Cloud Integration Expertise

Google Cloud Platform (GCP) is a leading suite of cloud computing services that offers Infrastructure-as-a-Service and Platform-as-a-Service products. GCP's share of the public cloud sector is behind only Amazon AWS and Microsoft Azure. As with vendors, Google Cloud utilizes the same extensive infrastructure that hosts its most popular applications. In Google's case, these include Google Search and YouTube. The GCB cloud stack contains more than 100 services that cover processing, data storage, database management, networking, business analytics, Big Data, machine learning, AI, access management, cybersecurity, Internet of Things, and centralized tools.

Progent offers expertise helping organizations of all sizes to plan, deploy, test, manage, and maintain IT ecosystems based on various network architectures including on-premises data centers, private clouds, one or multiple public clouds, or a hybrid combination of onsite and cloud infrastructure. Progent offers quick remote or onsite access to top-tier experts to help you to assess the potential benefits and limitations of different network models and understand the services and pricing structure of Google Cloud Platform vs. other public cloud vendors.

Progent's Microsoft, Linux, and Cisco consultants can assist you to expand your existing network resources with the Google Cloud Platform, and Progent's database management consultants can show you how to make your business-critical applications cloud ready so they can benefit fully from GCP products and services. Progent can help you to set up virtual machines on Google Cloud Compute Engine, design an efficient storage solution with Google Cloud Storage services, and simplify identity management with Google Cloud Identity. Progent can also help you to use GCP's unified tools to administer and monitor your GCP Cloud environment so it continually provides top business value.

Major Services Offered for the Google Cloud
Google Cloud has more than 100 Infrastructure-as-a-Service and Platform-as-a-Service services covering nearly all areas of IT including compute, data storage, database management, networking, system management, cybersecurity, web, mobility, and application development. Google Cloud services are offered on a subscription basis. Like other public cloud services, you are charged for what you use. Popular GCP products and services for which Progent can provide expert consulting and debugging include:

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

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

Other key benefits for GCP Compute Engine include:

• Always-encrypted local solid-state drive 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 visualizations
• Global load balancing for optimizing speed and availability at minimal cost
• Google Kubernetes Engine for managing and orchestrating Docker containers on Compute Engine VMs

Google Cloud Storage provides object storage that scales to exabytes of data. Data placed in GCP Cloud Storage are organized in containers called buckets. GCP provides four types of cloud storage, differentiated and priced based on the object's anticipated longevity and its access/at-rest ratio. As you progress through the storage classes from Standard to Archive storage, access expense increase, at-rest costs go down, and minimum storage duration increases. GCP's storage classes allow you to manage costs by designing the optimal cost/performance profile for your network, and Google's Object Life Cycle Management tool allows you to automate the progression of storage objects from high-access to low-access types over time. All types feature worldwide accessibility, unlimited storage (but a size limit of 5 TB for individual objects, no minimum object size, low latency, optional geo-redundancy, and a shared suite of security and management tools. A single API works with all Google Cloud Storage classes.

Standard Storage is Google Cloud's default type and is optimized for so-called "hot" storage accessed often or stored only briefly. There is no minimum storage time. For the highest speed and least network fees, Standard Storage data should be kept in the same geographical region as the virtual machine instances or the container clusters that interact with the data. Standard Storage delivers the top average availability for any regional distribution scheme. Nearline Storage is a low cost storage type designed for data accessed infrequently, ideally once per month or less. Examples of appropriate use scenarios are monthly backup and archiving. At-rest costs are lower than with GCP's Standard Storage, but data access costs more, availability is marginally lower, and duration is a minimum of one month.

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

Cloud Storage Encryption
Google Cloud Storage always encrypts stored data on the server side prior to placing it on disk. In addition to this routine encryption, you can choose more ways to encrypt your data. There are two supplemental server-side encryption services that cause objects to be encrypted after arriving at Google Cloud Storage but before being written to disk. The Customer-supplied encryption keys allows you to create and manage your own encryption keys. Google Cloud's Customer-managed encryption keys alternative allows you to generate and manage your encryption keys using Google's Cloud Key Management Service. Both these server-side encryption options create an extra layer of encryption over and above GCP's standard Cloud Storage encryption.

If you perform client-side encryption before transporting your data to GCP Cloud Storage, your encrypted data will also be subject to Google's server-side encryption.

Google Cloud Identity and Access Management (IAM) is Google's unified system for controlling access to network resources and assigning authority for users and services to use network resources for a specified duration. Examples of Google Cloud resources are Compute Engine instances and Cloud Storage buckets. Centralized tools give administrators control over access permissions for all services available within GCP. Cloud IAM features fine granularity in designing policies to assign groups and users rights to use only required resources while preventing access to non-essential resources.

With Cloud IAM, policies are composed of roles; roles are based on permissions; and permissions are associated with resources. Users or groups are added to policies, and by means of policy they are given access to the specific resources the roles give them. As an example of Cloud Identity and Access Management's role granularity, the Cloud Pub/Sub service can be accessed with a range of usage right 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 hierarchical, flowing downward from the organization to projects and lastly to resources. You can establish organization-wide policies, tune them for a given project, and tune them even more for a specific resource. You can assign policies to specific resources, to a project, or at the top organizational level. Policies assigned to an organization flow down to projects in the organization and then to resources in those projects.

Further refinement in managing resource access rights is offered by permitting admins to factor in context such as device security status, IP address, resource class, and time. You can control access rights via the graphical interface of the web-based Cloud Console tool, through programming by using Cloud IAM methods, or through the gcloud CLI tool. Cloud IAM automatically creates a full audit trail to facilitate regulatory compliance.

Cloud IAM is included at no extra cost to all GCP customers.

Google Kubernetes Engine is a Docker container service for orchestrating and managing containerized applications. Kubernetes was initially developed by Google to automate Docker container orchestration and was made available as open source in 2014. Since then Kubernetes has grown to be the most popular solution for managing containerized applications.

Google Kubernetes Engine is built on Google's Container-Optimized OS and runs Certified Kubernetes, ensuring workload compatibility with other Kubernetes platforms spanning cloud and on-premises environments. To streamline development, prebuilt open-source deployment templates for commercial apps are offered on Google Cloud Marketplace.

The Migrate for Anthos service, offered at no cost with GKE, enables you to move and convert your workloads easily from your existing environment 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 ongoing analysis of the processor and RAM usage of pods and for dynamically tuning CPU and memory requests across node pools.

Other features of Google Kubernetes Engine include preemptible virtual machines, persistent storage, always-encrypted local solid-state drive block storage, global load balancing to optimize performance and uptime, 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 insight into your Kubernetes clusters.

GKE complies with HIPAA and PCI DSS 3.1. standards. For stronger security, GKE Sandbox delivers an additional layer 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 security policies. Private clusters in Google Kubernetes Engine can be limited 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. Use of GCP Compute Engine resources is billed on a per-second basis with a one-minute minimum usage cost.

Cloud AI Building Blocks allow software developers, even without machine learning experience, to incorporate Google's advanced AI capabilities into their applications. Essential services cover vision, language, and speech. By using Google's APIs, you can take advantage of Google's out-of-the-box AI models and avoid having to deal with developing your own datasets and training and testing your own models. As Google's catalog of pre-trained models grows in sophistication and size, you can immediately add leading-edge AI technology to your applications. In addition, Google AutoML products provide the tools you need to train, test and deploy your custom domain-specific machine learning models. You can use any Google Cloud AI Building Block individually or in any 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 allow you to derive insights from your images. Both products use REST and RPC APIs and allow your application to detect 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 send them to the Google GCP Cloud or to a variety of edge devices.

Google Cloud's Vision API offers programmatic access to Google's pre-trained machine learning models. Developers can rapidly classify images using Google's collections of pre-trained labels. Vision API uses OCR tools to identify text, in more than 50 languages, embedded anywhere within images. Combined with Google's Document Understanding AI feature, you can use the same ML technology behind Google Search to extract useful insights from masses of free-form documents. You can discern web objects and pages, isolate a face from other objects and notice facial characteristics, and identify brand logos and famous landmarks. You can also detect mature or violent content in images.

Google GCP's AutoML Video Intelligence and Video Intelligence API services, which offer a comparably extensive array of capabilities as the Vision products, make it simpler to extract information from videos.

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

• Cloud Translation API
  This cloud service allows developers to enrich web sites and applications with real-time translation features based on Google's pre-trained neural machine translation technology. Google GCP offers a Basic and an Advanced version of Google's Translation API. Both options are based on Google's pre-trained, general-purpose model and feature automatic language detection, a REST API, transparent HTML support, and the ability to translate between over 100 language pairs. The Advanced option of Google Cloud Translation API adds a customizable glossary to preserve your branding in translated text, batch translation capability in Google Cloud Storage, the ability to incorporate custom Google AutoML Translation models, and an integrated gRPC open source API. The Cloud Translation service is priced per character.
• AutoML Translation
  This ML platform allows developers to create a custom translation model by training it with your own dataset. The custom dataset consists of matching pairs of sentences in the original and target languages. Google AutoML Translation applies statistical analysis to the pairs from your custom dataset to train the model, validates it, and scores its performance. After you assess the results of your model, you can tune your dataset and train a new model repeatedly until you are satisfied with the results. You can build custom translation models in more than fifty language pairs. Costs for using AutoML Translation are based on the hours of training required and the volume of characters you submit for translation.
• Cloud Natural Language API
  Google Cloud's Natural Language API uses a library of standard machine learning models to assist you to understand the themes and structure of documents. A content classification model discerns content categories in a document, like civil engineering, finance, or entertainment; an entity analysis model finds and tags common known entities referred to within the document, such as product, organization, or public figure); a sentiment analysis model assesses the author's positive or negative attitude expressed in the document and the magnitude of emotion; an entity sentiment analysis model integrates entity and sentiment analysis by identifying familiar entities within a document and determining the positive or negative attitude and the magnitude of feeling demonstrated in relation to those entities; a syntactic analysis model extracts structural organization by breaking text up into sentences and tokens (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 involves JSON requests and responses. Text to be analyzed can be included in the JSON request or resident in Google Cloud Storage.
• AutoML Natural Language
  Google Cloud's AutoML Natural Language product enables you to build and tune your own Natural Language models for classification, entity extraction, and sentiment analysis. For example, a custom sentiment analysis model created by an airline could be taught that a reference to lost luggage in social media counts as a negative sentiment. GCP's AutoML Natural Language product makes it simple to build a custom dataset, utilize the dataset to train a model, test the model, and refine your dataset until your model is ready to deploy.
• Dialogflow
  GCP's Dialogflow is a a development suite that uses the natural language technology behind Google Assistant to help you to create a conversational interface so your product or service can interact with your users by voice. You can port this capability to a smartphone app, website, interactive voice response system, or any other scenario that could be enhanced with natural voice interaction. Google Cloud's Dialogflow platform can analyze text or audio inputs and can respond via text or synthetic speech. Dialogflow can recognize a user's intent and extract pre-defined entities including time, date, and numbers. You can train your agent to recognize your custom entity types by submitting small sample datasets, or you can use more than 40 out-of-the-box agents as templates. Professional editions of Dialogflow are billed according to audio/phone time and the volume of characters and queries.
• Cloud Text-to-Speech
  Google Cloud's Text-to-Speech API transforms text or Speech Synthesis Markup Language to high-fidelity, natural-seeming speech in more than 30 languages and more than 180 voices. Google's Cloud Text-to-Speech service works with any app or device able to send REST or gRPC requests. This includes smartphones, PCs, tablets, and IoT devices such as cars, televisions, and audio speakers. Supported audio formats include mp3, Linear16, and Ogg Opus. You can include SSML tags to insert pauses, numbers, date and time formatting, etc. Cloud Text-to-Speech is billed per million characters of text processed.
• Speech-to-Text
  Google's Speech-to-Text API provides access to advanced automatic speech recognition (ASR) technology powered by Google's constantly refined deep-learning neural network algorithms. GCP's Speech-to-Text can translate streaming audio in real time and can be set to handle various sampling frequencies for phones, video, or voice commands and search. The API works with 120 languages and can recognize what language is spoken from a list of up to four. You can specify up to 5,000 words or phrases that pertain to your business, like brand or partner 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 differentiate among several speakers in a conference. Noise cancellation is built in, and for certain languages you can block inappropriate expressions. Supported encoding formats include FLAC, AMR, PCMU, and Linear-16. Cost is time based.

Progent can assist you to determine which of your applications are suited for GCP 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 local Hadoop, adopting Google Kubernetes Engine as a virtualization replacement, and deploying MongoDB Atlas on Google Cloud vs. on-premises MongoDB. Progent can provide as-needed online consulting expertise for short-term jobs to help you quickly overcome occasional technical hurdles or Progent can provide end-to-end project management outsourcing services to ensure your Google Cloud integration program is carried out on time and within budget.

Some of most frequently encountered technical issues businesses face when migrating to GCP or other public cloud platform is setting up firewalls and VPN connections to give users convenient but protected access to cloud services. Progent can provide the expertise of Cisco-certified CCIE network infrastructure consultants and firewall experts for security appliances from major suppliers such as Cisco, Palo Alto Networks, Barracuda, WatchGuard, and Fortinet to assist you to configure or troubleshoot firewalls for connecting to GCP. To support BYOD computing, Progent's iPhone and iPad technology consultants and Google Android integration consultants can assist you to integrate and administer protected mobile devices for your GCP users. Progent can work in conjunction with your internal technical team and Google's support engineers to mitigate Google Cloud connectivity issues quickly and affordably.

Popular remote consulting services provided by Progent to assist organizations expand their networks with GCP include:

• Check hybrid system plan for Google Compute Engine Virtual Machines and Google Cloud Storage
• Build and verify virtual machine images for Windows or Linux
• Set up, deploy and troubleshoot VPN tunnels for access to GCP
• Design configuration solutions for firewalls from Cisco, Palo Alto Networks, Barracuda, WatchGuard, and Fortinet and others
• Configure and troubleshoot mobile endpoints
• Define and implement security policies based on best practices
• Resolve IP addressing issues
• Design cost-effective allocation of GCP Cloud Storage
• Tune query performance on Google Cloud SQL
• Simplify software license management
• Fix certificate problems

Additional leading clouds supported by Progent include:

Progent's Microsoft Azure planning and integration experts can help you with any stage of Microsoft Azure migration including requirements definition, prerequisites assessment, solution design, pre-production testing, deployment, automated administration, performance tuning, license management, disaster recovery preparedness, security planning, and regulatory compliance assessment. Progent can help your IT staff to set up and troubleshoot firewall appliances and VPN connections so that your clients can securely connect to Azure resources, and Progent's Microsoft-certified consulting experts can assist you set up key Microsoft platforms to work in the cloud including Windows Server, Exchange Server, SQL and SharePoint. Progent can also help your organization to create a hybrid environment that transparently integrates on-premises datacenters with Azure services.

Microsoft has made a strong effort to enable transparent hybrid networks that integrate Microsoft 365 and on-premises Exchange. This allows you to have certain Exchange mailboxes located at your corporate datacenter or private cloud and other mailboxes hosted by Microsoft 365. Progent's Microsoft-certified Exchange consultants can help you with any phase of planning, integrating and debugging your hybrid Microsoft 365/Exchange network. Progent's Exchange consultants can deliver occasional expertise to help you resolve challenging technical bottlenecks and also can provide extensive project management outsourcing or co-sourcing to make sure your hybrid Exchange solution is completed on time and on budget. For details about Progent's online consulting services for integrating Microsoft 365 Exchange and on-premises Exchange systems, refer to Microsoft 365 Exchange Online integration with on-premises Exchange.

Progent's certified Microsoft Office and Microsoft 365 consultants can help companies of any size to integrate Microsoft Office desktop and Microsoft 365 apps such as Office Excel, Office Word, PowerPoint, Microsoft Outlook, Microsoft Access, Visio and OneNote into a cohesive solution that provides fast ROI and enables improved business outcomes. Progent can help you to integrate Microsoft Office or Microsoft 365 apps with each other and with additional key Microsoft technologies such as SharePoint Server, Microsoft Exchange Server and SQL Server running on-premises or in the cloud. Progent's consultants can also help you to resolve compatibility problems with different versions of Microsoft Office desktop and can provide customized online Office and Microsoft 365 training to individuals and teams.

Progent's Amazon AWS integration consultants can provide cost-effective online support to assist businesses of any size to integrate Amazon Web Services (AWS) cloud services such as Amazon EC2 for virtual server hosting, Amazon S3 for expandable high-performance storage, and Glacier for value-priced long-term archiving. Progent can assist you with every aspect of Amazon AWS integration including requirements analysis, preparedness assessment, system design, pilot testing, deployment, administration, performance optimization, software license management, backup/restore mechanisms, and security and compliance. Progent offers advanced expertise with firewall configuration and VPN technology and can show you how to deploy all-cloud or hybrid environments that seamlessly integrate Amazon AWS services. Progent offers as-needed expertise or Progent can provide comprehensive project management outsourcing or co-sourcing services to help you migrate efficiently to the Amazon AWS platform.

Amazon Marketplace Web Service (Amazon MWS) 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, payments, inbound and outbound fulfillment, and finances. By leveraging Amazon's extensive online selling environment and automating their sales processes, vendors can expand their market, lower their operating costs, accelerate response time to customers, and increase their bottom line. Progent's Amazon Marketplace Web Service (Amazon MWS) consultants can collaborate with your development team and provide programming, workflow integration, project management support, and mentoring so you can cut development time and costs and get to market quickly.

Contact Progent for Google Cloud Platform Integration Expertise
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.