![[WEBINAR] Why Automated Solutions Aren’t Enough When it Comes to Managing Microservices](/_next/image?url=%2Fapi%2Fimages%2Ffile%2F622fbf5a69cc21f4d54fdca9_skilup_shareables-01.webp&w=3840&q=75&dpl=dpl_6cWowUVaqpVvZ1fAj9Ty6Nt5MsFB)
Sedai sponsored the DevOps Institute’s 2022 SRE SKILUp Day. In this webinar, I chatted with Lee Gilmore, a Principal Software Engineer and AWS Serverless advocate about the difference between automated and autonomous systems.
If your team is constantly rewriting rules to keep up with workload changes, there is a better way. Book a demo to see what autonomous cloud management looks like in production.
While the shift from monolith to microservices changed the game regarding deployments and team velocity, it simultaneously introduced the monotony of daily repetitive work and manual tasks. SREs and DevOps now need to rethink how teams manage their applications on a day-to-day basis.
Ready to move beyond automation for microservices management?
Book a Sedai demo to leverage autonomous optimization that continuously improves microservices performance, reliability, and efficiency.
To streamline this work, teams typically look to automated systems and smart alerts to help them stay on top of critical activity in their cloud environments. While a highly automated approach can certainly help with application management, these systems are not independently intelligent.
“Automated” and “autonomous” sound interchangeable and it seems like only a few extra letters are the difference, but there’s one important differentiator that bridges the gap between them: intelligence. An automated system can eventually graduate into an autonomous system.
Autonomous cloud management replaces the rule maintenance burden with continuous learning — so your team stops writing and debugging scaling rules and starts seeing optimization outcomes. Book a demo to see how that applies to your microservices environment.