Author: Neha Bhardwaj

Couchbase Disaster recovery

Couchbase High Availability and Disaster Recovery: Part 2

Reading Time: 3 minutes In our previous blog we learned about how Couchbase achieves high availability. This post will focus on understanding Couchbase Disaster Recovery mechanisms to prevent data loss. Disaster Recovery Couchbase uses the following mechanisms to prevent potential data loss due to unplanned incidents or disasters. XDCR As discussed in the previous blog, Cross-Data Center Replication (XDCR) is a technology that lets us keep entire Data Centers Continue Reading

couchbase_xdcr

Couchbase High Availability and Disaster Recovery: Part 1

Reading Time: 4 minutes Couchbase Server is an open-source, distributed, NoSQL, document-oriented engagement database. It is designed to support strong features like:– Flexible data model– Simple administration– Query and Analytics– Memory first architecture– High Availability and many more Couchbase strongly emphasizes reliability, high availability, and simple management. It aims to perform operations while the system remains online, without interrupting running applications. High Availability Focused on high availability, it leverages Continue Reading

protecting sensitive data in docker

Running a Cron Job in Docker Container

Reading Time: 2 minutes Setting up a cron job within a docker container might not sound new to many of us. But depending upon the base image that we use to build the docker image we might end up struggling with different issues. In this blog, I will walk you through the different challenges that I dealt with while setting up a cron using bash in a docker container. Continue Reading

Serve Static Content on a Jetty Web Server using Docker Container

Reading Time: 2 minutes Docker is well known to containerize the application with all the necessary dependencies in order to make the application portable and deployable in a platform independent manner. And, on the other hand Jetty Server is widely used with Docker to deploy applications using war files.But, recently I came across a requirement to expose static files and jars on a given endpoint using a Jetty Web Continue Reading

KSQL: Streams and Tables

Reading Time: 3 minutes By now you must be familiar with KSQL and how to get started with it. If not, check out the Part1 KSQL: Getting started with Streaming SQL for Apache Kafka of this series. In this blog, we’ll move one step forward to get an understanding of the Dual streaming model to see what abstractions does KSQL use to process the data. All the data that we Continue Reading

Understanding laws of scalability and the effects on a distributed system

Reading Time: 4 minutes A reactive system primarily focuses on responsiveness, elasticity, message-driven, and resiliency as its core features. Elasticity is one of the main components in the reactive manifesto. An elastic system has the ability to scale up or scale down when there is an increase/decrease in demand while remaining responsive. Scenarios where a system needs to improve the throughput or needs to handle more concurrent users, we Continue Reading

Couchbase Java SDK Tutorial – CRUD Operations

Reading Time: 3 minutes In this blog, we will learn to implement CRUD operations in Couchbase with a Java application. So, let’s begin with a quick introduction of the Couchbase Server. Introduction to Couchbase Couchbase Server is an open source, distributed, NoSQL document-oriented engagement database with many advantages over traditional RDBMS like:- Fast key-value store with managed cache for sub-millisecond data operations. Purpose-built indexers for fast queries. A powerful Continue Reading

Error Registering Avro Schema | Multiple Schemas In One Topic

Reading Time: 4 minutes org.apache.kafka.common.errors.SerializationException: Error registering Avro schema: {“type”:”record”,”name”:”schema1″,”namespace”:”test”,”fields”:[{“name”:”Name”,”type”:”string”},{“name”:”Age”,”type”:”int”},{“name”:”Location”,”type”:”string”}]} Caused by: io.confluent.kafka.schemaregistry.client.rest.exceptions.RestClientException: Schema being registered is incompatible with an earlier schema; error code: 409 at io.confluent.kafka.schemaregistry.client.rest.RestService.sendHttpRequest(RestService.java:170) at io.confluent.kafka.schemaregistry.client.rest.RestService.httpRequest(RestService.java:188) at io.confluent.kafka.schemaregistry.client.rest.RestService.registerSchema(RestService.java:245) at io.confluent.kafka.schemaregistry.client.rest.RestService.registerSchema(RestService.java:237) at io.confluent.kafka.schemaregistry.client.rest.RestService.registerSchema(RestService.java:232) at io.confluent.kafka.schemaregistry.client.CachedSchemaRegistryClient.registerAndGetId(CachedSchemaRegistryClient.java:59) at io.confluent.kafka.schemaregistry.client.CachedSchemaRegistryClient.register(CachedSchemaRegistryClient.java:91) at io.confluent.kafka.serializers.AbstractKafkaAvroSerializer.serializeImpl(AbstractKafkaAvroSerializer.java:72) at io.confluent.kafka.formatter.AvroMessageReader.readMessage(AvroMessageReader.java:158) at kafka.tools.ConsoleProducer$.main(ConsoleProducer.scala:57) at kafka.tools.ConsoleProducer.main(ConsoleProducer.scala) You might have come across a similar exception while working with AVRO schemas. Kafka throws this exception due to a compatibility issue Continue Reading

Transforming to a New World with Blockchain Technology

Reading Time: 4 minutes The Blockchain technology is booming beyond belief. But apart from the definition or relating it to BITCOINS what else do we know about The Blockchain? Reading articles regarding this, all I could summarize about Blockchain is that it is a- Distributed and immutable (write once and read only) Database/System. A public ledger of all distributed transactions. Key features include Security, Integrity, Accessibility. A well-known implementation Continue Reading

Partitioning in Database

Reading Time: 3 minutes To speed up the query processing, we need to efficiently manage data. And partitioning the database is considered as one of the ways to enhance the processing speed. Using Partitioning, we can divide the data based on some value/field, so that data belonging to different groups are identified easily(may be stored on different nodes), and therefore processing a query won’t require a Full Table Scan, Continue Reading

Understanding Lightbend Telemetry

Reading Time: 2 minutes Let’s begin by understanding each of its meaning. Lightbend(formerly known as ‘Typesafe’) provides an open-source platform for building Reactive applications for the JVM, consisting of the Play Framework, Akka middleware and Scala programming language. And, Telemetry = tele(remote) + metron(measure) Lightbend Telemetry provides insight into applications built with Lightbend technologies. Some of the Lightbend technologies are mentioned below : Akka  Apache Cassandra  Apache Kafka  Apache Continue Reading

What makes CockroachDB Unique !!

Reading Time: 3 minutes In my blog today, I will be comparing CockroachDB with the existing databases like MySQL, Oracle, Cassandra, HBase and so on.. Let’s have a look at what makes CockroachDB different from other databases. Referring the following table we can compare different databases against each other depending on their features. As we can see, most of the features are present in CockroachDB, but the main concern Continue Reading