Google Cloud Platform Solutions and Technologies
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How do you quantify user happiness? It’s not easy to measure directly in our systems, but we can look for signals in the user journey. You may experience an outage or other problem that internally seems relatively small, but your users take to Twitter in droves and express their displeasure. Or, you may have a catastrophic event but receive few or no complaints from end users. It is impossible to get inside your users’ heads and see whether they are happy or not while using your service.To overcome this problem, we use the happiness metrics also known as Service Level Indicators (SLIs). SLIs specify, measure, and track user journey success. They are quantifiable measures of reliability. SLIs tell you whether you are in or out of compliance with your SLO targets and are therefore in danger of making users unhappy.Once you choose the services you want to measure, you can then think about the SLIs that you will use to measure users common tasks and critical activities. Choosing SLIs tha
Increasing visibility into our systems, code, and repositories is essential for effective DevOps processes. Previously repository audit logging was available for Docker repositories, but Google Cloud has expanded the capability to include Maven, npm, and Python repositories as well! This is a boon for visibility and monitoring! You can read about how to configure the monitoring by following the link included in this post.How have you implemented monitoring for your repositories? How mature is your organization in providing automated alerting and monitoring? Do you use the audit logging capabilities Google Cloud provides?https://cloud.google.com/artifact-registry/docs/audit-logging
Celebrate Juneteenth 2022! Learn more about Juneteenth and it’s significance, watch the video and learn about how “Juneteenth developed as a jubilee celebration in Texas and then how it moved from a regional holiday to a National one; becoming what is now known as Juneteenth National Independence Day.” Spend the Day Learning- https://www.cloudskillsboost.google/paths This Hands-on Lab focuses on Identifying Bias in Mortgage Data using Cloud AI Platform and the What-if Tool https://www.cloudskillsboost.google/focuses/10903?locale=it&parent=catalog
Let’s say it’s the first day in your new job and you have lots of questions. Where is the HR department located or how do I validate parking? Wouldn’t it be great if you could just ask a chatbot rather than reading through an internal Wiki? Here is a recipe to build one: Select your reference documents and pre-process them in Vertex AI Workbench Download a model from TensorFlow Hub and register with Vertex AI Have Vertex AI process your questions and answers Use Cloud Functions for your REST endpoint Use the Speech-To-Text and Text-To-Speech APIs to allow users using their voice rather than typing Sounds complicated? Nikita Namjoshi and Zack Akil demonstrate in this 16 minutes Google Cloud Applied ML Summit video how to do just that.https://youtu.be/5iSmX8sqtx8
Hi there! I’m new to the community and wondering if anyone knows of any GCP-compatible platforms out there to help us with create an app (software development). I don’t yet have a tech team, and I am not that technical - I’d like to build my MVP and launch it via the Google Play and App Store. I’ve looked into AppSheets but I dont think that will solve our needs. Our startup is in the healthcare space, so we need HIPAA compliance out of the gate as well for data collection. Finally, no matter what, it’s important to me that we own the source code of whatever we’re building - I am not interested in giving up equity for services at this stage. Thank you and I’m super glad to meet you all!
DIY Dialogflow CXUseful links and documentation:https://codelabs.developers.google.com/codelabs/dialogflow-cx-retail-agent#0Build a retail virtual agent from scratch with Dialogflow CX - Ultimate Chatbot Tutorials I am working on an Online course about Chatbots and would be happy to collect interesting links and more information on the implementation of Dialogflow CX.
Let us introduce you to our AI & ML Moderator: Markus KoyUsername: markuskBio:Markus is the founder of thefluent.me and a Google Build Partner and AI enthusiast based in Vancouver, British Columbia. Markus has 18 years of experience as a Business Analyst, IT Project Manager, IT Consultant, Strategic Controller, and Developer. Born and raised in Germany, Markus immigrated to Canada in 2008. His hobbies include fishing, snowshoeing, and hiking. Fine out more about Markus and thefluent.me here: https://community.c2cglobal.com/product-updates/using-ai-to-improve-spoken-language-fluency-with-markus-koy-founder-of-thefluent-me-1628Company: thefluent.meJob Title: Founder/ Owner
Have you thought about using machine learning to solve a problem but you are not sure if you can solve it fast with ML? If you decide you want to give it a try, but you don’t have much time to build a model from scratch, what are your options? And finally, what if you do not have enough data to train the model? Dale Markowitz, Applied AI Engineer at Google, provides a fast overview on how to approach these questions in this 13 minutes I/O 2022 video. https://youtu.be/BjTNJSQLIeA
Network Analyzer offers an out-of-the-box suite of always-on analyzers that continuously monitor GCE and GKE network configuration. These analyzers run in the background, monitoring network services like load balancers, hybrid connectivity, and connectivity to Google services like Cloud SQL. As users continually push out config changes or the metrics for their deployment changes, the relevant analyzers will automatically surface failure conditions or suboptimal configurations. Surfacing insights through Network AnalyzerNetwork Analyzer prioritizes and proactively surfaces insights to users at a project level or across multiple projects. It identifies the root cause of the surfaced insight and provides a link to the documentation with recommendations to fix the insight. 👉Read further Introducing Network Analyzer: detect service and network issues | Google Cloud Blog
The Data Cloud & ML Asia Pacific Summit is coming live to your screens, this 21-22 June! See how unified data solutions and the best in #ML can unlock limitless innovation in your business. Get ready for:Real world use cases Product demos Hands-on labs Register now [LINK]
On June 14th we're hosting BigQuery ML: Easy Access to Machine Learning.Join Mike Walker and Rob Vogelbacher, AI/ML Specialist Customer Engineers at Google Cloud, for a one-hour BigQuery Machine Learning overview and deep dive including:- Why your analytics data should be in BigQuery- BigQuery ML capabilities- Demos and getting started with BigQuery MLRegister here: https://community.c2cglobal.com/events/bigquery-ml-easy-access-to-machine-learning-139
The Google Cloud DevOps Research and Assessment (DORA) team is always hard at work. I am looking forward to their 2022 Accelerate State of DevOps Report, coming soon to a blog near you. In the meantime, check out the included link for access to the first chapter of the DevOps Enterprise Guidebook.https://cloud.google.com/blog/products/devops-sre/devops-enterprise-guidebook-chapter-1This free guidebook will provide “a concrete action plan for implementing recommendations using Google Cloud’s DORA research to initiate performance improvements.” (from the included article). The first chapter sets the stage for the remaining chapters of the book. It provides information on DORA, the Capabilities Assessment, and some initial steps to take to improve your company’s performance.I’m looking forward to reading the next chapter!What was your biggest takeaway from reading chapter 1?
A Fun Bakery Story Explains Cloud Service Models, Software vs Platform vs Infrastructure, and Which service to Use!
In our digital life and business, we use a lot of cloud services. Cloud serves us in many different ways. The most common service models are Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS).What does "as a service" mean?what are the differences between Software, Platform, and Infrastructure?Which cloud service model shall we use for our life and business?Good questions! Let me explain, in a simple story, a fun bakery story… (Hi, I am Della, I am a cloud professional, IT professor, and learning designer. I want to help you understand complicated cloud concepts, in simple and fun stories!You can find more from my channel “Simple ‘it’ Story Shows” for IT explainers animated videos)Yes, Cloud is complicated. But you can understand "it", one story at a time, and have fun!
Often called the sexiest career of the twenty-first century and the fastest-growing field in tech right now – the effect of Data Science in today's world may seem more mysterious and a difficult field to venture into for those outside the bounds technical field. Let us discover the best sources to learn data science online. To begin let us first explain what data science is and what the job entails.Data Science explainedData science is a subject that entails the gathering and analysis of data – both structured and unstructured – in order to generate insights and information that can be used by businesses to develop effective strategies. Patterns can assist data scientists to detect trends and provide recommendations to stakeholders that will help them locate new market opportunities, improve efficiency, lower costs, and gain a competitive advantage in their sector by collecting and analyzing data over time.Why should you study data science?A large amount of data is generated every day
Hello,I am working with a developer on how to create an app that uses Face Recognition (Vision API product). How do I connect the app to the vision API so the app works with the Vision API? I have not found the documentation that shows how to connect the two, so it can work as one. Can someone share the documentation or strategy on how to make it work?
Here are the latest updates, products, services and resources from GCP security teams on May: PSP protocol now open source: In order to better scale the security GCP offer their customers, they created a new cryptographic offload protocol for internal use that they open sourced in May. Intentionally designed to meet the requirements of large-scale data-center traffic, the PSP Protocol is a TLS-like protocol that is transport-independent, enables per-connection security, and is offload-friendly. Updating Siemplify SOAR: The future of security teams is heading towards “anywhere operations,” and the latest version of Siemplify SOAR can help get us there. It gives organizations the building blocks needed across cloud infrastructure, automation, collaboration, and analytics to accelerate processes for more timely responses and automated workflows. In turn, this can free up teams to focus on more strategic work. Guardrails and governance for Terraform: Popular open-source Infrastruct
Let us introduce you to our DevOps and SRE Moderators: Jennifer Bergstrom.Username: jennworks40Bio:Jenn Bergstrom is a multi-cloud solution architect with experience building cloud native solutions to meet complex customer requirements. She has over 15 years of experience in the software industry, with a focus over the last 5 years on Cloud, DevSecOps, and Chaos Engineering. Jenn enjoys helping others to grow in their knowledge and believes that mentoring is an imperative. Her curiosity and passion for learning has led to recognition as a Parsons Fellow for her cloud expertise and to opportunities to present at international summits and conferences. When not working to grow the community of cloud engineers, Jenn enjoys spending time enjoying nature’s beauty with her husband and two daughters, reading, and creating art.Company: ParsonsJob Title: PARSONS X Senior Technical Director Ahmed Tariq. Username: ahmedtariq1Bio:Hi, I'm Ahmed! I'm doing my bachelors in Computer science fro
The Applied ML Summit is exactly a week away! Here are the top three reasons you should join our event: Our opening keynote: Hear from Andrew Moore, VP and General Manager of Cloud AI and Industry Solutions at Google Cloud, and Priyanka Vergadia, Developer Advocate at Google Cloud, on accelerating the deployment of predictable ML in production. Insights in practitioner sessions: Discover how data scientists and ML experts at companies like Vodafone, Glance, General Mills, H&M, and CNA Insurance are developing, deploying, and safely managing long-running, self-improving AI services with Google Cloud. The latest product announcements: Be among the first to find out about the newest capabilities across Vertex AI, BigQuery ML, AutoML, and our integrated data services.Click here to register today!
Get started with Google Cloud training and certification on June 2.Event details as received and seen in website:Discover how training and certification can positively impact your career development, and your organization’s success with tomorrow’s no-cost training webinar from the Google Cloud Learning team.Explore the breadth of Google Cloud role-based training and certifications. Discover where to get started, how to earn learning credentials, and how training and certification can impact your career development and your organization's success. Check below link to register: Google cloud certifications webinar Listen from the experts on Google Cloud certifications. Have a great day 😊
Machine Learning (ML) model code accounts for approximately 5% of the total code needed to train, deploy, and run ML models in production according to Google research. The goal of MLOps is a production-level process, similar to DevOps, but with data as a first-class citizen. Robert Crowe, Tensorflow Developer Engineer, introduces TFX, an open-source project, in this 13 minutes I/O 2022 video. If you are interested in getting started with MLOps, this video is for you.https://io.google/2022/program/8f7765f2-2357-4829-8c87-e54d81e999a0/
PostgreSQL uses transaction IDs (also called TXIDs or XIDs) to implement Multi-Version Concurrency Control semantics (MVCC).To prevent transaction ID wraparound, PostgreSQL uses a vacuum mechanism, which operates as a background task called autovacuum (enabled by default), or it can be run manually using the VACUUM command. A vacuum operation freezes committed transaction IDs and releases them for further use. You can think of this mechanism as “recycling” of transaction IDs that keeps the database operating despite using a finite number to store the transaction ID.Vacuum can sometimes be blocked due to workload patterns, or it can become too slow to keep up with database activity. If transaction ID utilization continues to grow despite the freezing performed by autovacuum or manual vacuum, the database will eventually refuse to accept new commands to protect itself against TXID wraparound. To help you monitor your database and ensure that this doesn’t happen, Cloud SQL for PostgreSQL
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