Business Compass LLC’s Post

Learn how to optimize storage costs and query performance by compacting small log files into larger objects using AWS Step Functions via Josh Hart, Kim Banga, and Thomas Moore on Amazon Web Services (AWS) https://lnkd.in/dhR7BwsT #aws #awscloud

Do you use CloudWatch Log Classes? They can help you save big time on your CloudWatch bill. ☁💸 Checkout our latest post: https://lnkd.in/gFzBr848 #AWS #CloudWatch #FinOps #CloudCosts

Enhancing ACID Properties in Aurora Limitless Databases with Amazon Time Sync https://lnkd.in/dHNnmywT Amazon Web Services (AWS) #aws #awslambda #businesscompassllc

Amazon DataZone now integrates with AWS Lake Formation hybrid access mode to simplify secure and governed data sharing in the AWS Glue Data Catalog. This helps customers use Amazon DataZone for data access control across on-premises and cloud data lakes. #aws #awscloud #cloud #amazondatazone #announcements #awsglue #awslakeformation

In this post, we explore a pattern for compacting (or combining) large collections of small files into fewer, larger objects using AWS Step Functions. Compaction offers an alternative to archival-based solutions such as compressing and archiving logs stored in Amazon S3 and Amazon S3 Tar. By compacting many small objects together, they become large enough to exceed the 128 KB file size, resulting in lower management costs. Additionally, ad-hoc query performance is improved, and queries are executed in-place without making changes to existing code or tools. #AWS #AmazonWebServices #AWSBlogs #Cloud #CloudComputing https://lnkd.in/d9wwNYZv

Migrating data to the cloud can be complicated, but with Protegrity and Amazon Web Services (AWS), it can be both efficient and effective. In this post by Alexandre Charlet, Principal Solution Engineer at Protegrity, and Venkatesh A. of AWS, they describe value of a joint solution. I learned a lot. I hope you do too. https://lnkd.in/eeQ-TFdJ

Explore Object storage service in AWS i.e S3 #aws #s3 #cloud #objectstorage

Curious about how to build a multi-cloud resource data lake for SecOps, ITOps, and FinOps functions and how to normalize the data to perform analytics against it? Check out this Amazon Web Services (AWS) bog post that details how to avoid operational challenges with applications distributed across a cloud estate that spans not only multiple Cloud Service Providers (CSPs) but also regions and accounts on AWS (or Subscriptions and Projects on other providers).

The Amazon Athena Neptune connector is an AWS Lambda function that connects Athena to Neptune to query the graph. This post provides a guide to integrate the connector and query Neptune using Gremlin and SPARQL. #aws #awscloud #cloud #amazonathena #amazonneptune #awsglue #intermediate200 #technicalhowto

There are many very useful services on AWS that don't require you to spin up any VMs or setup anything else to use. One thing that is key to using AWS (and other cloud providers) is understanding how billing works and make sure you setup alarms for billing and use tools like Cost Anomaly Detection to help notice unexpected charges. This article from José David Arévalo is a very interesting read about a case where costs for the Amazon Athena service spun out of control for them and some tips on how to avoid something like this happening to you. Amazon Athena is a serverless query engine that allows you to run SQL-like queries on data sitting in S3 buckets. It is a great tool that allows you to look through your data without setting up an actual database. https://lnkd.in/eWB5wHq5