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Someone on Linkedin recently brought up the point that companies could save gobs of money by swapping out AWS Python lambdas for Rust ones. At least it’s an excuse to […] The post AWS Lambdas – Python vs Rust. While it raised the ire of many a Python Data Engineer, I thought it sounded like a great idea.
13 June 2023: AWS. The largest AWS region (us-east-1) degraded heavily for 3 hours, impacting 104 AWS services. We did a deepdive into this incident earlier in AWS’s us-east-1 outage. We’ll also learn how this article contributed to AWS publishing its first public postmortem in two years!
Recently, I’ve encountered a few projects that used AWS DMS, which is almost like an ELT solution. It was interesting to see AWS DMS used in this manner. As… Read more The post What Is AWS DMS And Why You Shouldn’t Use It As An ELT appeared first on Seattle Data Guy. But it’s not what DMS was built for.
Well, everyone is abuzz with the recently announced S3 Tables that came out of AWS reinvent this year. I tried them out, in real life that is, not just some marketing buzz, and it will leave most people, not all, be […] The post AWS S3 Tables. I’m going to call fools gold on this one right out of the gate.
Inside an AWS Lambda. I also enjoy doing simple things, things that have a “real-life” feel to them. I suppose I could be like the others […] The post Polars vs Pandas. appeared first on Confessions of a Data Guy.
Checkout this video where I dive into how I build just such a Lake House using Modern Data Stack tools like […] The post Building a Fast, Light, and CHEAP Lake House with DuckDB, Delta Lake, and AWS Lambda appeared first on Confessions of a Data Guy.
What was not clear, or easy, was trying to figure out how DuckDB would LIKE to read default AWS […] The post DuckDB … reading from s3 … with AWS Credentials and more. appeared first on Confessions of a Data Guy.
Jia Zhan, Senior Staff Software Engineer, Pinterest Sachin Holla, Principal Solution Architect, AWS Summary Pinterest is a visual search engine and powers over 550 million monthly active users globally. Pinterests infrastructure runs on AWS and leverages Amazon EC2 instances for its compute fleet. 4xl with up to 12.5 4xl with up to 12.5
Snowflake provides detailed usage insights, but integrating this data with AWS CloudWatch using External Functions allows organizations to track cost in real-time, set up alerts, and optimize warehouse utilization. What if we could integrate Snowflake warehouse cost tracking with AWS CloudWatch? link] Create the API Integration.
Understanding the AWS Shared Responsibility Model is essential for aligning security and compliance obligations. The model delineates the division of labor between AWS and its customers in securing cloud infrastructure and applications. Let us begin by defining the Shared Responsibility Model and its core purpose in the AWS ecosystem.
This article is for anyone looking to maximize their use of Amazon Web Services (AWS) generative AI (GenAI) services. Here are eight courses that range from beginner to expert level.
For a lot of my Data Engineering career I didn’t really think about or use AWS lambdas, I just saw them as little annoying flies […] The post AWS Lambdas. I guess I’ve taken them for granted over the years, even though they are incredibly useful. Useful for Data Engineering?
Introducing Serverless Support for AWS Instance Profiles: Uniform Data Access At Databricks, we continuously strive to simplify data access and drive innovation across.
There is an increasing number of cloud providers offering the ability to rent virtual machines, the largest being AWS, GCP, and Azure. How the product works: they currently monitor four cloud providers (AWS, GCP, Hetzner Cloud, Azure.) We envision building something comparable to AWS Fargate , or Google Cloud Run.
This is where the AWS data lake comes in. With the AWS data lake, organizations and businesses can store, analyze, and process structured and unstructured data of any size. Digital tools and technologies help organizations generate large amounts of data daily, requiring efficient governance and management.
We had a jam-packed week alongside more than 60,000 attendees at Amazon Web Services (AWS) re:Invent, one of the largest hands-on conferences in the cloud computing industry. To learn more about these recent developments on generative AI and integrations with AWS, tune in to BUILD, Snowflake’s upcoming virtual conference for developers.
Introduction S3 is Amazon Web Services cloud-based object storage service (AWS). It stores and retrieves large amounts of data, including photos, movies, documents, and other files, in a durable, accessible, and scalable manner.
The company racked up huge bills for the likes of AWS, Snowflake, and also Datadog. Prometheus can be self-hosted, but several cloud providers also offer managed Prometheus services: both Google Cloud and AWS have this service in production, while Azure has it in preview. We hit an all time high in our monthly transacting users of 11.4
“Of what use is, and what good does the best and most advanced architecture […] The post Fleetclusters for Databricks + AWS to reduce Costs. Here is my question, riddle me this all you hobbits. appeared first on Confessions of a Data Guy.
Today, we’re excited to announce the general availability of the Snowflake Native App Framework on AWS and Azure! The post Snowflake Native App Framework Now Generally Available on AWS and Azure appeared first on Snowflake. We’ve seen incredible momentum around Snowflake Native Apps.
Introduction Amazon Athena is an interactive query tool supplied by Amazon Web Services (AWS) that allows you to use conventional SQL queries to evaluate data stored in Amazon S3. Athena is a serverless service. Thus there are no servers to operate, and you pay for the queries you perform.
For Databricks and AWS, its not just about building togetherits about helping businesses succeed together. At AWS re:Invent. What makes a great partnership?
Introduction Amazon Redshift is a fully managed, petabyte-scale data warehousing Amazon Web Services (AWS). It allows users to easily set up, operate, and scale a data warehouse in the cloud. Redshift uses columnar storage techniques to store data efficiently and supports data warehousing workloads intelligence, reporting, and analytics.
After Zynga, he rejoined Amazon, and was the General Manager (GM) for Compute services at AWS, and later chief of staff, and advisor to AWS executives like Charlie Bell and Andy Jassy (Amazon’s current CEO.) The AWS re:invent conference in 2022 hosted a good in-depth overview of Amazon’s COE process.
We have seen other similar stories play out recently: In 2021, Elastisearch faced a similar “freerider” challenge from AWS. In response, AWS, GCP, Oracle, Snap and others are backing – and migrating to – the Valkey fork, which remains open source. In response, Elasticsearch ceased being open source.
AWS Infrastructure costs 4.3 Introduction 2. Objective 3. Prerequisite 4.2 Data lake structure 5. Code walkthrough 5.1 Loading user purchase data into the data warehouse 5.2 Loading classified movie review data into the data warehouse 5.3 Generating user behavior metric 5.4. Checking results 6. Tear down infra 7. Design considerations 8.
A lot of missing values in the dataset can affect the quality of prediction in the long run. Several methods can be used to fill the missing values and Datawig is one of the most efficient ones.
With Provisional Throughput (public preview soon on AWS), customers can reserve dedicated throughput, ensuring consistent and predictable performance for their workloads. Additionally, we launched cross-region inference , allowing you to access preferred LLMs even if they aren’t available in your primary region.
Introduction Data Proposed Workflow AWS Cloud Components Collecting the Data (Lambda Function 1) Writing the Data to the Table (Lambda Function 2) Converting the data in CSV
” Other registrars Other providers which several developers recommended, in order of popularity: AWS Route 53 : the obvious choice for those already on AWS. AWS uses Gandi under the hood for many of its domains. We see ourselves in the industry and reinforce that we as a registrar are not going away anytime soon!”
Unistore is made possible by Hybrid Tables (now generally available on AWS commercial regions with a few exceptions ), which enables fast, single-row reads and writes in order to support transactional workloads.
As noted in our previous blog post, our initial attribution approach relied on Sonar , an internal IP address tracking service that emits an event whenever an IP address in Netflixs AWS VPCs is assigned or unassigned to a workload. Netflixs cloud microservices operate across multiple AWS regions. With 30 c7i.2xlarge
The authorization furthers Snowflake’s commitment to helping our government customers secure and mobilize their mission-critical data It’s a milestone moment for Snowflake to have achieved FedRAMP High authorization on the AWS GovCloud (US-West and US-East Regions). Find out how Snowflake is leveraging modern data to advance national defense.
AWS launched in 2006, Azure in 2010, and GCP launched its first region in 2015. The segment really took off around 2018, although Cloud9 – which AWS acquired in 2017 – was founded in 2010. But the most recent 10 years suggest this is no longer the case. The Cloud is spreading and offering more capabilities.
Inference: Model Serving in Snowpark Container Services, now generally available in both AWS and Azure, offers easy and performant distributed inference with CPUs or GPUs for any model, regardless of where it was trained. Snowflake ML now also supports the ability to generate and use synthetic data, now in public preview.
Amazon Web Services (AWS) has also committed to provide up to $1 million in free Snowflake credits on AWS over four years to support startups building and offering applications on Snowflakes platform. Access to credits to help build : AWS provides participants with free Snowflake credits to build, test and launch their applications.
A prominent public health organization integrated data from multiple regional health entities within a hybrid multi-cloud environment (AWS, Azure, and on-premise). A leading meal kit provider migrated its data architecture to Cloudera on AWS, utilizing Cloudera’s Open Data Lakehouse capabilities.
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