarter.

Accessible machine learning

In addition to traditional logic construction with a wide range of 15+ operators, SignifAI puts advanced machine learning tools at your fingertips in an easy-to-understand format. Advanced NLP categorization, categorical and deep learning-based clustering, and a whole suite of similarity algorithms are available in the Decision builder and leveraged in Suggested Decisions.

The one-minute walkthrough

As acknowledged, you’re a busy engineer with more important things to do than spend forever learning how to use a clunky tool. Check out how quickly you can create a single Decision that results in noise reduction for your incoming application events:

https://www.youtube.com/watch?v=7se9sBQBpqE

Tell me more!
If you’re ready to get started, sign up for your FREE TRIAL today.

Originally published at blog.signifai.io on July 17, 2018.