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🟥 RED Metrics: A Better Way to Understand What Your Users Are Experiencing Most teams track CPU and memory for system health. But here’s the catch: ✅ Low CPU ≠ Happy Users ✅ High memory ≠ Slow App If you're not looking at request-level behaviour, you're missing what customers are experiencing.

🎯 RED metrics aren’t just another dashboard—they’re the foundation for SLO-driven monitoring and proactive issue detection. Start small. Instrument a few key endpoints. Build SLOs. Alert on what matters. Monitor what your users feel—not just what your servers see.

🟥 RED Metrics: A Better Way to Understand What Your Users Are Experiencing Most teams track CPU and memory for system health. But here’s the catch: ✅ Low CPU ≠ Happy Users ✅ High memory ≠ Slow App If you're not looking at request-level behaviour, you're missing what customers are experiencing.

Let’s take an example: Say you run an order service, and you want 📌 <5% error rate 📌 99% of orders complete <50ms With RED metrics, you can: ▪️Detect when latency spikes or errors increase ▪️Set meaningful alerts tied to user experience ▪️Debug faster with clear SLOs and performance signals

🟥 RED Metrics: A Better Way to Understand What Your Users Are Experiencing Most teams track CPU and memory for system health. But here’s the catch: ✅ Low CPU ≠ Happy Users ✅ High memory ≠ Slow App If you're not looking at request-level behaviour, you're missing what customers are experiencing.

🚨 Here are 5 tips (+ 1 bonus tip) on how to reduce your observability costs and increase your ROI 📌 1. Look at your customer journeys and understand how you can measure the user experience. Use that for creating your SLOs.

In a nutshell high quality telemetry helps you proactively identify & manage your customers experience, while low value telemetry adds noise & increase your cost.

🚨 Here are 5 tips (+ 1 bonus tip) on how to reduce your observability costs and increase your ROI 📌 1. Look at your customer journeys and understand how you can measure the user experience. Use that for creating your SLOs.

📌 5. Think about an information hierarchy when building dashboards and monitoring. You only need the details when you need to drill down.

🚨 Here are 5 tips (+ 1 bonus tip) on how to reduce your observability costs and increase your ROI 📌 1. Look at your customer journeys and understand how you can measure the user experience. Use that for creating your SLOs.

📌 3. High cardinality metrics can provide high visibility into your customer experience/SLO. High cardinality metrics are expensive - so choose wisely.

🚨 Here are 5 tips (+ 1 bonus tip) on how to reduce your observability costs and increase your ROI 📌 1. Look at your customer journeys and understand how you can measure the user experience. Use that for creating your SLOs.

Are there any downsides to having platform abstractions? 🤔 📌Our initial product was an internal developer platform + portal. We eat our own dog food. So once it was operational we used it for about a year before we pivoted. #kubernetes #PlatformEngineering

📌After one year, there was a clear difference in the kubernetes knowledge between the interns we hired before and the interns who just got hired when the platform was in place.

When there's an issue, I generally like to understand the events leading up to it as it helps to narrow down the root cause #observability #devops #sre #kubernetes

📌 Did it trigger any monitors? Any anomalies detected? 📌 Did we change configuration? 📌 When did we last deploy? 📌 Was there any node churn? or resource pressure events?

⛑️ There are multiple events related to a particular item. Each event caries a status among other meta data. These update events can happen every few seconds to every few hours ⬇️ #SoftwareArchitecture #SystemDesign #DistributedSystems

📌 We can store each status as columns in the item table OR 📌 We can store each status (and related data) in it's own table, which requires multiple joins ⬇️

⛑️ There are multiple events related to a particular item. Each event caries a status among other meta data. These update events can happen every few seconds to every few hours ⬇️ #SoftwareArchitecture #SystemDesign #DistributedSystems

Our journey into becoming an Observability vendor wasn't a straight line. We were always driven by how can we help customers make sense of what went wrong (root cause analysis) and more ambitiously warn that it may be trending that way (proactive insights).

Speaking with customers we realized, 🔴 The cost of observability was a real pain point 🔴 Data is ingested into these platforms at a higher cost, and customers spend enormous amount of time sifting through the data to make sense of it 🔴 Dashboards != Insights

Our journey into becoming an Observability vendor wasn't a straight line. We were always driven by how can we help customers make sense of what went wrong (root cause analysis) and more ambitiously warn that it may be trending that way (proactive insights).

SRE Teams face two challenges 📌 Identifying Issues quickly 📌 Figuring out how to resolve the issues Randoli Observability solution powered by #opentelemetry can help you with both! It can 💡 Automatically detect issues 💡 Match Runbooks to the issues #kubernetes #openshift #observability