# Aporia > To add a new model to Aporia using the Python SDK, you'll need to: ## Pages - [Adding new models](adding-new-models.md): To add a new model to Aporia using the Python SDK, you'll need to: - [Alerts Consolidation](alerts-consolidation.md): In the following guide we'll explain how you consolidate alerts within Aporia in order to avoid unnecessary noise whe... - [Analyzing Performance](analyzing-performance.md): Hooray! Your model is running in production, making predictions in order to improve your business KPIs. - [API Extended Reference](api-extended-reference.md): Complete API documentation can be found [here](https://platform.aporia.com/api/v1/docs#tag/Datasets/operation/connect... - [Aporia Docs](aporia-docs.md): Data Science and ML teams rely on Aporia to **visualize** their models in production, as well as **detect and resolve... - [Athena](athena.md): This guide describes how to connect Aporia to an Athena data source in order to monitor a new ML Model in production.... - [Batch Models](batch-models.md): If your model runs periodically every X days, we refer to it as a **batch model** (as opposed to a real-time model). - [BigQuery](big-query.md): This guide describes how to connect Aporia to a BigQuery data source in order to monitor your ML Model in production.... - [BigQuery](bigquery.md): This guide describes how to connect Aporia to a BigQuery data source in order to monitor a new ML Model in production... - [Binary Classification](binary.md): Binary classification models predict a binary outcome (one of two possible classes). In Aporia, these models are repr... - [Bodywork](bodywork.md): [Bodywork](https://bodywork.readthedocs.io/en/latest/) deploys machine learning projects developed in Python to Kuber... - [Cisco](cisco.md): You can integrate Aporia with Cisco's Full-Stack Observability Platform to receive alerts and notifications directly ... - [Code-Based Metrics](code-based-metrics.md): Code-based metrics allow users to define Pyspark-based metrics that allow for computation on raw data, element-wise o... - [Custom Metric Definition Language](custom-metric-definition-language.md): In Aporia, custom metrics are defined using syntax that is similar to python's. - [Custom Metric Syntax](custom-metric-syntax.md): In Aporia, custom metrics are defined using syntax that is similar to python's. - [Custom Metric](custom-metrics.md): In case the monitoring metrics provided by Aporia are insufficient for your use-case, you can define your own custom ... - [Custom Segment Syntax](custom-segment-syntax.md): In Aporia, [custom segments](https://docs.aporia.com/core-concepts/tracking-data-segments) are defined using SQL-base... - [Dashboards](dashboards.md): This guide will show you how to automatically add dashboards to your models using the Python SDK. - [Data Drift](data-drift.md): Data drifts are one of the top reasons why model accuracy degrades over time. Data drift is a change in model input d... - [Data Segments](data-segments.md): This guide will show you how to automatically add data segments to your model from code using the Python SDK. - [Delta Lake](delta-lake.md): This guide describes how to connect Aporia to a [Delta Lake](https://delta.io/) data source in order to monitor a new... - [Example: Question Answering](example-question-answering.md): **Question answering models can retrieve the answer to a question from a given text**, which is useful for searching ... - [Example: Text Classification](example-text-classification.md): For an example of a HuggingFace-based text classification model, please see [Intro to NLP Monitoring](https://docs.ap... - [Example: Token Classification](example-token-classification.md): Token classification is a natural language understanding task in which a label is assigned to some tokens in a text&#... - [Explainability](explainability.md): **"My model is working perfectly! But why?"** - [Getting started](getting-started.md): {% hint style="info" %} - [Glue Data Catalog](glue-data-catalog.md): This guide describes how to use the Glue Data Catalog data source in order to monitor a new ML Model in production.&#... - [Google Cloud Storage](google-cloud-storage.md): This guide describes how to connect Aporia to a Google Cloud Storage (GCS) data source in order to monitor your ML Mo... - [Intro to NLP Monitoring](intro-to-nlp-monitoring.md): This guide will walk you through the core concepts of NLP model monitoring. Before soon, you'll be able to detect dri... - [JIRA](jira.md): You can easily integrate Aporia with JIRA to create JIRA issues from Aporia alerts. - [Kubeflow / KServe](kserve.md): If you are using [Kubeflow](https://www.kubeflow.org/) or [KServe](https://github.com/kserve/kserve) for model servin... - [Logging to Aporia directly](logging-to-aporia-directly.md): This section will teach you how to integrate Aporia using [Python SDK](https://aporia-sdk-ref.netlify.app/), but you ... - [Metric Change](metric-change.md): Monitoring and measuring changes in features / raw inputs metrics allows for early detection of basic problems or cha... - [Metrics Glossary](metrics-glossary.md): Here you can find information about all the performance metrics supported by Aporia. - [Missing Values](missing-values.md): In real world data, there are often cases where a particular data element is missing. It is important to monitor the ... - [Model Activity](model-activity.md): In many cases, the number of model predictions is within a predictable range. Identifying deviations from the range c... - [Model Staleness](model-staleness.md): Monitoring the last time a model version was deployed helps track models that do not meet the organization's policy, ... - [Models & Versions](model-versions.md): In Aporia, a`model`is any system that can make predictions and can be improved through the use of data. - [Overview](monitor-overview.md): By now, you probably understand why monitoring your model is essential to keeping it healthy and up-to-date in produc... - [Overview](monitor-template.md): By now, you probably understand why monitoring your model is essential to keeping it healthy and up-to-date in produc... - [Monitors](monitors.md): This guide will show you how to automatically add monitors to your models from code using the Python SDK. For more in... - [Microsoft SQL Server](mssql.md): This guide describes how to connect Aporia to an MSSQL data source in order to monitor your ML Model in production.&#... - [Multi-Label Classification](multi-label-classification.md): Multi-label classification models predict multiple outcomes. In Aporia, these models are represented with the`multi-... - [Multiclass Classification](multiclass-classification.md): Multiclass classification models predict one of more than two outcomes. In Aporia, these models are represented with ... - [New Relic](new-relic.md): Aporia allows you to connect alerts generated from Aporia’s monitors to New Relic’s Incident Intelligence engine and ... - [New Values](new-values.md): Monitoring new values of **categorical fields** helps to locate and examine changes in the model's input. - [Oracle](oracle.md): This guide describes how to connect Aporia to an Oracle data source in order to monitor your ML Model in production.&... - [Overview](overview.md): **Monitoring your Machine Learning models begins with storing their inputs and outputs in production.** - [Performance Degradation](performance-degradation.md): ML models performance often unexpectedly degrade when they are deployed in real-world domains. It is very important t... - [PostgreSQL](postgresql.md): This guide describes how to connect Aporia to an PostgreSQL data source in order to monitor a new ML Model in product... - [Prediction Drift](prediction-drift.md): Prediction drift allows you to monitor a change in the distribution of the predicted label or value. - [Querying metrics](querying-metrics.md): To query metrics from Aporia, initialize a new client and call the`query_metrics`API: - [Quickstart](quickstart.md): With just a few lines of code, any Machine Learning model can be integrated and monitored in production with Aporia. - [Ranking](ranking.md): Ranking models are often used in recommendation systems, ads, search engines, etc. In Aporia, these models are repres... - [Role Based Access Control (RBAC)](rbac.md): Aporia supports full role based access control. Using account-level and workspace-level permissions, users will only ... - [Real-time Models (Kafka)](real-time-models-kafka.md): For high-throughput, real-time models (e.g models with an HTTP endpoint such as`POST /predict`and billions of predi... - [Real-time Models (Postgres)](real-time-models-postgres.md): For real-time models with mid-level throughput (e.g models with an HTTP endpoint such as`POST /predict`), you can in... - [Redshift](redshift.md): This guide describes how to connect Aporia to an Redshift data source in order to monitor a new ML Model in productio... - [Regression](regression.md): Regression models predict a`numeric`value. In Aporia, these models are represented with the`regression`model type. - [Release Notes 2023](release-notes-2023.md): Welcome 2023! :tada: We are extremely excited for the year ahead as we continuously enhance our platform to ensure th... - [Release Notes 2024](release-notes-2024.md): Welcome 2024! :tada: We are extremely excited for the year ahead as we continuously enhance our platform to ensure th... - [REST API](rest-api.md): Aporia provides a REST API, which is currently in beta. - [Amazon S3](s3.md): This guide describes how to connect Aporia to an S3 data source in order to monitor a new ML Model in production. - [SHAP values](shap-values.md): In the following guide we will explain how one can visualize SHAP values in Aporia to gain better explainability for ... - [Slack](slack-integration.md): You can integrate Aporia with Slack to receive alerts and notifications directly to your Slack workspace. - [Snowflake](snowflake.md): This guide describes how to connect Aporia to a Snowflake data source in order to monitor a new ML Model in productio... - [Single Sign On (SAML)](sso-saml-integration.md): You can easily give access to Aporia to your team using your favorite SAML Idp. - [Support](support.md): Need help? Want something more? Reach out! 📧 - [Teams](teams.md): You can integrate Aporia with Microsoft's Teams to receive alerts and notifications directly to your Teams channels. - [Tracking Data Segments](tracking-data-segments.md): Sometimes looking over our entire data doesn't supply us with enough insights to understand what is best to do. We ne... - [Understanding Data Drift](understanding-data-drift.md): Data drift occurs when the distribution of *production data* is different from a certain baseline (e.g *training data*). - [Value Range](value-range.md): Monitoring changes in the value range of numeric fields helps to locate and examine anomalies in the model's input. - [Webhook](webhook.md): Aporia allows you to send alerts generated from Aporia’s monitors to any system using webhooks. - [Welcome to Aporia!](welcome-to-aporia.md): Data Science and ML teams rely on Aporia to **visualize** their models in production, as well as **detect and resolve... - [Why Monitor ML Models?](why-monitor-ml-models.md): You spent *months* working on a sophisticated model, and finally deployed it to production.