Cloud Integration Consulting

Google Cloud Platform (GCP) is a leading suite of cloud services that includes Infrastructure-as-a-Service and Platform-as-a-Service products. GCP's penetration in the public cloud market trails only Amazon AWS and Azure. As with vendors, Google Cloud utilizes the same massive network infrastructure that hosts its core applications. In Google's case, these include Google Search and YouTube. The GCB cloud portfolio has more than 100 services that cover processing, data storage, database management, networking, analytics, Big Data, machine learning, artificial intelligence, identity, security, Internet of Things, and unified management.

Progent has experience assisting organizations from small offices to enterprises to plan, deploy, test, manage, and maintain IT ecosystems based on various network models including on-prem data centers, private clouds, one or multiple public clouds, or a hybrid combination of local and cloud infrastructure. Progent can provide quick online or onsite access to high-level experts to assist you to assess the potential benefits and limitations of different network models and compare the services and pricing structure of Google Cloud Platform vs. alternative cloud offerings.

Progent's Microsoft, Linux, and Cisco consultants can assist your organization to integrate your current network infrastructure with the Google Cloud Platform, and Progent's database management experts can show you how to make your key applications cloud ready so they can take full advantage of GCP products and services. Progent can help you to set up virtual machines on Google Cloud Compute Engine, plan an efficient storage system using Google Cloud Storage services, and simplify access management with GCP Cloud Identity. Progent can also help you to use GCP's tools to manage and monitor your Google Cloud ecosystem so it continually delivers maximum return on investment.

Key Services Offered for the Google Cloud Platform
Google Cloud offers more than 100 IaaS and PaaS services covering nearly all areas of IT including processing, storage, database management, networking, administration, security, web, mobility, and application development. GCP services are available on a subscription basis. Like other public cloud services, you pay for what you use. Popular Google Cloud services for which Progent can provide advanced consulting and technical support include:

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

Key features of the Google Cloud Compute Engine include live VM migration, which lets you keep virtual machines working even while undergoing system maintenance, and preemptible virtual machines, low-cost virtual machine compute instances which continue for up to 24 hours and are intended for running batch jobs that can be paused and resumed intermittently without compromising operations.

Additional available features for GCP Compute Engine include:

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

Google Cloud Storage is object storage that scales to exabytes of data. All data placed in Google Cloud Storage are organized in containers called buckets. Google Cloud provides four types of cloud storage, differentiated and priced according to the object's expected longevity and its access/at-rest ratio. As you progress through Google's storage classes from Standard to Archive, access expense go up, at-rest costs go down, and minimum storage time increases. Google's storage classes allow you to control expenses by designing the appropriate cost/performance profile 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 classes as they age. All storage classes share worldwide accessibility, unlimited scale (but a size limit of 5 TB for individual objects, no minimum size, low latency, on-request geo-redundancy, and a common set of cloud security and management tools. A single API applies to all storage classes.

Standard Storage is Google Cloud's default type and is intended for data used frequently or stored only for short periods. There is no minimum storage duration. To get the best speed and lowest network usage fees, Standard Storage objects should be kept in the same geographical region as the Compute Engine instances or the container clusters that interact with the objects. Standard Storage delivers the top average uptime for any regional distribution scheme. Nearline Storage is a economical storage option designed for objects accessed infrequently, preferably once per month or less. Examples of appropriate use cases are monthly backup and archiving. At-rest costs are less than with GCP's Standard Storage, but data access is more expensive, availability is slightly lower, and storage duration is at least one month.

Coldline Storage provides rock bottom storage costs for dormant data and is intended for scenarios where data are accessed less than once every 90 days Minimum duration is 90 days, availability is slightly lower than with GCP's Standard and Nearline Storage types, and data access pricing is comparatively expensive. Google Cloud's Archive Storage, which offers the lowest at-rest storage costs but has a minimum storage duration of one year, is the preferred storage class for data held exclusively for backup or archive scenarios. Access costs for Archive Storage are the most of any Google Cloud storage class.

Cloud Storage Encryption
GCP Cloud Storage always encrypts stored data on the server end before placing it on disk. Added to this routine encryption, you can select more options to encrypt your data. There are two supplemental server-side encryption options that allow data to be encrypted after arriving at Cloud Storage but before the data is stored to disk. The Customer-supplied encryption keys enables you to create and control your own encryption keys. The Customer-managed encryption keys alternative allows 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 default Cloud Storage encryption service.

In case you use client-side encryption before transporting your data to Google Cloud Storage, your pre-encrypted data will also undergo Google's server-side encryption.

Google Cloud Identity and Access Management (IAM) is Google's centralized platform for managing access to network resources and assigning permissions for users and services to use network resources for a specified period of time. Examples of GCP resources are Compute Engine VM instances and Cloud Storage buckets. Unified and consistent tools offer admins control over access rights for all services within the Google Cloud Platform. Google Cloud IAM features fine granularity in designing policies to grant groups and users permissions to access task-relevant resources while preventing access to unnecessary resources.

With Cloud IAM, policies are made up of roles; roles are based on permissions; and permissions are assigned to resources. Users or groups are assigned to policies, and through the policy they are given access to whatever resources the roles provide. As an example of 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 assigned the role of Owner, Editor, Viewer, Publisher, or Subscriber.

Cloud Identity and Access Management policies are hierarchy-based, cascading downward from the organization to projects and lastly to resources. You can establish organization-wide policies, tune them as appropriate for a given project, and tune them even more for a given 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 in the organization and from there resources within projects.

Further refinement in controlling resource permissions is provided by permitting administrators to include contextual attributes like device security status, IP address, resource class, and time. You can manage permissions by using the GUI interface of the web-based Cloud Console, through programming by using Google Cloud IAM methods, or through the gcloud command-line tool. Cloud IAM automatically creates a full audit trail to facilitate compliance.

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

Google Kubernetes Engine is a Docker container service for orchestrating and managing containerized apps. Kubernetes was initially created by Google to automate Docker container orchestration and was made available as open source at the end of 2014. Since then Kubernetes has grown to be the leading platform for managing containerized workloads.

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

The Migrate for Anthos service, offered for free with Google Kubernetes Engine, allows you to migrate and convert your workloads easily from your current infrastructure into GKE containers. These workloads can be physical servers and virtual machines located onsite, in GCP's Compute Engine, or in other clouds. GKE allows pod and cluster autoscaling for ongoing analysis of the processor and memory usage of pods and for dynamically adjusting CPU and memory requests across multiple node pools.

Other capabilities of Google Kubernetes Engine include preemptible virtual machines, persistent storage, always-encrypted local solid-state drive (SSD) block storage, global load balancing to optimize speed and availability, compatibility with both Windows and Linux nodes, the capability of running stateless serverless containers via the Google Cloud Run service, and usage metering for granular visibility into your Kubernetes clusters.

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

Google Kubernetes Engine charges for each GCP 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 without machine learning backgrounds, to incorporate Google's advanced AI technology into their applications. Essential capabilities address sight, language, and conversation. By using APIs, you can take advantage of Google's out-of-the-box models and avoid having to deal with creating your own datasets from scratch and training your own AI models. As Google's catalog of pre-trained models expands, you can immediately add state-of-the-art AI technology to your applications. Also, Google Cloud AutoML products give you the utilities required to train, test and deploy your custom domain-specific ML models. You can use any Google Cloud AI Building Block by itself or in combination with other AI tools depending on your business requirements.

For advanced imaging, Google Cloud AI Building Blocks include the AutoML Vision and Vision API services that allow you to extract insights from your images. Both products include REST and RPC APIs and allow your application to detect objects and their position within an image. AutoML Vision streamlines the training process for your home-grown machine learning (ML) models by offering an intuitive graphical interface. Once you optimize your models for accuracy, speed and size, you can send them to the Google Cloud or to various edge devices.

Vision API provides integration with Google's out-of-the-box models. You can quickly classify images using Google's extensive libraries of predefined labels. Vision API uses OCR technology to identify text, in more than 50 languages, embedded anywhere within images. Used in conjunction with Google's Document Understanding AI feature, you can use the same ML technology behind Google Search to derive useful information from masses of free-form documents. You can detect web objects and pages, distinguish a face from other items and notice facial attributes, and recognize brand logos and popular landmarks. You can also detect adult or violent content within images.

Google Cloud's AutoML Video Intelligence and Video Intelligence API products, which offer a comparably wide array of features as Google's Vision products, make it easy to extract value from videos.

Language Products
Language is Google's strong suit, and Google's portfolio of AI Building Blocks understandably includes a rich arsenal of services. Google Cloud language services include:

• Cloud Translation API
  This cloud service enables developers to enrich web sites and applications with dynamic language translation features based on Google’s pre-trained neural machine translation technology. Google Cloud offers a Basic and an Advanced version of Google's Translation API. Both versions use Google's pre-trained, general-purpose model and feature automatic language detection, an integrated REST API, seamless HTML support, and the capability to translate between more than 100 language pairs. The Advanced option of Google Cloud Translation API adds an extensible glossary to preserve your branding in translated copy, batch translation support in Google Cloud Storage, the ability to utilize custom Google AutoML Translation models, and a built-in gRPC open source API. Google's Cloud Translation service is priced per character.
• AutoML Translation
  This machine learning platform enables you to build a custom translation model by training it with your own dataset. The custom dataset is made of matching pairs of sentences in the source and target languages. Google AutoML Translation applies statistical analysis to the items from your dataset to train the model, tests it, and scores its performance. After you review the effectiveness of your custom model, you can modify your dataset and train a new model repeatedly until you are satisfied with the results. You can create your own translation models in over fifty language pairs. Costs for using AutoML Translation are based on the hours of training used and the volume of characters you submit for translation.
• Cloud Natural Language API
  GCP's Natural Language API marshals a library of standard ML models to assist you to understand the themes and structure of documents. A content classification model identifies content categories within a document, like civil engineering, investing, or entertainment; an entity analysis model identifies and labels familiar entities referred to within the document, like country, company, or public figure); a sentiment analysis model assesses the author's attitude expressed in the document and the strength of passion; an entity sentiment analysis model integrates entity and sentiment analysis by identifying familiar entities within a document and estimating the positive or negative attitude and the magnitude of feeling demonstrated in relation to those entities; a syntactic analysis model exposes structural information by breaking text up into sentences and 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 involves JSON requests and responses. Text to be analyzed can be included in the request or resident in Google Cloud Storage.
• AutoML Natural Language
  Google Cloud's AutoML Natural Language product allows you to create and tune your own Natural Language models for classification, entity extraction, and sentiment analysis. As an example, a sentiment analysis model created by an airline could learn that a reference to misplaced luggage in social media reflects a negative sentiment. Google's AutoML Natural Language product makes it easy to create your own dataset, utilize the dataset to train a model, validate the model, and refine your dataset until the model is ready to deploy.
• Dialogflow
  GCP's Dialogflow is a platform that uses the same natural language technology behind Google Assistant to help you to create a conversational interface so your product can interact with your customers by voice. You can port this capability to a mobile app, website, interactive voice response system, or any other application that could be improved with natural voice conversation. GCP's Dialogflow service can understand text or voice inputs and can respond through text or synthetic voice. Dialogflow can recognize a user’s intent and extract prebuilt entities such as time, date, and numbers. You can teach your Dialogflow agent to recognize your own custom 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
  GCP's Text-to-Speech API converts text or Speech Synthesis Markup Language (SSML) to high-quality, natural-sounding speech in more than 30 languages and over 180 voices. Cloud Text-to-Speech platform supports any application or device capable of sending REST or gRPC requests. This includes phones, desktop PCs, iPads or tablets, and IoT devices such as cars, TVs, and audio speakers. Supported audio formats include mp3, Linear16, and Ogg Opus. You can include Speech Synthesis Markup Language tags in order to add pauses, numbers, calendar and time formatting, and other instructions. Cloud Text-to-Speech is priced based on million characters submitted.
• Speech-to-Text
  Google Cloud's Speech-to-Text API provides access to leading-edge automatic speech recognition (ASR) technology based on Google's constantly evolving deep-learning neural network technology. GCP's Speech-to-Text can translate streaming audio in real time and can be set to support standard sampling frequencies for phones, video, or voice commands/search. Google's API supports 120 languages and can identify what language is spoken from a selection of as many as four languages. You can identify up to 5,000 words or phrases that pertain to your organization, like brand or stakeholder names. Google's technology can automatically capitalize names and places and format numbers into addresses, dates, phone numbers, and currencies. Video transcription can add punctuation, and the speaker diarization feature can differentiate among several speakers in a conference. Noise cancellation is included, and for some languages you can filter out inappropriate language. Supported encodings include FLAC, AMR, PCMU, and Linear-16. Billing is time based.

Progent can assist you to decide which of your applications are suited for Google Cloud and can show you how to make your legacy apps cloud compatible. Progent has experience helping clients evaluate migrating to Google Cloud SQL, using Google Dataproc for on-prem Hadoop, adopting Google Cloud Kubernetes Engine as a virtualization substitute, and deploying MongoDB Atlas on GCP vs. on-premises MongoDB. Progent can deliver as-needed remote consulting expertise for short-term jobs to help you quickly resolve stubborn technical hurdles or Progent can provide comprehensive project management consulting services to make sure your GCP integration initiative is successfully completed on time and within budget.

Some of most common technical issues organizations run into when integrating with GCP or other public cloud platform is reconfiguring firewalls and VPN tunnels to provide users with easy but secure access to cloud resources. Progent offers the services of Cisco-certified CCIE network infrastructure consultants and firewall specialists for security gateways from major vendors such as Cisco, Palo Alto Networks, Check Point, SonicWall, and Fortinet to assist you to set up or debug firewalls for accessing GCP. To support mobile computing, Progent's iPhone and iPad management consultants and Android integration consultants can assist you to configure and manage secure mobile endpoints for your Google Cloud users. Progent can work in conjunction with your internal technical team and Google's support engineers to resolve Google Cloud connectivity problems rapidly and economically.

Popular online consulting services provided by Progent to help businesses integrate their networks with GCP include:

• Review hybrid system plan for Google Compute Engine Virtual Machines and GCP Cloud Storage
• Create and verify VM images for Windows or Linux
• Configure, integrate and troubleshoot VPN tunnels for access to Google Cloud
• Plan configuration solutions for firewalls from Cisco, Palo Alto Networks, Barracuda, WatchGuard, and Fortinet and others
• Configure and troubleshoot mobile devices
• Create and implement policies based on leading practices
• Resolve IP addressing issues
• Design cost-effective allocation of GCP Cloud Storage
• Tune query performance on Cloud SQL
• Automate license management
• Resolve certificate issues

Additional public cloud platforms supported by Progent include:

Progent's Azure integration experts can assist you with every phase of Azure cloud integration such as needs analysis, prerequisites evaluation, solution architecture, pre-production testing, deployment, automated management, performance tuning, software license management, disaster recovery preparedness, security policy enforcement, and regulatory compliance validation. Progent can assist your IT staff to configure and debug firewalls and VPN connections so that your users can securely connect to Azure services, and Progent's Microsoft-certified consultants can help you integrate critical Microsoft platforms to run in the cloud including Microsoft Windows Server, Exchange, SQL and SharePoint. Progent can also assist you to create a hybrid ecosystem that seamlessly integrates physical datacenters with Azure-based services.

Microsoft supports seamless hybrid networks that combine Office 365 and local installations of Exchange. This allows you to have specific Exchange mailboxes hosted at your on-premises datacenter or private cloud and other mailboxes resident on Office 365. Progent's Microsoft-certified Exchange consulting team can assist your organization with any facet of planning, integrating and debugging your hybrid Office 365 solution. Progent's Exchange specialists can provide as-needed expertise to help you resolve challenging technical problems and also offer comprehensive project management outsourcing to ensure your hybrid Office 365 solution is carried out on schedule and on budget. For details about Progent's online consulting services for hybrid Office 365 and on-premises Exchange environments, see Exchange Online integration with on-premises Exchange.

Progent's Office and Office 365 consultants can assist companies to incorporate Office desktop and Microsoft Office 365 applications such as Office Excel, Office Word, PowerPoint, Microsoft Outlook, Access, Project and Publisher into a seamless productivity solution that provides quick return on investment and enables better business results. Progent can help your company to integrate Microsoft Office or Office 365 applications with one another and with other core Microsoft platforms including SharePoint, Microsoft Exchange Server and SQL Server running locally or in the cloud. Progent's consultants can also help you to resolve compatibility issues with various releases of Office and can provide customized online Office and Office 365 training to individuals and groups.

Progent's Amazon AWS cloud planning and integration consultants offer cost-effective online support to assist businesses to access Amazon Web Services (AWS) cloud services such as Elastic Compute Cloud (EC2) for virtual server hosting, Amazon S3 for expandable cloud storage, and Glacier for value-priced long-term archiving. Progent can assist you with every phase of Amazon AWS integration including requirements analysis, preparedness assessment, system design, pilot testing, deployment, administration, performance tuning, licensing management, disaster recovery mechanisms, and security and compliance. Progent offers advanced expertise with firewall configuration and VPN connections and can help you create cloud-based or hybrid ecosystems that efficiently incorporate Amazon AWS resources. Progent can provide occasional expertise or Progent can provide project management outsourcing to help you move efficiently to the Amazon AWS cloud.

Amazon Marketplace Web Service is an integrated library of APIs that enables Amazon sellers to improve the efficiency of their operations by automating key sales activities including listings, orders, shipments, fulfillment, and finances. By tapping into Amazon's vast online ecosystem and automating their sales, vendors can expand their market, reduce their cost of sales, improve reaction time to customers, and increase their bottom line. Progent's Amazon Marketplace Web Service consultants can work with your development staff and provide programming, workflow integration, project management support, and mentoring so you can cut development time and expedite your ROI.

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