The Google Cloud Platform is a set of Google’s provided cloud computing infrastructure. The platform provides a variety of hosting tools that run on Google Hardware for storage, computing, and application development. Google Cloud Platform facilities can be obtained through the public internet or through a fully committed network by cloud administrators, software developers, and other enterprises IT professionals. This detailed analysis incorporates some of Google Cloud services which are widely used. See the services and products below for the understanding.
This overview covers services of the following types:
- Computing and hosting
- Big data
- Machine learning
Computing and Hosting Services
- Work in an environment that is serverless.
- Using a framework managed for use.
- Take use of container technology to achieve a lot of versatility.
- To have the most control and flexibility, create your own cloud-based network.
You can consider a spectrum on which you have many resource management responsibilities at one end and Google has most of those obligations at the other.
You’ll possibly need to save any media files, archives, or other file-like objects whatever your application. Google Cloud provides a range of storage tools including:
Scalable, consistent, huge-capacity data storage in Cloud Storage. Cloud Storage available in several types:
- Standardized cloud storage gives maximum accessibility.
- Cloud storage Nearline offers archival storage on minimal cost for data that is used less than once a month.
- Cloud storage Coldline offers archival storage for data viewed less than once a quarter, even at a reduced cost.
- Cloud storage Archives offers the reduced price archival storage for the information you intend to use less than once a year for disaster recovery and backup.
- Persistent disks on the computing system, allowing the instances to be used as primary storage. Compute solution provides both persistent hard-disk based disks, labeled as standard persistent disks, and persistent solid-state (SSD) disks.
- NFS file servers are completely operated at Filestore. Filestore instances can be used to store data from applications operating on instances of the GKE clusters or Compute Engine VM.
To clarify the complete variety and advantages of Google Cloud storage services, get Google cloud certification for Google’s storage plans for more information.
Google Cloud offers a variety of services to the SQL and NoSQL databases:
- A database of SQL in Cloud SQL that includes either PostgreSQL or MySQL databases.
- A mission-critical, professionally operated, Cloud Spanner relational database infrastructure providing global scale accuracy, SQL querying, schemas, and high-availability automated, synchronous replication.
- NoSQL data storage has two options: Firestore, for data like a document, and Cloud Bigtable, for tabular data.
You may choose to use persistent disks to establish your preferred database technology on Compute Engine. You may set up MongoDB for storing of NoSQL data, for example. Read all about the Google Cloud databases to learn more about the differences among our database systems through Google cloud certification.
When you are running networking by Device Engine and GKE is using the Kubernetes framework, Compute Engine offers a range of networking resources. Such platforms enable you to load resource-wide traffic balancing, build DNS records, and link your current network to Google’s network.
Big Data Services
Big data tools help you to manage and test big data in the cloud in order to get easy explanations for complicated questions.
BigQuery offers tools for data processing. You will use BigQuery to:
- Build custom schemes that organize your data into tables and datasets.
- Load data from a broad variety of sources like stream data.
- Using SQL-like commands to very easily access large data sets. BigQuery is designed for speed and optimization.
- Using the web user interface, command-line interface, or API.
- Use jobs for query, load, export, and copy data.
- With permissions, handle data, and secure it.
Start using the Quickstart Web UI to test a public dataset and check out BigQuery fast and easily.
Streaming and Batch Data Processing
Dataflow offers a controlled framework and collection of SDKs that can be used to execute batch processing and streaming activities. Dataflow functions well for high volume computing, particularly when the processing activities can be divided into parallel workloads quickly and easily. Dataflow is also excellent for extract-transform-load ETL) functions, which are useful to transfer data from different storage devices, convert data into a more suitable format, or load information from the data storage system.
Pub/Sub is a messaging service asynchronous. Your application will submit messages to a publishing unit called a topic, as JSON data structures. Since Pub/Sub topics are a global tool, you can connect to the topic for other projects in projects you own to accept the messages in HTTP request or response bodies. See the Pub/Sub Quickstart get to know yourself for Pub/Sub.
Machine Learning Services
AI Platform has a range of efficient machine learning (ML) services to offer. Using a controlled TensorFlow platform, you can choose to use APIs which include pre-trained models customized for specific applications, or create and practice your own specialized, large-scale models.
Machine Learning APIs
Google Cloud provides a range of APIs that allow you to take benefit of Google’s ML without building your own models and training them.
- The Video Intelligence API helps you to use video analysis technology that offers features for label identification, explicit content identification, shot-change detection, and features for regionalization.
- To support your global user base, Speech-to-Text allows you to convert audio to text, recognizing over 110 variants and languages. You can transcribe the users’ text dictating to the microphone of an application, allow voice command-and-control, or transcripts voice recordings, among many other use cases.
- Cloud Vision enables quick incorporation of object identification tools, including image marking, facial and landmark identification, tagging of explicit content, and optical character recognition (OCR).
- You can add sentiment analysis, entity-sentiment analysis, entity analysis, syntax analysis, and content classification to the Cloud Natural Language API.
- Cloud Translation helps users to easily convert source text into any of the over one hundred languages supported. In cases where the source language is not known, language detection helps out.
- Dialogflow lets you create websites, smartphone apps, common chat channels, and IoT devices for conversational interfaces. You may use it to create interfaces, like “Chatbots”, which are capable of normal and rich human interactions.