Building a strong brand in today’s hyper-competitive business environment takes vision. It also requires a flexible, easily managed approach to digital asset management (DAM), so marketing professionals and other stakeholders can easily share, store, track, and manipulate assets to build the brand.

Many of today’s leading companies, including JetBlue, Slack, TripAdvisor, Lyft, and HealthONE, rely on Brandfolder to deliver consistent, organized, and efficient brand experiences. Brandfolder provides an easy-to-use platform that can scale across an entire company with little end-user training, empowering customers to distribute digital assets wherever they are needed. Customers also gain much greater insight into how those assets are used, and how to use them more effectively in marketing campaigns and brand messaging.

“Google Cloud made it easy to build an ML platform to quickly iterate through different brand intelligence use cases and release data-driven product features into the Brandfolder platform.”

—Ajay Rajasekharan, Head of Data Science, Brandfolder

Brandfolder is constantly advancing its development efforts to introduce new data-driven features without complicating the user experience. Big data, artificial intelligence (AI), and machine learning (ML) are key to meeting customers’ unique business needs, and essential for Brandfolder to compete in the fast-moving DAM industry. To enhance these capabilities, Brandfolder sought a public cloud provider that could help it scale its data pipeline cost effectively while providing access to advanced AI technologies.

After graduating from the Techstars startup accelerator program in 2013, Brandfolder tried two other cloud providers before standardizing on Google Cloud Platform (GCP).

“We saw a difference with Google Cloud from the very beginning because the interactions felt like a strategic relationship,” says Jim Hanifen, Head of Product at Brandfolder. “Google gave us startup credits and a lot of face-to-face support, which we hadn’t experienced with other cloud providers. We decided to move our entire infrastructure to Google Cloud Platform.”

Building an ML platform for brand intelligence

After performing an initial lift-and-shift migration of virtual machines (VMs) onto Compute Engine, Brandfolder built an ML platform using GCP managed services to seamlessly deliver its data products. The platform leverages Cloud SQL, Cloud Storage as the data lake, Cloud Dataproc for cloud-native Apache Spark computing clusters, Cloud Composer as the batch job scheduler, Cloud Pub/Sub as the backbone data pipeline, Container Registry to store Docker images, and Google Kubernetes Engine (GKE) as the application orchestrator. Cloud Dataflow brings data into the data lake and into BigQuery for analysis.

“Google Cloud made it easy to build an ML platform to quickly iterate through different brand intelligence use cases and release data-driven product features into the Brandfolder platform,” says Ajay Rajasekharan, Head of Data Science at Brandfolder, who describes the architecture in a detailed blog. “We simply ingest raw application and event data on one end and output an ML service on the other.”

“Moving to Google Cloud Platform allows us to complete more sophisticated data analysis and ML models much faster, and at a much lower cost. We can create brand-specific ML models 12x faster and get them into production quickly to address our customers’ unique business needs.”

—Brett Nekolny, Head of Engineering, Brandfolder

For many general use cases, Brandfolder does not need to build custom ML models, and instead relies on pre-trained API models from GCP. For example, it uses Vision API and Video Intelligence API to auto-tag creative assets on import to enable fast, intuitive searches across images and videos. When more product- and brand-specific modeling is required to address unique customer use cases, Brandfolder builds and trains custom ML models using its GCP pipeline or Cloud AutoML, a suite of products built on Google transfer learning and neural architecture search technology. For example, if a Brandfolder customer makes different types of grills, Brandfolder can use AutoML Vision to train a model to recognize the different grills.

“Moving to Google Cloud Platform allows us to complete more sophisticated data analysis and ML models much faster, and at a much lower cost,” explains Brett Nekolny, Head of Engineering at Brandfolder. “We can create brand-specific ML models 12x faster and get them into production quickly to address our customers’ unique business needs.”

Industry-leading security and performance

Google Cloud’s security model helps Brandfolder give existing and prospective customers peace of mind that their data will be protected. Cloud Identity & Access Management (Cloud IAM) provides enterprise-grade access control, while Cloud Identity-Aware Proxy (Cloud IAP) enables remote users to work more securely without the hassles of a VPN client. GCP also isolates cloud resources into projects, making it easy to assign permissions and keep data and VMs organized and segregated.

“With Google Cloud, everything begins and ends with security, which makes things very easy for us,” says Jim. “If we’re under a security review, we can submit a Google security white paper. If a potential customer has security concerns, we tell them we are hosted on GCP, and those concerns go away.”

To give customers even better application performance for accessing their brand assets, Brandfolder uses Cloud Memorystore, an in-memory data store service for Redis, to cache data and provide sub-millisecond data access for production applications.

“It was much easier for us to use Cloud Memorystore versus running Redis on our compute instances,” says Brett. “The high availability, replication across zones, and automatic failover with no data loss are big for us.”

Global private network interconnects between Google Cloud and the Fastly content delivery network (CDN) dramatically reduce latency, allowing Brandfolder’s customers to deliver and update even very large creative assets quickly around the world.

“What’s beautiful about the relationship between Google and Fastly is that if one of our customers uploads a new version of an asset, we can propagate that out to Fastly, and the new version will automatically show up in all the places where it’s referenced,” says Brett.

“The ability to quickly solve problems with AI has a substantial impact on our revenue, and that’s more apparent every quarter. Few of our competitors are doing product- or brand-specific modeling because it takes a lot of time and resources. We overcame those hurdles with Google Cloud.”

—Jim Hanifen, Head of Product, Brandfolder

Improving employee and customer productivity

Brandfolder also uses Google solutions for real-time collaboration and productivity, using G Suite to connect employees with intuitive, cloud-based apps. Teams use Gmail, Calendar, Docs, Drive, Sheets, Slides, and Hangouts Meet every day to move the business forward. Many of Brandfolder’s customers are also G Suite users, and Brandfolder offers a plug-in that allows them to view their creative assets inside of Docs and pull images in as needed. Customers can also log into Brandfolder with their G Suite credentials, making the solution even easier to use.

“We’ve been using G Suite since the beginning, and it’s helped us collaborate efficiently to build a successful, growing company,” says Jim. “Our teams expect to have that kind of close collaboration, and everyone here enjoys the G Suite experience.”

Driving 99 percent annual business growth

With automated tagging and other innovative AI-based features, Brandfolder is helping customers locate and distribute assets faster. As a result, Brandfolder is building customer loyalty and increasing sales, growing its business by 99 percent year-over-year. Since moving to GCP, Brandfolder has been able to scale its analytics and data pipeline 50x without a corresponding increase in costs and has not had to expand its development team.

“The ability to quickly solve problems with AI has a substantial impact on our revenue, and that’s more apparent every quarter,” says Jim. “Few of our competitors are doing product- or brand-specific modeling because it takes a lot of time and resources. We overcame those hurdles with Google Cloud.”

At Jeni’s Splendid Ice Creams, Jeni and her staff are all passionate about ice cream and sharing that passion with the world by creating ice creams that you can fall madly in love with. To do this every day, requires incredible teamwork and collaboration, and Google Workspace is helping support the cause from tracking inventory to managing quality control.

Jeni’s Splendid Ice Creams began small but had big dreams. Jeni Britton Bauer opened her first ice cream shop in Grandview Heights, Ohio in 2002, and turned to Google Workspace to help her manage everything from ingredients to employee scheduling. Today, Jeni has grown the business to 10 stores throughout Ohio and Tennessee and has a booming online shipping business, and she depends on Google Workspace to help her manage it all.

Google Docs helps Jeni’s Splendid Ice Creams employees share information from the kitchen with the planning teams on the ground at each location. And it gives her access to real-time information to ensure they have the ice cream, packaging, and manpower to handle spikes in online orders. Stores are also able to give feedback about each home-made batch of ice cream through a Google Docs form. So if there aren’t enough pecans in the Whiskey Pecan Ice Cream, Jeni’s team can add more in the next batch. Jeni even wrote her best-selling cookbook using Google Docs.

*Google Workspace was formerly known as G Suite 

As offices reopen, businesses aren’t keeping to a single formula. Many are embracing hybrid models, with employees splitting time between home and the office. Some are staying 100% remote. Others are returning the full workforce to offices with a greater focus on digitization.  

Regardless of their model, one thing is certain: technology is more central than ever to organizations’ ability to work smarter and more effectively. In particular, organizations need technology that can be tailored to specific business needs. For example, a retail store manager may need a way to ensure improved sanitation practices, or office workers may need to create an app to manage desk reservations. 

Google Workspace can help by bringing together everything you need to get things done, all in one place—including the ability to build custom apps and automations with AppSheet. AppSheet, Google Cloud’s no-code development platform, lets employees–even those with no programming experience–reclaim their time and talent by building custom apps and automations. 

Building solutions with AppSheet is often easier and faster than traditional coding, as AppSheet leverages Google’s machine learning expertise to help you quickly go from idea to solution, helping your business to match the pace and agility that today’s landscape requires. In this article, we’ll explore how you can use AppSheet to create custom solutions that will help your business adapt to shifting business needs. To illustrate, we’ll focus on a use case many businesses face: reservation and management of meeting rooms and other office resources, but this process can easily be adapted for a wide variety of use cases, from apps for retail pickup to incident reporting and more. 

Simplify and centralize with apps

The first thing to consider is whether your solution would be best managed via a custom interface. If you’re trying to simplify a process for someone, such as inspections or inventory tracking, or centralize information, such as resource portals or events calendars, creating a custom app is the way to go.

For this example app, we created a simple Google Sheet to hold our backend data. Sheets are ideal backend data sources when we know the amount of data will not grow exponentially, especially when piloting to a first office or group of users. We can switch our data seamlessly at any time to a scalable Google Cloud SQL database or other database if needed.

The example app has several worksheets to manage the different buildings, rooms, checkpoints and people (including their roles).

We can build an app in AppSheet directly from our Sheet by selecting Tools > AppSheet > Create an App. 

After creating our app, we see an overview of the data that we’ve connected, how pieces of data relate to each other, the views that are presented to the user, and a live interactive preview of the app. Refining the app is intuitive. When you input keywords, for instance, AppSheet surfaces appropriate functionality options that can be further customized. If we have address or location data, it’s automatically turned into a map view that we can further customize.

Our office management app will offer building managers and cleaners administrative features for managing equipment, disinfection schedules, and maintenance information, and it will also offer views for employees to check occupancy and safely reserve desks and equipment.

Opening an office and then a room in the app gives us an overview of both the floorplan and the occupancy and reservations for spaces and equipment in the room.

Users can then reserve spaces and equipment in the app, without having to first search for a form or page in the intranet, or even log onto their work computer. The reservation is an automation routine in AppSheet, which performs pre-configured actions when triggered.

As illustrated in the screenshot above, when the action is triggered either by pressing a button in the app, scanning a QR code, or tapping an RFC tag, the action simply sets the “Reserved by” and “Reserved at” columns to the current user and timestamp.

Streamline with automations

AppSheet Automation, which was recently made generally available, makes it possible to reduce repetitive tasks and streamline processes even further.

In this example, one challenge you may encounter is that users often forget to release a desk or resource when they’re finished, which means those reservations stay blocked until an administrator releases all blocked reservations. However, it’s also important that resources aren’t immediately released, as they first need to be cleaned and disinfected before being made available to new users.

AppSheet Automation can solve this challenge by periodically checking all resources that have been reserved for longer than four hours, then alerting the user to either re-reserve them or release them to be cleaned. If there is no answer, the automation can trigger the resources to be cleaned, then released.

We can configure this as a recurring event, and create a bot that sends the notifications and triggers actions based on the user input (or lack of input).

Optimize for multiple roles

Creating an app for one user is one thing–creating an app that fits the needs of multiple types of users is another. AppSheet has you covered for this kind of complexity because it lets you build multiple roles into a single app. 

In our office management app, for example, the office manager can have a particular view and dashboard, and workers in the office can have their own views and functionalities front and center. This makes it possible to automate tasks for all types of users with a single app. 

Likewise, AppSheet Automation lets you easily react to real-time changes in data, send notifications to groups of users, and initiate additional workflows using data shared between the app and the users. If a group needs to reserve a conference space for an important late-breaking meeting, for example, there might be ripple effects across a number of user groups. The ability to automate all these updates and interactions can ultimately save a lot of time and effort. 

AppSheet also supports advanced features such as QR codes, NFC, and bluetooth sensor integration. This could help users check into locations or workspaces, further streamlining the task of helping people safely navigate and collaborate within the office.

Mission critical solutions, faster than ever

In the past, the type of app explored in this article would have required a central data store, distribution to specific groups of users, management and dashboard capabilities, as well as smartphone sensor integration for NFC and image capturing. This would have necessitated a mammoth implementation project and a team of professional coders.  

But with no-code, you can effectively design and implement these requirements in hours and days rather than months and years. Changes can be made on the fly in any browser, including pushing out new versions to users. Though AppSheet opens up app building and digital automations to any knowledge worker, it also includes robust security and governance controls, ensuring that as you manage getting employees back into office, you don’t neglect IT security. 

Try out your own back-to-the-office app for free today at AppSheet.com, or explore and copy our sample app.

Poll three Site Reliability Engineers with the question “What is SRE?” and you’re likely to get five different answers: an implementation of DevOps, a role, a set of practices, a cultural shift, a snazzy title. While these definitions may not necessarily align with those in the SRE books, there is one throughline differentiating SRE from other ways of working: Service Level Objectives (SLOs). While simple to understand – intentionally! – SLOs are frequently challenging to define in practice. And even though the specifics of an SLO vary across industries and verticals, we have found there are a number of practices and strategies common amongst teams that have successfully implemented SLOs for their workloads. 

Bringing together product, development, and SRE teams to achieve a common understanding of the workload in question, and in particular its critical user journeys (CUJ), is a key first step. For many teams this means writing down, often for the first time, detailed sequence or flow diagrams for these CUJs. The maturity of and the relationship between the three “legs of the stool” (development, product, and SRE) will play a role in the level of effort required to complete this first step of the journey. Having a common understanding of your users’ expectations of your workload is a prerequisite to writing effective SLOs.

While modeling user journeys and decomposing them into SLOs is an art and no two applications are alike, there are a few key aspects upon which to anchor your discussion. The main question we recommend you keep top-of-mind when going through this process is “What do my users care about?” Framing your thought process in this way prevents implementation snafus and strategies that don’t approximate user expectations. Other aspects to consider include:

• Are there breakpoints where the user may choose not to take an action?
• Which parts of the interaction are we capable of measuring and which are we not (e.g., third-party dependencies)?
• Which parts of the user journey are common across many user journeys and thus are possible candidates for factoring out as their own CUJ (example: login)?
• Which parts of the journey can be measured in aggregate, and which must be separated because of differences in criticality, request rates, or other factors?
• Which steps of the journey have strict dependencies between one another?

Armed with answers to these questions, a detailed request diagram, and your application code, you’re ready to start putting pen to paper! Before jumping into your monitoring consoles, we recommend writing up an SLO design document which lays out the technical details of your chosen SLOs. We’ve made a template available to you to jump start this process (if you have a Google account, you can make a copy using this link). In it, you’ll find an empty template along with worked examples for reference as you create your own specifications. Whether you use this template or not, we recommend the following as you document your SLOs:

• Be pedantic with technical specifications – they will matter during implementation
• Maintain a section outlining clarifications, caveats, and/or tradeoffs made as a part of the design process
• Consider where you’re measuring – make sure it’s feasible
• Beware of summaries, averages, and other non-aggregatable statistics for latency SLOs
• Keep compliance periods consistent across your workload(s)

• We recommend the following defaults:
  • 28 days rolling for operational needs (error budget alerting)
  • Fixed calendar quarters for prioritization and lookback
• Changelog: Include one, even if your documentation tool has version history, so you can track major changes
• Put your SLO documentation in a location accessible by your team and company stakeholders
• Once your SLO PRD is finalized, treat your implementation as code and store it in your version control system
  • Remember – DRY!

We hope these recommendations and template give you a head start in bringing your SLOs to production. If you find yourself in need of a tool to implement your SLOs, consider Google Cloud SLO Monitoring which allows you to create SLOs for any metric available in Google Cloud Monitoring and computes your error budget automatically, enabling burn rate-based alerting. If this process still feels daunting or you find your team in need of help with any of the above, our reliability engineering professional services team can assist. For more information, visit cloud.google.com/sre or you can contact your Google Cloud account team.