Integrating FluxCD with CI/CD Pipelines: A Guide
Connect FluxCD to CI pipelines: bootstrap Flux, secure Git access, enable image automation, and validate GitOps deployments for Kubernetes.
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Blog posts in the Cloud Optimization category
VPA Best Practices for Kubernetes Clusters
VPA best practices for Kubernetes: install, modes, resource policies, monitoring, and integrating with HPA/Cluster Autoscaler to reduce waste and stabilise workloads.
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AI in DevOps: Reducing Recurring Incidents
AI reduces recurring DevOps incidents with predictive alerts, automated root-cause analysis, alert deduplication and self-healing.
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AI in Multi-Cloud Resource Optimisation
AI reduces multi‑cloud costs, automates rightsizing and governance, and boosts performance with predictive scaling and unified workload orchestration.
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AI in Multi-Cloud Risk Mitigation
AI monitors, detects and automates security, compliance and FinOps across multiple cloud providers to reduce risks and cut costs.
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How to Monitor MFA for Compliance Standards
Continuous MFA monitoring with centralised logs, anomaly detection and phishing-resistant authenticators is essential to close compliance gaps and stop identity attacks.
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Behavioural Anomaly Detection: Use Cases in DevOps
Behavioural anomaly detection uses ML on logs, metrics and traces to detect infrastructure, performance and security issues in cloud-native DevOps.
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Cloud Cost Overruns: Prevention Tactics
Practical tactics—budgets, autoscaling caps, rightsizing, tagging and governance—to cut cloud costs 15–25%.
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Service Mesh vs. API Gateway: Cost Impacts
Compare API gateway and service mesh costs across infrastructure, scaling, licensing and operations to see which is more cost‑effective for your cloud setup.
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Why Energy Efficiency Matters in CI/CD Pipelines
CI/CD pipelines waste energy and money; optimise triggers, images, caching and scheduling to cut carbon emissions and cloud costs.
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How to Track Idle Cloud Resources
Practical steps to find and manage idle cloud resources — tagging, monitoring, automation and audits to reduce waste and lower cloud costs.
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Reducing Cloud Costs with KEDA Autoscaling
Save 25–40% on Kubernetes cloud spend with KEDA: event-driven autoscaling that scales to zero, integrates with HPA and cluster autoscalers to cut idle costs.
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