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Posts by tag

Design

17 posts
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  • 3 min
  • Computing
  • Design
  • Multi-Cloud

Why Is Your Multicloud So Slow?

Many complain about the performance of their multicloud deployments these days, and for good reasons. Here are a few areas to look for answers. It’s a Wednesday, and the accounting team is closing out this month’s sales and running end-of-month processing on a multicloud platform deployed four months ago. They run sales order entries on one cloud provider and the accounting application on another. Spanning both clouds is a common security system and API manager, among other services. What took only a few hours last month to process from start to finish now takes almost a day. You get an…
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  • 4 min
  • Design
  • Engineering

The ABCs Of Building Reliable, Scalable, And Maintainable Web Applications – Reliability

Reliability, Scalability, and Maintainability are some of the least understood concepts of application development. Even with little understanding of these topics, many developers use them on a day-to-day basis during their work conversations. A proper and sound understanding of these concepts enables you to make proper use of these terminologies and think effectively to enforce these vital concepts in applications you build. As online applications get more sophisticated, efficient scalability, dependability, and maintainability, become increasingly important to ensure smooth performance and user pleasure. Effectively handling these parts of web app development can be difficult, especially for developers who are new…
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  • 5 min
  • Design
  • Engineering

How To Improve Query Speed To Make The Most Out Of Your Data

The world is getting more and more value out of data, as exemplified by the currently much-talked-about ChatGPT, which I believe is a robotic data analyst. However, in today’s era, what’s more important than the data itself is the ability to locate your wanted information among all the overflowing data quickly. So in this article, I will talk about how I improved overall data processing efficiency by optimizing the choice and usage of data warehouses. Too Much Data on My Plate The choice of data warehouses was never high on my worry list until 2021. I have been working as…
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  • 3 min
  • Cloud-Native
  • Computing
  • Design
  • Engineering

The Downsides Of Cloud-Native Solutions

A recent study by Gartner predicts that by 2025 more than 95% of application workloads will exist on cloud-native platforms (up from 30% in 2021). I tend not to believe these kinds of predictions because adoption is never linear. We run out of applications that are easy to convert to new development approaches (in this case, cloud native) and thus adoption slows down or ceases much earlier than most understand. If you’re still a bit confused by what the heck “cloud native” means, you’re not alone. Here’s my best explanation:  Cloud-native development is the process of designing, building, and running applications in…
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  • 8 min
  • Design
  • Engineering

6 Common Mistakes To Avoid In RESTful Web API Design

Imagine ordering a “ready-to-assemble” table online, only to find that the delivery package did not include the assembly instructions. You know what the end product looks like, but have little to no clue how to start assembling the individual pieces to get there. A poorly designed API tends to create a similar experience for a consumer developer. Well designed APIs make it easy for consumer developers to find, explore, access, and use them. In some cases, good quality APIs even spark new ideas and open up new use cases for consumer developers. There are methods to improve API design —…
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  • 5 min
  • Design
  • Engineering

4 Low-Effort, High-Impact Ways To Cut Your GKE Costs (And Your Carbon Footprint)

Controlling cloud costs is always top-of-mind for organizations. But how? It can be difficult to surface wasted resources and figure out how best to optimize them without sacrificing performance or availability. Here on the Google Kubernetes Engine (GKE) team, we’re eager to help in any way we can. And after participating in some recent capacity planning exercises of our own, we couldn’t help but notice that there are some low-hanging fruit when it comes to optimization opportunities: According to our internal research, up to one in ten of clusters across the GKE fleet is idle at any given time. Further,…
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  • 4 min
  • Computing
  • Design
  • Engineering

Flexible Committed Use Discounts — A Simple New Way To Discount Compute Engine Instances

Saving money never goes out of style. Today, many of our customers use Compute Engine resource-based committed use discounts (CUDs) to help them save on steady-state compute usage within a specific machine family and region. As part of our commitment to offer more flexible and easy ways for you to manage your spend, we now offer a new type of committed use discount for Compute Engine: flexible CUDs. Flexible CUDs are spend-based commitments that offer predictable and simple flat-rate discounts (28% off 1-year, and 46% off 3-years) that apply across multiple VM families and regions. Similar to resource-based CUDs, you…
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  • 2 min
  • Design
  • Engineering

How UX Researchers Make Google Cloud Better With User Feedback

Customer experiences are critical to user experience (UX) researchers at every level of developing Google Cloud products. Whether it’s migrating a user to Google Cloud, helping them understand it once they are there, or delving into using Cloud services, one thing is clear: learning from the people who use Google Cloud is fundamental. Understanding our users UX researchers touch various points of the customer journey, like migration, cloud operations, and data analytics. In each of these areas, understanding the customer’s business needs and goals grants the UX researcher greater insight into how to provide the best possible experience. This is…
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  • 7 min
  • Data
  • Design
  • Engineering

Benchmarking Your Dataflow Jobs For Performance, Cost And Capacity Planning

Calling all Dataflow developers, operators and users…So you developed your Dataflow job, and you’re now wondering how exactly will it perform in the wild, in particular: How many workers does it need to handle your peak load and is there sufficient capacity (e.g. CPU quota)? What is your pipeline’s total cost of ownership (TCO), and is there room to optimize performance/cost ratio? Will the pipeline meet your expected service-level objectives (SLOs) e.g. daily volume, event throughput and/or end-to-end latency? To answer all these questions, you need to performance test your pipeline with real data to measure things like throughput and…
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  • 6 min
  • Engineering
  • Practices

Spatial Clustering On BigQuery – Best Practices

Most data analysts are familiar with the concept of organizing data into clusters so that it can be queried faster and at a lower cost. The user behavior dictates how the dataset should be clustered: for example, when a user seeks to analyze or visualize geospatial data (a.k.a location data), it is most efficient to cluster on a geospatial column. This practice is known as spatial clustering, and in this blog, we will share best practices for implementing it in BigQuery (hint — let BigQuery do it for you). BigQuery is a petabyte-scale data warehouse that has many geospatial capabilities…
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