Google Cloud Platform (GCP) is a popular set of cloud computing services that includes IaaS and PaaS features. Google Cloud's penetration in the public cloud sector is behind only Amazon Web Services (AWS) and Microsoft Azure. As with competitors, GCP uses the same massive infrastructure that hosts its core online applications. In Google's case, these include Google Search and YouTube. The Google cloud stack has more than 100 products that cover processing, storage, database management, networking, business analytics, Big Data, machine learning, artificial intelligence (AI), access management, cybersecurity, Internet of Things, and centralized management.
Google Cloud Platform (GCP) uses the same massive infrastructure that supports Google Search and YouTube
Progent has experience helping organizations from small offices to enterprises to design, deploy, tune, manage, and maintain IT ecosystems based on a variety of network architectures including on-premises data centers, private clouds, one or more public clouds, or a hybrid combination of onsite and cloud-based infrastructure. Progent can provide quick remote or onsite access to seasoned experts to assist you to evaluate the advantages and limitations of different network architectures and understand the services and cost of Google Cloud vs. alternative public cloud vendors.
Progent's certified Microsoft, Linux, and Cisco experts can assist you to integrate your current network infrastructure with the Google Cloud, and Progent's database experts can show you how to make your business-critical applications cloud ready so they can benefit fully from Google Cloud services. Progent can assist you to deploy VMs on GCP Compute Engine, design an efficient storage system using Google Cloud Storage services, and streamline access management with Google Cloud Identity. Progent can also help you to use GCP's tools to manage and monitor your GCP Cloud ecosystem so it
continually delivers maximum return on investment.
Major Services Offered for the Google Cloud Platform
Google Cloud has over Infrastructure-as-a-Service and Platform-as-a-Service services covering nearly all areas of information technology including compute, storage, database management, networking, administration, security, web, mobility, and development. Google Cloud services are offered by subscription. As with other public cloud services, you are charged for what you use. Important Google Cloud services for which Progent offers expert consulting and debugging include:
Compute Engine is a service for running Windows and Linux virtual machines in the cloud, similar to Amazon EC2 or Microsoft Azure Virtual Machines. Compute Engine virtual machines have seamless access to GCP block storage and advanced infrastructure. GCP Compute Engine offers three classes of virtual machines in your choice of standard or custom sizes. GCP's N2 type virtual machine is value priced and intended for general-purpose applications like web hosting, business applications, and databases. The C2 type VM supports up to 60 virtual CPUs (vCPUs) for processor-intensive applications like ECAD and simulations. Google Cloud's M2 type virtual machine offers up to 11.5 TB of memory for RAM-intensive apps like in-memory databases or in-depth analytics. Google Cloud's sole-tenant node option provides a physical Compute Engine machine for your exclusive use.
Important features of the GCP Compute Engine include live VM migration, which keeps virtual machines running even during scheduled maintenance, and preemptible virtual machines, low-cost VM compute instances which last for up to 24 hours and are intended for executing batch operations that can be paused and resumed at any time without compromising productivity.
Other available features for GCP Compute Engine include:
Pricing for Google Cloud Compute Engine services is based on per-second usage according to virtual machine instances and classes, disks and images, network activity, sole-tenant nodes, graphics processing units, plus other selected resources and use.
- Always-encrypted local SSD block storage for high performance and data security
- Graphics Processing Unit (GPU) that can be included with VM instances for processor-intense apps like machine learning (ML) and 3D graphics
- Global load balancing for maximizing performance and uptime at low cost
- Google Kubernetes Engine for orchestrating Docker containers on Compute Engine VMs
Google Cloud Storage is object storage that can scale to exabytes of data. Objects held in Google Cloud Cloud Storage are logically organized in containers called buckets. Google provides four classes of cloud storage, distinguished and priced according to the object's anticipated duration and its hot/cold ratio. As you progress through Google's storage classes from Standard to Archive storage, access expense increase, at-rest expense decrease, and required minimum storage duration goes up. Google's storage classes allow you to control expenses by designing the optimal price/performance balance for your network, and Google Cloud's Object Life Cycle Management feature enables you to automate the migration of storage objects from high-access to low-access classes over time. All storage classes share global accessibility, virtually unlimited storage (but a maximum size limit of 5 TB for any given object, no minimum object size, low latency, on-request geo-redundancy, and a common set of security and management tools. A single API works with all Google Cloud Storage classes.
Standard Storage is Google Cloud's default class and is optimized for objects used often or stored only briefly. There is no minimum storage time. To get the highest performance and least network usage charges, Standard Storage data should reside in the same geographical region as the VM instances or the container clusters that interact with the objects. Standard Storage delivers the highest average availability for regions, dual-regions, and multi-regions. Nearline Storage is a economical storage option designed for data accessed only occasionally, ideally no more than once per month. Examples of appropriate use scenarios are monthly backup and archiving. At-rest pricing is lower than with Google Cloud's Standard Storage, but data access costs more, availability is slightly less, and storage duration is a minimum of 30 days.
Coldline Storage offers rock bottom storage pricing for dormant data and is intended for scenarios where objects are accessed less than once every 90 days Minimum storage duration is three months, availability is slightly less than with GCP's Standard and Nearline Storage services, and access costs are relatively high. Google's Archive Storage, which offers the least at-rest storage pricing but has a minimum storage duration of one year, is the preferred storage service for data kept only for backup or archive purposes. Data access costs for Archive Storage are the most of any GCP storage type.
Cloud Storage Encryption
GCP Cloud Storage always encrypts stored data on the server side before writing it to disk. In addition to this standard encryption, you can choose more ways to encrypt your data. GCP offers two server-side encryption services that cause objects to be encrypted after making it to Cloud Storage but before the data is stored to disk. The Customer-supplied encryption keys allows you to create and manage your own encryption keys. Google Cloud's Customer-managed encryption keys alternative enables you to create and manage your encryption keys using Google's Cloud Key Management Service. Both these server-side encryption options create an extra level of encryption over and above Google's default Cloud Storage encryption service.
If you use client-side encryption prior transporting your data to GCP Cloud Storage, your pre-encrypted data will also undergo Google's server-side encryption.
Google Cloud Identity and Access Management (IAM) is Google's unified system for controlling access to network resources and granting authority for users and services to access network resources for a specified duration. Examples of GCP resources are Compute Engine VM instances and Google Cloud Storage buckets. Centralized and consistent tools give administrators control over access rights for all services available within GCP. Cloud IAM features high precision in creating policies to assign groups and users rights to use task-relevant resources while blocking access to unnecessary resources.
With Google Cloud IAM, policies are based on roles; roles are made up of permissions; and permissions are assigned to resources. Users or groups are assigned to policies, and by means of policy they gain access to the specific resources the roles give them. As an example of Google Cloud IAM's role granularity, the Google Cloud Pub/Sub service can be accessed with a range of permissions depending on whether a user or group has been assigned the role of Owner, Editor, Viewer, Publisher, or Subscriber.
Cloud IAM policies are hierarchy-based, cascading downward from the organization to projects and then to resources. You can define organization-wide policies, tune them as appropriate for a given project, and refine them further for a specific resource. You can define policies to specific resources, to a project, or at the top organizational level. Policies you assign to an organization cascade down to projects within the organization and then to resources within projects.
Google Cloud IAM's policy hierarchy provides flexibility for allowing or restricting access to cloud resources
Additional flexibility in controlling resource access rights is provided by allowing administrators to include context such as device security status, IP address, resource type, and date/time. You can manage permissions via the graphical interface of the web-based Cloud Console, through automation with Google Cloud IAM methods, or through Google's gcloud CLI feature. Cloud IAM automatically maintains a full audit trail to simplify compliance.
Google Cloud IAM is provided at no extra cost to all Google Cloud Platform customers.
Google Kubernetes Engine (GKE is a container service for running containerized apps. Kubernetes was initially developed by Google to automate container orchestration and was offered as open source in 2014. Since then Kubernetes has grown to be the leading platform for managing containerized applications.
Google Kubernetes Engine is powered by Google's Container-Optimized OS and supports Certified Kubernetes, ensuring workload compatibility with other Kubernetes products across cloud and local environments. To accelerate development, prebuilt open-source deployment templates for enterprise-grade apps are offered on Google Cloud Marketplace.
The Migrate for Anthos tool, available for free with GKE, allows you to move and port your applications easily from your existing environment into Google Kubernetes Engine containers. These workloads can be physical servers and VMs located onsite, in Google's Compute Engine, or in third-party clouds. GKE allows pod and cluster autoscaling for continuous analysis of the processor and RAM usage of pods and for dynamically tuning CPU and RAM requests across node pools.
Other features of Google Kubernetes Engine include preemptible VMs, persistent storage, always-encrypted local solid-state drive (SSD) block storage, global load balancing to optimize performance and availability, support for both Windows Server and Linux nodes, the capability of running stateless serverless containers via the GCP Cloud Run service, and usage metering for fine-grained insight into Kubernetes clusters.
Google Kubernetes Engine complies with HIPAA and PCI DSS 3.1. For enhanced security, GKE Sandbox provides an extra layer of protection between containerized Google Kubernetes Engine workloads. GKE clusters offer native support for Kubernetes Network Policy to filter traffic by applying pod-level firewall policies. Private clusters in Google Kubernetes Engine can be limited to a private or public endpoint accessible only to specified addresses.
GKE charges for each GCP Compute Engine instance in a cluster. Usage of GCP Compute Engine resources is priced by the second with a one-minute minimum charge.
Cloud AI Building Blocks enable software developers, even without machine learning backgrounds, to integrate Google's advanced AI technology into their applications. Essential capabilities cover vision, language, and conversation. By using Google's APIs, you can access Google's out-of-the-box models and avoid having to hassle with creating your own datasets and training your own models. As Google's library of pre-trained models grows in sophistication and size, you can immediately add state-of-the-art AI technology to your apps. In addition, Google AutoML products provide the utilities you need to train, validate and deploy your own domain-specific ML models. You can use any Google AI Building Block by itself or in combination with other AI Building Blocks according to your requirements.
Google Cloud AI Building Blocks add vision, language, and speech capabilities to your apps
For advanced imaging, Google Cloud AI Building Blocks include the AutoML Vision and Vision API products that allow you to extract useful intelligence from your images. Both services support REST and RPC APIs and allow your application to discern objects and their location within an image. AutoML Vision simplifies training for your home-grown machine learning (ML) models by offering an intuitive graphical interface. Once you tune your models for accuracy, latency and size, you can send them to the Google Cloud or to a variety of edge devices.
Google Cloud's Vision API offers programmatic access to Google's pre-trained machine learning models. Developers can quickly classify images via Google's collections of pre-trained labels. Vision API uses OCR tools to identify text, in over 50 languages, embedded within your images. Combined with Google's Document Understanding AI feature, you can use the same machine learning technology that powers Google Search to extract useful insights from volumes of unstructured documents. You can detect web objects and pages, distinguish a face from other items and detect facial attributes, and recognize product logos and popular landmarks. You can also recognize mature or violent content within images.
Google Cloud's AutoML Video Intelligence and Video Intelligence API products, which provide a similarly extensive array of capabilities as the Vision products, make it easy to extract value from videos.
Language is Google's wheelhouse, and Google's portfolio of AI Building Blocks understandably includes a potent arsenal of products. Google Cloud language services include:
How Progent Can Help You with Google Cloud Integration
- Cloud Translation API
This cloud service enables developers to enrich web sites and programs with real-time translation features powered by Google’s neural translation technology. Google Cloud provides a Basic and an Advanced release of Google's Translation API. Both options are based on Google's pre-trained, general-purpose model and offer automatic language detection, a REST API, seamless HTML support, and the capability to translate between over 100 language pairs. The Advanced version of Cloud Translation API adds an extensible glossary to reflect your company's branding in translated copy, batch translation support in GCP Cloud Storage, the ability to incorporate custom AutoML Translation models, and an integrated gRPC open source API. The Cloud Translation service is priced per character.
- AutoML Translation
This ML platform allows you to create a custom translation model by training it using your own prepared dataset. The custom dataset is made of matching pairs of sentences in the original and target languages. Google AutoML Translation applies statistical analysis to the pairs from your custom dataset to train the model, tests it, and scores its performance. After you assess the results of your custom model, you can tune your dataset and train a new model repeatedly until you are satisfied with the outcome. You can build your own translation models in over fifty language pairs. Costs for using AutoML Translation are calculated based on the hours of training used and the number of characters you submit for translation.
- Cloud Natural Language API
GCP's Natural Language API uses a suite of proven machine learning models to assist you to understand the meaning and structure of documents. A content classification model discerns content categories within a document, such as civil engineering, investing, or sports; an entity analysis model finds and tags familiar entities referenced within the document, like product, company, or athlete); a sentiment analysis model evaluates the author's attitude suggested by the document and the magnitude of emotion; an entity sentiment analysis model integrates entity analysis and sentiment analysis by identifying familiar entities in a document and determining the positive or negative attitude and the strength of feeling demonstrated in relation to those entities; a syntactic analysis model extracts structural organization by breaking text up into sentences and tokens (words), which are further broken down into parts of speech and roots. Each API identifies the language of the text being analyzed if it is not specified. Google's Natural Language API is a REST API and uses JSON requests and responses. Text to be analyzed can be included in the JSON request or resident in Google Cloud Storage.
- AutoML Natural Language
Google Cloud's AutoML Natural Language service allows you to create and refine your own Natural Language models for classification, entity extraction, and sentiment analysis. As an example, a sentiment analysis model created by an airline could be taught that a reference to misplaced luggage in social media counts as a negative sentiment. Google Cloud's AutoML Natural Language service makes it easy to create your own dataset, use the dataset to train a model, test the model, and tune your dataset until your model is ready to deploy.
Google's Dialogflow is a a development suite that uses the same natural language understanding technology behind Google Assistant to enable you to create a conversational interface so your product or service can interact with your users by voice. You can add this technology to a smartphone app, website, interactive voice response system, or any other scenario that could be improved with natural voice conversation. Google's Dialogflow platform can understand text or voice inputs and can respond via text or synthetic voice. Dialogflow can detect a user’s intent and detect pre-defined entities like time, date, and numbers. You can teach your Dialogflow agent to identify your own custom entity types by providing small sample datasets, or you can use over 40 out-of-the-box agents as templates. Professional editions of Dialogflow are billed according to audio/phone time and the number of characters and queries.
- Cloud Text-to-Speech
GCP's Text-to-Speech API transforms text or Speech Synthesis Markup Language to high-fidelity, natural-sounding speech in over 30 languages and over 180 voices. Cloud Text-to-Speech platform works with any app or device capable of sending REST or gRPC requests. Devices can be phones, PCs, iPads or tablets, and IoT devices such as autos, TVs, and speakers. Supported audio formats include mp3, Linear16, and Ogg Opus. You can include SSML tags to add pauses, numbers, calendar and time formatting, and other instructions. Cloud Text-to-Speech is priced based on million characters of text submitted.
Google Cloud's Speech-to-Text API gives developers access to advanced automatic speech recognition (ASR) technology powered by Google's continually evolving deep-learning neural network algorithms. Google Cloud's Speech-to-Text can translate audio in real time and can be set to handle various sampling frequencies for phones, video, or voice commands and search. The API works with 120 languages and can identify what language is being used from a selection of as many as four. You can specify a maximum of 5,000 words or phrases that pertain to your organization, such as brand or stakeholder names. The technology can automatically capitalize proper names and convert spoken numbers into addresses, dates, phone numbers, and currencies. Video transcription includes punctuation, and speaker diarization technology can differentiate among multiple talkers in a conference. Noise cancellation is included, and for certain languages you have the ability to block inappropriate language. Supported encoding formats include FLAC, AMR, PCMU, and Linear-16. Cost is time based.
If you plan to integrate your network with Google Cloud, whether to build a cloud-based ecosystem or as a hybrid local/cloud solution, Progent can assist you to evaluate the advantages of GCP vs. competing public cloud vendors or to other network architectures. Progent can assist you with any stage of a move to Google Cloud including requirements analysis, solution architecture, testing, implementation, management automation, performance optimization, license management, disaster recovery strategies, and security and compliance review.
Progent can assist you to determine which of your applications are appropriate for Google Cloud and can help you make your legacy applications cloud compatible. Progent has experience helping clients evaluate running Google Cloud SQL, using Google Dataproc for on-prem Hadoop, adopting Google Kubernetes Engine as a virtualization substitute, and deploying MongoDB Atlas on Google Cloud vs. local MongoDB. Progent can deliver as-needed remote consulting support for short-term jobs to help you rapidly resolve occasional technical challenges or Progent can deliver end-to-end project management outsourcing services to ensure your GCP deployment program is completed on time and on budget.
Some of most frequently encountered technical issues businesses face when migrating to Google Cloud or other public cloud platform is setting up firewalls and VPN tunnels to provide users with convenient but protected access to cloud resources. Progent offers the services of Cisco-certified CCIE network infrastructure engineers and firewall experts for security appliances from major suppliers like Cisco, Palo Alto Networks, Check Point, WatchGuard, and Fortinet to help you to configure or debug firewalls for connecting to Google Cloud Platform. To accommodate mobile computing, Progent's iPhone and iPad management consultants and Android integration consultants can help you to configure and administer secure mobile devices for your Google Cloud users. Progent can work in concert with your in-house technical staff and Google's support engineers to resolve Google Cloud integration problems quickly and affordably.
Popular online consulting expertise offered by Progent to assist organizations integrate their networks with Google Cloud include:
Additional Cloud Integration Expertise Offered by Progent
- Check hybrid solution plan for Google Compute Engine Virtual Machines and Google Cloud Storage
- Build and verify virtual machine images for Windows or Linux
- Configure, deploy and troubleshoot VPN tunnels for access to Google Cloud
- Design integration solutions for firewalls from Cisco, Palo Alto Networks, Check Point, WatchGuard, and Fortinet and others
- Configure and debug mobile endpoints
- Create and implement policies based on leading practices
- Resolve IP addressing problems
- Define cost-effective allocation of Google Cloud Storage
- Optimize query performance on Google Cloud SQL
- Automate software license management
- Resolve certificate issues
A growing selection of public cloud products and services are in competition or work together with Google Cloud Platform. For a variety of reasons, it is common for enterprises to favor a network architecture that incorporates several public cloud platforms along with local or private cloud resources. Progent can assist you to assess the comparative advantages of major public cloud offerings and can help you to design, integrate and maintain IT environments that incorporate a combination of public and private clouds and on-prem data centers.
Other public cloud platforms supported by Progent include:
Progent's Azure cloud integration consultants can assist you with any phase of Azure cloud integration including needs analysis, readiness evaluation, system design, pilot testing, implementation, automated management, performance optimization, software license controls, disaster recovery strategies, security planning, and compliance validation. Progent can assist you to set up and troubleshoot firewalls and VPN connections so your clients can securely connect to Azure resources, and Progent's Microsoft-certified consultants can assist you set up key Microsoft technologies to work in the cloud including Microsoft Windows Server, Exchange, SQL and SharePoint. Progent can also help your organization to create a hybrid environment that transparently combines on-premises datacenters with Azure resources.
Microsoft supports seamless hybrid networks that combine Office 365 and on-premises installations of Exchange. This allows you to have some mailboxes hosted on your physical datacenter and other mailboxes resident on Office 365. Progent's Microsoft-certified consulting team can help your organization with any facet of planning, integrating and troubleshooting your hybrid Exchange network. Progent's Exchange consultants can deliver occasional support to help you through challenging technical issues and also can provide extensive project management outsourcing to ensure your hybrid Office 365 initiative is successfully completed on schedule and within budget. For details about Progent's consulting support for hybrid Office 365 and on-premises Exchange environments, see Office 365 Exchange Online integration with on-premises Exchange.
Progent's Office and Office 365 experts can assist companies to integrate Office desktop and Microsoft Office 365 applications such as Excel, Word, PowerPoint, Outlook, Microsoft Access, Visio and OneNote into a seamless solution that provides fast return on investment and enables improved business outcomes. Progent can help you to integrate Microsoft Office or Office 365 apps with one another and with other core Microsoft platforms including SharePoint, Exchange Server and Microsoft SQL Server running on-premises or hosted in the cloud. Progent's consultants can also help you to resolve compatibility problems with various versions of Office desktop and can provide customized online Office and Office 365 training to individuals and groups.
Progent's Amazon AWS integration experts can provide affordable online support to help businesses of any size to access Amazon Web Services (AWS) cloud services including Amazon EC2 for virtual server hosting, Amazon S3 for scalable high-performance storage, and Glacier for value-priced long-term archiving. Progent can help your IT team with every aspect of Amazon AWS integration including requirements analysis, preparedness assessment, system design and review, pilot testing, configuration, administration, performance tuning, software license management, backup/restore solutions, and security. Progent offers advanced expertise with firewall configuration and VPN access and can show you how to deploy all-cloud or hybrid environments that efficiently incorporate Amazon AWS resources. Progent can provide as-needed support or Progent can deliver project management outsourcing or co-sourcing services to help you migrate efficiently to the Amazon AWS platform.
Amazon Marketplace Web Service (Amazon MWS) is a library of APIs that allows Amazon sellers to streamline their operations by automating crucial sales activities such as listings, orders, payments, fulfillment, and reports. By tapping into Amazon's extensive online selling environment and automating their sales, vendors can broaden their market, reduce their cost of sales, improve response time to customers, and increase their profits. Progent's Amazon Marketplace Web Service (Amazon MWS) consultants can collaborate with your development team and provide application programming, workflow integration, project management support, and mentoring to help you cut development time and speed up your return on investment.
Contact Progent for Google Cloud Integration Consulting
If you are looking for assistance with any phase of integrating your network with Google Cloud Platform or any other public cloud platform, call Progent at 800-993-9400 or visit Contact Progent.