Monthly Archives: November 2018

AWS Lake Formation: the new Datalake solution proposed by Amazon

AWS Lake Formation is a service that makes it easy to set up a secure data lake in days. A data lake is a centralized, curated, and secured repository that stores all your data, both in its original form and prepared for analysis. A data lake enables you to break down data silos and combine different types of analytics to gain insights and guide better business decisions.

However, setting up and managing data lakes today involves a lot of manual, complicated, and time-consuming tasks. This work includes loading data from diverse sources, monitoring those data flows, setting up partitions, turning on encryption and managing keys, defining transformation jobs and monitoring their operation, re-organizing data into a columnar format, configuring access control settings, deduplicating redundant data, matching linked records, granting access to data sets, and auditing access over time.

Creating a data lake with Lake Formation is as simple as defining where your data resides and what data access and security policies you want to apply. Lake Formation then collects and catalogs data from databases and object storage, moves the data into your new Amazon S3 data lake, cleans and classifies data using machine learning algorithms, and secures access to your sensitive data. Your users can then access a centralized catalog of data which describes available data sets and their appropriate usage. Your users then leverage these data sets with their choice of analytics and machine learning services, like Amazon EMR for Apache Spark, Amazon Redshift, Amazon Athena, Amazon Sagemaker, and Amazon QuickSight. [aws.amazon.com]

Lake Formation automatically configures underlying AWS services, including S3, AWS Glue, AWS IAM, AWS KMS, Amazon Athena, Amazon Redshift, and Amazon EMR for Apache Spark, to ensure compliance with your defined policies. If you’ve set up transformation jobs spanning AWS services, Lake Formation configures the flows, centralizes their orchestration, and lets you monitor the execution of your jobs. With Lake Formation, you can configure and manage your data lake without manually integrating multiple underlying AWS services

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Building a Cloud-Agnostic Serverless infrastructure with Apache OpenWhisk

Apache OpenWhisk (Incubating) is an open source, distributed Serverless platform that executes functions (fx) in response to events at any scale. OpenWhisk manages the infrastructure, servers and scaling using Docker containers so you can focus on building amazing and efficient applications…

DEPLOY Anywhere: Since Apache OpenWhisk builds its components using containers it easily supports many deployment options both locally and within Cloud infrastructures. Options include many of today’s popular Container frameworks such as KubernetesMesos and Compose

ANY LANGUAGES: Work with what you know and love. OpenWhisk supports a growing list of your favorite languages such as NodeJSSwiftJavaGoScalaPythonPHP and Ruby.

If you need languages or libraries the current “out-of-the-box” runtimes do not support, you can create and customize your own executables as Zip Actions which run on the Docker runtime by using the Docker SDK. ” [openwhisk.apache.org]

Building a Cloud-Agnostic Serverless infrastructure with Knative

KNATIVE is Kubernetes-based platform to build, deploy, and manage modern serverless workloads

“Knative provides a set of middleware components that are essential to build modern, source-centric, and container-based applications that can run anywhere: on premises, in the cloud, or even in a third-party data center. Knative components are built on Kubernetes and codify the best practices shared by successful real-world Kubernetes-based frameworks. It enables developers to focus just on writing interesting code, without worrying about the “boring but difficult” parts of building, deploying, and managing an application.” [https://cloud.google.com/knative/]

“Knative has been developed by Google in close partnership with PivotalIBMRed Hat, and SAP.” [infoq.com]