Morrisons is a large supermarket chain in the United Kingdom, headquartered in Bradford, West Yorkshire, England.

Eleven million customers trust Morrisons, a leading UK supermarket, to provide quality food at affordable prices each week. With 120,000 staff nationwide across more than 500 sites, good communication is crucial. G Suite helps Morrisons connect every member of their team affordably, whether they’re picking stock in a warehouse or serving customers in-store.

Morrisons used to print half a million sheets of paper every week and file them in over 3,000 filing cabinets in order to fulfill compliance requirements. Now, with collaboration in Docs and rapid information collection with Forms, they’ve reduced paperwork. Outside the office, staff has replaced clunky VPNs and outdated handheld devices with G Suite, which can work on any device. And with Google’s intuitive administrative tools, local managers can set up new accounts in three minutes instead of five to ten days.

Instead of shared logins, all employees have a G Suite account, and Google+ brings these colleagues from across the company together to share tips and advice. Morrisons also improves services based on customer feedback collected by shop floor staff that use apps on mobile devices.

Businesses of all sizes use G Suite to breakdown information barriers and increase employee collaboration. It’s been especially helpful for start-ups and for those who run their own businesses, where juggling multiple jobs—from operations to administration to accounting—is second nature.

For many of these businesses, G Suite helps them collaborate securely and free up time so that they can focus on what really matters: their customers. Below are how three businesses use G Suite to both scale and mobilize while keeping their customers top of mind.

MobileOne Keeps its Employees Mobile

Workers spend up to 8 hours per week searching for, or consolidating, information. When you sift through emails to find files or dig through folders to attach documents, that time adds up.

MobileOne experienced this firsthand.

The company, which operates more than 125 T-Mobile premium retail stores in the US, found that its employees were sinking unnecessary time in email going back-and-forth searching for files.

Its previous productivity tools made it difficult to collaborate, especially for remote employees, and tough to share the latest information, like growth and performance metrics, at an accelerated pace. With this in mind, MobileOne moved to G Suite.

Revel Stark, MobileOne’s Director of Recruiting and Marketing, was heading to the beach with his family one Sunday when his colleague sent an urgent request for a document from him. It took just seconds to access the requested document in the Google Drive mobile app and share it, rather than having to search through files on a laptop, or wait until Monday when he was back in the office.

In addition, real-time editing in Docs and Sheets allows MobileOne employees to streamline how they share and edit documents since it eliminates version control. The company now creates central repositories of information in Docs and Sheets, ensuring everyone is working with the most up-to-date information, saved securely in the cloud.

JBGoodwin Realtors Streamlines Business Processes to Create New Home Owners

As a real-estate company with multiple offices in Texas and clients across the country, JBGoodwin Realtors needed a secure productivity solution that powered real-time employee collaboration.

But it also looked to a solution to help reduce costly maintenance, archive information securely in the cloud, and open up opportunities to streamline business processes. The company turned to G Suite to help.

By moving to G Suite, JBGoodwin Realtors adopted a cloud-first strategy that improved its data security by catching phishing attempts before they reached employees, and as a result, helped reduce time spent on platform maintenance by 30 percent.

Because Gmail allows users to easily archive emails in the cloud, the company no longer needs to invest in hard drive space to save messages. Its employees can easily access emails securely on any device both online or offline. Plus, the company can rest assured that their information stays secure with the help of built-in phishing protections.

Finally, via resources in the G Suite Marketplace, JBGoodwin Realtors automated its manual processes by connecting G Suite data with its CRM and marketing tools, so that its realtors can focus on making valuable connections with potential clients instead of inputting data in multiple systems.

TrueCar Drove a Smooth Transition to G Suite 

More than 1.5 billion people use Gmail everyday. Since employees are often already comfortable with using Gmail in their personal lives, transitioning to using it at work is a smooth process.

This was crucial for TrueCar, an automotive resale marketplace that connects sellers with potential buyers (and arms them with pricing information). Minimal onboarding support and training was needed when implementing G Suite.

The team took advantage of G Suite’s User Interface customizations, which can be tailored to a user’s preference in Settings. For example, at TrueCar, admins customized their Calendar interface to be a side-by-side calendar view so they could easily see multiple schedules on a single screen.

With G Suite, there are many ways to customize your apps to help you stay productive.

Mindful Containers is a fictitious company that is creating containerized microservice applications. They need a fully managed compute environment for deploying and scaling serverless containerized microservices. So, they are considering Cloud Run. 

They are excited about Cloud Run because it abstracts away the cluster configuration, monitoring, and management so they can focus on building the features for their apps. Cloud Run is a fully-managed compute environment for deploying and scaling serverless containerized microservices.

What is Cloud Run?

Cloud Run is a fully-managed compute environment for deploying and scaling serverless HTTP containers without worrying about provisioning machines, configuring clusters, or autoscaling.

• No vendor lock-in – Because Cloud Run takes standard OCI containers and implements the standard Knative Serving API, you can easily port over your applications to on-premises or any other cloud environment. 
• Fast autoscaling – Microservices deployed in Cloud Run scale automatically based on the number of incoming requests, without you having to configure or manage a full-fledged Kubernetes cluster. Cloud Run scales to zero— that is, uses no resources—if there are no requests.
• Split traffic – Cloud Run enables you to split traffic between multiple revisions, so you can perform gradual rollouts such as canary deployments or blue/green deployments.
• Custom domains – You can set up custom domain mapping in Cloud Run and it will provision a TLS certificate for your domain. 
• Automatic redundancy – Cloud Run offers automatic redundancy so you don’t have to worry about creating multiple instances for high availability

How to use Cloud Run

With Cloud Run, you write your code in your favorite language and/or use a binary library of your choice. Then push it to Cloud Build to create a container build. With a single command—“gcloud run deploy”—you go from a container image to a fully managed web application that runs on a domain with a TLS certificate and auto-scales with requests.

How does Cloud Run work?

Cloud Run service can be invoked in the following ways:

HTTPS: You can send HTTPS requests to trigger a Cloud Run-hosted service. Note that all Cloud Run services have a stable HTTPS URL. Some use cases include: 

• Custom RESTful web API
• Private microservice
• HTTP middleware or reverse proxy for your web applications
• Prepackaged web application

gRPC: You can use gRPC to connect Cloud Run services with other services—for example, to provide simple, high-performance communication between internal microservices. gRPC is a good option when you: 

• Want to communicate between internal microservices
• Support high data loads (gRPC uses protocol buffers, which are up to seven times faster than REST calls)
• Need only a simple service definition you don’t want to write a full client library
• Use streaming gRPCs in your gRPC server to build more responsive applications and APIs

WebSockets: WebSockets applications are supported on Cloud Run with no additional configuration required. Potential use cases include any application that requires a streaming service, such as a chat application.

Trigger from Pub/Sub: You can use Pub/Sub to push messages to the endpoint of your Cloud Run service, where the messages are subsequently delivered to containers as HTTP requests. Possible use cases include:

• Transforming data after receiving an event upon a file upload to a Cloud Storage bucket
• Processing your Google Cloud operations suite logs with Cloud Run by exporting them to Pub/Sub
• Publishing and processing your own custom events from your Cloud Run services

Running services on a schedule: You can use Cloud Scheduler to securely trigger a Cloud Run service on a schedule. This is similar to using cron jobs. Possible use cases include:

• Performing backups on a regular basis
• Performing recurrent administration tasks, such as regenerating a sitemap or deleting old data, content, configurations, synchronizations, or revisions
• Generating bills or other documents

Executing asynchronous tasks: You can use Cloud Tasks to securely enqueue a task to be asynchronously processed by a Cloud Run service. Typical use cases include:

• Handling requests through unexpected production incidents
• Smoothing traffic spikes by delaying work that is not user-facing
• Reducing user response time by delegating slow background operations, such as database updates or batch processing, to be handled by another service, 
• Limiting the call rate to backend services like databases and third-party APIs

Events from Eventrac: You can trigger Cloud Run with events from more than 60 Google Cloud sources. For example:

• Use a Cloud Storage event (via Cloud Audit Logs) to trigger a data processing pipeline 
• Use a BigQuery event (via Cloud Audit Logs) to initiate downstream processing in Cloud Run each time a job is completed

How is Cloud Run different from Cloud Functions?

Cloud Run and Cloud Functions are both fully managed services that run on Google Cloud’s serverless infrastructure, auto-scale, and handle HTTP requests or events. They do, however, have some important differences:

• Cloud Functions lets you deploy snippets of code (functions) written in a limited set of programming languages, while Cloud Run lets you deploy container images using the programming language of your choice. 
• Cloud Run also supports the use of any tool or system library from your application; Cloud Functions does not let you use custom executables. 
• Cloud Run offers a longer request timeout duration of up to 60 minutes, while with Cloud Functions the requests timeout can be set as high as 9 mins. 
• Cloud Functions only sends one request at a time to each function instance, while by default Cloud Run is configured to send multiple concurrent requests on each container instance. This is helpful to improve latency and reduce costs if you’re expecting large volumes. 

Pricing

Cloud Run comes with a generous free tier and is pay per use, which means you only pay while a request is being handled on your container instance. If it is idle with no traffic, then you don’t pay anything.

Conclusion

After learning about the ease of set up, scalability, and management capabilities of Cloud Run the Mindful Containers team is using it to deploy stateless microservices. If you are interested in learning more, check out the documentation.https://www.youtube.com/embed/oR4btKLRdn4?enablejsapi=1&

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

Since its initial release in 1995, MySQL has not only been the de-facto database for many data storage needs, but has gathered much attention over the years as one of the most well-recognized databases around when it comes to Relational Database Management Systems and transactional data processing.

Any application in retail, e-commerce, or banking has likely had its fair share of business depending on a relational database for its transactional needs. Many of these applications are built on MySQL due to its flexibility, open source nature, and strong community support.

Whether in the context of a migration from a relational database (like MySQL or PostgreSQL) , migration from a NoSQL database (like Cassandra), or a green grass workload, many companies turn to Cloud Spanner seeking a high availability SLA (99.99% for regional instances and 99.999% for multi region instances),  unlimited scale,  and low operational overhead – no patching required, no maintenance or other planned downtimes, just to name a few benefits.

The tooling and open source ecosystem around Spanner has evolved and grown ever since the service was introduced. HarbourBridge is a part of this ecosystem, and it’s meant to help customers port their existing MySQL or PostgreSQL schema to a Cloud Spanner schema. 

Application Migration Tips

Despite helpful tools like HarbourBridge, database migrations are never trivial. Here are a few things to pay attention to when migrating from MySQL to Spanner, and how to update your application logic to address them.

Note – The following snippets use the PHP client for Cloud Spanner. A couple of the snippets reference a partial Magento port that our friends over at Searce have been working on. Once you understand the operations, you should be able to implement the same in any of the other languages that Cloud Spanner supports.

Cloud spanner enforces strict data types  

In a MySQL query, the value of an attribute can be referenced as either a string or an integer. Example:

• select * from catalog_eav_attribute where attribute_id = 46;
• select * from catalog_eav_attribute where attribute_id = “46”;

Both are valid and equivalent. 

In Cloud Spanner, the query will return an error if you try to reference an integer type by using a string representation.

Here is an example of a working query from Cloud Spanner:

• select * from catalog_eav_attribute where attribute_id = 46; — this will work
• Select * from catalog_eav_attribute where attribute_id = “46” — will fail, since we are supplying a string with “46” 

You may use a function like the following to assist you with such transformations.

  /**
    * Formats the SQL for Cloud Spanner
    * Example
    * Input SQL : <select statement> WHERE 
    *    (`product_id` = '340') ORDER BY position  ASC
    * Output SQL : <select statement> WHERE 
    *    (`product_id` = 340) ORDER BY position  ASC
    * In the above example integer 
    *`340` is sanitized by removing single quotes.
    * Sanitization is required since Cloud Spanner
    * has strict typing
    * @param string $sql
    * @return string $sql
    */
   public function sanitizeSql(string $sql)
   {
       if (preg_match_all("/('[^']*')/", $sql, $m)) {
           $matches = array_shift($m);
           for($i = 0; $i < count($matches); $i++) {
               $curr =  $matches[$i];
               $curr = filter_var($curr, 
                   FILTER_SANITIZE_NUMBER_INT);
               if (is_numeric($curr)) {
                   $sql = str_replace($matches[$i], 
                       $curr, $sql);
               }
           }
       }
       return $sql;
   }

Using sequences in primary keys is not a Spanner best practice

Cloud Spanner does not implement a sequence generator,  and it is not a Spanner best practice to use sequential IDs because doing so can cause hotspotting.

An alternative mechanism of generating a unique primary key is to use a UUID or any other similar mechanisms that result in non-sequential values. For more information, please refer to this article.

In order to convert all existing primary keys to a UUID pattern, you can change the schema using the snippet here

You may use this code snippet to modify the application code to generate the UUID for the auto increment. There are other ways to do this as well, such as using PHP built-in uniqid function.

  /**
    * Generate UUID.
    * @return string
    */
   public function getAutoIncrement()
   {
       if (function_exists('com_create_guid') === true) {
           return trim(com_create_guid(), '{}');
       }
       return sprintf('%04X%04X-%04X-%04X-%04X-%04X%04X%04X',
           mt_rand(0, 65535), mt_rand(0, 65535),
           mt_rand(0, 65535), mt_rand(16384, 20479), 
           mt_rand(32768, 49151),  mt_rand(0, 65535),
           mt_rand(0, 65535), mt_rand(0, 65535));   
   }

Implicit casting and the need for explicit casting of field data types 

Both MySQL and Cloud Spanner follow the SQL standard, hence much of the query syntax is the same. One notable difference is that the Cloud Spanner field types are implicitly cast to an appropriate data type out of the ones mentioned here. When implicit casting of the field type fails, Spanner returns a read error, so it would be safer to perform the casting to the appropriate type when issuing the SELECT statement.

Modify application code to cast to respective data type before execution of query.

  $con = $this->getSpannerConnection();
 /**
 * Cloud Spanner follows strict type so cast the columns appropriately
*/
$select = $con->addCast($select, "`t_d`.`value`", 'string');
$select = $con->addCast($select, "`t_s`.`value`", 'string');
$select = $con->addCast($select, "IF(t_s.value_id IS NULL, 
    t_d.value, t_s.value)", 'string');
$values = $con->fetchAll($select);

Modify the application code to cast the column to its respective type 

  /**
    * Cast the column with type
    * @param string $sql
    * @param string $col
    * @param string $type
    * @return string
    */
   public function addCast(string $sql,
       string $col, string $type)
   {
      $cast = "cast(".$col." as ".$type.")";
      return str_replace($col, $cast, $sql);
   }

Using interleaved tables to improve read performance

Cloud Spanner’s table interleaving is a great choice for many parent-child relationships where the child table’s primary key includes the parent table’s primary key columns. Interleaving ensures that child rows are collocated with their parent rows, which can significantly improve query performance.

Refer to the statements here for a few samples of creating interleaved tables. To learn more about table interleaving, visit the documentation.

Conclusion

Database migrations are complicated.  Hopefully, using HarbourBridge and the  list of tips in this article can make that task easier.  For additional tips, please take a look at this migration guide and read more about HarbourBridge.