Cloud Integration Support

Google Cloud Platform (GCP) is a popular suite of cloud computing services that offers Infrastructure-as-a-Service and Platform-as-a-Service features. Google Cloud's share of the public cloud market trails only Amazon Web Services (AWS) and Microsoft Azure. Like these competitors, Google Cloud utilizes the same massive infrastructure that hosts its most popular online applications. In Google's case, these include Google Search and YouTube. The GCB cloud stack contains over 100 products that cover compute, data storage, database management, networking, business analytics, Big Data, machine learning, AI, access management, cybersecurity, Internet of Things, and unified management.

Progent offers expertise assisting businesses of all sizes to design, configure, tune, manage, and troubleshoot IT ecosystems based on a variety of network architectures including on-prem data centers, private clouds, one or multiple public clouds, or a hybrid mix of local and cloud-based infrastructure. Progent offers fast online or onsite access to top-tier consultants who can assist you to assess the advantages and limitations of possible network architectures and compare the services and pricing structure of Google Cloud Platform vs. alternative public cloud offerings.

Progent's Microsoft, Linux, and Cisco consultants can help you to integrate your current network infrastructure with the Google Cloud Platform, and Progent's database management experts can help make your key applications cloud ready so they can benefit fully from Google Cloud products and services. Progent can assist you to deploy virtual machines on Google Cloud Compute Engine, design an efficient storage solution using GCP Cloud Storage services, and streamline access management with GCP Cloud Identity. Progent can also help you to use GCP's tools to manage and track your Google Cloud ecosystem so it consistently provides top return on investment.

Popular Services Available for the Google Cloud
Google Cloud offers more than 100 Infrastructure-as-a-Service and Platform-as-a-Service services covering nearly all facets of IT including processing, storage, database management, networking, system management, security, web, mobile computing, and application development. GCP services are available by subscription. Like other public cloud services, you are charged for the resources you use. Popular Google Cloud products and services for which Progent offers expert consulting and debugging include:

Compute Engine is a 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 state-of-the-art infrastructure. GCP Compute Engine offers three basic classes of virtual machines in your choice of pre-defined or custom machine sizes. Google's N2 type VM is affordably priced and designed for common applications such as web hosting, business apps, and databases. The C2 type virtual machine provides up to 60 virtual CPUs for compute-intensive apps such as ECAD and simulations. Google Cloud's M2 class virtual machine offers as much as 11.5 TB of RAM for RAM-intensive applications such as in-memory databases or time-critical analytics. Google's sole-tenant node option features a physical Compute Engine machine for your exclusive use.

Important features of the GCP Compute Engine include live VM migration, which lets you keep virtual machines running even during scheduled maintenance, and preemptible VMs, low-cost VM compute instances which continue for up to 24 hours and are designed for executing batch jobs that can be paused and resumed at any time without impacting operations.

Other key features for Google Cloud Compute Engine include:

• Always-encrypted local solid-state drive (SSD) block storage for enhanced speed and data security
• Graphics Processing Unit that can be included with virtual machine instances for processor-intense applications like machine learning and 3D visualizations
• Global load balancing for maximizing speed and availability at low cost
• Google Kubernetes Engine for orchestrating Docker containers on Compute Engine virtual machines

Google Cloud Storage is object storage that can scale to exabytes of data. All data placed in Google Cloud Storage are logically organized in containers called buckets. GCP offers four classes of cloud storage, differentiated and priced based on the object's expected longevity and its access/at-rest ratio. As you progress through the storage types from Standard to Archive, access expense go up, at-rest expense decrease, and minimum storage duration increases. Google's storage classes allow you to control expenses by designing the appropriate cost/performance balance for your environment, and Google's Object Life Cycle Management feature allows you to automate the migration of storage objects from hot to cold types over time. All storage types feature global accessibility, virtually unlimited scale (but a maximum size limit of 5 TB for individual objects, no minimum size, low latency, on-request geo-redundancy, and a shared suite of security and management utilities. A single API applies to all storage types.

Standard Storage is Google Cloud's default type and is intended for so-called "hot" storage accessed often or stored only briefly. There is no minimum storage time. To get the best speed and lowest network usage fees, Standard Storage objects should reside in the same geographical location as the virtual machine instances or the container clusters that use the objects. Standard Storage offers the top average uptime across regions, dual-regions, and multi-regions. Nearline Storage is a economical storage option designed for objects accessed infrequently, preferably no more than once per month. Examples of appropriate use scenarios are monthly backup and archiving. At-rest pricing is lower than with Google's Standard Storage, but data access costs more, availability is slightly less, and storage duration is at least one month.

Coldline Storage offers very low storage costs for dormant data and is designed for scenarios where data are accessed less than once a quarter. Minimum storage duration is three months, availability is slightly lower than with Google's Standard and Nearline Storage types, and data access costs are relatively high. GCP's Archive Storage, which features the least at-rest storage costs but has a minimum storage duration of one year, is the best storage service for objects kept only for backup or archive purposes. Data access pricing for Archive Storage is the highest of any GCP storage service.

Cloud Storage Encryption
Google Cloud Storage always encrypts stored data on the server side prior to writing it to disk. Added to this standard encryption process, you can choose more options to encrypt your data. There are two supplemental server-side encryption services that allow data to be encrypted after arriving at Google Cloud Storage but before being written to disk. Google Cloud'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 generate and manage your encryption keys via Google's Cloud Key Management Service. Both these server-side encryption services provide an extra level of encryption over and above Google's standard Cloud Storage encryption service.

If you use client-side encryption before 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 resources and assigning permissions for users and services to access resources for a specified period of time. Examples of GCP resources are Compute Engine instances and Google Cloud Storage buckets. Unified and consistent tools offer admins the ability to manage access rights for all services available within the Google Cloud Platform. Cloud Identity and Access Management offers fine granularity in designing policies to grant groups and users rights to use task-relevant resources while preventing access to non-essential resources.

With Google Cloud Identity and Access Management, policies are made up of roles; roles are composed of permissions; and permissions are assigned to resources. Users or groups are added to policies, and by means of policy they are given access to whatever resources the roles provide. As an example of Google Cloud IAM's role granularity, the Google Cloud Pub/Sub service can be accessed under a range of permissions depending on 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, flowing downward from the organization to projects and lastly to resources. You can define organization-wide policies, tune them for a given project, and tune them further for a given resource. You can assign policies to specific resources, to a project, or at the top organizational level. Policies you assign to an organization cascade down to projects within the organization and from there resources within projects.

Further flexibility in controlling resource permissions is offered by allowing administrators to include contextual attributes like device security status, IP address, resource type, and date/time. You can control permissions by using the graphical interface of the web-based Cloud Console, through automation by using Google Cloud IAM methods, or through the gcloud CLI tool. Cloud IAM automatically maintains a complete audit trail to simplify compliance.

Google Cloud Identity and Access Management is included at no additional cost to all Google Cloud customers.

Google Kubernetes Engine (GKE is a container service for running containerized apps. Kubernetes was initially created by Google to automate container orchestration and was offered as open source in 2014. Since that time Kubernetes has grown to be the most popular solution for managing containerized applications.

Google Kubernetes Engine is powered by Google's Container-Optimized OS and supports Certified Kubernetes, allowing workload compatibility with other Kubernetes platforms spanning cloud and local networks. To accelerate software development, prebuilt open-source deployment templates for commercial apps are available on Google Cloud Marketplace.

The Migrate for Anthos service, offered at no cost with Google Kubernetes Engine, enables you to migrate and port your workloads easily from your existing environment into Google Kubernetes Engine containers. These workloads can be physical servers and VMs situated onsite, in Google's Compute Engine, or in third-party clouds. Google Kubernetes Engine supports pod and cluster autoscaling for ongoing analysis of the processor and RAM usage of pods and for automatically tuning processor and RAM requests across multiple node pools.

Additional features of GKE include preemptible VMs, persistent storage, always-encrypted local solid-state drive (SSD) block storage, global load balancing to maximize performance and availability, 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 complies with HIPAA and PCI DSS 3.1. For enhanced security, GKE Sandbox provides an additional level of protection between containerized GKE workloads. Google Kubernetes Engine clusters provide native support for Kubernetes Network Policy to filter traffic via pod-level firewall security policies. Private clusters in GKE can be confined to a private or public endpoint accessible only to distinct address ranges.

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

Cloud AI Building Blocks enable software developers, even without machine learning experience, to incorporate Google's leading-edge AI technology into their applications. Core capabilities cover sight, language, and conversation. By using APIs, you can access Google's out-of-the-box AI models and avoid having to deal with developing your own datasets from scratch and training your own 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. In addition, Google Cloud AutoML products provide the utilities required to train, validate and deploy your custom domain-specific ML models. Developers can use any Google Cloud AI Building Block individually or in any combination with other AI tools according to your requirements.

For AI-enhanced imaging, Google Cloud AI Building Blocks include the AutoML Vision and Vision API services that help you to extract insights from image libraries. Both services use REST and RPC APIs and enable your app to discern objects and their location inside the image. AutoML Vision simplifies training for your custom machine learning (ML) models by offering an easy-to-use graphical interface. Once you tune your models for accuracy, speed and size, you can export them to the Google Cloud or to various edge devices.

Vision API offers programmatic access to Google's out-of-the-box models. You can quickly classify images using Google's extensive collections of predefined labels. Vision API uses OCR tools to identify text, in over 50 languages, embedded within images. Used in conjunction with Google's Document Understanding AI technology, 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 entities and pages, distinguish a face from other objects and detect facial attributes, and recognize 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 services, which provide a comparably extensive range of capabilities as the Vision products, make it simpler to mine value from video files.

Language Products
Language is Google's strong suit, and Google's stack of AI Building Blocks understandably includes a rich suite of products. Google GCP language products include:

• Cloud Translation API
  This service allows developers to enhance web sites and programs with real-time language translation features based on Google’s neural translation technology. Google Cloud provides a Basic and an Advanced release of the Translation API. Both options 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 version of Cloud Translation API adds an extensible glossary to reflect your company's branding in translated copy, batch translation support in GCP Cloud Storage, the ability to incorporate custom AutoML Translation models, and an integrated gRPC open source API. Google's Cloud Translation service charges per character.
• AutoML Translation
  This ML tool allows you to create 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 items from your custom 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 until you are satisfied with the results. You can create custom translation models in more than 50 language pairs. Pricing 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 pre-built ML models to help you to understand the themes and structure of documents. A content classification model discerns content categories within a document, like civil engineering, investing, or sports; an entity analysis model finds and labels common known entities referenced within the document, like country, company, or public figure); a sentiment analysis model evaluates the author's positive or negative attitude expressed in the document and the strength of passion; an entity sentiment analysis model integrates entity and sentiment analysis by detecting known entities within a document and estimating the attitude and the strength of emotion demonstrated in relation to those entities; a syntactic analysis model extracts structural information by deconstructing text into sentences and words, which are then parsed into parts of speech and roots. Each API identifies the language of the text being analyzed if it is not specified. The's Natural Language API is a REST API and uses JSON requests and responses. Text to be analyzed 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 your own Natural Language models for classification, entity extraction, and sentiment analysis. As an example, a sentiment analysis model designed by an airline could be taught that a mention of lost baggage in a tweet counts as a negative rather than positive sentiment. Google's AutoML Natural Language product makes it easy to create a dataset, use the dataset to train a model, test the resulting model, and refine the dataset until the model is ready to deploy.
• Dialogflow
  GCP's Dialogflow is a platform that uses the natural language understanding technology that powers Google Assistant to enable you to build a conversational interface so your product can interact with your users by voice. You can port this capability to a mobile app, website, voice response system, or other application that could be improved with natural voice conversation. Google Cloud's Dialogflow service can analyze text or voice inputs and can reply via text or synthetic speech. Dialogflow can detect a user’s intent and extract pre-defined entities like time, date, and numbers. You can train your Dialogflow agent to identify your custom entity types by providing small sample datasets, or you can use more than 40 tested agents as templates. Commercial versions of Dialogflow are billed based on audio/phone time and the volume of characters and queries.
• Cloud Text-to-Speech
  GCP's Text-to-Speech API transforms text or Speech Synthesis Markup Language (SSML) to high-quality, natural-seeming speech in more than 30 languages and more than 180 voices. Cloud Text-to-Speech service works with any application or device able to send REST or gRPC requests. This includes smartphones, PCs, tablets, and IoT devices like autos, televisions, and audio speakers. Accepted audio coding formats include mp3, Linear16, and Ogg Opus. You can use SSML tags to add pauses, numbers, calendar and time formatting, etc. Cloud Text-to-Speech is billed per million characters of text processed.
• Speech-to-Text
  GCP's Speech-to-Text API gives developers access to advanced automatic speech recognition (ASR) technology powered by Google's constantly evolving deep-learning neural network algorithms. Google Cloud'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 and search. The API works with 120 languages and can recognize what language is being used from a list of as many as four. You can identify a maximum of 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 speaker diarization technology can distinguish among multiple speakers in a conference. Noise cancellation is built in, and for certain languages you can filter out inappropriate language. Supported encodings include FLAC, AMR, PCMU, and Linear-16. Billing is time based.

Progent can assist your organization to decide which of your applications are appropriate for Google Cloud and can help you make your legacy applications cloud compatible. Progent has helped 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 on-demand online consulting expertise for short-term jobs to help you rapidly overcome stubborn technical challenges or Progent can provide end-to-end project management outsourcing services to ensure your Google Cloud integration initiative is successfully carried out on schedule and within budget.

Among the most common technical obstacles organizations face when migrating to Google Cloud or other public cloud is reconfiguring firewalls and VPN tunnels to give users convenient but protected access to cloud services. Progent offers the services of Cisco-certified CCIE network infrastructure engineers and firewall experts for security gateways from major suppliers such as Cisco, Palo Alto Networks, Barracuda, SonicWall, and Fortinet to help you to configure or troubleshoot firewalls for connecting to Google Cloud Platform. To support mobile computing, Progent's iPhone and iPad technology consultants and Android integration consultants can assist you to configure and manage secure mobile devices for your GCP users. Progent can work in concert with your internal IT staff and Google's support engineers to mitigate GCP connectivity issues quickly and economically.

Examples of remote consulting expertise offered by Progent to assist organizations expand their networks with Google Cloud include:

• Check hybrid system design for Google Compute Engine Virtual Machines and GCP Cloud Storage
• Build and verify VM images for Windows or Linux
• Set up, integrate and debug VPN tunnels for connectivity with Google Cloud
• Plan configuration solutions for firewalls from Cisco, Palo Alto Networks, Barracuda, SonicWall, and Fortinet and others
• Configure and troubleshoot mobile endpoints
• Create and implement policies based on leading practices
• Fix IP addressing problems
• Define cost-effective plan for GCP Cloud Storage
• Optimize query efficiency on Cloud SQL
• Simplify software license management
• Fix certificate problems

Other public cloud platforms supported by Progent include:

Progent's Azure cloud integration experts can help you with any stage of Microsoft Azure migration such as requirements definition, prerequisites assessment, system design, pilot testing, deployment, centralized administration, performance tuning, license controls, disaster recovery preparedness, security policy enforcement, and compliance validation. Progent can help you to set up and troubleshoot firewalls and VPN tunnels so that your users can safely access to Azure-based services, and Progent's Microsoft-certified consulting experts can help you set up critical Microsoft technologies to run in Azure including Microsoft Windows Server, Exchange, SQL and SharePoint. Progent can also help you to set up a hybrid environment that transparently combines physical datacenters with Azure resources.

Microsoft allows you to create seamless hybrid environments that combine Office 365 Exchange Online and on-premises Exchange deployments. This permits you to have specific mailboxes located on your on-premises datacenter and other mailboxes hosted by Office 365. Progent's Microsoft-certified Exchange consultants can assist your organization with any phase of designing, implementing and troubleshooting your hybrid Office 365/Exchange solution. Progent's Exchange specialists can deliver as-needed expertise to help you resolve stubborn technical problems and also can provide extensive project management outsourcing to make sure your hybrid Office 365 initiative is successfully completed on schedule and on budget. For more information about Progent's online consulting services for hybrid Office 365 and on-premises Exchange systems, visit Office 365 Exchange Online integration with on-premises Exchange.

Progent's certified Microsoft Office and Office 365 consultants can help businesses of any size to incorporate Office desktop and Office 365 applications such as Office Excel, Word, PowerPoint, Microsoft Outlook, Access, Project and OneNote into a cohesive solution that provides quick ROI and promotes better business outcomes. Progent can help your company to integrate Microsoft Office or Office 365 apps with one another and with additional core Microsoft technologies including SharePoint Server, Microsoft Exchange Server and SQL Server running on-premises or in the cloud. Progent's consultants can also assist you to fix compatibility problems with various releases of Office and can provide live online Office and Office 365 training to individual users and teams.

Progent's Amazon AWS cloud integration consultants offer cost-effective remote support to help companies of any size to integrate Amazon AWS cloud services such as Elastic Compute Cloud (EC2) for virtual machine hosting, Amazon Simple Storage Service (Amazon S3) for scalable cloud storage, and Amazon Glacier for low-cost archival storage. Progent can assist you with every aspect of Amazon AWS migration and troubleshooting including needs analysis, preparedness evaluation, architectural design, pilot testing, deployment, administration, performance optimization, licensing management, backup/restore solutions, and security and compliance. Progent offers advanced expertise with firewalls and VPN technology and can help you deploy cloud-based or hybrid environments that seamlessly incorporate Amazon AWS resources. Progent can provide occasional support or Progent can deliver comprehensive project management outsourcing or co-sourcing to help you move efficiently to the Amazon AWS cloud platform.

Amazon Marketplace Web Service is a library of APIs that enables Amazon sellers to streamline their business processes by automating key sales functions such as listings, orders, shipments, fulfillment, and reports. By tapping into Amazon's extensive online selling environment and automating their sales processes, vendors can expand their reach, lower their operating costs, accelerate reaction time to customers, and increase their profits. Progent's Amazon Marketplace Web Service (Amazon MWS) consultants can work with your development staff and provide application programming, workflow integration, project management support, and mentoring to help you shorten development time and expedite your ROI.

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