Start your 2022 New Year’s resolutions by learning at no cost how to use Google Cloud with the following training opportunities:

30 day access to Google Cloud Skills Boost 

Register by January 31, 2022 and claim 30 days free access to Google Cloud Skills Boost to complete the Getting Started with Google Cloud learning path. 

Google Cloud Skills Boost is the definitive destination for skills development where you can personalize learning paths, track progress, and validate your newly-earned expertise with skill badges. 

The Getting Started with Google Cloud learning path will give you the opportunity to earn three skill badges after you complete hands-on labs and courses designed for aspiring cloud engineers and architects. It covers the fundamentals of Google Cloud including core infrastructure, big data and ML, writing gcloud commands, using Cloud Shell, deploying virtual machines, and running containerized applications on GKE.

Cloud OnBoard: half day training on getting started with Google Cloud fundamentals

Attend the Getting Started Cloud OnBoard on January 20 for a comprehensive Google Cloud orientation. Google Cloud experts will show you how to execute your compute, available storage options, how to secure your data, and available Google Cloud managed services. 

Cloud Study Jam: expert-guided hands-on lab

Google Cloud experts will walk you through a hands-on lab included in Google Cloud Skill Boost’s Getting Started with Google Cloud learning path when you join our Cloud Study Jam on January 27. Google Cloud experts will also answer questions live via chat during this event.

Reliably executing tasks on a schedule is critical for everything from data engineering, to infrastructure management, and application maintenance. Today, we are thrilled to announce that Google Cloud Scheduler, our enterprise-grade scheduling service, is now available in more GCP regions and multiple regions can now be used from a single project removing the prior limit of a single region per project.

With many enterprise customers deploying complex distributed cloud systems, Cloud Scheduler has helped solve the problem of single-server cron scheduling being a single point of failure. With this update you are now able to create Scheduler jobs across distinct cloud regions that can help satisfy cross-regional availability and fail-over scenarios. 

Furthermore, you are no longer required to create an AppEngine application in order to use Cloud Scheduler. For existing Cloud Scheduler jobs, it is safe to disable the AppEngine application within the project. Jobs will continue to function without an AppEngine application. 

Creating jobs in different regions is easy. You simply pick the location where you would like your job to run. For example you can specify a location when creating a job through the gcloud command line :

HTTP Targets

  gcloud scheduler jobs create http <job-name> 
--location <cloud-region>
--schedule <cron-schedule> 
--uri <target-uri>

Pub/Sub Topics

  gcloud scheduler jobs create pubsub <job-name> 
--location <cloud-region>
--schedule <cron-schedule>
--topic <topic-name>
(--message-body <message-body> | --message-body-from-file <file-path>)

AppEngine Services

  gcloud scheduler jobs create app-engine <job-name>
--location <cloud-region> 
--schedule <cron-schedule>

Or you can pick a location when creating a job through the Cloud Console:

Google Cloud Scheduler is now available in 23 GCP Regions,  and this number is expected to grow in the future. You can always find an up-to-date list of available regions by running:

  gcloud scheduler locations list

We hope you are as excited about this launch as we are. Please reach out to us with any suggestions or questions in our public issue tracker.

Editor’s note: In this blog post we learn how TapClicks migrated to Google Cloud to offer their marketing customers a unified platform for data management, operations, insights, and analysis.

TapClicks is a smart marketing cloud, powered by data, that unifies our customer’s marketing. By choosing to migrate our core applications last year to Google Cloud, we cut costs, solved data-sharing concerns for our customers, and opened our stack up to a new ecosystem of possibilities. 

The core problem that we’re solving for our customers is how to manage their marketing infrastructures data and operations. Life isn’t easy for marketers now. There are 7,000 different vendors servicing this space today – creating much complexity between digital agencies, media, and brands. Marketers face challenges in navigating all of these systems, logging in and out, understanding pacing goals, and managing the flow of marketing data so they can analyze and report internally as well as to their clients at scale.

We unify omnichannel campaign data (250 API connectors and 6000 Smart Connectors ™ ) from a plethora of marketing sources on an automated data warehousing solution, creating simplicity for organizations. Over 4,000 agencies, media companies, and brands use our Marketing Operations and Data Management Platform, which imports data at scale and creates an automatic data warehouse on Google Cloud. Teams can also leverage TapClicks, like our world class Facebook connector, to import data directly into Google Data Studios.  Beyond importing and storing, we also provide data exporting to other Google solutions like Google Data Studio and Google Sheets.  We also create interactive dashboards that let stakeholders and clients analyze their data, as well as automated, multi-channel reports that go out to clients at specified times. So channel comparisons, optimizations, attribution, and calculations are easily performed.  Some of our customers are able to generate hundreds of thousands of individual reports and dashboards for their clients.

Although we may be best known for our reporting and analytics, we also empower teams managing the marketing operations workflow from customers and internal stakeholders, especially at scale. Our user-friendly, configurable system helps manage their orders and campaigns. Through automation of this process, we deliver tremendous amounts of efficiency, time saving, cost savings, and reduction of errors. The combination of these solutions makes up our unified platform, with additional capabilities like marketing intelligence that offers competitive and brand-level analysis. This is a disruptive solution in use by all leading media companies, agencies and many brands.

Partnering for possibilities

We faced a few challenges with our original tech stack, which included a mix of the leader in web services revenue, leaders in high performance data warehousing, as well as vendors on bare metal servers. 

• One challenge was around costs, which were growing. 
• Second, many of our customers work with multiple brands, and are very hesitant to share their data with the leader in web services, who’s often viewed as their competitor. 
• Third, these vendors are more focused on their own revenue rather than a true long term partnership that would enable their customers to enjoy similar success as they have experienced.

When looking at other cloud providers, Google Cloud emerged for us as the front runner. They were competitive on costs, and their native Kubernetes support was superior— a big selling point for our DevOps team. There’s also a movement in the marketing and advertising industry away from AWS toward Google Cloud because of the data-sharing concern. Finally, most of our customers are already using Google Cloud tools, so there’s brand recognition and familiarity there, and easier integrations with their own systems.

Migrating to Google Cloud

Our migration, which took about five months, involved moving a significant chunk of our infrastructure, including our core applications, using Google Kubernetes Engine (GKE). In our legacy architecture, each of our clients was assigned to one of our virtual machines (VMs), and there was a lot of unused capacity because we had to provision for the max usage. We appreciated GKE’s cloud native capabilities, especially autoscaling, a huge benefit for our web application. We have varying usage patterns during the day, and though our application is mostly used during business hours, there are also days in the month of higher usage, and autoscaling saves us time and costs. GKE also makes deployments much easier, and we anticipate a lot of benefits there for our developer environments. We’ve moved some of our microservices into GKE and plan to move more in the future. All in all, we were able to migrate our core products and the bulk of our AWS spend successfully to Google Cloud. 

We also moved from our other vendors Relational Database Service (RDS) to running MySQL on our own VMs on Google Cloud, which gives us more flexibility in terms of settings and fine tuning. We’re still trying to find the best mix as we’re modernizing our infrastructure, and we took this opportunity to migrate from MySQL 5.7 to 8.0.  

Our next stage is exploring more of the capabilities and services of Google Cloud, including BigQuery, which we’re considering for our own data warehouse. The fact that we could also run Snowflake on Google Cloud, if needed, was another selling point for our migration. 

We’re especially interested in BigQuery ML’s machine learning and natural language processing capabilities, which enabled better predictive insights. Our customers want insights from their campaigns— which are working, which are paying off, where should they invest next? Using our platform, they’re looking not only to generate reporting, but also identify opportunities to improve campaign performance. We plan to use AI and ML to improve those capabilities, so that our customers can seamlessly unlock insight and intelligence from their marketing data and campaigns.

Double-clicking on Google Cloud

For us, being able to deeply leverage and partner with Google Cloud to deliver those solutions on a single stack is critical, and we think our customers will love it. We see TapClicks and Google Cloud partnering at a level beyond what you typically see in a cloud provider relationship. Already, fifty percent of our company is working with various Google Cloud solutions, and we envision TapClicks and Google Cloud as extensions of each other, providing a single, powerful platform solution. 

Google Cloud understands the partnership concept, and their team was able to shine a light on their services and what they could bring to the table. Compared to our previous experiences, dealing with the Google Cloud team has been a true pleasure. Now that we’ve migrated, we’re ready to take our next steps into the services available to us in the Google Cloud ecosystem, and the problems we’ll continue to solve for our customers. Learn more about TapClicks and BigQuery ML.