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How to resolving Mozilla Certificate error (SEC_ERROR_UNKNOWN_ISSUER ) while browsing Https site from Apache web server.

In my earlier post, I provided step-by-step instructions to host a website on an Apache web server and secure it thru HTTPS. I have found that the site works perfectly fine in IE and Chrome but it throws a certificate error while browsing it thru Mozilla. It throws the SEC_ERROR_UNKNOWN_ISSUER error. So in this blog post we will explore the solution of this problem.

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Step by Step :How to install Apache Web Server and deploy SSL (HTTPS) enabled site?

In this post, we will go thru step by step instructions for Apache Web server installation. After Apache Server Installation we will create an SSL certificate creation request to generate the certificates from Certificate Authority and then deploy the SSL certificates on Apache Web Server. We will also learn how to modify browser settings to make the certificate works in case the site is accessed from outside the corporate intranet where Root certificates are not installed on the machine.

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How to configure Power BI Enterprise Gateway Proxy configuration?

Power BI service allows connectivity thru PowerBI Gateway in case you do not want to expose the on-premise data sources. Power BI Gateway can be installed on a server /VM deployed in the on-premise environment. Now If you deploy the Enterprise gateway in the On-Premise network your network team may not be happy and they will not open the firewall to expose the Enterprise Gateway to connect to the Internet. But do not worry and here is the good news, in order for the Enterprise gateway to function properly it requires certain ports to be open. Let’s learn how to configure the environment so it is secure.

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How to connect Databricks to Azure Data Lake?

Databricks is a version of the popular open-source Apache Spark analytics and data processing engine. Azure Databricks is the fully managed version of Databricks and is a premium offering on Azure, that brings you an enterprise-grade and secure cloud-based Big Data and Machine Learning platform.

Data can be ingested in a variety of ways into Azure Databricks. For real-time Machine learning projects, you can ingest data through a wide range of technologies including Kafka, Event Hubs or ,IoT Hubs. In addition, you can ingest batches of data using Azure Data Factory from a variety of data stores including Azure Blob Storage, Azure Data Lake Storage, Azure Cosmos DB, or Azure SQL Data Warehouse which can then be used in the Spark-based engine within Databricks.

In this article, we are going to connect the data bricks to Azure Data Lakes.

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