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Easy Telemetry Instrumentation on GKE with the OpenTelemetry Operator In recent years, the application monitoring landscape has exploded with instrumentation libraries, SDKs, and backends for storage and visualization. But a major friction point is still the investment required to instrument applications with these libraries, and libraries are often tied to a small set of telemetry …

Easy Deployment of MEAN stack with MongoDB Atlas, Cloud Run, and Terraform Serverless computing promises the ability to spend less time on infrastructure and more time on developing your application. But historically, if you used serverless offerings from different vendors you didn’t see this benefit. Instead, you often spent a significant amount of time configuring …

In the context of Natural Language Processing (NLP), topic modeling is an unsupervised learning problem whose goal is to find abstract topics in a collection of documents. Topic Modeling answers the question: “Given a text corpus of many documents, can we find the abstract topics that the text is talking about?” In this tutorial, you’ll: Learn about two …

Once you have identified who a user is (authenticated them) using Cloud Identity, the next step is to define what they can do on Google Cloud (authorize them) so they can access the resources they are permitted to use. Access control for Google Cloud resources is managed by Cloud IAM policies for humans and by …

Geospatial data has many uses outside of traditional mapping, such as site selection and land intelligence. Accordingly, many businesses are finding ways to incorporate geospatial data into their data warehouses and analytics. Google Earth Engine and BigQuery  are both tools on Google Cloud Platform that allow you to interpret, analyze, and visualize geospatial data. For …

Plea and the Pledge: Truly Serverless As modern application developers, we’re juggling many priorities: performance, flexibility, usability, security, reliability, and maintainability. On top of that, we’re handling dependencies, configuration, and deployment of multiple components in multiple environments and sometimes multiple repositories as well. And then we have to keep things secure and simple. Ah, the …

In January, we previewed Neo4j’s and Google Cloud Vertex AI’s partnership in a blog about how you can use graphs for smarter AI when using Neo4j AuraDS to generate graph embeddings. This blog post garnered a lot of attention from data scientists looking to amplify their machine learning (ML) pipelines by feeding knowledge (graph features) …

Two weeks ago, we announced the Chrome Enterprise Connectors Framework, enabling plug-and-play integrations with industry-leading security solutions and platforms. Together with our security partners, this new framework will help organizations work toward a Zero Trust model to keep their corporate data and users secure.   With enterprise security being our shared top priority, Splunk, the …

How many times have you filled out forms requesting personal information? It’s probably too many times to count. When online and signed in, you can save a lot of time thanks to your browser’s autofill feature. In other cases, you often have to provide the same data manually, again and again. The first Document AI …

Cloud Storage as a File System in Vertex AI User Managed Notebooks What if I told you there is no need to `gsutil cp -r `? If you’ve developed machine learning models before, you know that data quality and governance issues are predominant. When developing models, you’ll spin up a Vertex AI Workbench Jupyter Notebook …