Operations | Monitoring | ITSM | DevOps | Cloud

How to test the reliability of a Point of Sale (POS) system

Point of Sale (POS) systems are the backbone of any retail store. A single outage can cost retail companies thousands of dollars each minute in lost sales, and even more if the outage happens during peak hours. If the outage goes on too long, it can cause even more costly damage as customers abandon carts and turn to competitors. In an industry where customer loyalty is worth its weight in gold, that brand damage can end up even more costly than the initial lost sales.

Chaos Engineering works, but it has to scale

Over the years, Chaos Engineering has proven its effectiveness time and time again, uncovering risks and saving companies millions they would have lost in painful, brand-impacting outages. But as Chaos Engineering adoption increased, we found organizations running into the same stumbling blocks when they tried to scale. Individual teams would get great results with Chaos Engineering, then stall as they tried to get more teams involved.

3 things you can do to get closer to five nines

5 minutes. That’s how much downtime some of the world’s largest enterprises will tolerate. For most organizations, five nines (99.999%) of availability sounds like a pipedream. But the trick to increasing availability isn’t massive infrastructure spending or complex system redesigns. All it takes are three key practices that any team can adopt and implement. In this post, we’ll present these practices and how we implement them at Gremlin.

{unscripted} AI in Chaos Engineering

Harness AI enhances your chaos engineering capabilities by leveraging artificial intelligence to automate and optimize reliability testing and analysis. One of the challenges of scaling up the Chaos Engineering practice within the organization is skilling up the users to create or run chaos experiments and to come up with solutions to mitigate the risks that are identified during the chaos experiment execution. The Chaos Engineering module comes with an AI Agent called "AI Reliability Agent" that helps in these aspects.