Posts
ODPE reframes telemetry as a product to deliver end-to-end visibility for real-time AI workloads, with architecture, instrumentation, pipelines, and GitOps-driven automation.
Patterns and trade-offs for observability in distributed ML: signals, pipelines, feature and model telemetry, tracing, alerting, and privacy controls to detect drift and reduce time to resolution.
Design and tune Kubernetes liveness, readiness, and startup probes for reliable rollouts, graceful shutdowns, mesh-aware health, and actionable observability that avoids unsafe restarts.
A field-tested Kubernetes multi-tenancy blueprint using namespaces, HNC, and NetworkPolicy, with guardrails, corrections, and references. Includes practical patterns, pitfalls, and proven add-ons for security, scale, and autonomy.
eBPF closes the Kubernetes kernel visibility gap and adds real-time runtime security. Learn architecture, deployment, tuning and pitfalls so you can profile, trace and secure clusters in production.
Advanced Kubernetes tuning improves scalability and performance via resource optimization, intelligent scheduling, and observability.
Master production chaos engineering through gradual adoption, comprehensive observability, and strategic experimentation to build antifragile systems.
Actionable architectures and real-world strategies for Kubernetes observability with modern open-source tools, secure telemetry design, and SaaS use cases.
Comprehensive comparison of Docker Engine, containerd, and CRI-O for Kubernetes production deployments, covering performance, security, and operational considerations.
Technical strategies and real-world guidance for building secure, reliable cloud-native observability frameworks with open-source tools, emphasizing practical adoption phases, SLO-driven design, and actionable integration steps.
Modern infrastructure often lacks proper documentation, leading to inefficiencies, security risks, and operational chaos. Here is why it matters and how to fix it.
Implement effective guardrails for LLM tools in your developer stack to enhance productivity while maintaining security, with practical strategies for risk assessment, access control, data protection, and continuous monitoring.
Explore actionable strategies to make internal platforms more usable, reducing developer friction and boosting delivery speed. Learn how feedback, documentation, consistency, and self-service drive meaningful improvements.
AI is becoming a powerful co-pilot for developers, changing how they work. It assists with coding, debugging, automation, and learning. The role evolves, requiring skills in leveraging and validating AI tools for higher-level work.
AI code assistants promise efficiency, but their real significance for platform engineering is deeper: shifting bottlenecks, enhancing collaboration, and raising the bar on architecture and system resilience—not just writing code faster.
Learn how to implement SLOs to balance reliability and innovation for cloud-native applications
Cloud costs can quickly spiral out of control, but FinOps best practices offer a way to rein them in. Learn how to understand your cloud costs, implement budgeting and forecasting, optimize your resources, and foster a culture of cost awareness.
Learn how observability enhances cloud-native security. Detect and respond to threats in real-time.
Learn how to balance automation and human oversight in cloud-native incident response to ensure speed, accuracy, and control in dynamic environments.
Explore strategies for managing multiple Kubernetes clusters, ensuring consistency and control across environments.
Progressive delivery minimizes risks in cloud-native deployments by rolling out updates gradually. Learn why it matters, how it reduces errors, and its real-world benefits for safer, faster releases.
Learn strategies to manage data gravity in cloud-native apps, reducing costs and latency while improving performance through practical examples and tools.
Learn how to integrate Open Policy Agent and Conftest into your GitOps pipeline, write a Rego rule to block mutable image tags, and configure OPA audit logging for real-time compliance reporting.
Defend your CI/CD pipeline against supply chain attacks. Learn practical patterns: secure source code, manage dependencies, harden builds, sign artifacts, protect secrets, and monitor activity. Protect your software from compromise.
Resource quotas in Kubernetes prevent resource starvation and noisy neighbors by limiting resource consumption per namespace. This ensures fair allocation and stable performance across applications.
Turn cloud costs into actionable tests by adding money checks to CI/CD. Learn why cost belongs next to unit tests, which tools to use, and how to fail builds when budgets break.
Apply GitOps principles to database schemas for consistent migrations and prevent production drift. Use Git for version control, automation, and drift detection.
Internal developer platforms (IDPs) face scaling challenges beyond initial setup. This post identifies common operational bottlenecks like onboarding friction, integration complexity, and performance issues, offering strategies like standardization, automation, and observability to ensure sustainable growth.
Building an effective Internal Developer Platform requires focusing on developer experience (DX), not just technology. Treat the platform like a product, engage with developers, and invest in documentation and support to bridge the DX gap.
Hidden failures in Kubernetes can quietly erode reliability. Learn how to trace, diagnose, and fix these issues using the right tools and practical examples to surface problems before they escalate.
Many teams fail at platform engineering by trying to build everything in-house. Learn concrete anti-patterns, with examples, and practical lessons on focus, sustainability, and user-driven internal platform development.
Automating production rollbacks can backfire. This post covers where teams stumble, practical rollback patterns, trade-offs, and the critical aspects often missed when protecting systems with automation.
Concrete strategies for building cost-efficient cloud-native systems without losing reliability. Covers right-sizing, managed services, scaling, observability, graceful degradation, and real-world examples.
Pattern-driven incident response playbooks use modular, reusable patterns for flexible, effective handling of incidents in cloud-native environments. This approach beats static scripts, adapts to change, and improves response quality and speed.
Pragmatic guidance for cloud-native teams adopting zero trust networking: core patterns, real-world use cases, and common pitfalls to avoid. Move past buzzwords with practical examples for modern cloud security.
How to move security, compliance, and observability to the start of your Terraform workflow by using policy as code, automated checks, and standardized modules, with practical examples and actionable advice.
Revised strategies for managing multi-cloud security, including centralized management, policy standardization, and continuous monitoring, provide clear steps to reduce complexity and risk while enhancing team knowledge.
Explore pivotal lessons and best practices for building a cloud-native observability framework. Learn how to integrate observability from the start using industry-standard tools and data-focused strategies.