Key Metrics for Multi-Cloud Application Monitoring
Six core metrics—latency, traffic, UX, uptime, capacity and cost—with thresholds and standard labels for consistent multi‑cloud monitoring.
Read moreBlog posts in the Performance category
Six core metrics—latency, traffic, UX, uptime, capacity and cost—with thresholds and standard labels for consistent multi‑cloud monitoring.
Read morePractical steps to reduce video CDN bills: optimise cache keys and TTLs, add origin shielding, tune encoding/ABR, use multi‑CDN routing and monitor £/GB.
Read moreManaged testing is faster to start, but deeper control needs more setup — benchmark at multiple load levels with the same external tool.
Read moreDon’t pick the cheapest cross-cloud path unless it meets latency, throughput and reliability—egress costs and instability add up fast.
Read moreSidecar proxies, Prometheus, tracing and logs reveal service-to-service traffic, pinpoint slow hops and diagnose errors without app changes.
Read moreCompare mesh runtime cost, latency and features to choose the lightest option that meets your security, routing and observability needs.
Read moreStandardise telemetry, alert on user impact, trace critical flows and control telemetry volume to get observability working at scale.
Read moreMeasure 2-4 weeks of usage, set requests and limits from p90–p99, and test under live traffic to cut costs and avoid throttling or OOMs.
Read morePublic cloud often uses less energy per workload; hybrid can be greener when latency, data residency or placement matter.
Read moreUse forecast-led predictive scaling with reactive fallback to reduce latency and cloud spend for repeatable workloads.
Read moreCut serverless tail latency by pre-warming; size provisioned concurrency for p95/p99, test lighter runtimes and schedule to save cost.
Read moreCut search costs and improve reliability: keep shard sizes 10–50 GB, match replicas to failure needs, tier old data and review sizing regularly.
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