Build reproducible training snapshots from Kafka
Define a bounded Kafka record window, preserve its output and offset manifest, and run the snapshot job on Polyaxon.
DataOpsKafkaMLOps
All blog articles
Practical guides to building, running, and improving ML and AI in production.
All articles
Page 16 of 22
Evaluate a SageMaker endpoint from Polyaxon
Call an existing SageMaker endpoint from a Polyaxon job and retain model-specific predictions and evaluation results.
MLOpsSagemakerEvaluation
Hand off Polyaxon model artifacts to KServe
Move an approved model artifact from a Polyaxon run to a separately managed KServe InferenceService.
MLOpsKServeModel Serving
Investigate Polyaxon workload health with Prometheus
Correlate Kubernetes object state, container usage, and node health when investigating a Polyaxon workload.
KubernetesPrometheusMonitoring
Monitor Polyaxon services with Prometheus
Instrument application request metrics in a Polyaxon service and configure a separate Prometheus collector to scrape them.
KubernetesPrometheusMonitoring
Optimize multi-cloud costs for ML workloads
Control multi-cloud ML spending with normalized allocation, workload unit economics, placement policies, elastic capacity, and reproducible efficiency measurements.
FinopsCost OptimizationMLOps
Run an existing TFX pipeline in a Polyaxon job
Wrap a local TensorFlow Extended pipeline in one Polyaxon job while preserving its own metadata and artifacts.
MLOpsTensorFlowPipelines
Serve a TensorFlow SavedModel with Polyaxon
Package a versioned SavedModel with TensorFlow Serving and run its REST endpoint as a Polyaxon service.
MLOpsTensorFlowModel Serving
Submit a Polyaxon workflow from AWS Lambda
Hand a trusted operation from a short AWS Lambda invocation to Polyaxon while accounting for retries and uncertain responses.
MLOpsAWSAutomation
Trigger Polyaxon workflows from Kafka events
Connect validated Kafka events to fixed Polyaxon operations with a durable submission ledger and replay handling.
MLOpsKafkaAutomation
Kubernetes monitoring for ML workloads
Monitor Kubernetes control planes, nodes, containers, schedulers, applications, and ML outcomes with useful correlations and controlled cardinality.
KubernetesMonitoringMLOps
Minikube for local Kubernetes development
How to use Minikube for local Kubernetes development, basic cluster operations, and testing ML workloads before moving to shared infrastructure.
KubernetesGuides
Kubernetes storage classes overview
Understand Kubernetes StorageClasses, dynamic provisioning, reclaim policies, volume binding, and persistent volume claims.
KubernetesGuides
Datadog vs. CloudWatch for AWS ML platforms
Choose between Datadog, Amazon CloudWatch, or a combined approach for EKS and ML workloads by testing coverage, ownership, portability, and cost.
AWSObservabilityMonitoring
How to deploy Postgres on Kubernetes
Deploy a single PostgreSQL instance with a Secret, persistent storage, and private access, then verify that its data survives a Pod replacement.
KubernetesGuides
Azure Storage best practices for ML data and artifacts
Design Azure Storage accounts for ML datasets and artifacts with clear boundaries, workload identities, network controls, lifecycle rules, and recovery tests.
AzureStorageMLOps
Kubectl command not found: causes and fixes
Diagnose kubectl command not found errors caused by missing installs, PATH issues, permissions, Docker state, or Minikube command syntax.
KubernetesGuides
How to use the Kubernetes control plane
Understand the Kubernetes control plane, its core components, and the operational practices that keep scheduling and reconciliation healthy.
KubernetesGuides
Protect Kubernetes workloads from DDoS attacks
Build layered Kubernetes DDoS protection with upstream filtering, edge controls, workload isolation, resource safeguards, observability, and tested response plans.
KubernetesSecurityNetworking
Datadog vs. AppDynamics for ML platform monitoring
Evaluate Datadog and AppDynamics against application transactions, Kubernetes infrastructure, ML workflows, telemetry governance, and operating cost.
ObservabilityMonitoringMLOps
Detect malicious activity in Amazon EKS
Detect and contain suspicious Amazon EKS behavior by correlating Kubernetes audit, AWS API, DNS, network, runtime, and workload context.
AWSEKSSecurity
Encrypt container traffic in Kubernetes
Design encryption for Kubernetes data at rest and in transit, with workload identity, certificate rotation, key ownership, and verifiable coverage.
KubernetesEncryptionSecurity
Kubernetes Workloads Basics
Kubernetes fundamental notions and basics of workloads for data-scientists and machine learning engineers.
KubernetesGuides
Datadog vs. New Relic for ML platform observability
Compare Datadog and New Relic for Kubernetes-based ML workloads using telemetry coverage, workflow context, investigation speed, governance, and cost.
ObservabilityMonitoringMLOps