DigitalOcean vs Google Cloud Platform

August 19, 2023 | Author: Michael Stromann
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DigitalOcean
The developer cloud helping millions of developers easily build, test, manage, and scale applications of any size – faster than ever before.
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Google Cloud Platform
Google Cloud Platform is a set of modular cloud-based services that allow you to create anything from simple websites to complex applications. Cloud Platform provides the building blocks so you can quickly develop everything from simple websites to complex applications. Explore how you can make Cloud Platform work for you.
DigitalOcean and Google Cloud Platform (GCP) are two prominent cloud service providers with distinct offerings. DigitalOcean is known for its simplicity, developer-friendly environment, and cost-effective solutions. It specializes in providing virtual private servers (Droplets) and offers a straightforward interface, quick deployment, and competitive pricing. DigitalOcean is popular among developers and small to medium-sized businesses seeking an easy-to-use platform with reliable performance.

On the other hand, Google Cloud Platform (GCP) is a comprehensive cloud computing platform that caters to a wide range of users, from startups to large enterprises. GCP offers a vast array of services, including compute, storage, networking, AI, machine learning, and big data analytics. It leverages Google's infrastructure and advanced technology to deliver high scalability, global reach, and powerful data processing capabilities. GCP's ecosystem also integrates well with other Google services, providing seamless integration and a unified experience.

See also: Top 10 Public Cloud Platforms
DigitalOcean vs Google Cloud Platform in our news:

2024. Google injects generative AI into its cloud security tools


Google has rolled out a suite of new cloud-based security offerings alongside updates to its existing lineup, targeting enterprises handling extensive, multi-tenant networks. Among these introductions is Gemini in Threat Intelligence, a fresh addition to Google's Mandiant cybersecurity platform, harnessing Gemini's capabilities. Currently available for public preview, Gemini in Threat Intelligence empowers users to analyze significant volumes of potentially malicious code, conduct natural language searches for ongoing threats or signs of compromise, and distill insights from open source intelligence reports across the internet. And in Security Command Center, Google’s enterprise cybersecurity and risk management suite, a new Gemini-driven feature lets security teams search for threats using natural language while providing summaries of misconfigurations, vulnerabilities and possible attack paths.


2022. Google Cloud will shutter its IoT Core service next year



This week, Google Cloud made the announcement that it will be discontinuing its IoT Core service, allowing customers a one-year timeframe to transition to a partner for the management of their IoT devices. Google believes that relying on partners to handle the process on behalf of customers is a more effective approach. A Google spokesperson explained, "Since the launch of IoT Core, it has become evident that our customers' needs can be better met by our network of partners who specialize in IoT applications and services. We have diligently worked to offer customers migration options and alternative solutions, and we are providing a year-long transition period before discontinuing IoT Core."


2022. Google expands Vertex, its managed AI service, with new features



Roughly one year ago, Google introduced Vertex AI, a managed AI platform designed to expedite the deployment of AI models for businesses. Today, Google has announced upcoming enhancements for Vertex, including a dedicated server for AI system training and the introduction of "example-based" explanations. As Google has consistently emphasized, Vertex offers the advantage of integrating Google Cloud services for AI within a unified user interface (UI) and application programming interface (API). According to Google, notable customers such as Ford, Seagate, Wayfair, Cashapp, Cruise, and Lowe's utilize Vertex to construct, train, and deploy machine learning models within a single environment, effectively transitioning from experimental stages to production.


2020. Cloud for developers DigitalOcean raises $50M



DigitalOcean, a leading cloud provider for developing modern applications, has announced the successful closure of a $50 million Series C funding round. The funding was led by Access Industries, with participation from Andreessen Horowitz. DigitalOcean Cloud offers simplified app creation capabilities for a wide range of developers, including individuals, startups, and small to medium-sized businesses. With its infrastructure and platform-as-a-service (IaaS and PaaS) solutions, DigitalOcean provides a seamless experience that eliminates the need for extensive DevOps expertise. This empowers developers to dedicate their efforts towards building innovative software. Following this funding round, the company's valuation has reached $1.15 billion, indicating a significant increase from its pre-money valuation of $1.1 billion.


2020. Cloud infrastructure provider DigitalOcean raises $100M



DigitalOcean, a cloud infrastructure provider with a focus on smaller businesses and younger companies, has announced today that it successfully raised $100 million. Unlike traditional sales-driven models, DigitalOcean operates as a self-serve SaaS business, allowing users to easily get started without requiring assistance. This approach avoids the costly and time-consuming sales cycles. However, while the convenience of self-signup appeals to small companies, this acquisition method often leads to high customer turnover. To address this, DigitalOcean is dedicated to establishing a niche in SMB and developer-oriented cloud infrastructure, maintaining favorable economics through low customer acquisition costs and self-service revenue generation. The profits generated from this approach sustain the company's growth, enabling it to invest in itself through debt rather than equity. Overall, this unexpected news adds an exciting element to the day.


2019. Google Cloud gets a new family of cheaper general-purpose compute instances



Google Cloud has recently introduced its new E2 family of compute instances, specifically designed for general-purpose workloads. These instances offer a significant cost advantage, delivering savings of approximately 31% when compared to the existing N1 general-purpose instances. Moreover, the new system incorporates enhanced intelligence in terms of VM placement, granting the flexibility to migrate them to alternative hosts as required. To achieve these advancements, Google has developed a custom CPU scheduler. Unlike comparable alternatives offered by other cloud providers, E2 VMs from Google can sustain high CPU loads without artificial throttling or complex pricing structures. It will be intriguing to witness benchmark tests that compare the performance of the E2 family against similar offerings from AWS and Azure.


2018. Google Cloud adds new applications performance monitoring tool



Google has introduced a significant addition for developers working on applications within the Google Cloud Platform. They now have access to a comprehensive suite of application performance management tools known as Stackdriver APM. This suite empowers developers to directly track and address issues within the applications they have built, eliminating the need to rely solely on operations teams. The underlying idea is that developers, being intimately familiar with the code, are best positioned to comprehend the signals emanating from it. Stackdriver APM consists of three primary tools: Profiler, Trace, and Debugger. While Trace and Debugger were already available, the integration of Profiler allows all three tools to seamlessly collaborate in identifying, monitoring, and resolving code-related issues.


2018. Google Compute Engine adds simple machine learning service


Google has introduced AutoML, a groundbreaking service available on Google Compute Engine that empowers developers, even those without prior machine learning (ML) expertise, to construct personalized models for image recognition. The scarcity of machine learning experts and data scientists in today's market is widely acknowledged. To address this challenge, Google's new service enables virtually anyone to submit their images, upload them (and import or create tags within the application), and automatically generate a custom machine learning model using Google's advanced systems. The entire process, from data importation to tagging and model training, is facilitated through a user-friendly drag and drop interface. It's important to note that this service goes beyond the capabilities of Microsoft's Azure ML studio, which offers a Yahoo Pipes-like interface for model building, training, and evaluation.


2017. Google Cloud Platform cuts the price of GPUs by up to 36 percent



Google is implementing a price reduction for Nvidia's Tesla GPUs on its Compute Engine service, with savings of up to 36 percent. In U.S. regions, the cost of utilizing the slightly older K80 GPUs has been reduced to $0.45 per hour, while the more advanced and powerful P100 machines will now cost $1.46 per hour, both with per-second billing. By doing so, Google aims to attract developers who seek to execute their own machine learning workloads on its cloud platform. Additionally, various other applications, such as physical simulations and molecular modeling, can greatly benefit from the extensive number of cores provided by these GPUs.


2017. Google Cloud Platform gets a cheaper, lower-performance networking tier



Google is introducing a new networking option for users of its Cloud Platform that offers a more affordable solution. Developers now have the choice between a premium tier, which prioritizes routing traffic over Google's high-speed networks to minimize distance and hops, and a standard tier, which relies on the public internet with potential slowdowns and additional hops. The standard tier is priced 24-33 percent lower than the premium tier in North America and Europe. However, Google applies different pricing models to each tier. The premium tier's pricing is based on the source and destination of the traffic, accounting for the distance it travels over Google's network. In contrast, the standard tier's prices are determined solely by the source location. This new offering provides Cloud Platform users with increased flexibility and cost savings depending on their networking requirements.

Author: Michael Stromann
Michael is an expert in IT Service Management, IT Security and software development. With his extensive experience as a software developer and active involvement in multiple ERP implementation projects, Michael brings a wealth of practical knowledge to his writings. Having previously worked at SAP, he has honed his expertise and gained a deep understanding of software development and implementation processes. Currently, as a freelance developer, Michael continues to contribute to the IT community by sharing his insights through guest articles published on several IT portals. You can contact Michael by email stromann@liventerprise.com