Containerized apps with prebuilt deployment and unified billing. Package manager for build artifacts and dependencies. Components to create Kubernetes-native cloud-based software.
IDE support to write, run, and debug Kubernetes applications. Platform for BI, data applications, and embedded analytics. Messaging service for event ingestion and delivery. Service for running Apache Spark and Apache Hadoop clusters. Data integration for building and managing data pipelines. Workflow orchestration service built on Apache Airflow. Service to prepare data for analysis and machine learning.
Intelligent data fabric for unifying data management across silos. Metadata service for discovering, understanding, and managing data. Service for securely and efficiently exchanging data analytics assets.
Cloud-native wide-column database for large scale, low-latency workloads. Cloud-native document database for building rich mobile, web, and IoT apps. In-memory database for managed Redis and Memcached. Cloud-native relational database with unlimited scale and Serverless, minimal downtime migrations to Cloud SQL. Infrastructure to run specialized Oracle workloads on Google Cloud. NoSQL database for storing and syncing data in real time. Serverless change data capture and replication service.
Universal package manager for build artifacts and dependencies. Continuous integration and continuous delivery platform. Service for creating and managing Google Cloud resources. Command line tools and libraries for Google Cloud. Cron job scheduler for task automation and management. Private Git repository to store, manage, and track code.
Task management service for asynchronous task execution. Fully managed continuous delivery to Google Kubernetes Engine. Full cloud control from Windows PowerShell. Healthcare and Life Sciences. Solution for bridging existing care systems and apps on Google Cloud. Tools for managing, processing, and transforming biomedical data. Real-time insights from unstructured medical text.
Integration that provides a serverless development platform on GKE. Tool to move workloads and existing applications to GKE. Service for executing builds on Google Cloud infrastructure. Traffic control pane and management for open service mesh. API management, development, and security platform. Fully managed solutions for the edge and data centers. Internet of Things. IoT device management, integration, and connection service. Automate policy and security for your deployments.
Dashboard to view and export Google Cloud carbon emissions reports. Programmatic interfaces for Google Cloud services. Web-based interface for managing and monitoring cloud apps. App to manage Google Cloud services from your mobile device.
Interactive shell environment with a built-in command line. Kubernetes add-on for managing Google Cloud resources. Tools for monitoring, controlling, and optimizing your costs. Tools for easily managing performance, security, and cost. Service catalog for admins managing internal enterprise solutions. Open source tool to provision Google Cloud resources with declarative configuration files.
Media and Gaming. Game server management service running on Google Kubernetes Engine. Open source render manager for visual effects and animation. Convert video files and package them for optimized delivery. App migration to the cloud for low-cost refresh cycles.
Data import service for scheduling and moving data into BigQuery. Reference templates for Deployment Manager and Terraform. Components for migrating VMs and physical servers to Compute Engine.
Storage server for moving large volumes of data to Google Cloud. Data transfers from online and on-premises sources to Cloud Storage. Migrate and run your VMware workloads natively on Google Cloud.
Security policies and defense against web and DDoS attacks. Content delivery network for serving web and video content. Domain name system for reliable and low-latency name lookups. Service for distributing traffic across applications and regions.
NAT service for giving private instances internet access. Connectivity options for VPN, peering, and enterprise needs. You can specify which version you want to use by specifying the name and version values. Note than when you specify latest , the SDK determines the latest library version at deployment time. Once deployed, the library version will not change. The only way to get a different version of the library is to deploy again.
If you're developing an application that doesn't have users yet: you don't need to track new versions. But if your application is being actively used, beware: you might be surprised that your application starts using a new not-backward-compatible library version. For a list of the included third-party libraries, see Third-party Libraries. You can use additional pure-python third-party libraries by installing them into a local directory.
If you are using the flexible environment, see Using Python libraries in the flexible environment. To manage your app with the gcloud tool, use the service element instead. The name of the runtime environment that is used by your app. To specify Python 2. Supported only by the gcloud tool or Cloud SDK-based plugins, for example: gcloud app deploy. Required if creating a service.
Optional for the default service. Each service and each version must have a name. A name can contain numbers, letters, and hyphens.
Choose a unique name for each service and each version. Don't reuse names between services and versions. Note: The gcloud app deploy command is backwards compatible and supports existing app. The specified service account will be used when accessing other Google Cloud services and executing tasks.
The value is either a regular expression, or a list of regular expressions. Any filename that matches any of the regular expressions is omitted from the list of files to upload when the application is uploaded. Filenames are relative to the project directory.
The default pattern excludes Emacs backup files with names of the form To extend the above regular expression list, copy and paste the above list into your app. For example, to skip files whose names end in.
To skip a full directory, add the directory name to the list. For example, to skip a directory named logs , add the following line to the previously described ones:. Configures your application to use concurrent requests.
If using Python's threading library , the thread-local data, as returned by threading. Note: The threadsafe directive is required for Python 2. That is, each script must be specified in a script: directive a using Python module path, with package names separated by dots.
The last component of a script: directive using a Python module path is the name of a global variable in the service: that variable must be a WSGI app, and is usually called app by convention. The recommended approach is to remove the version element from your app. For more information about using this command, see Deploying Your App. An identifier for the version of your application code that you deploy to App Engine.
The version ID can contain lowercase letters, digits, and hyphens. It cannot begin with the prefix ah- and the names default and latest are reserved and cannot be used. Note: Version names should begin with a letter, to distinguish them from numeric instances which are always specified by a number. This avoids the ambiguity with URLs like dot-my-service.
If that version does not exist, the target will be instance number of the default version of the service. Each version of an application retains its own copy of app. When an application is uploaded, the version mentioned in the app. An administrator can change which version of the application is serving traffic by using the Google Cloud Console , and can also test other versions before configuring them to receive traffic.
Configures your application to use a Serverless VPC Access connector, enabling the application to send requests to internal resources in your VPC network.
For more information, see Connecting to a VPC network. The handlers element is a required element in the app. The element provides a list of URL patterns and descriptions of how they should be handled. Patterns are evaluated in the order they appear in the app. The first mapping whose pattern matches the URL is the one used to handle the request.
The following table lists the subelements of the handlers element that control the behavior for scripts, static files, static directories, and other settings.
You can set HTTP headers for responses of your static file or directory handlers. If you need to set HTTP headers in your script handlers, you should instead do that in your app's code. For information about which response headers influence caching, see Caching static content. One important use of this feature is to support cross-origin resource sharing CORS , such as accessing files hosted by another App Engine app.
For example, you could have a game app mygame. Here is how you would make your static file handler return that required response header value:. If specified, all files served by this handler will be served using the specified MIME type.
If not specified, the MIME type for a file will be derived from the file's filename extension. If the same file is uploaded with multiple extensions, the resulting extension can depend on the order in which the uploads occurred. If the parameter is not present, will be returned. Specifies the path to the script from the application root directory:.
A script: directive must be a python import path, for example, package. The last component of a script: directive using a Python module path is the name of a global variable in the module: that variable must be a WSGI app, and is usually called app by convention.
In newer App Engine runtimes, the the behavior of this field has changed. Google Accounts sign-in and sign-out are always performed using a secure connection, unrelated to how the application's URLs are configured. The path to the directory containing the static files, from the application root directory.
All of the files in the given directory are uploaded as static files, and none of them can be run as scripts. All files in this directory are uploaded with your app as static files. App Engine stores and serves static files separately from your app's files.
Static files are not available in the app's file system by default. A static file pattern handler associates a URL pattern with paths to static files uploaded with the application.
The URL pattern regular expression can define regular expression groupings to be used in the construction of the file path. App Engine stores and serves static files separately from application files. Static files are not available in the application's file system by default. Static files cannot be the same as application code files. If a static file path matches a path to a script used in a dynamic handler, the script will not be available to the dynamic handler.
A regular expression that matches the file paths for all files that will be referenced by this handler. Static files are uploaded and handled separately from application files. Required element under handlers. The URL pattern, as a regular expression. The expression can contain groupings that can be referred to in the file path to the script with regular expression back-references.
The URL pattern has some differences in behavior when used with the following elements:. The elements in following table configure how your application scales. To learn more about how App Engine apps scale, see Scaling types. Applicable only for applications that use an instance class of F1 or higher.
Specify this element to change default settings for automatic scaling, such as setting minimum and maximum levels for number of instances, latency, and concurrent connections for a service. This parameter specifies the maximum number of instances for App Engine to create for this module version. This is useful to limit the costs of a module. Specify a value from 0 to You can set the parameter to the value 0 to allow scaling to 0 instances to lower costs when no requests are being served.
Note that you are charged for the number of instances specified whether they are receiving traffic or not. The maximum number of idle instances that App Engine should maintain for this version. Specify a value from 1 to If not specified, the default value is automatic , which means App Engine will manage the number of idle instances.
Keep the following in mind:. Note: When settling back to normal levels after a load spike, the number of idle instances can temporarily exceed your specified maximum. However, you will not be charged for more instances than the maximum number you've specified. Optional: The number of additional instances to be kept running and ready to serve traffic for this version.
A high minimum allows you to prime the application for rapid spikes in request load. App Engine keeps the minimum number of instances running to serve incoming requests. You are charged for the number of instances specified, whether or not they are handling requests. If you set a minimum number of idle instances, pending latency will have less effect on your application's performance. This parameter specifies the CPU usage threshold at which new instances will be started to handle traffic, enabling you to balance between performance and cost, with lower values increasing performance and increasing cost, and higher values decreasing performance but also decreasing cost.
For example, a value of 0. The number of concurrent requests an automatic scaling instance can accept before the scheduler spawns a new instance Default: 10, Maximum: A value of less than 10 is likely to result in more instances being created than you need for a threadsafe app, and that may lead to unnecessary cost. If this setting is too high, you might experience increased API latency. Note that the scheduler might spawn a new instance before the actual maximum number of requests is reached.
The maximum amount of time that App Engine should allow a request to wait in the pending queue before starting additional instances to handle requests so that pending latency is reduced. When this threshold is reached, it is a signal to scale up, and results in an increase in the number of instances. If not specified, the default value is automatic.
This means requests can remain in the pending queue for up to 10s, the maximum pending request time limit , before new instance starts are triggered. A low maximum means App Engine will start new instances sooner for pending requests, improving performance but raising running costs. A high maximum means users might wait longer for their requests to be served if there are pending requests and no idle instances to serve them , but your application will cost less to run.
An optional element you can set to specify the minimum amount of time that App Engine should allow a request to wait in the pending queue before starting a new instance to handle it.
Specifying a value can lower running costs but increase the time users must wait for their requests to be served. For free apps, the default value is ms. For paid apps, the default value is 0. If pending requests are in the queue:. This element enables basic scaling of instance classes B1 and higher, can contain the following elements:. This element enables manual scaling of instance classes B1 and higher, and can contain the following element:.
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4. For details, see the Google Developers Site Policies. If pending requests are in the queue:. This element enables basic scaling of instance classes B1 and higher, can contain the following elements:. This element enables manual scaling of instance classes B1 and higher, and can contain the following element:. Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.
For details, see the Google Developers Site Policies. Why Google close Discover why leading businesses choose Google Cloud Whether your business is early in its journey or well on its way to digital transformation, Google Cloud can help you solve your toughest challenges. Learn more.
Key benefits Overview. Run your apps wherever you need them. Keep your data secure and compliant. Build on the same infrastructure as Google. Data cloud. Unify data across your organization. Scale with open, flexible technology.
Run on the cleanest cloud in the industry. Connect your teams with AI-powered apps. Resources Events. Browse upcoming Google Cloud events. Read our latest product news and stories. Read what industry analysts say about us. Reduce cost, increase operational agility, and capture new market opportunities. Analytics and collaboration tools for the retail value chain. Solutions for CPG digital transformation and brand growth. Computing, data management, and analytics tools for financial services.
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Migration solutions for VMs, apps, databases, and more. Automatic cloud resource optimization and increased security. End-to-end migration program to simplify your path to the cloud. Ensure your business continuity needs are met. Change the way teams work with solutions designed for humans and built for impact. Collaboration and productivity tools for enterprises.
Secure video meetings and modern collaboration for teams. Unified platform for IT admins to manage user devices and apps. Enterprise search for employees to quickly find company information. Detect, investigate, and respond to online threats to help protect your business. Solution for analyzing petabytes of security telemetry.
Threat and fraud protection for your web applications and APIs. Solutions for each phase of the security and resilience life cycle. Solution to modernize your governance, risk, and compliance function with automation. Data warehouse to jumpstart your migration and unlock insights. Services for building and modernizing your data lake. Run and write Spark where you need it, serverless and integrated. Insights from ingesting, processing, and analyzing event streams.
Solutions for modernizing your BI stack and creating rich data experiences. Solutions for collecting, analyzing, and activating customer data. Solutions for building a more prosperous and sustainable business. Data from Google, public, and commercial providers to enrich your analytics and AI initiatives. Accelerate startup and SMB growth with tailored solutions and programs. Get financial, business, and technical support to take your startup to the next level. Explore solutions for web hosting, app development, AI, and analytics.
Build better SaaS products, scale efficiently, and grow your business. Options for every business to train deep learning and machine learning models cost-effectively. Conversation applications and systems development suite for virtual agents. Service for training ML models with structured data. API Management. Manage the full life cycle of APIs anywhere with visibility and control. API-first integration to connect existing data and applications.
Solution to bridge existing care systems and apps on Google Cloud. No-code development platform to build and extend applications.
Develop, deploy, secure, and manage APIs with a fully managed gateway. Serverless application platform for apps and back ends. Server and virtual machine migration to Compute Engine. Compute instances for batch jobs and fault-tolerant workloads. Reinforced virtual machines on Google Cloud. Dedicated hardware for compliance, licensing, and management. Infrastructure to run specialized workloads on Google Cloud.
Usage recommendations for Google Cloud products and services. Fully managed, native VMware Cloud Foundation software stack. Registry for storing, managing, and securing Docker images. Container environment security for each stage of the life cycle. Solution for running build steps in a Docker container. Containers with data science frameworks, libraries, and tools. Containerized apps with prebuilt deployment and unified billing. Package manager for build artifacts and dependencies.
Components to create Kubernetes-native cloud-based software. IDE support to write, run, and debug Kubernetes applications. Platform for BI, data applications, and embedded analytics.
Messaging service for event ingestion and delivery. Service for running Apache Spark and Apache Hadoop clusters. Data integration for building and managing data pipelines. Workflow orchestration service built on Apache Airflow. Service to prepare data for analysis and machine learning. Intelligent data fabric for unifying data management across silos.
Metadata service for discovering, understanding, and managing data. Service for securely and efficiently exchanging data analytics assets. Cloud-native wide-column database for large scale, low-latency workloads. Cloud-native document database for building rich mobile, web, and IoT apps. In-memory database for managed Redis and Memcached. Cloud-native relational database with unlimited scale and Serverless, minimal downtime migrations to Cloud SQL.
Infrastructure to run specialized Oracle workloads on Google Cloud. NoSQL database for storing and syncing data in real time. Serverless change data capture and replication service. Universal package manager for build artifacts and dependencies. Continuous integration and continuous delivery platform. Service for creating and managing Google Cloud resources. Command line tools and libraries for Google Cloud. Cron job scheduler for task automation and management. Private Git repository to store, manage, and track code.
Task management service for asynchronous task execution. Fully managed continuous delivery to Google Kubernetes Engine. Full cloud control from Windows PowerShell. Healthcare and Life Sciences. Solution for bridging existing care systems and apps on Google Cloud. Tools for managing, processing, and transforming biomedical data. Real-time insights from unstructured medical text. Integration that provides a serverless development platform on GKE.
Tool to move workloads and existing applications to GKE. Service for executing builds on Google Cloud infrastructure. Traffic control pane and management for open service mesh. API management, development, and security platform.
Fully managed solutions for the edge and data centers. Internet of Things. IoT device management, integration, and connection service. Automate policy and security for your deployments. Dashboard to view and export Google Cloud carbon emissions reports. Programmatic interfaces for Google Cloud services.
Web-based interface for managing and monitoring cloud apps. App to manage Google Cloud services from your mobile device. Interactive shell environment with a built-in command line. Kubernetes add-on for managing Google Cloud resources. Tools for monitoring, controlling, and optimizing your costs. Tools for easily managing performance, security, and cost. Service catalog for admins managing internal enterprise solutions. Open source tool to provision Google Cloud resources with declarative configuration files.
Media and Gaming. Game server management service running on Google Kubernetes Engine. Open source render manager for visual effects and animation. Convert video files and package them for optimized delivery. App migration to the cloud for low-cost refresh cycles. Data import service for scheduling and moving data into BigQuery. Reference templates for Deployment Manager and Terraform.
Components for migrating VMs and physical servers to Compute Engine. Storage server for moving large volumes of data to Google Cloud. Data transfers from online and on-premises sources to Cloud Storage. Migrate and run your VMware workloads natively on Google Cloud. Security policies and defense against web and DDoS attacks.
Content delivery network for serving web and video content. Domain name system for reliable and low-latency name lookups. Service for distributing traffic across applications and regions.
NAT service for giving private instances internet access. Connectivity options for VPN, peering, and enterprise needs. Connectivity management to help simplify and scale networks. Network monitoring, verification, and optimization platform. Cloud network options based on performance, availability, and cost. VPC flow logs for network monitoring, forensics, and security.
Google Cloud audit, platform, and application logs management. Infrastructure and application health with rich metrics. Application error identification and analysis. GKE app development and troubleshooting. Tracing system collecting latency data from applications. CPU and heap profiler for analyzing application performance.
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