Rahul Singhai Blog

By default, there is no encryption, authentication, or ACLs configured in Elasticsearch/Kafka. Any client can communicate to ES nodes / Kafka brokers via the PLAINTEXT port. It is critical that access via this port is restricted to trusted clients only. Network segmentation and/or authorization ACLs can be used to restrict access to trusted IPs in such cases. If neither is used, the cluster is wide open and can be accessed by anyone. While non-secured clusters are supported, as are a mix of authenticated, unauthenticated, encrypted and non-encrypted clients, it is recommended to secure the components in your cluster. Secure Sockets Layer (SSL) is the predecessor of Transport Layer Security (TLS) , and SSL has been deprecated since June 2015. However, generally people use the term SSL instead of TLS in configuration and code. SSL can be configured for encryption or authentication. You may configure just SSL encryption (by default SSL encryption includes certificate authenticatio

While trying to install logstash plugin, I was getting below error: $ /work/logstash/logstash-5.5.2/bin/logstash-plugin install logstash-input-cloudwatch WARNING: A maven settings file already exist at ~/.m2/settings.xml, please review the content to make sure it include your proxies configuration. Validating logstash-input-cloudwatch Installing logstash-input-cloudwatch Error Bundler::InstallError, retrying 1/10 An error occurred while installing logstash-core (5.5.2), and Bundler cannot continue. Make sure that `gem install logstash-core -v '5.5.2'` succeeds before bundling. Error Bundler::InstallError, retrying 2/10 An error occurred while installing logstash-core (5.5.2), and Bundler cannot continue. Make sure that `gem install logstash-core -v '5.5.2'` succeeds before bundling. Here are the things I did to make it work: Created maven ~/.m2/settings.xml file <?xml version="1.0" encoding="UTF-8"?> <settings xmlns="http://maven.ap

Let's say we want to read and parse a CSV file containing Key value pairs. We will be using Alpakka's CSVParser for this. A snippet of a file (src/main/resources/CountryNicCurrencyKeyValueMap.csv) that shows mapping from Country NIC code to currency code with pipe (|) as field delimiter: AD|EUR AE|AED AF|AFN AG|XCD AI|XCD AL|ALL AM|AMD AN|ANG AO|AOA AQ|AQD AR|ARS AS|EUR AT|EUR AU|AUD AW|ANG AX|EUR AZ|AZN BA|BAM BB|BBD BD|BDT BE|EUR BF|XOF BG|BGN BH|BHD BI|BIF BJ|XOF BL|EUR BM|BMD BN|BND BO|BOB BR|BRL BS|BSD BT|INR Following is the code: import java.io.File import java.nio.charset.StandardCharsets import akka.actor.ActorSystem import akka.stream._ import akka.stream.alpakka.csv.scaladsl.CsvParsing import akka.stream.scaladsl.{FileIO, Flow, Sink} import akka.util.ByteString import scala.collection.immutable import scala.concurrent.{ExecutionContext, _} import scala.concurrent.duration._ implicit val system: ActorSystem = ActorSystem("TestApplication") implicit

Performance Tuning of Kafka is critical when your cluster grow in size. Below are few points to consider to improve Kafka performance: Consumer group ID : Never use same exact consumer group ID for dozens of machines consuming from different topics. All of those commits will end up on the same exact partition of __consumer_offsets , hence the same broker, and this might in turn cause performance problems. Choose the consumer group ID to group_id+topic_name . Skewed : A broker is skewed if its number of partitions is greater that the average of partitions per broker on the given topic. Example: 2 brokers share 4 partitions, if one of them has 3 partitions, it is skewed (3 > 2). Try to make sure that none of the brokers is skewed. Spread : Brokers spread is the percentage of brokers in the cluster that has partitions for the given topic. Example: 3 brokers share a topic that has 2 partitions, so 66% of the brokers have partitions for this topic. Try to achieve 100% broker spread