In today’s digital world, organizations are constantly undergoing change. They’re moving to the cloud and rolling out DevOps at scale—all in the name of driving innovation. But moving from a monolith to microservices can lead to applications becoming increasingly distributed. When problems arise, customers don’t care how many teams and services you have, or how complex your architecture is. They only care that your services work when they need them to.
If you asked your engineering team how well they can handle all of the security and observability data they’re managing, would you get a resounding “Yeah boss, we’re good to go!” in response? Possible, but unlikely. Chances are they feel like they’re stuck on a boat that’s taking on water, spending their day using tiny buckets to scoop some of it out, with no way to plug any of the leaks.
What is AIOps? How does an AIOps platform help your observability practice? AIOps platforms analyze telemetry and events, and identify meaningful patterns that provide insights to support proactive responses. AIOps platforms have five characteristics:1 The above is Gartner’s definition and is part of the Gartner® “Market Guide for AIOps Platforms.” The Gartner definition is also aligned with our view.
This is the second tutorial in a two-part series. You can also learn how to automate AWS Lambda function deployments to AWS CDK.
Cloud has become the de facto way to build infrastructure, meaning cloud providers end up in charge of a significant amount of the apps we use every day. From the likes of Netflix, Slack, Ring and Doordash running on AWS or PayPal, Twitter and HSBC on GCP, it's easy to see how impactful a failure of any type can be. Let's look at some of the issues that have happened recently that have led business to consider how dependent they are on a single provider.