Cloud Integration Consulting

Google Cloud Platform (GCP) is a popular set of cloud services that includes Infrastructure-as-a-Service and Platform-as-a-Service features. GCP's penetration in the public cloud market trails only Amazon AWS and Microsoft Azure. As with competitors, GCP uses the same extensive infrastructure that supports its most popular online applications. For Google, these apps include Google Search and YouTube. The Google cloud stack contains over 100 products that cover compute, storage, database management, networking, business analytics, Big Data, machine learning, AI, access management, cybersecurity, IoT, and unified tools.

Progent has experience assisting businesses from small offices to enterprises to plan, configure, tune, administer, and troubleshoot IT environments that use various network models including on-prem data centers, private clouds, one or multiple public clouds, or a hybrid combination of local and cloud-based resources. Progent can provide quick online or onsite access to seasoned experts who can assist you to assess the advantages and limitations of possible network architectures and compare the services and pricing structure of Google Cloud vs. alternative cloud offerings.

Progent's certified Microsoft, Linux, and Cisco experts can assist you to expand your existing network resources with the Google Cloud, and Progent's database management consultants can help make your key applications cloud capable so they can take full advantage of Google Cloud products and services. Progent can help you to deploy virtual machines on GCP Compute Engine, design a cost-effective storage system using GCP Cloud Storage services, and streamline access management with Google Cloud Identity. Progent can also assist you to utilize GCP's unified tools to manage and monitor your Google Cloud environment so it continually provides top return on investment.

Popular Services Available for the Google Cloud Platform
Google Cloud Platform offers more than 100 Infrastructure-as-a-Service and Platform-as-a-Service services covering virtually all facets of IT including compute, storage, database management, networking, system management, security, web, mobility, and application development. Google Cloud services are available on a subscription basis. As with other public cloud services, you are charged for what you use. Popular GCP 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 VMs have seamless access to Google Cloud block storage and advanced infrastructure. Google Cloud Compute Engine offers three classes of VMs in either standard or custom machine sizes. Google Cloud's N2 type virtual machine is affordably priced and intended for common applications such as web hosting, business applications, and databases. The C2 type virtual machine supports up to 60 virtual CPUs (vCPUs) for compute-intensive applications such as electronic computer-aided design (ECAD) and simulations. Google's M2 class virtual machine includes up to 11.5 TB of memory for memory-intensive apps like in-memory databases or in-depth analytics. Google's sole-tenant node option provides a physical Compute Engine machine dedicated to your exclusive use.

Key benefits of the Google Compute Engine include live virtual machine migration, which lets you keep virtual machines on line even while undergoing scheduled maintenance, and preemptible virtual machines, low-priced VM compute instances which last for a max of 24 hours and are designed for running batch jobs that can be paused and continued intermittently without compromising productivity.

Other available benefits for Google Compute Engine include:

• Always-encrypted local SSD block storage for enhanced speed and security
• Graphics Processing Unit (GPU) that can be included with virtual machine instances for CPU-intense apps such as machine learning and 3D graphics
• Global load balancing for maximizing speed and uptime at low cost
• Google Kubernetes Engine for managing and orchestrating containers on Compute Engine virtual machines

Google Cloud Storage is object storage that can scale to exabytes of data. Objects placed in Google Cloud Storage are logically organized in containers referred to as buckets. Google offers four classes of cloud storage, differentiated and priced according to the object's expected duration and its busy/dormant ratio. As you progress through Google's storage classes from Standard to Archive, access expense increase, at-rest expense decrease, and required minimum storage time goes up. Google's storage classes make it possible to manage costs by planning the optimal price/performance balance for your environment, and Google Cloud's Object Life Cycle Management tool enables you to automate the migration of storage objects from high-access to low-access types over time. All storage classes feature worldwide accessibility, unlimited storage (but a size limit of 5 TB for individual objects, no minimum size, low latency, optional geo-redundancy, and a shared suite of security and management tools. A single API applies to all Google Cloud Storage types.

Standard Storage is Google Cloud's default class and is optimized for so-called "hot" storage accessed often or stored only briefly. There is no minimum storage duration. To get the best performance and lowest network usage fees, Standard Storage objects should reside in the same geographical location as the Compute Engine instances or the container clusters that interact with the objects. Standard Storage delivers the highest average uptime for any regional distribution scheme. Nearline Storage is a economical storage type intended for data accessed infrequently, preferably once per month or less. Examples of suitable use cases are periodic backup and archiving. At-rest pricing is less than with GCP's Standard Storage, but access costs more, availability is marginally less, and duration is a minimum of 30 days.

Coldline Storage offers very low storage costs for dormant data and is intended for situations where data are accessed less than once a quarter. Minimum duration is 90 days, availability is marginally less than with GCP's Standard and Nearline Storage classes, and access pricing is relatively expensive. GCP's Archive Storage, which features the least at-rest storage pricing but has a minimum storage duration of one year, is the preferred storage class for objects kept only for backup or archive purposes. Data access pricing for Archive Storage is the most of any Google storage service.

Cloud Storage Encryption
Google Cloud Storage always encrypts stored data on the server end prior to writing it to disk. In addition to this standard encryption, you can select more options to encrypt your data. There are two supplemental server-side encryption services that allow objects to be encrypted after arriving at Cloud Storage but before the data is written to disk. Google's Customer-supplied encryption keys allows you to create and control your own encryption keys. Google Cloud's Customer-managed encryption keys option enables you to create and manage your encryption keys via Google's Cloud Key Management Service. Both these server-side encryption services create an additional layer of encryption above GCP's standard Cloud Storage encryption.

If you perform client-side encryption prior transporting data to Google Cloud Storage, your encrypted data will also undergo Google's server-side encryption.

Google Cloud Identity and Access Management (IAM) is Google's centralized system for controlling access to network resources and assigning authority for users and services to use network resources for a specified duration. Examples of GCP resources are Compute Engine instances and Cloud Storage buckets. Unified and consistent tools offer admins control over access rights for all services within Google Cloud. Cloud Identity and Access Management offers fine granularity in creating policies to grant groups and users permissions to access task-relevant resources while preventing access to non-essential resources.

With Google Cloud Identity and Access Management, policies are composed of roles; roles are composed of permissions; and permissions are associated with resources. Users or groups are added to policies, and through the policy they gain access to whatever resources their roles provide. As an example of Cloud IAM's role granularity, the Cloud Pub/Sub service can be accessed under a variety of permissions determined by whether a user or group has been given the role of Owner, Editor, Viewer, Publisher, or Subscriber.

Cloud Identity and Access Management policies are hierarchy-based, cascading down from the organization to projects and then to resources. You can establish organization-wide policies, refine them as appropriate for a specific project, and refine them even more for a given resource. You can assign access policies to individual resources, to a project, or at the top organizational level. Policies assigned to an organization flow down to projects in the organization and from there resources within projects.

Further flexibility in managing resource permissions is provided by allowing admins to factor in contextual attributes such as device security status, IP address, resource class, and date/time. You can control permissions by using the GUI interface of the web-based Cloud Console tool, via programming with Google Cloud IAM methods, or through Google's gcloud CLI tool. Google Cloud IAM automatically creates a complete audit trail to facilitate regulatory compliance.

Cloud Identity and Access Management is included without extra cost to all Google Cloud Platform licensees.

Google Kubernetes Engine is a Docker 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 that time Kubernetes has grown to be the leading solution for managing containerized workloads.

Google Kubernetes Engine (GKE) is powered by Google's Container-Optimized OS and runs Certified Kubernetes, ensuring workload portability to other Kubernetes platforms spanning cloud and local environments. To streamline development, ready-to-go open-source deployment templates for commercial applications are available on Google Cloud Marketplace.

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

Additional features of GKE include preemptible virtual machines, persistent disks, always-encrypted local SSD block storage, global load balancing to maximize speed and uptime, support for both Windows and Linux nodes, the ability to run stateless serverless containers with the GCP Cloud Run service, and usage metering for granular visibility into Kubernetes clusters.

Google Kubernetes Engine complies with HIPAA and PCI DSS 3.1. For stronger cybersecurity, GKE Sandbox provides an additional level of defense between containerized GKE workloads. Google Kubernetes Engine clusters provide native support for Kubernetes Network Policy to filter traffic by applying pod-level firewall policies. Private clusters in Google Kubernetes Engine can be confined to a private or public device accessible only to specified addresses.

Google Kubernetes Engine charges for each Google Compute Engine instance in a cluster. Usage of Google Compute Engine resources is priced by the second with a one-minute minimum usage cost.

Cloud AI Building Blocks enable developers, even without machine learning (ML) backgrounds, to integrate Google's leading-edge AI technology into their applications. Core capabilities address vision, language, and conversation. By using Google's APIs, you can access Google's pre-trained models rather than having to hassle with developing your own datasets from scratch and training and testing your own AI models. As Google's library of pre-trained models grows in sophistication and size, you can quickly add leading-edge AI technology to your applications. Also, Google AutoML products give you the tools required to train, validate and deploy your custom domain-specific machine learning models. You can use any Google AI Building Block individually or in combination with other AI tools according to your business requirements.

For advanced imaging, Google Cloud AI Building Blocks include the AutoML Vision and Vision API services that help you to extract insights from image libraries. Both products support REST and RPC APIs and allow your app to discern objects and their position inside an image. AutoML Vision simplifies the training process for your home-grown machine learning (ML) models by providing an easy-to-use graphical interface. Once you refine 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 integration with Google's pre-trained machine learning models. Developers can rapidly classify images using Google's extensive libraries of predefined labels. Vision API uses OCR tools to identify text, in more than 50 languages, embedded within your images. Used in conjunction with Google's Document Understanding AI feature, you can benefit from the same machine learning technology behind Google Search to extract actionable insights from masses of free-form documents. You can detect web objects and pages, distinguish a face from other objects and notice facial attributes, and identify product logos and popular landmarks. You can also recognize adult or violent content in images.

Google GCP's AutoML Video Intelligence and Video Intelligence API services, which offer a comparably wide range of features as Google's Vision products, make it simpler to mine information from videos.

Language Services
Language is Google's wheelhouse, and Google's stack of AI Building Blocks predictably includes a rich arsenal of products. Google GCP language products include:

• Cloud Translation API
  This cloud service enables you to enrich web sites and applications with dynamic translation features powered by Google's pre-trained neural translation technology. Google GCP offers a Basic and an Advanced version of the Translation API. Both options are based on Google's pre-trained, general-purpose model and offer automatic language identification, 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 branding in translated text, batch translation capability in GCP Cloud Storage, the ability to incorporate (but not create) custom Google AutoML Translation models, and an integrated gRPC open source API. The Cloud Translation service charges on a per-character basis.
• AutoML Translation
  This ML tool enables developers to build a custom translation model by training it with your own prepared dataset. The custom dataset is made of matching pairs of sentences in the original and target languages. AutoML Translation applies statistical analysis to the pairs from your dataset to train the model, validates it, and rates its accuracy. After you review the results of your model, you can modify your dataset and train a new model repeatedly until you are happy with the results. You can create your own translation models in over 50 language pairs. Costs for using AutoML Translation are based on the hours of training used and the number of characters you submit for translation.
• Cloud Natural Language API
  Google Cloud's Natural Language API uses a library of proven ML models to assist you to grasp the themes and structure of documents. A content classification model discerns content categories within a document, such as architecture, finance, or entertainment; an entity analysis model finds and labels familiar entities referenced within the document, such as product, organization, or athlete); a sentiment analysis model assesses the author's attitude expressed in the document and the strength of conviction; an entity sentiment analysis model combines entity and sentiment analysis by detecting familiar entities in a document and determining the attitude and the magnitude of emotion expressed in relation to those entities; a syntactic analysis model exposes structural information by deconstructing text into sentences and words, which are further broken down into parts of speech and roots. Each API detects the language of the target text if it is not declared. The's Natural Language API is a REST API and involves JSON requests and responses. Target text can be embedded in the JSON request or resident in Google Cloud Storage.
• AutoML Natural Language
  Google's AutoML Natural Language product enables you to build and refine custom Natural Language models for classification, entity extraction, and sentiment analysis. For example, a custom sentiment analysis model designed by an airline could be taught that a reference to lost luggage in a tweet counts as a negative rather than positive sentiment. Google Cloud's AutoML Natural Language service makes it easy to build a custom dataset, use the dataset to train a model, test the resulting model, and tweak your dataset until your model is suitable for production.
• Dialogflow
  Google's Dialogflow is a a development suite that uses the natural language technology behind Google Assistant to enable you to create a conversational interface so your product can interact with your users by voice. You can add this technology to a smartphone app, website, interactive voice response system, or other scenario that could be improved with voice conversation. GCP's Dialogflow service can understand text or audio inputs and can respond through text or synthetic speech. Dialogflow can recognize a user's meaning and extract pre-defined entities such as time, date, and numbers. You can teach your agent to recognize your own entity types by submitting small sample datasets, or you can use over 40 tested agents as templates. Commercial 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-quality, natural-seeming speech in over 30 languages and more than 180 voices. Cloud Text-to-Speech platform supports any application or device capable of sending REST or gRPC requests. This includes smartphones, desktop PCs, iPads or tablets, and IoT devices such as cars, TVs, and speakers. Accepted audio coding formats include mp3, Linear16, and Ogg Opus. You can use Speech Synthesis Markup Language tags to insert pauses, numbers, date and time formatting, and other instructions. Cloud Text-to-Speech is priced per million characters processed.
• Speech-to-Text
  Google Cloud's Speech-to-Text API gives developers access to leading-edge automatic speech recognition (ASR) technology powered by Google's constantly refined deep-learning neural network algorithms. GCP's Speech-to-Text can translate audio in real time and can be optimized to support standard sampling rates associated with phones, video, or voice commands/search. The API works with 120 languages and can recognize what language is being used from a selection of up to four languages. You can specify up to 5,000 words or phrases that relate to your organization, like brand or partner names. The technology can automatically capitalize proper names and format numbers into addresses, dates, phone numbers, and currencies. Video transcription can add punctuation, and speaker diarization technology can distinguish among several speakers in a conference. Noise cancellation is built in, and for certain languages you have the ability to filter out inappropriate language. Supported encodings include FLAC, AMR, PCMU, and Linear-16. Billing is time based.

Progent can help your organization to decide which of your applications are appropriate for Google Cloud and can show you how to make your legacy apps cloud compatible. Progent has helped clients evaluate migrating to Google Cloud SQL, using Google Dataproc for on-premises Hadoop, adopting Google Cloud 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 short-term tasks to help you quickly overcome stubborn technical challenges or Progent can deliver comprehensive project management outsourcing services to make sure your GCP integration initiative is successfully carried out on schedule and within budget.

Some of most common technical obstacles businesses run into when integrating with GCP or other public cloud is reconfiguring firewalls and VPN tunnels to provide users with easy but secure access to cloud services. Progent can provide the expertise of Cisco-certified CCIE network infrastructure engineers and firewall experts for security gateways from major vendors like Cisco, Palo Alto Networks, Barracuda, WatchGuard, and Fortinet to assist you to set up or debug firewalls for connecting to GCP. To support BYOD computing, Progent's iPhone and iPad technology consultants and Google Android integration experts can assist you to configure and manage secure mobile endpoints for your Google Cloud users. Progent can work in conjunction with your internal IT team and Google's support engineers to mitigate GCP integration problems quickly and affordably.

Examples of remote consulting services offered by Progent to assist organizations integrate their networks with GCP include:

• Review hybrid solution design for Google Compute Engine VMs and GCP Cloud Storage
• Create and test virtual machine images for Windows or Linux
• Configure, deploy and troubleshoot VPN tunnels for connectivity with Google Cloud
• Plan integration solutions for firewalls from Cisco, Palo Alto Networks, Check Point, WatchGuard, and Fortinet and others
• Configure and troubleshoot mobile endpoints
• Define and verify security policies based on best practices
• Fix IP addressing problems
• Define cost-managed plan for 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 Azure planning and integration consultants can assist you with any phase of Azure cloud migration such as needs analysis, prerequisites evaluation, solution architecture, pilot testing, deployment, centralized administration, performance optimization, software license management, disaster recovery strategies, security policy enforcement, and compliance validation. Progent can assist your IT staff to set up and troubleshoot firewall appliances and VPN tunnels so your users can safely access to Azure-based resources, and Progent's Microsoft-certified consultants can help you set up key Microsoft platforms to work in Azure including Windows Server, Exchange, SQL Server and SharePoint. Progent can also help your organization to create a hybrid environment that transparently combines on-premises datacenters with Azure-based resources.

Microsoft allows you to create transparent hybrid ecosystems that integrate Microsoft 365 and local installations of Exchange. This permits you to have certain Exchange mailboxes located on your on-premises datacenter and other mailboxes resident on Microsoft 365. Progent's certified Exchange consulting team can assist your organization with any facet of designing, implementing and debugging your hybrid Exchange solution. Progent's Exchange specialists can deliver occasional expertise to help you resolve stubborn technical issues and also can provide comprehensive project management outsourcing or co-sourcing to ensure your hybrid Microsoft 365/Exchange initiative is carried out on schedule and within budget. For more information about Progent's consulting services for hybrid Microsoft 365 Exchange and on-premises Exchange systems, visit Microsoft 365 Exchange Online integration with on-prem Exchange.

Progent's certified Microsoft Office and Microsoft 365 consultants can assist businesses of any size to integrate Microsoft Office desktop and Microsoft 365 applications such as Excel, Word, PowerPoint, Microsoft Outlook, Microsoft Access, Project and OneNote into a cohesive solution that provides quick ROI and enables better business results. Progent can help your company to integrate Microsoft Office or Microsoft 365 applications with one another and with other key Microsoft platforms such as SharePoint Server, Microsoft Exchange Server and SQL Server running locally or in the cloud. Progent's consultants can also assist you to fix compatibility issues with various versions of Office desktop and can provide customized online Microsoft Office and Microsoft 365 instruction to individual users or teams.

Progent's Amazon AWS integration experts offer cost-effective online consulting to assist businesses to integrate Amazon AWS cloud services such as Elastic Compute Cloud (EC2) for virtual server hosting, Amazon S3 for scalable cloud storage, and Amazon Glacier for low-cost archival storage. Progent can help you with every aspect of Amazon AWS integration including requirements analysis, readiness evaluation, architectural design, testing, deployment, centralized administration, performance tuning, software license management, backup/restore mechanisms, and security. Progent can provide advanced expertise with firewalls and VPN access and can help you create all-cloud or hybrid ecosystems that efficiently integrate Amazon AWS cloud services. Progent can provide occasional support or Progent can provide comprehensive project management outsourcing or co-sourcing services to help you move efficiently to the Amazon AWS cloud platform.

Amazon Marketplace Web Service is an integrated collection of APIs that enables Amazon sellers to improve the efficiency of their operations by automating key sales functions including listings, orders, payments, fulfillment, and reports. By leveraging Amazon's extensive online ecosystem and automating their sales, merchants can expand their reach, lower their cost of sales, improve response time to customers, and increase their bottom line. Progent's Amazon Marketplace Web Service (Amazon MWS) developers can collaborate with your development team and provide programming, workflow integration, project management support, and training to help you shorten development time and costs and expedite your ROI.

Contact Progent for Google Cloud Integration Consulting
If you need assistance with any facet of integrating your IT system with Google Cloud or any other public cloud platform, call Progent at 800-993-9400 or visit Contact Progent.