Cloud Integration Expertise

Google Cloud Platform (GCP) is a popular set of cloud services that offers Infrastructure-as-a-Service and Platform-as-a-Service products. GCP's penetration in the public cloud sector is behind only Amazon AWS and Microsoft Azure. Like these vendors, GCP utilizes the same massive network infrastructure that supports its core online applications. For Google, these apps include Google Search and YouTube. The GCB cloud stack has more than 100 products that cover compute, data storage, database management, network infrastructure, business analytics, Big Data, machine learning, AI, identity, cybersecurity, Internet of Things, and unified tools.

Progent has experience helping businesses from small offices to enterprises to design, configure, test, manage, and maintain IT ecosystems based on a variety of network models including on-premises data centers, private clouds, one or more public clouds, or a hybrid combination of local and cloud-based infrastructure. Progent can provide quick remote or onsite access to seasoned consultants to help you to assess the advantages and limitations of possible network models and compare the feature set and cost of Google Cloud vs. alternative cloud vendors.

Progent's certified Microsoft, Linux, and Cisco experts can assist your organization to integrate your current IT resources with the Google Cloud Platform, and Progent's database management experts can show you how to make your business-critical applications cloud capable so they can benefit fully from Google Cloud products and services. Progent can assist you to set up VMs on Google Cloud Compute Engine, design a cost-effective storage system with GCP Cloud Storage services, and streamline access management with GCP Cloud Identity. Progent can also assist you to utilize GCP's tools to manage and monitor your GCP Cloud environment so it continually delivers maximum return on investment.

Key Services Available for the Google Cloud Platform
Google Cloud offers over IaaS and PaaS services addressing virtually all areas of information technology including compute, storage, database management, networking, administration, security, web, mobility, and application development. GCP services are available by subscription. Like other public cloud services, you are charged for the resources you use. Important GCP products and services for which Progent offers advanced consulting and debugging include:

Compute Engine is an IaaS service for running Windows and Linux VMs in the cloud, comparable to Amazon EC2 or Azure Virtual Machines. Compute Engine VMs have seamless access to Google Cloud block storage and advanced infrastructure. GCP offers three types of VMs in either pre-defined or custom sizes. GCP's N2 type virtual machine is value priced and designed for common applications such as web hosting, business apps, and databases. The C2 type VM provides up to 60 virtual CPUs (vCPUs) for processor-intensive apps such as ECAD and simulations. Google Cloud's M2 class VM offers up to 11.5 TB of RAM for memory-intensive applications like in-memory databases or in-depth analytics. Google's sole-tenant node option features a physical Compute Engine machine dedicated to your exclusive use.

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

Other available features for GCP Compute Engine include:

• Always-encrypted local solid-state drive (SSD) block storage for enhanced performance and data security
• Graphics Processing Unit (GPU) that can be added to VM instances for processor-intense apps like machine learning and 3D visualizations
• Global load balancing for maximizing performance and availability at minimal cost
• Google Kubernetes Engine for orchestrating Docker containers on Compute Engine VMs

Google Cloud Storage provides object storage that can scale to exabytes of data. Objects held in Google Cloud Cloud Storage are organized in containers known as buckets. GCP provides four classes of cloud storage, distinguished and priced according to the object's anticipated longevity and its busy/dormant ratio. As you progress along the storage classes from Standard to Archive storage, access costs go up, at-rest expense decrease, and required minimum storage duration increases. Google Cloud's storage classes make it possible to control costs by designing the appropriate price/performance profile for your network, and Google's Object Life Cycle Management feature allows you to program the progression of storage objects from high-access to low-access classes over time. All classes feature global accessibility, virtually unlimited scale (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 applies to all storage types.

Standard Storage is Google Cloud's default type and is optimized for data accessed frequently or stored only for short periods. There is no minimum storage time. To get the best performance and lowest network charges, Standard Storage objects should be kept in the same geographical region as the Compute Engine instances or the container clusters that use the objects. Standard Storage offers the top average uptime across any regional distribution scheme. Nearline Storage is a low cost storage option intended for data accessed only occasionally, preferably around once per month. Examples of suitable use cases are periodic backup and archiving. At-rest costs are lower than with Google Cloud's Standard Storage, but access is more expensive, availability is slightly lower, and storage duration is at least 30 days.

Coldline Storage provides very low storage costs for at-rest data and is designed for scenarios where data are accessed less than once a quarter. Minimum storage duration is three months, availability is marginally less than with Google's Standard and Nearline Storage classes, and data access costs are comparatively high. Google's Archive Storage, which features the lowest at-rest storage pricing but has a minimum duration of one year, is the preferred storage service for objects held only for backup or archive purposes. Access costs for Archive Storage are the most of any GCP storage class.

Cloud Storage Encryption
GCP Cloud Storage always encrypts data on the server end before placing it on disk. Added to this standard encryption, you can choose more ways to encrypt your data. Google Cloud offers two supplemental server-side encryption services that cause objects to be encrypted after making it to Cloud Storage but before the data is stored to disk. Google Cloud's Customer-supplied encryption keys allows you to supply and control your own encryption keys. The Customer-managed encryption keys alternative enables you to generate and control your encryption keys via Google's Cloud Key Management Service. Both these server-side encryption options create an additional layer of encryption over and above GCP's standard Cloud Storage encryption service.

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

Google Cloud Identity and Access Management (IAM) is Google's unified platform for managing access to network resources and granting permissions for users and services to use network resources for a specified period of time. Examples of GCP resources are Compute Engine instances and Google Cloud Storage buckets. Unified tools offer admins the ability to control access permissions for all services available within GCP. Cloud IAM features high precision in designing policies to assign groups and users permissions to access only required resources while preventing access to unnecessary resources.

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

Cloud IAM policies are hierarchical, flowing downward from the organization to projects and then to resources. You can establish organization-wide policies, tune them for a specific project, and tune them even more for a specific resource. You can assign access policies to specific resources, to a project, or at the organizational level. Policies assigned to an organization flow down to projects within the organization and from there resources within projects.

Further refinement in controlling resource access rights is offered by enabling administrators to factor in contextual attributes such as endpoint security status, IP address, resource class, and time. You can control access rights by using the GUI interface of the web-based Cloud Console, via programming with Google Cloud IAM methods, or through the gcloud CLI feature. Cloud IAM automatically maintains a full audit trail to simplify regulatory compliance.

Google Cloud Identity and Access Management is provided at no extra cost to all GCP customers.

Google Kubernetes Engine (GKE is a Docker container service for orchestrating and managing containerized applications. Kubernetes was originally created by Google to automate Docker container orchestration and was offered as open source in 2014. Since that time Kubernetes has become the most popular solution for managing containerized applications.

Google Kubernetes Engine (GKE) is powered by Google's Container-Optimized OS and supports Certified Kubernetes, allowing workload portability to other Kubernetes platforms across cloud and on-premises environments. To streamline development, ready-to-go open-source deployment templates for enterprise-grade apps are available on Google Cloud Marketplace.

The Migrate for Anthos tool, offered at no cost with GKE, allows you to move and port your workloads easily from your current infrastructure into GKE containers. These workloads can include physical servers and VMs located onsite, in GCP's Compute Engine, or in other clouds. GKE supports pod and cluster autoscaling for continuous analysis of the CPU and memory usage of pods and for automatically tuning CPU and memory requests across node pools.

Other features of GKE include preemptible VMs, persistent disks, always-encrypted local solid-state drive (SSD) block storage, global load balancing to maximize performance and uptime, compatibility with both Windows and Linux nodes, the capability of running stateless serverless containers via the GCP Cloud Run service, and usage metering for fine-grained visibility into your Kubernetes clusters.

GKE is compliant with HIPAA and PCI DSS 3.1. standards. For stronger cybersecurity, GKE Sandbox provides an additional layer of protection 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 limited to a private or public endpoint accessible only to distinct address ranges.

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

Cloud AI Building Blocks enable developers, even with little or no machine learning experience, to integrate Google's leading-edge AI capabilities into their applications. Essential services cover vision, language, and speech. By using APIs, you can access Google's pre-trained AI models and avoid having to deal with creating your own datasets and training and validating your own AI models. As Google's catalog of pre-trained models grows in sophistication and size, you can quickly add leading-edge AI technology to your apps. Also, Google AutoML products give you the tools you need to train, validate and deploy your own domain-specific ML models. You can use any Google AI Building Block individually or in any combination with other AI Building Blocks depending on your business requirements.

For advanced imaging, Google GCP Cloud AI Building Blocks include the AutoML Vision and Vision API services that help you to extract insights from your images. Both products use REST and RPC APIs and allow your application to discern objects and their position within the image. AutoML Vision simplifies training for your custom machine learning (ML) models by offering an easy-to-use graphical interface. Once you refine your models for accuracy, speed and size, you can export them to the Google Cloud or to various edge devices.

Vision API provides integration with Google's out-of-the-box models. Developers can quickly classify images using Google's extensive collections of predefined labels. Google Cloud's Vision API uses OCR technology to identify text, in more than 50 languages, contained within images. Used in conjunction with Google's Document Understanding AI feature, you can use the same machine learning technology that powers Google Search to extract actionable insights from volumes of free-form documents. You can discern web objects and pages, isolate a face from other items and notice facial attributes, and identify brand logos and famous 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 wide array of features as Google's Vision products, make it easy to derive information from video files.

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

• Cloud Translation API
  This cloud service enables you to enrich web sites and applications with real-time language translation features powered by Google’s pre-trained neural machine translation technology. Google Cloud 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, transparent HTML support, and the ability to translate between over 100 language pairs. The Advanced version of Cloud Translation API includes an extensible glossary to reflect your branding in translated text, batch translation capability in Google Cloud Storage, the ability to utilize custom Google AutoML Translation models, and an integrated gRPC open source API. Google's Cloud Translation service charges on a per-character basis.
• AutoML Translation
  This ML platform enables you to build a custom translation model by training it using your own 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 items from your custom dataset to train the model, validates it, and scores its performance. After you assess the effectiveness of your model, you can tune your dataset and train a new model until you are happy with the outcome. You can create custom translation models in over fifty language pairs. Costs for using AutoML Translation are calculated based on the hours of training used and the volume of characters you include for translation.
• Cloud Natural Language API
  Google Cloud's Natural Language API uses a library of pre-built machine learning models to assist you to grasp the themes and structure of documents. A content classification model identifies content categories in a document, like civil engineering, investing, or sports; an entity analysis model finds and tags common known entities referenced in the document, such as product, company, or athlete); a sentiment analysis model assesses the author's attitude suggested by the document and the magnitude of passion; an entity sentiment analysis model integrates entity analysis and sentiment analysis by identifying familiar entities within a document and estimating the positive or negative attitude and the magnitude of emotion demonstrated towards those entities; a syntactic analysis model exposes structural organization by breaking text up into sentences and tokens (words), which are then broken down into parts of speech and roots. Each API identifies the language of the target text if it is not specified. The's Natural Language API is a REST API and involves JSON requests and responses. Text to be analyzed can be embedded in the JSON request or held in Google Cloud Storage.
• AutoML Natural Language
  Google Cloud's AutoML Natural Language product enables you to create and tune custom Natural Language models for classification, entity extraction, and sentiment analysis. For example, a sentiment analysis model designed by an airline could learn that a mention of lost baggage in a tweet reflects a negative rather than positive sentiment. Google's AutoML Natural Language service makes it simple to create a dataset, utilize the dataset to train a model, test the resulting model, and refine your dataset until your model is ready to deploy.
• Dialogflow
  GCP's Dialogflow is a platform that uses the same natural language understanding technology that powers Google Assistant to help you to create a conversational interface so your product or service can interact with your customers by voice. You can add this technology to a mobile app, website, interactive voice response system, or any other application that could be improved with voice interaction. Google's Dialogflow platform can analyze text or voice inputs and can reply through text or synthetic voice. Dialogflow can detect a user’s meaning and extract prebuilt entities such as time, date, and numbers. You can teach your agent to identify your own custom entity types by providing small sample datasets, or you can utilize more than 40 tested agents as templates. Professional editions of Dialogflow are billed based on audio/phone time and the number of characters and queries.
• Cloud Text-to-Speech
  Google Cloud's Text-to-Speech API converts text or Speech Synthesis Markup Language to high-fidelity, natural-sounding speech in over 30 languages and over 180 voices. Google's Cloud Text-to-Speech service supports any application or device capable of sending REST or gRPC requests. This includes smartphones, desktop PCs, iPads or tablets, and IoT devices like autos, TVs, and audio speakers. Accepted audio coding formats include mp3, Linear16, and Ogg Opus. You can use SSML tags in order to add pauses, numbers, calendar and time formatting, and other instructions. Cloud Text-to-Speech is billed based on million characters of text submitted.
• Speech-to-Text
  Google's Speech-to-Text API provides access to advanced automatic speech recognition (ASR) technology based on Google's continually refined deep-learning neural network algorithms. Google Cloud's Speech-to-Text can translate streaming audio in real time and can be set to handle standard sampling frequencies for phones, video, or voice commands and search. Google's API supports 120 languages and can identify what language is being used from a selection of as many as four languages. You can specify up to 5,000 words or phrases that relate to your business, 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 the speaker diarization feature can distinguish among several talkers in a group. Noise cancellation is included, and for some languages you have the option to filter out inappropriate expressions. Supported encoding formats include FLAC, AMR, PCMU, and Linear-16. Pricing is time based.

Progent can help you to decide which of your applications are appropriate for GCP and can show you how to make your legacy applications cloud ready. Progent has experience helping clients assess the value of running Google Cloud SQL, using Google Dataproc for on-prem Hadoop, adopting Google Kubernetes Engine as a virtualization replacement, and deploying MongoDB Atlas on GCP vs. on-premises MongoDB. Progent can provide as-needed remote consulting support for short-term tasks to help you quickly resolve occasional technical challenges or Progent can deliver comprehensive project management consulting services to ensure your Google Cloud integration initiative is successfully completed on schedule and on budget.

Some of most frequently encountered technical obstacles businesses run into when integrating with Google Cloud or other public cloud is reconfiguring firewalls and VPN tunnels to give users convenient but protected access to cloud services. Progent can provide the services of Cisco-certified CCIE network infrastructure engineers and firewall experts for security appliances from leading vendors such as Cisco, Palo Alto Networks, Barracuda, WatchGuard, and Fortinet to assist you to configure or troubleshoot firewalls for connecting to Google Cloud Platform. To support mobile computing, Progent's iPhone and iPad management consultants and Google Android integration experts can help you to integrate and administer secure mobile endpoints for your GCP users. Progent can work in conjunction with your in-house IT staff and Google's support engineers to mitigate Google Cloud connectivity problems quickly and affordably.

Examples of online consulting expertise offered by Progent to assist businesses expand their networks with Google Cloud Platform include:

• Check hybrid system plan for Google Compute Engine VMs and GCP Cloud Storage
• Create and verify VM images for Windows or Linux
• Configure, integrate and troubleshoot VPN tunnels for access to GCP
• Design integration solutions for firewalls from Cisco, Palo Alto Networks, Check Point, SonicWall, and Fortinet and others
• Set up and debug mobile devices
• Create and implement policies following best practices
• Fix IP addressing issues
• Design cost-managed allocation of GCP Cloud Storage
• Tune query performance on Cloud SQL
• Simplify software license management
• Fix certificate issues

Other leading cloud platforms supported by Progent include:

Progent's Microsoft Azure planning and integration experts can help you with every phase of Microsoft Azure integration such as requirements definition, prerequisites assessment, solution design, pilot testing, implementation, centralized administration, performance optimization, software license controls, disaster recovery strategies, security planning, and compliance validation. Progent can assist your IT staff to configure and debug firewall appliances and VPN tunnels so your clients can safely connect to Azure-based resources, and Progent's Microsoft-certified consultants can assist you set up critical Microsoft technologies to run in Azure including Windows Server, Exchange Server, SQL and Skype for Business. Progent can also assist your organization to set up a hybrid environment that transparently integrates physical datacenters with Azure-based services.

Microsoft allows you to create transparent hybrid ecosystems that combine Microsoft 365 and local installations of Exchange. This permits you to have certain mailboxes hosted on your physical datacenter and other mailboxes resident on Microsoft 365. Progent's certified Exchange consulting team can help you with any phase of planning, implementing and debugging your hybrid Exchange solution. Progent's Exchange specialists can deliver as-needed expertise to help you resolve challenging technical bottlenecks and also offer extensive project management outsourcing to ensure your hybrid Microsoft 365/Exchange solution is carried out on schedule and within budget. To learn more about Progent's consulting expertise for hybrid Microsoft 365 Exchange and on-premises Exchange systems, refer to Microsoft 365 Exchange Online integration solutions with on-prem Exchange.

Progent's Office and Microsoft 365 experts can assist businesses to integrate Office desktop and Microsoft 365 applications including Office Excel, Word, PowerPoint, Microsoft Outlook, Microsoft Access, Project and Publisher into a cohesive solution that provides fast return on investment and enables improved business outcomes. Progent can assist your company to interface Microsoft Office or Microsoft 365 apps with each other and with additional core Microsoft platforms such as SharePoint, Microsoft Exchange Server and Microsoft SQL Server deployed locally or hosted in the cloud. Progent can also assist you to resolve compatibility issues between different versions of Microsoft Office and can provide customized online Microsoft Office and Microsoft 365 instruction to individuals and teams.

Progent's Amazon AWS planning and integration experts can provide affordable online support to assist businesses of any size to integrate Amazon Web Services (AWS) cloud services such as Elastic Compute Cloud (EC2) for virtual server hosting, Amazon Simple Storage Service (Amazon S3) for scalable cloud storage, and Glacier for low-cost long-term archiving. Progent can help you with every aspect of Amazon AWS migration and troubleshooting including needs analysis, preparedness evaluation, system design, pilot testing, deployment, centralized administration, performance tuning, software license management, backup/restore mechanisms, and security. Progent offers advanced expertise with firewalls and VPN technology and can help you deploy cloud-based or hybrid networking models that efficiently incorporate Amazon AWS cloud services. Progent can provide occasional support or Progent can provide project management outsourcing or co-sourcing to help you migrate smoothly to the Amazon AWS cloud platform.

Amazon Marketplace Web Service (Amazon MWS) is an integrated collection of APIs that allows Amazon sellers to streamline their operations by automating crucial sales activities including listings, orders, payments, fulfillment, and finances. By leveraging Amazon's extensive online selling environment and automating their sales, merchants can expand their market, reduce their operating costs, accelerate reaction time to customers, and increase their profits. 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 so you can shorten development time and costs and expedite your ROI.

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