Quanta Services is the leading specialty contractor with the largest and highly-skilled trained workforce in North America. It provides fully-integrated solutions for the electric power

pipeline industrial and telecommunications industries the company’s geographic footprint which includes North America Latin America and Australia.

It’s network of companies ensures world-class execution with local delivery and has over 40,000 employees.

“The exciting thing about Backstory is it allows us to land massive amounts of data from all of our different security tools and then Chronicle worries about how to correlate and aggregate this information for us. We can then focus on the highest priority threats.”

Richard Breaux, Manager Security Operations Quanta Services

Because Quanta Services’ customers provide energy and telecommunications to their customers, they have world-class cybersecurity requirements.

“We must ensure that Quanta leads the industry given the fact that our business is building the core infrastructure that powers people’s lives. It’s crucial that we meet their cybersecurity requirements,” says James Stinson, VP-IT, Quanta Services.

To support this goal Quanta implemented a number of security tools that generate terabytes of security telemetry. Over time, however, these systems generated an information overload for the company’s limited pool of qualified security resources.

“Our logging tools also couldn’t keep up with the rapidly growing information. With limited resources we need to focus our security analysts time on high quality work instead of digging through mountains of data,” says Stinson.

They achieve this by implementing Backstory and Chronicle, which is on Google Cloud.

“The exciting thing about Backstory is it allows us to land massive amounts of data from all of our different security tools and then Chronicle worries about how to correlate and aggregate this information for us. We can then focus on the highest priority threats,” says Richard Breaux, Manager Security Operations Quanta Services.

As a result, the company’s security  team spends less time getting to the core information they need to address these incidents.

“What used to take us 15 minutes or more, we can now accomplish in seconds,” says Breaux.

About FNM Group

FNM Group is the main private, integrated group in transportation and mobility in the North of Italy.

Industries: Other

Location: Italy

About Innext

Innext, one of Italy’s select Google Cloud Premier Partners, helps companies turn objectives into tangible actions, and change into a competitive advantage.

Industries:

Location:

Founded in 1877, the FNM Group is Italy’s second largest railway company, operating in the Lombardy region. With 700,000 passengers a day, the core business remains with railway operations, but in recent years the FNM Group has redefined itself as a mobility service provider rather than just a public transport operator, with transport solutions like car-sharing platforms in parts of the country disconnected from the main railway lines. As part of this evolution, in 2016, FNM Group initiated a new strategy to overhaul its technology and build a platform that could support its ambitious, new direction.

“We needed an IT system that could rapidly adapt to the new market requirements we are planning to address,” says Augusto de Castro, Director of Human Resources, Organization, and IT at FNM Group. “To achieve this goal, we decided to modernize our information system and move to a cloud-based infrastructure, so we started testing various solutions. For us, the best came from Google.”

Collaborative office productivity

Since 2005, the FNM Group had used SAP Business Suite for its platform, using on-premises servers to manage its technology and database solutions. By 2016, when the group expanded its horizons, the on-premises infrastructure was showing its age and limitations. In addition, FNM Group office productivity tools limited workers’ mobility and flexibility. The company decided that a cloud-based solution was the most economical and effective infrastructure for its new innovation-focused strategy, but also wanted to continue the high-quality service it received from SAP.

In April 2017, FNM Group teamed up with Innext, a leading Italian consultancy and Google Cloud Premier Partner, to help transition to the cloud. After taking the time to assess specific needs at FNM Group, Innext supported the company’s decision to start the project with a migration to G Suite, replacing the existing email and office productivity platform. With help from Innext, FNM Group provided its workers with new tools such as Gmail, cloud-based storage on Google Drive, and fast, effective collaboration with Google Hangouts. As well as technical help, Innext brought a whole change management program designed to help FMN workers take full advantage of the new platform. “One of our top goals in any project is the adoption of the G Suite platform,” says Andrea Servili, Co-founder and Partner at Innext.

Cloud-based enterprise solutions with SAP HANA and SAP S/4HANA

While defining the G Suite migration, Innext and FNM Group began looking for an infrastructure solution. The timing was perfect. Earlier in the year, Google announced that SAP HANA and SAP S/4HANA, the latest software from SAP, would be able to run on Google Cloud Platform (GCP). Running on Google Compute Engine instances, Google Cloud Storage for backups, and Google Virtual Private Cloud as a networking solution, FNM Group can continue to use the enterprise platform of its choice along with all the advantages of Google cloud technology. By July, 2018, FNM Group plans to have fully migrated to SAP HANA and SAP S/4HANA on GCP and have its 1,200 employees using G Suite.

“SAP HANA and SAP S/4HANA on Google Cloud Platform and G Suite will make our employees much more mobile,” says Augusto. “They can access the system through a web browser if they have to, so they’re not tied to a local physical interface.”

Building a platform to last

With Innext and SAP HANA and SAP S/4HANA on GCP, FNM Group is building an enterprise infrastructure that can handle the demands of its traditional public transport operations and adapt to the company’s more innovative activities, such as car-sharing or energy management. By the time the migration is complete in 2018, FNM Group will save on infrastructure costs by only paying for the resources it uses with flexible pricing from Google. G Suite lets the company’s workers stay mobile and effective, and with Google Compute Engine, FNM Group can easily scale its infrastructure up or down to meet whatever challenges it faces in the future. Meanwhile, Google Cloud Storage helps ensure that FNM Group will have a highly secure, reliable backup solution. Once the migration is complete, FNM Group can start exploring other ways in which Google can help its business, especially with data analytic products like Google BigQuery or Google Cloud AI machine learning tools. Whatever the challenge, FNM Group knows that it can rely on Innext and Google to provide the right solution.

“Our main priority is to shut down our on-premises infrastructure and take advantage of the benefits of the cloud,” says Augusto. “Google Cloud Platform and SAP HANA and SAP S/4HANA will help us reduce our maintenance costs and improve our flexibility. I think we will spend less time continually upgrading our infrastructure and more time improving our productivity.”

Gone are the days when technology was relegated to the sidelines of a business, only considered essential for industries and professionals directly dealing with it. Today, it is not just a value-add, but an integral part of every enterprise’s operations and ultimately, its success. This has wrought many changes in the way we work, the most noteworthy of which is creating the necessity for every executive – not just the CIO & CTO – to familiarise themselves with the technologies of the future.

Among these is cloud computing, which is essential to doing business in the 21^st century. As the IT infrastructure needs of enterprises grow, and we inch closer to true mobility, it’s no surprise that cloud adoption is increasing by leaps and bounds. Unfortunately, too many C-suite executives dismiss cloud computing as being outside of their area of expertise. And while ignoring the technology aspect may have been possible for CEOs and CFOs in the past, it has now infiltrated every aspect of work, and arguably life itself. This makes it essential for executives across different functions and departments to familiarise themselves with at least the very basics of up-and-coming innovations.

One myth that has followed cloud computing is that it is a one-size-fits-all solution that businesses can merely install and use for storage. And while cookie-cutter solutions do exist, they end up doing more harm than good in the long term. To avoid this pitfall, it’s important for enterprises to understand the range of offerings at their disposal, and pick the one that most closely aligns with their needs.

Most people associate cloud deployment with subscribing to a third-party cloud service provider, which owns and manages all the resources that a firm might require. Known as the public cloud, this is the most popular option, especially for small and medium businesses that cannot bear the cost of IT infrastructure. Cost-effectiveness isn’t the only upside of this technology, though, since public clouds offer the added benefits of increased security, greater scalability, maximum uptime and ease of setting up.

Though the public cloud is the most widely used, it’s far from the only option that a business has. Enterprises seeking an added degree of customisation might find private cloud solutions to their liking. These offer an added layer of privacy, which may be mandated by the industry or jurisdiction that they operate in. Moreover, private clouds can allow access even in cases where geography or connectivity is unreliable. One of the factors that has held people back from switching to the private cloud has been the fact that they might need to buy and maintain the requisite infrastructure. In such cases, the Virtual Private Cloud (VPC) lets businesses tap into resources stored on a public cloud, within an isolated environment, with more granular control over virtual networks.

A fourth solution, known as the hybrid cloud, also offers the best of two worlds by utilising resources that are on-prem as well as on the public cloud. It is ideal for companies that already have money invested in IT infrastructure, but still want to make the most of the emerging technology. It can also serve as a stepping stone for ventures that are looking to make the switch, but have their reservations about the public cloud.

Each of these offerings comes with its own set of advantages and disadvantages. The key lies in evaluating your needs against the options at your disposal, and making sure that the two align. Only then will you be able to reap all the rewards of cloud implementation.

At Google Cloud, our customers are at the forefront of digital transformation—launching entirely new businesses and products built in the cloud, redefining entire industries with data and artificial intelligence, delivering innovative new consumer experiences, or committing to sustainable new ways of doing business.

We’re committed to our customers’ success, and over the past two years we’ve invested significantly in providing ongoing and integrated support through our customer care portfolio, including launching new Premium and Mission Critical Support offerings that allow us to monitor, prevent, and mitigate impacts quickly, while delivering the fastest response times in the industry.

Today, I’m proud to unveil several new resources and offerings for our customers, including a new Custom AI Solutions practice, new Global Delivery Centers, expanded Executive Briefing Centers, and new leaders to help continue to drive our organization forward.

Helping businesses innovate with a new Custom AI Solutions practice

We are investing in services and offerings to help our customers innovate and drive innovative change to business processes, culture, and customer experiences with Google Cloud products and services. Artificial intelligence (AI) and machine learning (ML) technologies are foundational for many such digital transformations, and to help customers create real business value with these technologies, we’re excited to launch a Custom AI offering to address our customers’ most critical innovation needs. 

AI and ML technologies are foundational to digital transformations, yet they are not “one size fits all.” Each customers’ problems and opportunities are unique; a rideshare company will use AI differently than a brick and mortar retailer, or a healthcare company, or an insurance firm. To help organizations deploy AI and ML more effectively, we’re launching a new Custom AI Solutions practice, offering customers custom-built AI and ML solutions built into Vertex AI; access to Google’s engineering expertise; and predictable, subscription-based pricing. 

Our teams are already partnering closely with early customers to build and deploy custom AI solutions. For instance, USAA, the large North American insurer, is using Google Cloud ML to process near-real-time damage estimates based on digital images to create a streamlined operations experience.

Learn more about our Custom AI Solutions practice offering here, and how we work together with our customers here. To get in touch, please contact our sales team.

Launching new Global Delivery Centers

Our drive to digitally transform our customers’ businesses is often manifested through our Global Delivery Centers, which expand our professional consulting and emerging practices capabilities available to customers and partners around the world.

The teams at our Global Delivery Centers help customers get up-and-running on Google Cloud quickly and cost effectively, and consult with customers to rapidly build capacity in areas like data analytics, hybrid and multi-cloud, artificial intelligence, and machine learning. More importantly, they help customers successfully execute projects in support of their most mission-critical business objectives. Critically, these centers also help our global partner ecosystem quickly ramp their Google Cloud practices, and get fast, expert consultation for their customers too.

In 2022, we aim to triple the size of our Global Delivery Center teams in Argentina, Poland, and India. In addition, we’ll invest in building deep Google Cloud talent in Mexico and Portugal, furthering our commitment to the industry’s best expert consultation for customers and partners around the world.

Expanding our Executive Briefing Centers footprint

In addition to our Global Delivery Centers, we’re also pleased to expand our resources and facilities that enable digital and face-to-face meetings and working sessions with our customers. This year, we will launch four new Executive Briefing Centers, located on Google Cloud campuses in London, Paris, Singapore, and Munich. 

These centers provide an opportunity to listen to our customers, share the best of Google Cloud’s solutions, and inspire digital transformation, in conversations facilitated by Google Cloud leadership, engineers, and industry experts. By bringing this experience to our customers in-region we can foster deeper partnerships and develop cloud solutions that meet their requirements for security, privacy, and digital sovereignty without compromising on functionality or innovation. 

Adding new leadership to enable customer success

Finally, I’m excited to welcome two new leaders to Google Cloud on the Customer Experience team, who will help scale our Delivery Centers and deliver exceptional experiences for our customers.

Heading our Global Delivery Center experience is Sunil Rao. Sunil comes to Google Cloud from Accenture, where he spent 18-plus years working with large technology customers across many industry verticals and managed large global teams in Accenture Advanced Technology Center. Sunil will also lead our Technical Onboarding Center, which helps businesses around the world get up to speed with technologies that are critical to understanding customer and business process contexts, and delivering great experiences.

Additionally, Lee Moore is joining Google Cloud to lead Customer Experience in North America. Lee spent nearly 30 years at Accenture in various leadership positions, including services integration for complex problem-solving, product development across a number of industry verticals, and building long-term customer relationships.

You’ll be hearing much more from us in the coming months, as we build out even more powerful and effective cloud-based services and offerings, work with customers to deliver new analytics- and AI-based tools and services, and work with our growing list of partners to help ensure customer success, across the globe.

Picking the right database for your application is not easy. The choice depends heavily on your use case—transactional processing, analytical processing, in-memory database, and so on—but it also depends on other factors. This post covers the different database options available within Google Cloud across relational (SQL) and non-relational (NoSQL) databases and explains which use cases are best suited for each database option. 

Relational databases 

In relational databases information is stored in tables, rows and columns, which typically works best for structured data. As a result they are used for applications in which the structure of the data does not change often. SQL (Structured Query Language) is used when interacting with most relational databases. They offer ACID consistency mode for the data, which means:

• Atomic: All operations in a transaction succeed or the operation is rolled back.
• Consistent: On the completion of a transaction, the database is structurally sound.
• Isolated: Transactions do not contend with one another. Contentious access to data is moderated by the database so that transactions appear to run sequentially.
• Durable: The results of applying a transaction are permanent, even in the presence of failures.

Because of these properties, relational databases are used in applications that require high accuracy and for transactional queries such as financial and retail transactions. For example: In banking when a customer makes a funds transfer request, you want to make sure the transaction is possible and it actually happens on the most up-to-date account balance, in this case an error or resubmit request is likely fine.

There are three relational database options in Google Cloud: Cloud SQL, Cloud Spanner, and Bare Metal Solution.

Cloud SQL: Provides managed MySQL, PostgreSQL and SQL Server databases on Google Cloud. It reduces maintenance cost and automates database provisioning, storage capacity management, back ups, and out-of-the-box high availability and disaster recovery/failover. For these reasons it is best for general-purpose web frameworks, CRM, ERP, SaaS and e-commerce applications.

Cloud Spanner: Cloud Spanner is an enterprise-grade, globally-distributed, and strongly-consistent database that offers up to 99.999% availability, built specifically to combine the benefits of relational database structure with non-relational horizontal scale. It is a unique database that combines ACID transactions, SQL queries, and relational structure with the scalability that you typically associate with non-relational or NoSQL databases. As a result, Spanner is best used for applications such as gaming, payment solutions, global financial ledgers, retail banking and inventory management that require ability to scale limitlessly with strong-consistency and high-availability. 

Bare Metal Solution: Provides hardware to run specialized workloads with low latency on Google Cloud. This is specifically useful if there is an Oracle database that you want to lift and shift into Google Cloud. This enables data center retirements and paves a path to modernize legacy applications. 

Non-relational databases

Non-relational databases (or NoSQL databases) store compex, unstructured data in a non-tabular form such as documents. Non-relational databases are often used when large quantities of complex and diverse data need to be organized. Unlike relational databases, they perform faster because a query doesn’t have to access several tables to deliver an answer, making them ideal for storing data that may change frequently or for applications that handle many different kinds of data. 

For example, an apparel store might have a database in which shirts have their own document containing all of their information, including size, brand, and color with room for adding more parameters later such as sleeve size, collars, and so on.

Qualities that make NoSQL databases fast:

• Eventual consistency: stores usually exhibit consistency at some later point (e.g., lazily at read time)
• Horizontal scaling, usually using hashed distributions
• Typically, they are optimized for a specific workload pattern (i.e., key-value, graph, wide-column)
• Typically, they don’t support cross shard transactions or flexible isolation modes.

Because of these properties, non-relational databases are used in applications that require large scale, reliability, availability, and frequent data changes.They can easily scale horizontally by adding more servers, unlike some relational databases, which scale vertically by increasing the machine size as the data grows. Although, some relations databases such as Cloud Spanner support scale-out and strict consistency.

Non-relational databases can store a variety of unstructured data such as documents, key-value, graphs, wide columns, and more. Here are your non-relational database options in Google Cloud: 

• Document databases: Store information as documents (in formats such as JSON and XML). For example: Firestore
• Key-value stores: Group associated data in collections with records that are identified with unique keys for easy retrieval. Key-value stores have just enough structure to mirror the value of relational databases while still preserving the benefits of NoSQL. For example: Datastore, Bigtable, Memorystore
• In-memory database: Purpose-built database that relies primarily on memory for data storage. These are designed to attain minimal response time by eliminating the need to access disks. They are ideal for applications that require microsecond response times and can have large spikes in traffic. For example: Memorystore
• Wide-column databases: Use the tabular format but allow a wide variance in how data is named and formatted in each row, even in the same table. They have some basic structure while preserving a lot of flexibility. For example: Bigtable
• Graph databases: Use graph structures to define the relationships between stored data points; useful for identifying patterns in unstructured and semi-structured information. For example: JanusGraph

There are three non-relational databases in Google Cloud:

• Firestore: Is a serverless document database which scales on demand and acts as a backend-as-a-service. It is DBaaS that increases the speed of building applications. It is perfect for all general purpose uses cases such as ecommerce, gaming, IoT and real time dashboards. With Firestore users can interact with and collaborate on live and offline data making it great for real-time application and mobile apps.  
• Cloud Bigtable: Cloud Bigtable is a sparsely populated table that can scale to billions of rows and thousands of columns, enabling you to store terabytes or even petabytes of data. It is ideal for storing very large amounts of single-keyed data with very low latency. It supports high read and write throughput at sub-millisecond latency, and it is an ideal data source for MapReduce operations. It also supports the open-source HBase API standard to easily integrate with the Apache ecosystem including HBase, Beam, Hadoop and Spark along with Google Cloud ecosystem.
• Memorystore: Memorystore is a fully managed in-memory data store service for Redis and Memcached at Google Cloud. It is best for in-memory and transient data stores and automates the complex tasks of provisioning, replication, failover, and patching so you can spend more time coding. Because it offers extremely low latency and high performance, Memorystore is great for web and mobile, gaming, leaderboard, social, chat, and news feed applications.

Conclusion

Choosing a relational or a non-relational database largely depends on the use case. Broadly, if your application requires ACID transactions and your data structure is not going to change much, select a relational database. 

In Google Cloud use Cloud SQL for any general-purpose SQL database and Cloud Spanner for large-scale globally scalable, strongly consistent use cases. In general, if your data structure may change later and if scale and availability is a bigger requirement than consistency then a non-relational database is a preferable choice.  Google Cloud offers Firestore, Memorystore, and Cloud Bigtable to support a variety of use cases across the document, key-value, and wide column database spectrum.

For more comparison resources on each database check out the overview. For more hands-on experience with Bigtable, check out our on-demand training here and learn about migrating databases to managed services check out this whitepaper.  

https://youtube.com/watch?v=2TZXSnCTd7E%3Fenablejsapi%3D1%26

For more #GCPSketchnote, follow the GitHub repo. For similar cloud content follow me on Twitter @pvergadia and keep an eye out on thecloudgirl.dev.