Cloud

If you want to get right into using Google Cloud Scheduler, check out this interactive tutorial!

So, there you are relishing in the fact that you’ve just set up a new database and pipeline to process large amounts of your organization’s data regularly. Feeling alive! 

Your manager congratulates you (great job, btw!) and then informs you that you’re now in charge of maintaining this moving forward. Something she didn’t mention when you started this project. 

You quickly begin to visualize your weekends taken up by the heavily manual process of backing up the database and making sure that it’s properly feeding into the pipeline, before the start of each week. Long hours, using multiple interfaces to make sure nothing fails and starting over  when things do. 

Well you’re not alone, managing large-scale operations that involve many different tasks and dependencies is one of the biggest challenges that developers and businesses face.  

Not only is it manual, time consuming and hard to keep track of everything going on in your cloud environment, it also makes it really difficult to scale your organization’s IT by creating  bottlenecks. 

If only you could have a way to schedule all of these minute administrative tasks to be completed for you, so you could focus on  more strategic, impactful tasks.  

Well, from the title of this blogpost you can probably guess that Google Cloud Scheduler (Cloud Scheduler) IS your fully-managed, highly reliable, scheduling service. 

It allows you to schedule and automate tasks that perform routine maintenance, data processing or to trigger workflows. Think –  scheduled data backups, updates, batch processing, application monitoring, automated testing and report generation. Plus, it comes with an intelligent retry mechanism that you can configure to rerun failed jobs, up until the point that you specify.

It supports a variety of scheduling options, including specific date and time, recurring intervals and cron expressions or jobs. 

Cron jobs are a commonly used scheduling tool in the software development industry (Linux and Unix world), allowing developers to schedule tasks at specific intervals or on specific dates and times. These intervals are specified using a formatbased onunix-cron.

You can use Cloud Scheduler to accomplish tasks like:

easily scheduling recurring data backups, ensuring your data is safe and secure in the event of a system failure or data loss

processing large amounts of data in batches at specific intervals 

monitoring your applications for errors or performance issues and send notifications to your team if issues are detected

Cloud Scheduler is designed to make it easier to manage your cloud environment by allowing you to define schedules, run tasks and manage results, all from a single, centralized location – this gives you better control and more visibility over your infrastructure. 

Plus, the fully managed part, means you have the reliability of Google’s robust infrastructure, so you can be confident that

your jobs will run when they are scheduled to do so

they’ll scale automatically to meet your needs – handling any volume of jobs from a few tasks per day to thousands of tasks at a time, without any additional configuration. (no worrying about capacity constraints!)

The automation of these processes reduces the risk of human error and frees up your time and mental energy to focus on more important tasks, making you more productive and organized.

So… how does it work?

Cloud Scheduler works by allowing developers to create jobs that run at specific intervals or when triggered by an event based on specific conditions. 

Jobs can be created using the Cloud Scheduler UI, a command line interface or via the API. 

Cloud Scheduler can trigger your jobs in a variety of ways and currently supports a wide range of job types, including HTTP/HTTPS requests, and Pub/Sub messages You can also define custom job types using Cloud Functions or Cloud Run, which gives you the flexibility to run any type of task in your cloud environment.

Once a job is created, you can specify the schedule for it to run on and from there Cloud scheduler takes care of the rest. It automatically triggers your task at the specified time or interval and ensures that it runs reliably and consistently.  

As mentioned above, you can create schedules using Unix cron expressions to specify seconds, minutes, hours, days, months and weekdays. 

The scheduler then triggers the job at  the target location specified. This can be any web service or application, and the request can include parameters and data. The target location can then process the request and perform the necessary tasks. 

For example, if you wanted to schedule a job to run a data import from BigQuery, you could create a job that specifies the file location and the target location (cloud storage in this case) for the imported data.

After the job is executed, Cloud Scheduler provides detailed information about its status and results. This information is stored in logs and can be accessed using the Google Cloud Console, APIs or third-party tools.  It’s especially useful to set up Cloud Logging and Cloud Monitoring, which provide real-time visibility into the status and performance of scheduled jobs, enabling you to monitor job execution, troubleshoot issues, and optimize performance. 

If you’re thinking – this all sounds great, but am I going to have to give an arm instead of my weekends to make this happen? No, keep your arm. Cloud Scheduler is a cost-effective solution where you only pay for the tasks that are executed AND it has a tier that provides up to three jobs a month for free (at the account level, not project level).

 With Cloud Scheduler you can schedule:

Data backups for databases, file systems and other data sources – ensuring your organizations critical data is backed up regularly and can be restored in case of a disaster

Resource management tasks, such as starting and stopping VM instances, deleting temporary files and cleaning up unused resources, which can help optimize resource usage and reduce costs

Data pipeline tasks that move and transform data across different systems both inside and outside of Google Cloud. 

Fundamentally, Cloud Scheduler is more than just a simple job scheduling tool. Its flexibility and integration with other Google Cloud services make it a powerful tool for orchestrating complex workflows, managing resources, automating tasks and saving weekends. 

For some hands-on play time with Cloud Scheduler right now, check out this interactive tutorial where you can run your first job for free!

Good practices alone aren’t enough to ship software regularly. You need good tools! There is no shortage of great tools for releasing software into production, but Cloud Deploy brings unique value to the table. Cloud Deploy is a fully managed, opinionated continuous delivery service that makes it faster and easier for you to consistently release software to runtimes like Google Kubernetes Engine and Cloud Run, and some exciting new features make it even more powerful.

We were mindful of the developer experience right from the beginning as you are interacting with Cloud Deploy in the console. The GUI navigation experience is unambiguous — what you see is what you have to work with. When possible, context switching is minimized to reduce developer toil while getting up to speed with new features.

Let’s dive a bit deeper into the feature-rich power of Cloud Deploy and how it is streamlining your deployment journey:

Release promotion, rollback, and approvals

Detecting problems earlier in the software development life cycle reduces costly outages and makes developers more productive. Cloud Deploy brings the idea of shifting left on CI/CD to reality. For safeguards against unwanted approvals, Cloud Deploy allows you to take advantage of flow management features such as release promotion, rollback, and approvals. In fact, in arecent developer research study, we found that Cloud Deploy helps to automate DevOps-style continuous delivery tasks like release promotion and approval are 2.4x faster on Google Cloud than with competing cloud services.

When your release is deployed into a target defined in your delivery pipeline, you can promote it to the next target, with just one click. Promotions kick off right away once initiated. This is consistent with any target whether that’s a Google kubernetes cluster, an Anthos cluster, or Cloud Run. 

Cloud Deploy supports rolling back your deployed application in any target. A rollback consists of triggering a rollout against the last successfully deployed release. The new rollout uses the same parameters that were used in that successful deployment and can all be controlled within the interface you are used to working with.

Cloud Deploy brings the idea of shifting left on CI/CD to reality. For example, gone are the days of reaching out to multiple Program Managers/Operators/etc to get approvals or submitting a ticket and being added to a long queue since we have baked the approval process directly into your interface. Now you can require approvals for any target, and you can approve or reject releases into that target. Approvals can be managed programmatically by integrating your workflow management system (such as ServiceNow), or other system, with Google Cloud Deploy using Pub/Sub and the Google Cloud Deploy API. By bringing the approval process into the interface helps organizations maintain their policy via software, rather than manually, time consuming approvals. 

Multi-location deployments

In the time since we ran the above-mentioned research study in 2022, we have made exciting updates to Cloud Deploy features that speed up development. For instance, we know that being able to deploy to multiple targets at the same time can speed up your rollouts — and in March, we showed you that Cloud Deploy can do just that. 

Before, updating all clusters required waiting for a sequential Cloud Deploy pipeline to run and update each cluster, one at a time, which was not optimal. With this new update to Cloud Deploy, you can concurrently deploy to all members in a group of either Google Kuberentes Engine clusters, Cloud Run instances, or Anthos clusters at once. This ability to “parallel deploy” clusters will tremendously speed up, for example, updating all clusters of a globally distributed application. 

Imagine a scenario where an application is deployed globally. In each region, there may be multiple clusters. In this example, the Asia region has four clusters.

Cloud Deploy makes it possible to deploy to all four clusters in the Asia east region simultaneously. If all goes well, then a promotion to the clusters in europe-west can begin.

Canary is now in Public Preview

Canary deployments allow customers to deploy a new version of an application alongside an existing version of that same app. The canary (new version) can be rolled out in customer defined percentages. Each percentage increase is called a phase. When the phase ends, customers can either choose to advance the rollout to the next phase. Customers can also opt to rollback for whatever reason. This makes it possible to perform safe, gradual rollouts that minimize disruption.

Conclusion

With Cloud Deploy, we want to be the simplest and fastest way to deploy your workload onto Google Cloud runtimes and we are excited for you to see future product updates that will continue to drive this mission. Not only that, but we are making continuous delivery to GKE, Cloud Run, and Anthos easy and powerful today, so be sure to get hands on with Cloud Deploy below: 

Interactive tutorials: GKE + Cloud Deploy | Cloud Run + Cloud Deploy

Quickstart: Deploy an application to two GKE targets

Interactive Tutorial: Cloud Deploy End-to-End

The journey of any enterprise includes the transformation of processes related to presales, sales, procurement, service, production, quality, maintenance, warehousing, and finance operations, adhering to the principles of optimization and faster implementation. The goal is to create a uniform user experience, branching and connecting each enterprise function with minimal transformation effort. With a traditional approach, achieving this is not easy. Some of the other hurdles organizations face are:

Lack of localization know-how, especially with respects to  legal and fiscal compliance 

Low transparency across business functions

Legacy SAP business processes

Geo-specific, fragmented and heavily customized legacy SAP ERP systems

A complex integration landscape across in-house and cloud technologies

Inability to scale with business growth

Tata Consultancy Service (TCS) PreCast is an integrated business solution certified by SAP as a Qualified Partner Packaged solution (QPPS), leveraging SAP’s market leading software, best practices and innovations. Together with partner services, TCS brings a specialist’s functional knowledge and IP, for rapid deployment with low risk and high predictability for SAP S/4HANA greenfield and migration projects, all at a highly affordable price point.

To gain higher efficiencies, you can complement TCS PreCast on Google Cloud as a package with TCS SAP Monitoring as a Service, for proactive monitoring of SAP and Google Cloud infrastructure landscape. With 50+ predefined alerts and 25+ predefined reports on cloud usage, customers will experience enhanced observability of their business-critical ERP applications, with benefits such as:

Higher application availability 

Lower management and operating costs 

Better management of SAP

Solution highlights

The solution package content is:

A preconfigured solution for 120+ processes, localized for multiple regions

Re-designed and enhanced configuration to support multinational corporations

Available as an appliance with database backup

TCP PreCast provides the following benefits:

Accelerated time for deployment 

Adoption of SAP standards and best practices 

End-to-end transformation accelerators for the project

A positive impact on Total Cost of Implementation (TCI) and Total Cost of Ownership (TCO) 

Is ready to scale through Google Cloud Partner Engagement, providing optimized business process and accelerated innovation

TCS PreCast integrates well with Google Cloud products such as BigQuery, Anthos, Apigee and Google Cloud Cortex Framework, providing customers with an AI-driven intelligent enterprise. Google Cloud Cortex Framework offers pre-configured SAP content for scenario-driven, data-driven, cloud-native reference architectures enabling faster time to market. These services enable our customers to achieve “cloudification” of the ERP digital core and superior business outcomes, to gain resilience, a better customer experience and the flexibility of an open, scalable, and democratized ecosystem.

A Netherlands-based global pipe manufacturer, Wavin IT, and a Canada-based leading garments company were some of the many clients who were grappling with the above challenges to make the first move towards SAP S4HANA landscape transformation to support their innovation and growth.

Both of these customers can operate more efficiently and effectively. They’re able to make better decisions, improve their customer service and have now successfully realized their growth strategies by partnering with TCS ERP on Google Cloud and implementing PreCast.

“The partnership with TCS for their ERP on Google Cloud is pivotal to our expansion strategy and cloud-first approach. By leveraging the out-of-the-box solution with TCS’ experience in localized deployments, end-to-end capabilities and single point of accountability, enabled faster deployment, better user adoption, as well as resilient and scalable processes.” —Allan Jones, Global VP – IT, Wavin 

If you have challenges in your SAP landscape, irrespective of your size, the complexity of your existing journey or budget challenges, we are just a call away for a one-stop-shop experience. To learn more about how to implement TCS PreCast on Google Cloud, please reach out to GBU.marketing@tcs.com or talk to a Google Cloud sales specialist.

Editor’s note: Jack Ngare is a Technical Director in Google Cloud’s Office of the CTO based in Nairobi, Kenya. A native of Kenya, he worked in telecommunications abroad for 12 years before returning home to work for a large African financial institution and a U.S. technology company. He joined Google Cloud last year with a mission to digitize and modernize Cloud’s global top customers, while simultaneously growing Africa’s entrepreneurial technology culture. 

What is the opportunity you see before you?

Working at Google Cloud, I’m able to bring people some of the world’s best software and hardware engineering. I also see the possibility of taking the capabilities that Google Cloud offers leading banks, retailers, telecommunications companies, and others in the developed world, and putting them in place in Africa. Not only would this create efficiency and end waste in a dramatic fashion, but it would also be an opportunity for Google Cloud to help advance Africa’s potential and inspire people with the creativity and drive within the organization.

African technology development is a two-way exchange. Google Cloud customers I have worked with across the globe have similar challenges and opportunities, including identifying how to improve efficiency, how to optimize data pipelines, and how to apply AI in productive, cost-effective ways. Common challenges are best addressed from diverse perspectives. In the past 30 years, we’ve seen how customers in China, India, and Africa, unhampered by maintaining legacy infrastructures, leapfrogged development in mobile and fiber optic technologies. 

What do you think are the biggest misconceptions about Africa?

One of the most common misconceptions is thinking of Africa as one place. Sub-Saharan Africa has nearly 50 countries, with more than a billion people spread over millions of square miles. There are several different cultures, economies, customers, and opportunities. 

Africa shouldn’t be considered a place with nothing but needs. The region has a lot to give. There’s a young population that is very tech savvy. Many people are doing gig work in areas like coding, design, social media, and AI for large global companies. They understand those things very well, and are keen to do more.

Is it hard to know where to start?

In some ways, that is the hardest thing. There’s so much potential, and we need to show how Google Cloud can be a strong partner across all industries and business sizes — 70% of African businesses are small and medium-sized enterprises. 

Outside of my day job, I continue to help bring technology to Africa in several ways. I participate in creating a curriculum for kids here in grades K-12 to learn how to code, I work on getting companies to sponsor schools that need to be wired to high speed Internet, and I speak at universities.

What would you say is your biggest motivation?

My biggest motivation is urgency. Opportunity doesn’t hang around forever waiting for you. It wants to be understood and engaged with. This is an extraordinary time. On the one hand, the entrepreneurial drive was always here in Africa, but it had a hard time attaching itself to the larger world, or even connecting to good networks! The cloud, and good connectivity, can change that.

Take for example, Google’s recently commissioned report from Africa Practice, which is about the impact of its Equiano subsea cable. It’s estimated that it could cut data prices by up to a fifth, and help create 1.6 million jobs as a result of increased connectivity. Equiano will connect Europe with Togo, Nigeria, Namibia, and South Africa (and even, away from Africa). It’s a big step.

At the same time, we have to move fast, we have to move with knowledge. Two years ago, Google made a $1 billion commitment to develop business in Africa, and in October we gave an update: Our first data center in the region was built, support is in place for entrepreneurs, and Artificial Intelligence is being used to map buildings. However, history shows that it’s possible to spend $1 billion and make little impact. You have to take action and you must follow-up.

What makes you confident?

I’m a citizen of Kenya, an African who was fortunate enough to get the right breaks in education and the right opportunities. It has brought me so far. While I’m confident in myself, I’m even more confident that there could be 100 or 1,000 people like me who can succeed more than I have. I’m confident that we can give them that chance with Google Cloud, and if we get it right, the results will astonish the world. The time is now.

Creating a virtual machine (VM), a computer you can use without needing to purchase, set up, or keep around, is one of the most basic functions of the cloud.  You can rent as many computers as you need and delete them when you’re done with them.

But VMs are only a benefit if setting up a virtual machine is easy.  In Google Cloud, creating a VM is done with the Compute Engine service.  There’s a short (about 5 minutes) interactive tutorial to get you started.  I’ll explain what’s going on in that tutorial here, but you should walk through the tutorial as well to see all of the exact steps.

Once you’ve finished this tutorial, be sure to check the references to learn more about creating and using VMs.

Selecting a project

Everything in your application will be in a project, so you’ll either need to create or select a project to do this tutorial in.  Projects need to be associated with a billing account, so if you don’t have one, consider signing up for the Free Trial.  You’ll start in the Cloud Console.

Enabling APIs

Normally you will go to APIs and services from the Navigation menu to enable the Compute Engine API, but the tutorial will let you do this by just clicking a button.  If you’ve already enabled the Compute Engine API for a project, you won’t need to enable it again.

Creating a VM

In this tutorial, you’ll create a Windows Server VM.  (Don’t worry; if you want a Linux VM, there’s a tutorial for that too!)  From the Navigation menu, select Computer Engine.  By default, you’ll go to the first item in the submenu, which is VM instances.  

You can then click Create instance to create a new VM.  You’ll notice there are a lot of options, allowing you to change the name, the machine configuration, the boot disk, and far more.  As you change options, notice how the price for the VM changes in the upper right of the screen.

The tutorial will give you suggested changes to make to change the operating system and allow HTTP traffic.  These options can be seen further down the options screen, as shown in Figure 2.  It will also help you find the right places to enter this information–the first time you see these screens they may be a bit overwhelming!

There are a variety of different operating systems available as shown in the Boot disk section (Figure 3).  Once you’ve selected an operating system, you may also need to select the particular version of that OS.  For operating systems with a licensing fee, that fee will be included in the price of the VM.  Try some out and see how the price changes.

The boot disk section also gives you the ability to use custom images, snapshots, and existing VMs to create your image.  You can find out more about these in the reference section.

Connecting to the VM 

Once you’ve set the options, select Create, which will return you to the VM instances page, as shown in Figure 4.  Once there’s a checkmark next to the VM, it’s ready to go.  Before accessing the VM, you’ll need to set up a password.  This is easy enough to do by clicking the down arrow in the Connect column and selecting Set Windows password.  Be sure to save the password!  

Once you have a password, you can connect to the server using your RDP client.   If you have problems, information on troubleshooting RDP is available.  At this point you can administer the machine, set up accounts, install software, etc. just as you’d do with any Windows machine.

Cleaning up

There is a charge to both keep a VM running and to store its boot disk.  You can stop the charge to run the VM by selecting it on the VM instances page and then clicking stop.  If you won’t be using this VM again, you can select the VM and press Delete instead.

Yes, the tutorial shows you exactly how to do this!

While there are lots more details about Compute Engine, you’ve got the big picture now.  Go do something creative and useful with it!

So what now?

What are you ready to explore next?  There are lots of Compute Engine interactive tutorials available, but some good next steps include:

Create a Linux VM instance in Compute Engine: interactive tutorial, documentation page 

Transfer files to a Windows VM: interactive tutorial, documentation page

Create an IIS web server VM: interactive tutorial, documentation page

Create a new template instance: interactive tutorial, documentation page 

Restoring a VM from a snapshot: interactive tutorial, documentation page

Troubleshoot VM shutdowns and reboots: interactive tutorial, documentation page