A guide to using the Arconia framework to add Quarkus-like Dev Services and observability features to Spring Boot applications.
A curated collection of articles on software architecture, development practices, Java updates, and testing strategies for tech professionals.
A guide to deploying and using a custom Azure Local Deep Insights workbook for enhanced observability of guest VMs and cluster health.
A critique of the 'pillars of observability' as a marketing term, arguing for a focus on technical 'signals' like traces, metrics, and logs instead.
Explains how Kubernetes API server concurrency controls like --max-requests-inflight work to manage performance and prevent overload.
The author seeks community input on observability practices and software buying strategies for a tech book update.
Learn how to extend monitoring for Windows EC2 instances by deploying and configuring the Amazon CloudWatch Agent using AWS CDK.
Author seeks advice from experienced software buyers for a new 'Observability Governance' section in the upcoming second edition of 'Observability Engineering'.
Explains why P95 and P99 latency metrics are crucial for understanding real user experience, not just average response times.
A guide to using an open-source command-line tool for populating Azure Storage Accounts with demo data for testing, training, and dashboard visualization.
A comprehensive guide to implementing and using the Python logging module for application monitoring and performance analysis.
Five practical strategies to reduce Datadog logging costs by optimizing ingestion, indexing, retention, and using metrics.
Advice on when and why to form a computer performance engineering team, based on the author's experience at Netflix and Intel.
A software engineer shares three highly effective production alerts for catching bugs and system issues, based on real-world experience.
A developer's technical walkthrough of instrumenting LLM tracing for litellm using Braintrust and Langfuse, detailing setup and challenges.
A technical guide on instrumenting AI agentic applications using Arize Phoenix and litellm for observability and trace grouping.
An engineer shares his 3-year experience of working remotely from Australia for a US firm, detailing the challenges of extreme timezone differences.
Explores the synergy between observability and performance in modern software, highlighting tools like Jaeger and Prometheus for microservices.
A tech founder reflects on using Twitter for technical discourse, product development, and personal motivation, while acknowledging its addictive nature.
A critique of the "Observability 3.0" label and a discussion on the evolution from multi-pillar to unified storage models in software telemetry.
