harish11g's profile picture. Ex-CTO , 13 yrs in Cloud. Tweets about AWS, AI, Data, Kubernetes
@invisibl_io

Harish Ganesan

@harish11g

Ex-CTO , 13 yrs in Cloud. Tweets about AWS, AI, Data, Kubernetes @invisibl_io

Building Internal Kubernetes Platforms: Part 1 – Self Service #Kubernetes #platforms invisibl.io/blog/building-…


Does @TigerGraphDB have neo4j graph data science library equivalent to make our life easy ? any python libraries for the same will be useful in our evaluation


Currently evaluating Neo4j vs AWS Neptune ? any suggestions which is better for building knowledge graphs, complex traversals and integration with ML/AI community.neo4j.com/t/neo4j-vs-aws… #neptune #neo4j


TimescaleDB vs. InfluxDB comparison. We have chosen TimescaleDB as our storage, will share my experience in coming months. blog.timescale.com/blog/timescale… #timeseries #influxdb #timescaledb


Harish Ganesan 已轉發

1/ Out of all #reInvent announcements so far, the only announcement that I keep going back in my head is the S3 strong read-after-write consistency. Read on 👇 🧵#aws #s3


Good one

1/ Some thoughts from the Kinesis event summary (that caused widespread service disruptions in AWS us-east-1 region last week)👇 aws.amazon.com/message/11201/



Harish Ganesan 已轉發

1/ We have had @dynamodb streams for Change Data Capture of DynamoDB tables for few years now. But yesterday a new Kinesis Data Streams based model was announced and it got me digging into the differences between them. A thread on the key differences 👇 aws.amazon.com/about-aws/what…


Harish Ganesan 已轉發

You have a Data Lake on S3. Your users use many #AWS services (Athena, Glue, EMR) to analyze data. You have sensitive data that needs to be restricted to only few users. Irrespective of which service they use. Here’s how: cloudstaq.io/column-level-p… #datalake #datagovernance


Harish Ganesan 已轉發

If you are building a Data Lake, here’s a logical view of all the components that are involved The top section “Governance & Security” is super important and is often not well thought through until issues start cropping up #datalake #analytics #datagovernance

raghuramanb's tweet image. If you are building a Data Lake, here’s a logical view of all the components that are involved

The top section “Governance & Security” is super important and is often not well thought through until issues start cropping up

#datalake #analytics #datagovernance

Harish Ganesan 已轉發

1/ How to build an analytics pipeline on #AWS that can analyse a TB of data for $100? A thread 👇


Harish Ganesan 已轉發

1/ One of the AWS services that always amazes and excites me is @dynamodb . And I also eagerly wait every year for @jeffbarr update on how AWS powered Prime Day that year where I rush to see DynamoDB numbers. A thread on how DynamoDB has evolved and scaled over the years 👇


Excellent thread on #awscloud #dynamodb by @raghuramanb

1/ One of the AWS services that always amazes and excites me is @dynamodb . And I also eagerly wait every year for @jeffbarr update on how AWS powered Prime Day that year where I rush to see DynamoDB numbers. A thread on how DynamoDB has evolved and scaled over the years 👇



Harish Ganesan 已轉發

1/ Everyone understands the power of APIs. But what happens when a Database gets an API? #AWS #Redshift got one recently and it opens up plenty of new use cases. A thread 👇


Harish Ganesan 已轉發

Streaming ETL in AWS Glue now supports reading from self managed Kafka. With this, you can use Glue to process streaming data from Kinesis Data Streams, Amazon MSK, Self managed Kafka anywhere (cloud or on-prem). More details here: docs.aws.amazon.com/glue/latest/dg… #AWSGlue #Kafka


Harish Ganesan 已轉發

If you are building a Data Lake, it is super important that these 3 pillars are completely de-coupled: Compute, Storage and Catalog. This will allow you to solve wide range of use cases and provide maximum flexibility in tools that you can use #datalake


Harish Ganesan 已轉發

Congrats to everyone at @awscloud on the release of AWS Lambda Extensions. @theburningmonk has written up our take on it and how we're supporting it bit.ly/3ltEGkO


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