Cloud Integration Consulting

Google Cloud Platform (GCP) is a popular set of cloud services that provides Infrastructure-as-a-Service and Platform-as-a-Service products. GCP's penetration in the public cloud market trails only Amazon AWS and Microsoft Azure. Like these competitors, Google Cloud utilizes the same extensive network infrastructure that supports its core online applications. In Google's case, these apps include Google Search as well as YouTube. The GCB cloud portfolio has over 100 services that cover processing, data storage, database management, networking, analytics, Big Data, machine learning, artificial intelligence, access management, cybersecurity, Internet of Things, and unified tools.

Progent has experience helping businesses of all sizes to design, deploy, tune, administer, and troubleshoot IT ecosystems that use various network models including on-prem data centers, private clouds, one or multiple public clouds, or a hybrid combination of local and cloud-based infrastructure. Progent can provide quick online or onsite access to top-tier consultants to assist you to evaluate the potential benefits and drawbacks of different network architectures and compare the services and cost of Google Cloud vs. alternative cloud offerings.

Progent's certified Microsoft, Linux, and Cisco consultants can assist you to integrate your existing network resources with the Google Cloud Platform, and Progent's database management consultants can show you how to make your key applications cloud ready so they can take full advantage of GCP services. Progent can assist you to deploy VMs on Google Cloud Compute Engine, design a cost-effective storage solution with Google Cloud Storage services, and simplify identity management with Google Cloud Identity. Progent can also help you to utilize GCP's tools to manage and track your Google Cloud ecosystem so it consistently delivers maximum return on investment.

Popular Services Available for the Google Cloud
Google Cloud Platform offers over Infrastructure-as-a-Service and Platform-as-a-Service services addressing nearly all facets of information technology including processing, data storage, database management, networking, administration, security, web, mobile computing, and development. GCP services are offered by subscription. Like other public cloud services, you are charged for the resources you use. Important Google Cloud 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, comparable to Amazon EC2 or Azure Virtual Machines. Compute Engine virtual machines have transparent access to Google Cloud block storage and state-of-the-art infrastructure. Google Cloud Compute Engine offers three classes of virtual machines in your choice of standard or custom sizes. GCP's N2 type VM is affordably priced and designed for common applications such as web hosting, business applications, and databases. The C2 type virtual machine provides up to 60 virtual CPUs for processor-intensive applications like electronic computer-aided design (ECAD) and simulations. Google Cloud's M2 class VM includes as much as 11.5 TB of RAM for RAM-intensive apps such as in-memory databases or in-depth analytics. Google's sole-tenant node option provides a physical Compute Engine server dedicated to your exclusive use.

Key benefits of the Google Cloud Compute Engine include live VM migration, which keeps virtual machines on line even while undergoing system maintenance, and preemptible virtual machines, low-cost virtual machine compute instances which continue for a max of 24 hours and are designed for executing batch jobs that can be paused and resumed intermittently without impacting operations.

Additional available benefits for Google Compute Engine include:

• Always-encrypted local SSD block storage for high speed and data security
• GPU accelerators that can be included with virtual machine instances for processor-intense applications such as machine learning and 3D graphics
• Global load balancing for maximizing performance and availability at low cost
• Google Kubernetes Engine for managing Docker containers on Compute Engine virtual machines

Google Cloud Storage is object storage that can scale to exabytes of data. All data held in GCP Cloud Storage are organized in containers called buckets. Google Cloud provides four types of cloud storage, differentiated and priced based on the object's expected longevity and its busy/dormant ratio. As you progress through Google's storage types from Standard to Archive, access costs increase, at-rest costs decrease, and required minimum storage duration increases. Google Cloud's storage classes make it possible to control expenses by planning the appropriate cost/performance balance for your environment, and Google Cloud's Object Life Cycle Management feature allows you to automate the progression of storage objects from hot to cold types over time. All storage classes share worldwide accessibility, unlimited storage (but a size limit of 5 TB for any given object, no minimum object size, low latency, optional geo-redundancy, and a common set of security and management tools. A single API applies to all storage types.

Standard Storage is Google Cloud's default type and is intended for objects used frequently or stored only for short periods. There is no minimum storage duration. To get the highest speed and least network usage charges, Standard Storage objects should reside in the same geographical location as the virtual machine instances or the container clusters that interact with the data. Standard Storage delivers the highest average availability across regions, dual-regions, and multi-regions. Nearline Storage is a low cost storage class designed for data accessed only occasionally, ideally once per month or less. Examples of suitable use cases are periodic backup and archiving. At-rest pricing is less than with Google Cloud's Standard Storage, but access costs more, availability is marginally lower, and duration is a minimum of one month.

Coldline Storage provides rock bottom storage costs for at-rest data and is intended for scenarios where data are accessed less than once a quarter. Minimum storage duration is three months, availability is slightly less than with Google Cloud's Standard and Nearline Storage types, and access costs are relatively high. Google's Archive Storage, which features the least at-rest storage costs but has a minimum duration of one year, is the best storage service for data kept exclusively for backup or archive scenarios. Access pricing for Archive Storage is the most of any Google Cloud storage type.

Cloud Storage Encryption
Google Cloud Storage always encrypts stored data on the server end before writing it to disk. In addition to this routine encryption process, you can select other options to encrypt your data. GCP offers two server-side encryption options that cause objects to be encrypted after making it to Google Cloud Storage but before the data is written to disk. The Customer-supplied encryption keys enables you to create and control your own encryption keys. The Customer-managed encryption keys option enables you to create and control your encryption keys using Google's Cloud Key Management Service. Both these server-side encryption services provide an extra level of encryption over and above Google's default Cloud Storage encryption service.

In case you perform client-side encryption before sending data to Google Cloud Storage, your encrypted data will also be subject to server-side encryption.

Google Cloud Identity and Access Management (IAM) is Google's centralized system for controlling access to resources and assigning permissions for users and services to access network resources for a specified duration. Examples of GCP resources are Compute Engine virtual machine instances and Google Cloud Storage buckets. Unified and consistent tools give admins the ability to manage access permissions for all services 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 unnecessary resources.

With Google 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 gain access to whatever resources the roles provide. As an example of Cloud Identity and Access Management's role granularity, the Google Cloud Pub/Sub service can be accessed under a variety of permissions depending on whether a user or group has been assigned the role of Owner, Editor, Viewer, Publisher, or Subscriber.

Google 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, refine them as appropriate for a specific project, and tune them further for a specific resource. You can assign access policies to individual 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 access rights is provided by permitting admins to factor in contextual attributes like device security status, IP address, resource type, and time. You can control access rights via the GUI interface of Google's web-based Cloud Console tool, via programming by using Google Cloud IAM methods, or through Google's gcloud CLI tool. Cloud IAM automatically creates a complete audit trail to simplify compliance.

Cloud Identity and Access Management is included without additional cost to all Google Cloud Platform customers.

Google Kubernetes Engine (GKE is a Docker container service for running containerized apps. Kubernetes was originally created by Google to automate 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 applications.

Google Kubernetes Engine is powered by Google's Container-Optimized OS and runs Certified Kubernetes, ensuring workload portability to other Kubernetes platforms spanning cloud and on-premises networks. To streamline development, prebuilt open-source deployment templates for enterprise-grade apps are offered on Google Cloud Marketplace.

The Migrate for Anthos tool, available for free with GKE, enables you to move and convert your workloads easily from your existing environment into Google Kubernetes Engine containers. These workloads can include physical servers and virtual machines located onsite, in Google's Compute Engine, or in third-party clouds. GKE supports pod and cluster autoscaling for continuous analysis of the processor and memory usage of pods and for dynamically adjusting processor and memory requests across node pools.

Other features of GKE include preemptible virtual machines, persistent disks, always-encrypted local solid-state drive (SSD) block storage, global load balancing to maximize performance and uptime, compatibility with both Windows Server and Linux nodes, the ability to run stateless serverless containers with the GCP Cloud Run service, and usage metering for granular insight into Kubernetes clusters.

Google Kubernetes Engine is compliant with HIPAA and PCI DSS 3.1. For stronger security, GKE Sandbox provides an additional level of protection between containerized Google Kubernetes Engine workloads. GKE clusters provide integrated support for Kubernetes Network Policy to filter traffic by applying pod-level firewall security policies. Private clusters in GKE can be confined to a private or public device with access limited to distinct addresses.

Google Kubernetes Engine is priced based on 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 software developers, even without machine learning experience, to integrate Google's advanced AI technology into their applications. Essential capabilities cover sight, language, and conversation. By using Google's APIs, you can access Google's pre-trained models rather than having to hassle with developing your own datasets from scratch and training and testing your own models. As Google's catalog of pre-trained models expands, you can quickly add state-of-the-art AI technology to your applications. In addition, Google AutoML products give you the tools required to train, validate and deploy your own domain-specific machine learning models. You can use any Google AI Building Block individually or in combination with other AI Building Blocks depending on your requirements.

For advanced imaging, Google Cloud AI Building Blocks include the AutoML Vision and Vision API products that allow you to extract useful intelligence from image libraries. Both products include REST and RPC APIs and allow your app to discern objects and their location within the image. AutoML Vision simplifies training for your home-grown machine learning (ML) models by providing an intuitive graphical interface. Once you optimize your models for accuracy, latency and size, you can export them to the Google Cloud or to a variety of edge devices.

Google Cloud's Vision API offers integration with Google's out-of-the-box models. Developers can rapidly classify images via Google's collections of expertly trained labels. Google Cloud's Vision API uses OCR technology to detect text, in over 50 languages, contained anywhere within images. Used in conjunction with Google's Document Understanding AI technology, you can benefit from the same ML technology that powers Google Search to derive useful information from masses of unstructured documents. You can detect web objects and pages, isolate a face from other objects and detect facial attributes, and recognize brand logos and famous landmarks. You can also recognize adult or violent content within images.

Google Cloud's AutoML Video Intelligence and Video Intelligence API services, which offer a similarly wide array of capabilities as Google's Vision products, make it simpler to derive information from video files.

Language Products
Language is Google's wheelhouse, and Google's stack of AI Building Blocks predictably includes a potent suite of products. Google Cloud language products include:

• Cloud Translation API
  This service enables you to enrich web sites and programs with real-time translation features powered by Google’s pre-trained neural machine translation technology. Google GCP provides a Basic and an Advanced version of the Translation API. Both options are based on Google's pre-trained, generalized model and feature automatic language detection, an integrated REST API, seamless HTML support, and the ability to translate between over 100 language pairs. The Advanced version of Google Cloud Translation API adds a customizable glossary to reflect your company's branding in translated text, batch translation support in Google Cloud Storage, the ability to utilize (but not create) custom Google AutoML Translation models, and a built-in gRPC API. The Cloud Translation service charges per character.
• AutoML Translation
  This machine learning tool allows developers to create a custom translation model by training it with your own dataset. The dataset consists of matching pairs of sentences in the original and target languages. Google AutoML Translation applies statistical analysis to the items from your dataset to train the model, validates it, and scores its accuracy. After you assess the results of your model, you can modify your dataset and train a new model repeatedly until you are happy with the outcome. You can build your own translation models in more than 50 language pairs. Costs for using AutoML Translation are calculated based on the hours of training required and the number of characters you include for translation.
• Cloud Natural Language API
  Google's Natural Language API uses a suite of proven ML models to help you to understand the meaning and structure of documents. A content classification model identifies content categories in a document, like architecture, investing, or sports; an entity analysis model identifies and tags common known entities referred to in the document, like product, company, or athlete); a sentiment analysis model evaluates the author's attitude expressed in the document and the strength of conviction; an entity sentiment analysis model combines entity analysis and sentiment analysis by identifying known entities in a document and determining the attitude and the strength of emotion demonstrated towards those entities; a syntactic analysis model exposes structural organization by deconstructing text into sentences and words, which are then broken down into parts of speech and roots. Each API identifies the language of the text being analyzed if it is not declared. Google'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's AutoML Natural Language product allows you to create and refine your own Natural Language models for classification, entity extraction, and sentiment analysis. For example, a custom sentiment analysis model designed by an airline could learn that a reference to lost baggage in social media counts as a negative rather than positive sentiment. Google Cloud's AutoML Natural Language service makes it easy to build a dataset, utilize the dataset to train a model, test the model, and tweak the dataset until your model is ready for production.
• Dialogflow
  GCP's Dialogflow is a platform that uses the natural language technology behind Google Assistant to enable you to create a conversational interface so your product or service can interact with your customers by voice. You can port this technology to a mobile app, website, interactive voice response system, or other application that could be enhanced with natural voice interaction. GCP's Dialogflow service can understand text or voice inputs and can respond through text or synthetic voice. Dialogflow can detect a user’s intent and extract pre-defined entities including time, date, and numbers. You can teach 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. Professional editions of Dialogflow are billed according to audio/phone time and the number of characters and queries.
• Cloud Text-to-Speech
  Google's Text-to-Speech API converts text or Speech Synthesis Markup Language to high-quality, natural-sounding speech in more than 30 languages and more than 180 voices. Google's Cloud Text-to-Speech platform supports any app or device capable of sending REST or gRPC requests. Devices can be phones, PCs, iPads or tablets, and IoT devices like cars, TVs, and speakers. Supported audio formats include mp3, Linear16, and Ogg Opus. You can use SSML tags in order to insert pauses, numbers, date and time formatting, etc. Cloud Text-to-Speech is billed based on million characters of text submitted.
• Speech-to-Text
  GCP's Speech-to-Text API provides 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 set to handle various sampling rates for phones, video, or voice commands/search. The API supports 120 languages and can recognize what language is being used from a list of up to four languages. You can identify a maximum of 5,000 words or phrases that pertain to your business, like product or stakeholder names. Google's 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 differentiate among multiple speakers in a conference. Noise cancellation is included, and for some languages you have the ability to filter out inappropriate expressions. Supported encoding formats include FLAC, AMR, PCMU, and Linear-16. Billing is time based.

Progent can help you to decide which of your applications are suited for Google Cloud and can help you make your legacy applications cloud ready. Progent has helped clients evaluate running Google Cloud SQL, using Google Cloud Dataproc for on-premises Hadoop, adopting Google Kubernetes Engine as a virtualization replacement, and deploying MongoDB Atlas on Google Cloud vs. local MongoDB. Progent can provide as-needed remote consulting expertise for short-term jobs to help you rapidly overcome stubborn technical challenges or Progent can deliver end-to-end project management consulting services to ensure your GCP integration initiative is successfully completed on time and within budget.

Some of most common technical issues organizations run into when integrating with Google Cloud or other public cloud platform is reconfiguring firewalls and VPN tunnels to provide users with easy but protected access to cloud services. Progent offers the expertise of Cisco-certified CCIE network infrastructure consultants and firewall specialists for security gateways from major suppliers like Cisco, Palo Alto Networks, Check Point, WatchGuard, and Fortinet to help you to configure or debug firewalls for connecting to Google Cloud Platform. To support BYOD computing, Progent's iPhone and iPad management consultants and Android integration experts can help you to configure and manage protected mobile endpoints for your GCP users. Progent can work in conjunction with your internal IT staff and Google's support engineers to mitigate Google Cloud integration issues quickly and affordably.

Popular remote consulting expertise offered by Progent to help 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 virtual machine images for Windows or Linux
• Set up, deploy and debug VPN tunnels for connectivity with Google Cloud
• Design configuration solutions for firewalls from Cisco, Palo Alto Networks, Check Point, SonicWall, and Fortinet and others
• Configure and troubleshoot mobile endpoints
• Create and implement policies following leading practices
• Fix IP addressing problems
• Define cost-effective plan for GCP Cloud Storage
• Optimize query efficiency on Google Cloud SQL
• Automate software license management
• Resolve certificate problems

Additional public clouds supported by Progent include:

Progent's Microsoft Azure integration consultants can help you with any stage of Microsoft Azure integration including needs analysis, prerequisites evaluation, solution architecture, pilot testing, implementation, centralized management, performance tuning, software license management, disaster recovery preparedness, security policy enforcement, and compliance assessment. Progent can help you to set up and troubleshoot firewall appliances and VPN tunnels so that your clients can safely connect to Azure-based services, and Progent's Microsoft-certified consulting experts can help you integrate key Microsoft platforms to run in the cloud including Microsoft Windows Server, Exchange Server, SQL and Skype for Business. Progent can also assist your organization to create a hybrid ecosystem that transparently integrates on-premises datacenters with Azure-based services.

Microsoft supports seamless hybrid ecosystems that combine Office 365 Exchange Online and on-premises Exchange deployments. This permits you to have some Exchange mailboxes hosted on your corporate datacenter or private cloud and other mailboxes hosted by Office 365. Progent's Microsoft-certified Exchange consulting team can help your organization with any facet of designing, integrating and troubleshooting your hybrid Office 365 solution. Progent's Exchange specialists can deliver as-needed support to help you resolve challenging technical issues and also offer comprehensive project management outsourcing or co-sourcing to make sure your hybrid Office 365 initiative is successfully completed on schedule and on budget. To learn more about Progent's consulting support for integrating Office 365 and on-premises Exchange systems, go to Office 365 Exchange Online integration solutions with on-premises Exchange.

Progent's certified Office and Office 365 experts can assist companies to incorporate Microsoft Office desktop and Microsoft Office 365 apps including Office Excel, Office Word, PowerPoint, Outlook, Microsoft Access, Visio and Publisher into a seamless solution that provides fast ROI and enables better business outcomes. Progent can assist you to integrate Microsoft Office or Office 365 apps with one another and with other key Microsoft technologies such as SharePoint Server, Exchange Server and Microsoft SQL Server deployed locally or hosted in the cloud. Progent's consultants can also assist you to fix compatibility problems with different releases of Microsoft Office and can provide customized online Office and Office 365 training to individuals and teams.

Progent's Amazon AWS planning and integration consultants offer cost-effective online consulting to help companies to integrate Amazon Web Services (AWS) cloud services including Amazon EC2 for virtual machine hosting, Amazon Simple Storage Service (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 needs analysis, preparedness evaluation, system design and review, testing, deployment, administration, performance optimization, software license management, disaster recovery solutions, and security. Progent can provide advanced expertise with firewall configuration and VPN access and can help you deploy cloud-centric or hybrid ecosystems that seamlessly integrate Amazon AWS resources. Progent offers occasional expertise or Progent can provide comprehensive project management outsourcing or co-sourcing to help you migrate efficiently to the Amazon AWS cloud.

Amazon Marketplace Web Service is a collection of APIs that enables Amazon sellers to improve the efficiency of their business processes by automating key sales functions including listings, orders, shipments, fulfillment, and reports. By leveraging Amazon's vast online selling environment and automating their sales processes, merchants can broaden their market, lower their cost of sales, accelerate reaction time to customers, and increase their bottom line. Progent's Amazon Marketplace Web Service (Amazon MWS) developers can collaborate with your development staff and provide application programming, workflow integration, project management support, and training so you can shorten development time and get to market quickly.

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

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