All About Cloud Run, its Scalability and Management Features

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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
City of San Jose Ensures Critical Services Reach Community Using AI Translation

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San José is one of the most diverse U.S. cities, with residents speaking more than 100 languages. Several years ago, we set out to improve city community interactions through more equitable service management and delivery. This demanded a new approach to automating the intake of requests from a majority population whose first language is not English.
We first created the 311 portal and app, which was an important step as we effectively separated resident service requests from emergencies. The way we describe it to our citizens, you call 311 for a burning question, and 911 for a burning building. In the last fiscal year, San José 311 received nearly 210,000 contacts by phone and an additional 211,000 service requests through the SJ 311 app.
Through the portal and app, we gave citizens an omnichannel experience enabling them to interact with the city to request improvements, access useful information, and get emergency help when they need it.
In order to truly serve our diverse communities, we recognized language translation services would be required to offer truly equitable services to everyone. That’s when we started working closely with SpringML, Google Cloud, and other partners with involvement from our Mayor and City CIO.
Building public services with community engagement in mind
When we first rolled out the My San José website and mobile app, we used an out-of-the-box translation service that ended up not working. It had poor accuracy and did not meet our needs to provide all citizens with coherent services. After looking at many other options, we decided to partner with SpringML and Google Cloud to leverage the AutoML Translation with other technologies such as our virtual agent.
SpringML was selected through an open RFP process, and helped us to build and optimize our integrations, interfaces, and more between several systems, making the app and website more intuitive to manage. SpringML delivered the product we needed on time and up to specifications, and additional value came from the training sessions they provided to our team. This enabled us to understand everything we could do with AutoML and opened the door to other enhancements such as simplifying the vernacular used with our residents, making government access easier to navigate regardless of natural language spoken.
After establishing the My San José app’s translation capabilities using AutoML, SpringML also helped us incorporate Dialogflow virtual agents. Dialogflow also positions us to make modifications with our own staffing practices – something that has become increasingly important amid the frequent changes in service levels from COVID-19 response in the past year.
Responding to community needs
With the app up-and-running, our next step was to bring in community members to help with testing, improvements, and more. We wanted the app and the website to not just be something we provided to the community, but rather something they helped us build so they would readily adopt it.
Thanks to the greater accuracy of translation supported by Google Cloud services, we were able to leverage the expertise of a small pool of community members to evaluate translations. AutoML Translation and Glossary proved to be a powerful combination that pushed us closer to our goals.
Our primary targets were Spanish and Vietnamese translations. We are now seeing 90 percent accuracy in automated Spanish translations while Vietnamese translations continue to improve. We continue to work to simplify the language used in these services, which makes a big difference in terms of ensuring optimal language accessibility.
This work includes best serving our community members who primarily use phones to get in touch with us through 311 services. Using Google Cloud Contact Center AI, we have been able to effectively manage the calls we receive 24×7 and communicate with residents who speak Spanish as well as English. No matter which channel one of our residents choose to use to reach out, we can serve them efficiently.
A well-timed release
We’re proud of the work we’ve done. We’ve made many government services available to our community 24 hours a day, 7 days a week — accessible through many channels. Regardless of a person’s native language, the consistency of experiences enjoyed by everyone is improving every day thanks to AI. We’re also actively incorporating more language translation capabilities to better serve more people.
While we began this process several years ago, the recent integration of machine learning language translation with our customer relationship management system in late 2020 was very well-timed because we were able to incorporate this into our COVID-19 pandemic response.
We’re also beginning to work with other municipalities across the U.S. to share some of the lessons we’ve learned and success we’ve seen in hopes of furthering more equitable citizen services far beyond our City limits.
We are excited to continue working with SpringML, Google Cloud, and other partners to improve our city and the equity and quality of services that our residents enjoy.
Learn more about how you can work with a Google Cloud Partner here.
RAMPing Up Cloud Migration Process

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As enterprises accelerate their migration to the cloud, they experience more notable mid- and late-phase migration challenges. Specifically, 41% face challenges when optimizing apps in the cloud post-migration, and 38% struggle with performance issues on workloads migrated to the cloud. Further, organizations have also increased reliance on outside consultants and other service providers for early-stage cloud migration tasks to ongoing management post-implementation.1
To help customers through these challenges with a simple, quick path to a successful cloud migration, Google Cloud created our comprehensive Rapid Assessment & Migration Program (RAMP). And we’ve got some exciting developments to share with our customers and partners:
Expanded focus on post-migration TCO/ROI
Given the complex nature of cloud migrations, we are committed to meeting our customers where they’re at in their cloud journeys and partnering with them to achieve their business goals — be it building customer value through innovation, driving cost efficiencies, or increasing competitive differentiation and productivity. RAMP is a holistic framework based on tangible customer TCO and ROI analyses, that supports our customers’ journeys all the way through: from assessing their digital landscapes across multiple sources including on-prem and other clouds, and identifying prioritized target workloads to building a comprehensive migration and modernization plan.
Accelerate positive outcomes with expert partners
Customers can also now expect a more streamlined migration experience through our ecosystem of partners who have completed their cloud migration specialization. Last week, we announced industry-leading updates to our partner funding programs with new assessment and consumption packages that simplify and accelerate our customers’ journey to Google Cloud, at little-to-no cost. These packages offer prescriptive pathways for infrastructure and application modernization initiatives, empowering our partners to support our customers at every stage — from discovery and planning to migration and modernization.
Through our partner ecosystem, our customers can expect:
- Distinct funding packages for assessment, planning, and migration
- Faster approval processes for accelerated deployments
- More partners eligible to participate in RAMP and access these new funding packages
Sustainability through migration
Another major focus area for RAMP is helping enterprises optimize their migration planning and maximize their ROI by including their business and technical considerations early in the process and including any sustainability goals they may have. To aid with their sustainability efforts, we are excited to share that customers can now receive a Digital Sustainability Report along with their IT assessments – enabling sustainability to be built into their migration strategies. The report provides actionable insights to measure and reduce their environmental impact, and is based on some of Google Cloud’s own best practices, having been carbon-neutral for decades and looking to run on carbon-free energy by 2030.
We are committed to solving complex problems for our customers and partners, and these updates are a reflection of the feedback we receive. Simplify your cloud migration strategy today by requesting your free assessment, finding a partner to work with, or talking to your existing partner to get started.
1. Forrester Consulting, State Of Public Cloud Migration; A study commissioned by Google, 2022
Google Cloud Celebrates Journey of 3 Inspiring Founders for the Asian Pacific American Heritage Month

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May is Asian Pacific American Heritage Month —a time for us to come together to celebrate and remember the important people and history of Asian and Pacific Island heritage. This feature highlights three AAPI founders from the Google For Startups community.
Read on to learn how these three founders built their businesses, leverage Google tech, and suggestion they have for aspiring entrepreneurs.

CultivatePeople
Founder: Lola Han
Description: CultivatePeople’s compensation software, Kamsa, provides global market pay rate data and helps companies make data-driven salary decisions so they can attract and retain their most valuable asset: employees.
Why GCP: “CultivatePeople began using GCP when integrating SSO/SAML authentication after our SaaS product became a high priority. We were able to exceed our clients’ expectations and increase their level of trust in our platform’s capabilities. We’re currently investigating additional machine learning products, such as Cloud AutoML, that will allow us to quickly deliver exciting features.”
Note from the Founder: “I grew up with immigrant parents who value stability and are risk-averse. My parents discouraged me from starting my own company because they didn’t want to see me struggle financially or see my health suffer (due to stress). I felt strongly about what CultivatePeople could do, so I started the company as a sole founder in 2017 and watched it double in size year over year since. While the ones I love most may not have cheered me on initially, it was important for me to hang on to the encouraging words of former bosses, executives, and founders to keep me focused on my mission.
My advice for other AAPI founders is to be a “silent assassin” and believe in the mission and values of your organization. Always remember to stop along the way and:
1) Enjoy the journey by celebrating wins and giving yourself credit;
2) Follow your intuition—it’s (almost) always right;
3) Recognize and invest in your people regularly (ie. give increases more than once a year, if warranted);
4) Give regular words of affirmation to employees on even small achievements.”

Swit
Founder: Josh Lee and Max Lim
Description: Swit is a team collaboration platform that seamlessly combines team chat with task management by allowing teams to turn their conversations into trackable tasks and share tasks to chat with simple drag-and-drop functionality, ensuring everyone is on the same page and projects get done faster.
Why GCP: “Swit is a cross-category hybrid work tool for chat and tasks. This functionality requires more complicated and heavier architecture for performance. So, configuring and managing virtual machines was really challenging to scale up our systems, while handling occasional unexpected traffic surges and frequent updates. Eventually we divided our monolithic architecture into 35 microservices when we launched our official product. The migration to GKE took around one month, and it turned out to be well worth the effort—our systems became able to offer high scalability and enough resilience to keep its uptime no matter what happened. Now we’re operating 84 workloads and 252 microservices with high stability with remarkably low downtime – less than 0.00001%/year.”
Note from the Founder: “As an AAPI founder based in Silicon Valley, I feel proud of the work ethics and diligence fellow Korean American entrepreneurs and professionals have long demonstrated here. Especially with K-pop breaking into the mainstream, I feel even more proud of our culture that strives toward an absolute perfection molded through years of training and dedication. The mission-driven culture of Silicon Valley coupled with Google’s edging technology and creativity really helped us build a product that not only encompasses verticals but also transcends cultures. Swit is growing at an unprecedented rate, and we hope to join the long list of successful AAPI entrepreneurs here. Swit’s close network with the AAPI community wouldn’t have been possible without Google support. We are grateful for this collaborative environment, and we hope to become the next-generation ambassador for collaboration after Google.”
Check out more from Swit in their founder story.

WISY
Founder: Min Chen
Description: Wisy develops technology to bring digital efficiency into the physical world, supporting consumer products businesses and making them thrive in the new economy. All of us have a bad experience when we can’t find the product we want to buy. That is a $1.9T problem in the consumer-packaged goods industry that Wisy is solving with AI and analytics to help manufacturers and retailers sell more by reducing out-of-stocks and waste at a global scale.
Why GCP: “GCP has an intuitive, easy to use interface, was lower cost, and offered preemptible instances with flexible compute options. Some of the reasons why Wisy decided to use GCP include instance and payment configurability, privacy and traffic security, cost-efficiency, and Machine Learning.
Wisy has been able to advance quickly with product development, as well as collaborate better and iterate faster in the creation of our AI models, while reducing costs by 40%. At Wisy, we are solving a problem that affects everyone who shops at a store.“
Note from the Founder: “Two years ago, I moved to San Francisco to expand my second startup, Wisy. This is when I learned that my name ‘Min’ stands for ‘minority.’ I was born in China, raised in a Black community in Panama, received scholarships to attend both Carnegie Mellon and UC Berkeley. I worked for 20 years in several countries, but I have never felt so discriminated against due to my race, ethnicity, gender and age than during my time in Silicon Valley. However, this is also the place I learned that my diverse life experience is my competitive advantage. My background enables me to recruit and relate to people in different countries, create scalable and flexible products for multinational customers, and run global operations efficiently.
My recommendation to AAPI founders is to find strength in their multicultural background. Don’t hide what makes you unique, do not limit yourselves, and do not let others limit you. You will lose your edge when trading authenticity for validation. Be proud and own your story.”
If you want to learn more about how Google Cloud can help your startup, visit our Startup Program application page here and sign up for our monthly startup newsletter to get a peek at our community activities, digital events, special offers, and more.To learn more about how you can help #StopAsianHate during Asian Pacific American Heritage Month and beyond, visit their website here.
IT Team Figures Out Easiest Way to Build Data Pipelines and Create ML Models

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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.”
Media CDN to Intelligently Deliver Streaming Experiences to Viewers around the World!

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The digital media and entertainment industry is experiencing dramatic growth, as audiences migrate to online experiences and content providers seek to deliver new and innovative content. According to The Global Internet Phenomena Report, streaming video accounted for 53.7% of internet bandwidth traffic, up by 4.8% from a year ago. This rapid growth of over-the-top content is straining existing infrastructure, fueling media companies’ shift to the public clouds with their global presence and greater distribution capacities. In addition, other use cases such as gaming, social networks, AR/VR experiences, and education continue to fuel the need for intelligent media services and operations.
Today, at the 2022 NAB Show Streaming Summit, we’re excited to announce the general availability of Media CDN — a modern, extensible platform for delivering immersive experiences with unparalleled scale and intelligence. Media CDN will enable media and entertainment customers to efficiently and intelligently deliver streaming experiences to viewers anywhere in the world. The same infrastructure that Google has built over the last decade to serve YouTube content to over 2 billion users is now being leveraged to deliver media at scale to Google Cloud customers with Media CDN.
Unparalleled planet-scale reach and scale
Media CDN’s foundational advantage is the Google network. We have invested decades of resources to build tremendous capacity and reach in over 200 countries and more than 1,300 cities around the globe. Modern video applications are sensitive to fluctuations in latency, so getting content closer to users enables higher bitrates and reduces rebuffers, resulting in a superior experience for the end user. Media CDN builds on the success of the existing Cloud CDN portfolio for web and API acceleration and complements it by enabling delivery of immersive media experiences.
In addition to running on planet-scale infrastructure, Media CDN tailors delivery protocols to individual users and network conditions. Media CDN includes out-of-the-box support for QUIC (HTTP/3), TLS 1.3, and BBR, optimizing for last-mile delivery . When the Chrome team rolled out widespread support for QUIC, video rebuffer time decreased by more than 9% and mobile throughput increased by over 7%.
Media CDN also achieves industry-leading offload rates. With multiple tiers of caching, we minimize calls to origin — even for infrequently accessed content. This alleviates performance or capacity stress in the content origin and saves costs. These features are built into the product and seamlessly support customer content hosted on Google Cloud, on-premises, or on a third-party cloud.
“We are excited to leverage Media CDN to continue to deliver an exceptional streaming experience for Stan users across Australia. With Google’s massive network, and a deep reach into the ISPs, we are able to deliver the highest quality video for our users, no matter where they are”—John Hogan, Chief Technology Officer, Stan
“Our mission at U-NEXT is to deliver the highest quality and most entertaining content to our users. Google Cloud’s Media CDN helps us efficiently scale our infrastructure, which is challenging with a vast library of content. Media CDN offloaded 98.3% of requests from our origin server while delivering consistent great quality.”—Rutong Li, Chief Technology Officer, U-NEXT
Broader platform for monetization and immersive experiences
While global distribution is critical for a high-quality end-user experience, it’s only one piece of delivering a world-class platform for immersive experiences. Media CDN offers additional capabilities to enable this transformation — ad insertion, ecosystem integrations and platform extensibility, and powerful AI/ML analytics for interactive experiences.
Streaming providers can improve monetization through integrated ad serving via the Video Stitcher API, which allows manipulation of video content to dynamically insert ads.
Through extensible ecosystem integrations, Media CDN connects customers to key capabilities to simplify their operations. For example, the Transcoder API supports custom streaming formats, while the Live Stream API transcodes mezzanine live signals into direct-to-consumer streaming formats, for multiple device platforms.
Media CDN is built with AI/ML that will give viewers more control over how they see, experience, and even interact with content. For example, sports fans watching a game can obtain real-time stats and analytics, viewers can purchase items from virtual billboards, etc.
Cloud-native and developer-friendly operations
Media companies are under pressure to develop and deploy innovative experiences at a furious pace. Media CDN was built by developers, for developers, with automation and observability built in, giving media providers the speed and flexibility they need to integrate delivery provisioning and management into their content release processes.
Media CDN offers comprehensive APIs and automation tools such as Terraform. Detailed, pre-aggregated metrics and playback tracing make it easy to diagnose performance across the entire infrastructure stack. Real-time visibility is provided via Google Cloud’s operations suite, and integrates with tools that developers already use such as Grafana and ElasticSearch.
“Leveraging the same infrastructure as YouTube, Google Cloud’s Media CDN combines geographic reach, API-first architecture and integration with the Cloud operations suite. This is a transformative move that is aligned with the future of the CDN industry.”— Ghassan Abdo, Research Vice President, WW Telecom, Virtualization and CDN, IDC
“Viewers around the world are demanding best-in-class video quality and performance across modes of consumption. A video-first delivery network can be a game changer in this space. We’re excited to partner with Google Cloud and to leverage Media CDN to enable premium video experiences and customer engagements.”—Juan Martin, Founder and CTO, Firstlight Media
Planet-scale advanced security
Media CDN lets streaming media providers take advantage of Google’s decades-long experience delivering video safely, securely, and reliably. The platform includes deep integration with Google Cloud Armor for planet-scale DDoS protection and a rich set of capabilities to detect and mitigate attacks, prevent abuse, manage risk, and comply with regulatory or licensing requirements.
If you want to deliver rich, immersive experiences to global audiences with an extensible, modern delivery platform, we’d love to hear from you. For more information, including technical specifications and platform architecture, please visit cloud.google.com/media-cdn. To get started with Media CDN, contact your sales team.
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