Cloud Integration Support

Google Cloud Platform (GCP) is a leading suite of cloud computing services that includes Infrastructure-as-a-Service and Platform-as-a-Service features. Google Cloud's share of the public cloud market is behind only Amazon AWS and Microsoft Azure. As with vendors, Google Cloud utilizes the same extensive network infrastructure that hosts its core applications. For Google, these include Google Search as well as YouTube. The GCB cloud portfolio contains more than 100 products that cover compute, storage, database management, network infrastructure, analytics, Big Data, machine learning (ML), AI, identity, security, IoT, and centralized tools.

Progent has experience assisting organizations from small offices to enterprises to plan, deploy, test, manage, and troubleshoot IT ecosystems based on a variety of network models such as on-premises data centers, private clouds, one or more public clouds, or a hybrid combination of local and cloud resources. Progent offers fast remote or onsite access to high-level consultants who can assist you to evaluate the potential benefits and limitations of different network models and understand the feature set and pricing structure of Google Cloud Platform vs. other public cloud vendors.

Progent's Microsoft, Linux, and Cisco consultants can help your organization to expand your existing network resources with the Google Cloud Platform, and Progent's database management consultants 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 set up VMs on GCP Compute Engine, plan a cost-effective storage solution with GCP Cloud Storage services, and streamline identity management with GCP Cloud Identity. Progent can also help you to use GCP's unified tools to administer and track your GCP Cloud environment so it consistently provides maximum return on investment.

Major Services Offered for the Google Cloud
Google Cloud offers more than 100 Infrastructure-as-a-Service and Platform-as-a-Service services covering virtually all facets of information technology including processing, storage, database management, networking, system management, security, web, mobility, and application development. GCP services are offered by subscription. Like other public cloud services, you are charged for what you use. Important Google Cloud services for which Progent offers expert consulting and technical support include:

Compute Engine is an IaaS service for running Windows and Linux virtual machines in the cloud, similar to Amazon EC2 or Azure Virtual Machines. Compute Engine virtual machines have seamless access to Google Cloud block storage and state-of-the-art infrastructure. Google Cloud Compute Engine offers three basic classes of virtual machines in your choice of standard or custom machine sizes. Google Cloud's N2 type VM is value priced and intended for general-purpose applications like web hosting, business applications, and databases. The C2 type virtual machine provides up to 60 virtual CPUs for processor-intensive applications like ECAD and simulations. Google's M2 type VM offers up to 11.5 TB of RAM for RAM-intensive applications such as in-memory databases or in-depth analytics. Google's sole-tenant node product features a physical Compute Engine machine dedicated to your exclusive use.

Important features of the GCP Compute Engine include live virtual machine migration, which keeps VMs working even while undergoing scheduled maintenance, and preemptible virtual machines, low-priced VM compute instances which continue for a max of 24 hours and are intended for executing batch jobs that can be paused and continued at any time without impacting operations.

Additional available features for Google Compute Engine include:

• Always-encrypted local SSD block storage for high performance and security
• GPU accelerators that can be included with virtual machine instances for CPU-intense applications like machine learning and 3D graphics
• Global load balancing for optimizing speed and availability at minimal cost
• Google Kubernetes Engine for managing Docker containers on Compute Engine VMs

Google Cloud Storage provides object storage that can scale to exabytes of data. All data placed in Google Cloud Cloud Storage are logically organized in containers called buckets. GCP provides four classes of cloud storage, differentiated and priced according to the object's anticipated duration and its access/at-rest ratio. As you move through Google's storage types from Standard to Archive storage, access expense go up, at-rest costs decrease, and required minimum storage time goes up. GCP's storage classes allow you to manage costs by designing the appropriate price/performance balance for your environment, and Google Cloud's Object Life Cycle Management feature allows you to program the progression of storage objects from high-access to low-access types as they age. All types feature global accessibility, unlimited storage (but a size limit of 5 TB for any given object, no minimum size, low latency, on-request geo-redundancy, and a shared set of security and management tools. A single API works with all storage classes.

Standard Storage is Google Cloud's default type and is intended for data used often or stored only for short periods. There is no minimum storage time. For the highest speed and lowest network charges, Standard Storage objects should be kept in the same geographical location as the virtual machine instances or the container clusters that interact with the data. Standard Storage offers the top average availability across any regional distribution scheme. Nearline Storage is a low-priced storage option intended for objects accessed infrequently, preferably no more than once per month. Examples of appropriate use cases are monthly backup and archiving. At-rest pricing is less than with Google Cloud's Standard Storage, but data access costs more, availability is marginally less, and storage duration is a minimum of one month.

Coldline Storage provides very low storage costs for at-rest data and is suitable for scenarios where objects are accessed less than once a quarter. Minimum storage duration is 90 days, availability is marginally lower than with GCP's Standard and Nearline Storage services, and data access costs are relatively high. GCP's Archive Storage, which offers the least at-rest storage costs and a minimum duration of one year, is the best storage service for data kept only for backup or archive purposes. Access costs for Archive Storage are the highest of any Google storage type.

Cloud Storage Encryption
Google Cloud Storage always encrypts data on the server end prior to placing it on disk. In addition to this routine encryption process, you can choose more ways to encrypt your data. Google Cloud offers two server-side encryption options that allow objects to be encrypted after arriving at Cloud Storage but before being stored to disk. Google Cloud's Customer-supplied encryption keys enables you to supply and control your own encryption keys. The Customer-managed encryption keys alternative enables you to generate and manage your encryption keys via Google's Cloud Key Management Service. Both these server-side encryption options create an extra level of encryption above GCP's default Cloud Storage encryption service.

In case you perform client-side encryption before sending your data to Google Cloud Storage, your pre-encrypted data will also undergo server-side encryption.

Google Cloud Identity and Access Management (IAM) is Google's unified system for managing access to network resources and assigning permissions for users and services to access network resources for a specified period of time. Examples of Google Cloud resources are Compute Engine instances and Cloud Storage buckets. Unified tools offer admins the ability to control access permissions for all services available within Google Cloud. Cloud Identity and Access Management features fine granularity in creating policies to assign groups and users permissions to access only required resources while preventing access to non-essential resources.

With Cloud IAM, policies are based on roles; roles are composed of permissions; and permissions are assigned to resources. Users or groups are added to policies, and through the policy they are given access to the specific resources their roles give them. As an example of Cloud Identity and Access Management's role granularity, the Cloud Pub/Sub service can be accessed with a range of usage right determined by whether a user or group has been given the role of Owner, Editor, Viewer, Publisher, or Subscriber.

Google Cloud Identity and Access Management policies are hierarchical, flowing down from the organization to projects and then to resources. You can establish organization-wide policies, refine them as appropriate for a given project, and refine them further for a given resource. You can define access policies to individual resources, to a project, or at the organizational level. Policies you assign to an organization cascade down to projects in the organization and from there resources within projects.

Additional flexibility in managing resource access rights is provided by enabling admins to include context like endpoint security status, IP address, resource type, and date/time. You can manage access rights by using the graphical interface of the web-based Cloud Console, through automation by using Google Cloud IAM methods, or through Google's gcloud command-line feature. Google Cloud IAM automatically maintains a full audit trail to simplify regulatory compliance.

Google Cloud IAM is provided at no extra cost to all Google Cloud customers.

Google Kubernetes Engine is a container service for running containerized apps. Kubernetes was initially developed by Google to automate Docker container orchestration and was made available as open source at the end of 2014. Since that time Kubernetes has grown to be the most popular 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 platforms spanning cloud and on-premises networks. To streamline development, ready-to-go open-source deployment templates for enterprise-grade applications are offered on Google Cloud Marketplace.

The Migrate for Anthos service, offered at no cost with Google Kubernetes Engine, enables you to migrate and convert your applications directly from your existing environment into Google Kubernetes Engine containers. These workloads can include physical servers and virtual machines located on-premises, in GCP's Compute Engine, or in other clouds. GKE supports pod and cluster autoscaling for continuous analysis of the CPU and RAM usage of pods and for automatically tuning CPU and memory requests across multiple node pools.

Additional capabilities of Google Kubernetes Engine include preemptible VMs, persistent storage, always-encrypted local SSD block storage, global load balancing to maximize speed and availability, compatibility with both Windows Server and Linux nodes, the ability to run stateless serverless containers with the Google Cloud Run service, and usage metering for granular insight into your Kubernetes clusters.

Google Kubernetes Engine complies with HIPAA and PCI DSS 3.1. For enhanced security, GKE Sandbox delivers an extra layer of protection between containerized GKE workloads. Google Kubernetes Engine clusters provide native support for Kubernetes Network Policy to filter traffic via pod-level firewall policies. Private clusters in Google Kubernetes Engine can be confined to a private or public device accessible only to distinct addresses.

GKE is priced based on each Google Compute Engine instance in a cluster. Use of Google Compute Engine resources is billed by the second with a one-minute minimum usage charge.

Cloud AI Building Blocks allow developers, even with little or no machine learning backgrounds, to integrate Google's advanced AI capabilities into their applications. Core services address vision, language, and speech. By using APIs, you can take advantage of Google's out-of-the-box AI models rather than having to hassle with creating your own datasets from scratch and training and validating 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. Also, Google Cloud AutoML products give you the utilities required to train, test and deploy your custom domain-specific ML models. Developers can use any Google Cloud AI Building Block by itself or in any combination with other AI tools depending on your requirements.

For advanced imaging, Google Cloud AI Building Blocks include the AutoML Vision and Vision API products that help you to derive useful intelligence from your images. Both products support REST and RPC APIs and allow your app to discern objects and their location within an image. AutoML Vision streamlines training for your custom machine learning (ML) models by offering an intuitive graphical interface. After you optimize your models for accuracy, speed and size, you can send them to the Google Cloud or to a variety of edge devices.

Vision API provides programmatic access to Google's pre-trained machine learning models. You can rapidly classify images via Google's libraries of predefined labels. Vision API uses OCR technology to detect text, in more than 50 languages, contained within images. Used in conjunction with Google's Document Understanding AI technology, you can benefit from the same machine learning technology that powers Google Search to extract actionable insights from volumes of unstructured documents. You can detect web entities and pages, isolate a face from other objects and notice facial characteristics, 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 offer a comparably extensive array of features as the Vision services, make it simpler to mine information from videos.

Language Services
Language is Google's strong suit, and Google's stack of AI Building Blocks understandably includes a rich suite of services. Google Cloud language services include:

• Cloud Translation API
  This service enables you to enhance web sites and applications with dynamic translation capability powered by Google’s neural translation technology. Google Cloud provides a Basic and an Advanced release of the Translation API. Both options are based on Google's pre-trained, general-purpose model and offer automatic language detection, an integrated REST API, seamless HTML support, and the ability to translate between over 100 language pairs. The Advanced version of Cloud Translation API adds a customizable glossary to reflect your company's branding in translated text, batch translation capability in Google Cloud Storage, the ability to utilize (but not create) custom Google AutoML Translation models, and an integrated gRPC API. The Cloud Translation service charges per character.
• AutoML Translation
  This ML platform enables you to create a custom translation model by training it using your own dataset. The dataset consists of matching pairs of sentences in the source and target languages. Google AutoML Translation applies statistical analysis to the items from your custom dataset to train the model, tests it, and rates its performance. After you assess the results of your model, you can modify your dataset and train a new model until you are satisfied with the outcome. You can create custom translation models in over fifty language pairs. Costs for using AutoML Translation are based on the hours of training required and the number of characters you include for translation.
• Cloud Natural Language API
  Google's Natural Language API uses a library of proven ML models to help you to grasp the themes and structure of documents. A content classification model discerns content categories in a document, such as architecture, investing, or sports; an entity analysis model finds and tags familiar entities referenced within the document, such as country, company, or public figure); a sentiment analysis model assesses the author's attitude suggested by the document and the magnitude of emotion; an entity sentiment analysis model integrates entity and sentiment analysis by identifying familiar entities in a document and determining the attitude and the magnitude of feeling demonstrated in relation to those entities; a syntactic analysis model extracts structural information by deconstructing text into sentences and tokens (words), which are further broken down into parts of speech and roots. Each API detects the language of the text being analyzed if it is not declared. The's Natural Language API is a REST API and uses JSON requests and responses. Target text can be embedded in the JSON request or resident in Google Cloud Storage.
• AutoML Natural Language
  Google Cloud's AutoML Natural Language service enables you to build and refine custom Natural Language models for classification, entity extraction, and sentiment analysis. For example, a custom sentiment analysis model created by an airline could be taught that a reference to lost luggage in a tweet reflects a negative rather than positive sentiment. Google's AutoML Natural Language product makes it simple to build a custom dataset, utilize the dataset to train a model, validate the resulting model, and tweak the dataset until the model is suitable for production.
• Dialogflow
  Google's Dialogflow is a platform that uses the same natural language understanding technology that powers Google Assistant to help you to build a conversational interface so your product or service can interact with your customers by voice. You can port this capability to a smartphone app, website, voice response system, or any other application that could be enhanced with voice interaction. Google's Dialogflow service can understand text or voice inputs and can respond via text or synthetic speech. Dialogflow can detect a user’s intent and extract pre-defined entities including time, date, and numbers. You can teach your agent to identify your custom entity types by submitting small sample datasets, or you can use over 40 out-of-the-box agents as templates. Professional editions of Dialogflow are priced based on audio/phone time and the volume of characters and queries.
• Cloud Text-to-Speech
  Google's Text-to-Speech API converts text or Speech Synthesis Markup Language to high-fidelity, natural-seeming speech in over 30 languages and over 180 voices. Cloud Text-to-Speech platform works with any app or device able to send REST or gRPC requests. This includes phones, desktop PCs, tablets, and IoT devices like cars, televisions, and audio speakers. Accepted audio coding formats include mp3, Linear16, and Ogg Opus. You can include SSML tags in order to insert pauses, numbers, calendar and time formatting, and other instructions. Cloud Text-to-Speech is priced per million characters processed.
• Speech-to-Text
  Google's Speech-to-Text API gives developers access to advanced automatic speech recognition (ASR) technology powered by Google's continually refined deep-learning neural network technology. Google's Speech-to-Text can translate streaming audio in real time and can be optimized to handle various sampling rates for phones, video, or voice commands/search. Google's API works with 120 languages and can recognize what language is spoken from a list of as many as four. You can identify a maximum of 5,000 words or phrases that pertain to your organization, like product or partner names. Google's technology can automatically capitalize proper names and convert spoken numbers into addresses, dates, phone numbers, and currencies. Video transcription can add punctuation, and the speaker diarization feature can distinguish among multiple speakers in a conference. Noise cancellation is built in, and for certain languages you can block offensive language. Supported encoding formats include FLAC, AMR, PCMU, and Linear-16. Cost is time based.

Progent can help your organization to decide which of your applications are suited for GCP and can help you make your legacy applications cloud compatible. Progent has helped clients evaluate migrating to Google Cloud SQL, using Google Cloud 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 on-demand online consulting support for small jobs to help you quickly resolve occasional technical challenges or Progent can deliver comprehensive project management outsourcing services to ensure your GCP integration program is carried out on schedule and within budget.

Among the most common technical issues businesses face when migrating to Google Cloud or other public cloud is reconfiguring firewalls and VPN connections to provide users with convenient but protected access to cloud services. Progent offers the expertise of Cisco-certified CCIE network engineers and firewall experts for security gateways from leading vendors like Cisco, Palo Alto Networks, Check Point, SonicWall, and Fortinet to assist you to set up or debug firewalls for accessing GCP. To support BYOD computing, Progent's iPhone and iPad technology consultants and Google Android integration experts can help you to integrate and manage protected mobile endpoints for your GCP users. Progent can work in concert with your internal IT staff and Google's support engineers to resolve Google Cloud connectivity problems quickly and economically.

Popular remote consulting expertise provided by Progent to help organizations expand their networks with Google Cloud Platform include:

• Check hybrid solution plan for Google Compute Engine VMs and GCP Cloud Storage
• Build and verify VM images for Windows or Linux
• Set up, integrate and troubleshoot VPN tunnels for access to Google Cloud
• Design configuration solutions for firewalls from Cisco, Palo Alto Networks, Check Point, WatchGuard, and Fortinet and others
• Set up and troubleshoot mobile devices
• Create and verify security policies based on best practices
• Fix IP addressing issues
• Design cost-effective allocation of GCP Cloud Storage
• Optimize query performance on Cloud SQL
• Automate software license management
• Resolve certificate problems

Additional public clouds supported by Progent include:

Progent's Microsoft Azure cloud integration consultants can assist you with any aspect of Azure cloud integration including needs definition, readiness assessment, system design, pilot testing, implementation, automated management, performance tuning, license controls, disaster recovery strategies, security policy enforcement, and compliance assessment. Progent can assist your IT staff to configure and troubleshoot firewall appliances and VPN tunnels so your clients can securely access to Azure-based services, and Progent's Microsoft-certified consulting experts can help you integrate critical Microsoft platforms to work in Azure including Microsoft Windows Server, Exchange, SQL Server and Skype for Business. Progent can also assist your organization to set up a hybrid ecosystem that transparently combines physical datacenters with Azure resources.

Microsoft allows you to create seamless hybrid networks that combine Office 365 and on-premises Exchange deployments. This allows you to have some mailboxes located on your corporate datacenter or private cloud and other mailboxes resident on Office 365. Progent's certified Exchange consulting team can assist your organization with any phase of planning, implementing and troubleshooting your hybrid Office 365/Exchange solution. Progent's Exchange consultants can deliver occasional expertise to help you through challenging technical problems and also can provide comprehensive project management outsourcing to make sure your hybrid Office 365 initiative is successfully completed on time and within budget. To learn more about Progent's online consulting services for integrating Office 365 and on-premises Exchange environments, refer to Office 365 Exchange Online integration with on-premises Exchange.

Progent's certified Microsoft Office and Office 365 experts can help businesses to integrate Office desktop and Office 365 applications such as Excel, Word, PowerPoint, Outlook, Microsoft Access, Project and Publisher into a seamless solution that offers fast return on investment and promotes improved business outcomes. Progent can help you to integrate Microsoft Office or Office 365 applications with one another and with other core Microsoft technologies such as SharePoint, Exchange Server and SQL Server running locally or in the cloud. Progent can also help you to resolve compatibility problems with various releases of Office desktop and offers customized online Microsoft Office and Office 365 instruction to individual users or teams.

Progent's Amazon Web Services (AWS) planning and integration consultants can provide cost-effective remote support to assist companies to integrate Amazon Web Services (AWS) cloud services including Amazon EC2 for virtual machine hosting, Amazon Simple Storage Service (Amazon S3) for expandable cloud storage, and Glacier for value-priced archival storage. Progent can assist you with every phase of Amazon AWS migration and troubleshooting including requirements analysis, preparedness evaluation, architectural design and review, testing, configuration, centralized administration, performance optimization, licensing management, backup/restore mechanisms, and security. Progent offers advanced expertise with firewall configuration and VPN technology and can help you deploy all-cloud or hybrid networking models that efficiently incorporate Amazon AWS resources. Progent can provide as-needed consulting or Progent can provide comprehensive project management outsourcing or co-sourcing services to help you move smoothly to the Amazon AWS platform.

Amazon Marketplace Web Service (Amazon MWS) is a library of APIs that enables Amazon sellers to improve the efficiency of their business processes by automating crucial sales activities such as listings, orders, shipments, fulfillment, and finances. By tapping into Amazon's vast online ecosystem and automating their sales, merchants can broaden their market, reduce their cost of sales, accelerate reaction time to customers, and increase their bottom line. Progent's Amazon Marketplace Web Service (Amazon MWS) consultants can collaborate with your development team and provide programming, workflow integration, project management support, and mentoring to help you shorten development time and get to market quickly.

Contact Progent for Google Cloud Platform Integration Expertise
If you are looking for assistance with any aspect of integrating your IT system with Google Cloud Platform or other public cloud platform, call Progent at 800-993-9400 or visit Contact Progent.