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Compute Engine instances can run the public images for Linux and Windows Server that Google provides as well as private custom images that you can create or import from your existing systems. You can also deploy Docker containers, which are automatically launched on instances running the Container-Optimized OS public image.
You can choose the machine properties of your instances, such as the number of virtual CPUs and the amount of memory, by using a set of predefined machine types or by creating your own custom machine types.
App Engine is a fully managed, serverless platform for developing and hosting web applications at scale. You can choose from several popular languages, libraries, and frameworks to develop your apps, then let App Engine take care of provisioning servers and scaling your app instances based on demand.
Popular Programming Languages | Build your application in Node.js, Java, Ruby, C#, Go, Python, or PHP—or bring your own language runtime.
Open and Flexible | Custom runtimes allow you to bring any library and framework to App Engine by supplying a Docker container.
Fully Managed | A fully managed environment lets you focus on code while App Engine manages infrastructure concerns.
Google Kubernetes Engine (GKE) provides a managed environment for deploying, managing, and scaling your containerized applications using Google infrastructure. The GKE environment consists of multiple machines (specifically, Compute Engine instances) grouped together to form a cluster. GKE clusters are powered by the Kubernetes open source cluster management system. Kubernetes provides the mechanisms through which you interact with your cluster. You use Kubernetes commands and resources to deploy and manage your applications, perform administration tasks, set policies, and monitor the health of your deployed workloads.
Google Cloud Functions is a serverless execution environment for building and connecting cloud services. With Cloud Functions you write simple, single-purpose functions that are attached to events emitted from your cloud infrastructure and services. Your function is triggered when an event being watched is fired. Your code executes in a fully managed environment. There is no need to provision any infrastructure or worry about managing any servers.
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100% availability and low latency | Use Google’s infrastructure for production quality and high-volume authoritative DNS serving. Your users will have reliable, low-latency access from anywhere in the world using our anycast name servers.
Automatic scaling | Cloud DNS can scale to large numbers of DNS zones and records. You can reliably create and update millions of DNS records. Our name servers automatically scale to handle query volume.
Fast anycast name servers | Cloud DNS uses our global network of anycast name servers to serve your DNS zones from redundant locations around the world, providing high availability and lower latency for your users.
Global distribution with anycast IP | With edge caches peered with nearly every major end-user ISP globally, Cloud CDN offers connectivity to more users everywhere. Thanks to anycast architecture, your site gets a single global IP address, combining consistent performance worldwide with easy management.
Integrated with Google Cloud | Cloud CDN is tightly integrated with Cloud Monitoring and Cloud Logging, providing detailed latency metrics out of the box, as well as raw HTTP request logs for deeper visibility. Logs can be exported into Cloud Storage and/or BigQuery for further analysis with just a few clicks.
Use Case | Using Cloud CDN with HTTP(S) load balancing Cloud CDN works with HTTP(S) load balancing to deliver content to your users. The HTTP(S) load balancer provides the frontend IP addresses and ports that receive requests and the back ends that respond to the requests. You can also configure Cloud CDN for use with load balancing and GKE.
Global load balancing with single anycast IP | With Cloud Load Balancing, a single anycast IP front-ends all your backend instances in regions around the world. It provides cross-region load balancing, including automatic multi-region failover, which gently moves traffic in fractions if backends become unhealthy. In contrast to DNS-based global load balancing solutions, Cloud Load Balancing reacts instantaneously to changes in users, traffic, network, backend health, and other related conditions.
Over one million queries per second | Cloud Load Balancing is built on the same frontend-serving infrastructure that powers Google. It supports 1 million+ queries per second with consistent high performance and low latency. Traffic enters Cloud Load Balancing through 80+ distinct global load balancing locations, maximizing the distance traveled on Google's fast private network backbone.
Seamless autoscaling | Cloud Load Balancing can scale as your users and traffic grow, including easily handling huge, unexpected, and instantaneous spikes by diverting traffic to other regions in the world that can take traffic. Autoscaling does not require pre-warming: you can scale from zero to full throttle in a matter of seconds.
Cloud CDN integration | Enable Cloud CDN for HTTP(S) load balancing for optimizing application delivery for your users with a single checkbox.
Always on, always up | One thing every customer needs when transitioning mission-critical workloads to the cloud is the assurance that your resources will be available when you need them — connections that are reliable and durable. Guaranteed uptime isn’t just a nice-to-have, it’s a critical business concern. Dedicated Interconnect offers some of the best SLAs in the industry, with guaranteed uptime of 99.99%. If you can’t meet us at one of our Dedicated Interconnect locations, you can work with your partner of choice to get SLA-guaranteed uptime through Partner Interconnect.
Hybrid made easy | Today’s business climate demands flexibility. Connecting your on-premises resources to your cloud resources seamlessly, with minimum latency or interruption, is a business-critical requirement. The speed and reliability of Cloud Interconnect lets you extend your organization’s data center network into Google Cloud, simply and easily, while options such as Cloud VPN provide flexibility for all your workloads. This unlocks the potential of hybrid app development and all the benefits the cloud has to offer.
Do business on a global scale | If your business does business worldwide, getting the most out of the cloud is often a difficult proposition. With Cloud Interconnect’s global routing capabilities, you get connectivity to any region, around the globe, from one connection with our base offering — no premium add-ons, no difficult implementation, no hassle.
Cloud SQL is a fully-managed database service that helps you set up, maintain, manage, and administer your relational databases on Google Cloud Platform. You can use Cloud SQL with MySQL, PostgreSQL, or Microsoft SQL Server.
Integrated | Access Cloud SQL instances from just about any application. Easily connect from App Engine, Compute Engine, Google Kubernetes Engine, and your workstation. Open up analytics possibilities by using BigQuery to directly query your Cloud SQL databases.
Reliable | Easily configure replication and backups to protect your data. Go further by enabling automatic failover to make your database highly available. Your data is automatically encrypted, and Cloud SQL is SSAE 16, ISO 27001, and PCI DSS v3.0 compliant and supports HIPAA compliance.
Use Case | Build a containerized app with a scalable databaseGoogle Kubernetes Engine enables rapid development by making it easy to deploy, update, and manage your applications and services. Cloud SQL makes it easy to set up, manage, and administer your Postgres databases on Google Cloud. This use case is a building block of a microservices architecture that is backed by an independent storage service, decentralizing data management and ensuring that each service is independently scalable
Cloud Bigtable is Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. Cloud Bigtable is a sparsely populated table that can scale to billions of rows and thousands of columns, enabling you to store terabytes or even petabytes of data. A single value in each row is indexed; this value is known as the row key. Cloud Bigtable is ideal for storing very large amounts of single-keyed data with very low latency. It supports high read and write throughput at low latency, and it is an ideal data source for MapReduce operations.
Globally distributed, ACID-compliant database that automatically handles replicas, sharding, and transaction processing, so you can quickly scale to meet any usage pattern and ensure success of your products. Cloud Spanner is built on Google’s dedicated network and battle tested by Google services used by billions. It offers up to 99.999% availability with zero downtime for planned maintenance and schema changes.
Datastore is a highly scalable NoSQL database for your web and mobile applications. Firestore is the next generation of Datastore. Learn more about upgrading to Firestore. Datastore is a highly scalable NoSQL database for your applications. Datastore automatically handles sharding and replication, providing you with a highly available and durable database that scales automatically to handle your applications' load. Datastore provides a myriad of capabilities such as ACID transactions, SQL-like queries, indexes, and much more.
Serverless, highly scalable, and cost-effective multi-cloud data warehouse designed for business agility.
Gain insights with real-time and predictive analyticsQuery streaming data in real time and get up-to-date information on all your business processes. Predict business outcomes easily with built-in machine learning and without the need to move data.
BigQuery ML | BigQuery ML enables data scientists and data analysts to build and operationalize ML models on planet-scale structured or semi-structured data, directly inside BigQuery, using simple SQL—in a fraction of the time. Export BigQuery ML models for online prediction into Cloud AI Platform or your own serving layer.
BigQuery BI Engine | BigQuery BI Engine is a blazing-fast in-memory analysis service for BigQuery that allows users to analyze large and complex datasets interactively with sub-second query response time and high concurrency. BigQuery BI Engine seamlessly integrates with familiar tools like Data Studio and will help accelerate data exploration and analysis for Looker, Sheets, and our BI partners in the coming months.
Connected Sheets | Connected Sheets allows users to analyze billions of rows of live BigQuery data in Google Sheets without requiring SQL knowledge. Users can apply familiar tools—like pivot tables, charts, and formulas—to easily derive insights from big data
Unified stream and batch data processing that's serverless, fast, and cost-effective.
Streaming data analytics with speed | Dataflow enables fast, simplified streaming data pipeline development with lower data latency.
Simplify operations and management | Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads.
Reduce total cost of ownership | Resource autoscaling paired with cost-optimized batch processing capabilities means Dataflow offers virtually limitless capacity to manage your seasonal and spiky workloads without overspending.
Dataproc makes open source data and analytics processing fast, easy, and more secure in the cloud.
Automated cluster management | Managed deployment, logging, and monitoring let you focus on your data, not on your cluster. Dataproc clusters are stable, scalable, and speedy.
Containerize OSS jobs | When you build your OSS jobs (e.g., Apache Spark) on Dataproc, you can quickly containerize them with Kubernetes and deploy them anywhere a GKE cluster lives.
Use Case | Move your Hadoop and Spark clusters to the cloudEnterprises are migrating their existing on-premises Apache Hadoop and Spark clusters over to Dataproc to manage costs and unlock the power of elastic scale. With Dataproc, enterprises get a fully managed, purpose-built cluster that can autoscale to support any data or analytics processing job.
An enterprise platform for business intelligence, data applications, and embedded analytics.
Powering Data Experiences | Looker gives you the tools to power a multitude of data experiences, from modern business intelligence and embedded analytics to workflow integrations and custom data apps. Regardless of where your data resides, Looker offers a unified surface to access the truest, most up-to-date version of your company’s data. And with data integrated into users’ daily workflows, organizations can extract value from their data at web scales.
Integrated End-to-End Multi-Cloud Platform | Connect, analyze, and visualize data across Google Cloud, Azure, AWS, on-premises databases, or ISV SaaS applications with equal ease at high scale, with the reliability and trust of Google Cloud.
Enterprise-grade access control | Cloud Identity and Access Management (IAM) lets administrators authorize who can take action on specific resources, giving you full control and visibility to manage Google Cloud resources centrally. For enterprises with complex organizational structures, hundreds of workgroups, and many projects, Cloud IAM provides a unified view into security policy across your entire organization, with built-in auditing to ease compliance processes.
Smart access control | Permissions management can be a time-consuming task. Recommender helps admins remove unwanted access to Google Cloud resources by using machine learning to make smart access-control recommendations. With Recommender, security teams can automatically detect overly permissive access and rightsize them based on similar users in the organization and their access patterns.
Get granular with context-aware access | Cloud IAM enables you to grant access to cloud resources at fine-grained levels, well beyond project-level access. Create more granular access control policies to resources based on attributes like device security status, IP address, resource type, and date/time. These policies help ensure that the appropriate security controls are in place when granting access to cloud resources.
Asset discovery and inventory | Discover and view your assets in near-real time across App Engine, BigQuery, Cloud SQL, Cloud Storage, Compute Engine, Cloud Identity and Access Management, Google Kubernetes Engine, and more. Review historical discovery scans to identify new, modified, or deleted assets.
Threat prevention | Understand the security state of your Google Cloud assets. Uncover common web application vulnerabilities such as cross-site scripting or outdated libraries in your web applications running on App Engine, GKE, and Compute Engine. Quickly resolve misconfigurations by clicking directly on the impacted resource and following the proscribed steps on how to fix it.
Threat detection | Detect threats using logs running in Google Cloud at scale. Detect some of the most common container attacks, including suspicious binary, suspicious library, and reverse shell.
Simpler for cloud admins | Secure access to apps in less time than it takes to implement a VPN. Let your developers focus on application logic, while IAP takes care of authentication and authorization.
Simpler for remote workers | End users point their web browser to an internet-accessible URL to access IAP-secured applications. No VPN client required.
Increased security | Admins can create and enforce granular access-control policies based on attributes like user identity, device security status, and IP address.
Works with cloud and on-premises apps | IAP can protect access to applications hosted on Google Cloud, other clouds, and on-premises.
IP-based and geo-based access control | Filter your incoming traffic based on IPv4 and IPv6 addresses or CIDRs. Enforce geography-based access controls to allow or deny traffic based on source geo using Google’s geoIP mapping.
Support for hybrid and multi-cloud deployments | Help defend applications from DDoS or web attacks and enforce Layer 7 security policies whether your application is deployed on Google Cloud or in a hybrid or multi-cloud architecture.
Pre-configured WAF rules | Out-of-the-box rules from the ModSecurity Core Rule Set to help defend against attacks like cross-site scripting (XSS) and SQL injection. RFI, LFI, and RCE rules are also available in beta.
Gain visibility into the data you store and process | Create dashboards and audit reports. Automate tagging, remediation, or policy based on findings. Connect DLP results into Security Command Center, Data Catalog, or export to your own SIEM or governance tool.
Configure data inspection and monitoring with ease | Schedule inspection jobs directly in the console UI or stream data into our API to inspect or protect workloads on Google Cloud, on-premises, mobile applications, or other cloud service providers.
Reduce risk to unlock more data for your business | Protection of sensitive data, like personally identifiable information (PII), is critical to your business. Deploy de-identification in migrations, data workloads, and real-time data collection and processing.
Classify data across your enterprise | Cloud DLP can help classify your data on or off cloud giving you the insights you need to ensure proper governance, control, and compliance. Save detailed findings to BigQuery for analysis or publish summary findings to other services like Data Catalog, Security Command Center, Cloud Monitoring, and Pub/Sub. Audit and monitor your data in Cloud Console or build custom reports and dashboards using Google Data Studio or your tool of choice.
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