LLM Evaluation: Metrics, Benchmarks, and Evals
Build evaluation pipelines for LLM applications with automated metrics, LLM-as-judge patterns, and custom benchmark suites.
1745 posts · page 11 of 37
Build evaluation pipelines for LLM applications with automated metrics, LLM-as-judge patterns, and custom benchmark suites.
Learn how to break complex AI tasks into sequential prompt chains that improve accuracy, debuggability, and output quality.
Understand core AI safety concepts and practical alignment techniques that every developer building AI systems should know.
Reduce LLM API costs and latency by caching responses based on semantic similarity rather than exact string matching.
Extract structured data from unstructured text using LLMs with JSON mode, Pydantic validation, and provider-specific structured output APIs.
Use large language models to generate high-quality synthetic datasets for training, testing, and evaluating AI systems.
Compare API versioning approaches: URL path, custom headers, query parameters, and content negotiation. Includes migration strategies and real-world tradeoffs.
Understand the three core caching patterns with practical examples. Covers consistency tradeoffs, invalidation strategies, cache stampede prevention, and when to use each pattern.
Understand why database connection pooling matters and how to configure it. Covers pool sizing, PgBouncer, application-level pools, and common misconfigurations.
Learn database migration patterns that avoid downtime. Covers expand-contract, backfill strategies, backward-compatible schema changes, and rollback techniques.
Implement distributed locks with Redis. Covers single-instance locks, the Redlock algorithm, fencing tokens, lock renewal, and common pitfalls to avoid.
Design health check endpoints that actually help. Covers liveness vs readiness, dependency checks, degraded states, and Kubernetes probe configuration.
Implement graceful shutdown in backend services. Covers signal handling, draining connections, health check coordination, and timeout strategies.
Replace unstructured log lines with structured JSON logging. Covers log levels, correlation IDs, context propagation, and integration with observability tools.
Implement rate limiting with token bucket, sliding window, and fixed window algorithms. Covers Redis-backed solutions, response headers, and distributed setups.
Build a reliable webhook delivery system. Covers retry strategies, idempotency keys, signature verification, dead letter queues, and delivery guarantees.
Build automated rollback systems that use health checks, error rate thresholds, and observability signals to detect failures and revert deployments without human intervention.
Integrate security scanning into CI/CD pipelines: SAST, SCA, container scanning, secrets detection, and policies that block vulnerable code before it reaches production.
A hands-on guide to writing Ansible playbooks that configure servers, deploy apps, and enforce desired state across your fleet.
Compare blue-green and canary deployment strategies with practical examples to choose the right zero-downtime release approach for your team.
Reduce Docker image size and build time with multi-stage builds, layer caching, distroless bases, and practical Dockerfile patterns.
Integrate security scanning into your CI/CD pipeline with practical examples covering SAST, SCA, container scanning, and secrets detection.
A hands-on guide to implementing GitOps with ArgoCD: declarative deployments, sync policies, and multi-environment management.
Design effective Git repository structures and branching strategies for GitOps-driven Kubernetes deployments with Flux and Argo CD.
A practical guide to designing Grafana dashboards that surface the right metrics, from panel types to dashboard-as-code workflows.
Learn how Pulumi lets you define cloud infrastructure using TypeScript, Python, or Go instead of domain-specific languages.
A practical guide to structuring incident response, writing actionable runbooks, and running postmortems that actually improve reliability.
Detect and fix infrastructure drift with Terraform, automated CI checks, and policy enforcement to keep your cloud state in sync with code.
Master Kubernetes autoscaling using HPA for horizontal scaling, VPA for right-sizing, and KEDA for event-driven workloads.
A practical guide to instrumenting applications with OpenTelemetry for traces, metrics, and logs across distributed systems.
Understand platform engineering fundamentals: internal developer platforms, golden paths, self-service infrastructure, and measuring platform success.
Learn to write Prometheus alerting rules, configure AlertManager routing, and build an effective on-call notification pipeline.
Encrypt secrets in Git safely using Mozilla SOPS and age encryption for Kubernetes, Terraform, and CI/CD workflows.
Learn what a service mesh is, why Istio exists, and how to configure traffic management, observability, and mTLS for your microservices.
Learn the four golden signals of monitoring from Google SRE and how to implement them with Prometheus for reliable production systems.
Learn how to define SLIs, set SLOs, and use error budgets to balance reliability with feature velocity in your engineering team.
Learn how to build, structure, and publish Terraform modules to create reusable, composable infrastructure as code.
Learn how to use HashiCorp Vault to store, access, and rotate secrets securely across your infrastructure and applications.
Integrate Celery with Django for background task processing — setup, writing tasks, retries, periodic tasks, and monitoring with Flower.
Add real-time WebSocket support to Django with Channels — consumers, routing, channel layers, groups, and building a live chat.
Build custom managers and chainable QuerySets in Django to encapsulate query logic, keep views thin, and write expressive ORM code.
Eliminate N+1 queries in Django with select_related, prefetch_related, Prefetch objects, annotations, and query profiling tools.
Build custom Django middleware — request/response processing, exception handling, middleware ordering, and real-world examples.
Implement multi-tenancy in Django using shared database schemas — tenant models, middleware, filtered QuerySets, and data isolation.
Speed up Django with Redis caching — per-view cache, template fragment cache, low-level cache API, and cache invalidation strategies.
Build REST APIs with Django REST Framework ViewSets and Routers — ModelViewSet, custom actions, filtering, and URL generation.
Harden your Django app for production — security settings, CSRF, XSS, SQL injection, HTTPS, headers, secrets, and deployment checks.
Master Django signals — connect to post_save and pre_delete, write custom signals, avoid common pitfalls, and know when to use them.