https://platform.instabase.com/docs/26.04/infra-admin/index.html Recent content in Infrastructure administration on Instabase Platform Documentation Hugo -- gohugo.io en-us https://platform.instabase.com/docs/26.04/infra-admin/infrastructure-principles/index.html Mon, 01 Jan 0001 00:00:00 +0000 https://platform.instabase.com/docs/26.04/infra-admin/infrastructure-principles/index.html Table of Contents Architecture design principles Availability and fault tolerance Scalability Fault tolerance and resiliency Network protocols Pod failures and retries File system Database The Instabase webapp runs as a collection of services, which are packaged as Docker containers and deployed in a Kubernetes cluster. In the cluster, each Instabase deployment represents an Instabase service. The number of pods for each deployment can grow and shrink depending on the load. https://platform.instabase.com/docs/26.04/infra-admin/infra-requirements/index.html Mon, 01 Jan 0001 00:00:00 +0000 https://platform.instabase.com/docs/26.04/infra-admin/infra-requirements/index.html Table of Contents Kubernetes cluster requirements Resources created PVC storage Pod security policy Kubernetes roles Workload autoscaling Database Storage AWS S3 Azure Blob storage Container registry Network requirements Security DNS Load balancer Firewall Deployment machine requirements Observability requirements To deploy Instabase, your infrastructure must meet certain requirements. Your environment must have a machine or virtual machine to serve as a jump box or passthrough, from which deployments can be done. https://platform.instabase.com/docs/26.04/infra-admin/dl-infra-requirements/index.html Mon, 01 Jan 0001 00:00:00 +0000 https://platform.instabase.com/docs/26.04/infra-admin/dl-infra-requirements/index.html Model inference and training have specific requirements to ensure the best performance. Model inference relies on sufficient local volume to reach production level throughput, while model training requires a robust GPU to handle the demands of training jobs. Model inference Model inference functionality is provided through the model service. To support reliable inference, you must allocate a sizable amount of resources towards the model service. Model service pods must be provisioned with at least 16 GB of memory and four cores each. https://platform.instabase.com/docs/26.04/infra-admin/mtls-requirements/index.html Mon, 01 Jan 0001 00:00:00 +0000 https://platform.instabase.com/docs/26.04/infra-admin/mtls-requirements/index.html Mutual Transport Layer Security (mTLS) can be used to secure inter-pod traffic within the Instabase cluster. Unsupported ports The following ports, primarily used for metrics scraping, are not encrypted even when pod-to-pod mTLS is enabled (as of release 23.04). Service Name Port Name Port Number service-alertmanager http 29093 service-api-server stats 29080 service-apps-server stats 29080 service-celery-app-tasks stats-port 29080 service-celery-core-tasks stats-port 29080 service-celery-webdriver-tasks stats-port 29080 service-control-plane stats 29080 service-core-platform-service stats 29080 service-grpc-file-service stats-grpc-port 29081 service-jaeger jaeger-metrics 24269 service-job-service stats 29080 service-kube-state-metrics http 28080 service-license-service stats 29080 service-loki-read http 23101 service-loki-write http 23100 service-model-service stats-port 29080 service-model-training-tasks-gpu stats-port 29080 service-opensearch stats 39114 service-rabbitmq stats 25692 service-ray-head stats-port 29080 service-ray-model-training-worker stats-port 29080 service-redis stats 29121 service-redis-file-service stats 59121 service-redis-persistent stats 19121 service-search-tservice stats 29080 service-victoriametrics http 28428 service-webapp stats 29080 Enabling pod to pod mTLS To enable pod-to-pod mTLS in your Instabase cluster: https://platform.instabase.com/docs/26.04/infra-admin/deployment-manager/index.html Mon, 01 Jan 0001 00:00:00 +0000 https://platform.instabase.com/docs/26.04/infra-admin/deployment-manager/index.html Manage and understand your infrastructure with Deployment Manager. Introduction to Deployment ManagerIntroduction to Deployment Manager. Instabase Installer guideInstall Instabase using the Instabase Installer. Configuration managementManage configurations from the Deployment Manager Configs tab. Writing YAML and JSON patchesLearn about writing YAML and JSON patches. Managing base configurationsAdd new services and update images. Performing upgradesPerform platform version upgrades. Info Deployment Manager was previously called the Instabase control plane. Some backend elements, such as Deployment Manager APIs, variables, and files, still reference this name. https://platform.instabase.com/docs/26.04/infra-admin/ms_ocr/index.html Mon, 01 Jan 0001 00:00:00 +0000 https://platform.instabase.com/docs/26.04/infra-admin/ms_ocr/index.html Deploying Microsoft optical character recognition (OCR) containers in the Instabase environment enables additional flexibility for different use cases and provide new features. To use Microsoft (OCR) in Instabase, you must configure it correctly. To run a flow with Microsoft OCR, change the OCR model type to Microsoft OCR in the Process Files step. Configuration status Configuration is required to implement Microsoft OCR to run in your Instabase environment. To confirm that your Microsoft OCR setup is correctly configured, check the logs of a pod in the ocr-msft deployment. https://platform.instabase.com/docs/26.04/infra-admin/extendinginstabase/index.html Mon, 01 Jan 0001 00:00:00 +0000 https://platform.instabase.com/docs/26.04/infra-admin/extendinginstabase/index.html Infrastructure administrators can extend the capabilities of celery-app-tasks by using the Instabase container as a base, and then installing additional packages on top of it. The option to extend certified images exists for scenarios where you need additional Python packages to achieve specific custom functionality in user-defined functions (UDFs). Warning Instabase is not responsible for supporting extensions to certified images. Extending the certified celery-app-tasks image is done at your own risk. https://platform.instabase.com/docs/26.04/infra-admin/workload-autoscaling/index.html Mon, 01 Jan 0001 00:00:00 +0000 https://platform.instabase.com/docs/26.04/infra-admin/workload-autoscaling/index.html Table of Contents Enable workload autoscaling Enable autoscaling during an upgrade Enable autoscaling during an installation Enable autoscaling outside of an upgrade or installation Configure workload autoscaling Calculate HPA minReplicas for autoscaled services Disable autoscaling Deployments with standard resourcing sizing Deployments with custom resourcing sizing Verifying autoscaling configuration changes Enabling autoscaling controllers Binary Autoscaler Scale down to zero controller Workload autoscaling lets Instabase autoscale data services based on demand. Autoscaling optimizes service resources to maximize efficiency and performance for any workload at a given time.